diff --git a/libs/astradb/langchain_astradb/utils/astradb.py b/libs/astradb/langchain_astradb/utils/astradb.py index 9e33f80..ae7d332 100644 --- a/libs/astradb/langchain_astradb/utils/astradb.py +++ b/libs/astradb/langchain_astradb/utils/astradb.py @@ -35,6 +35,9 @@ # Thread/coroutine count for one-doc-at-a-time deletes: MAX_CONCURRENT_DOCUMENT_DELETIONS = 20 +# Amount of (max) number of documents for surveying a collection +SURVEY_NUMBER_OF_DOCUMENTS = 15 + logger = logging.getLogger() @@ -46,6 +49,42 @@ class SetupMode(Enum): OFF = 3 +def _survey_collection( + collection_name: str, + *, + token: str | TokenProvider | None = None, + api_endpoint: str | None = None, + environment: str | None = None, + astra_db_client: AstraDB | None = None, + async_astra_db_client: AsyncAstraDB | None = None, + namespace: str | None = None, +) -> tuple[CollectionDescriptor | None, list[dict[str, Any]]]: + """Return the collection descriptor (if found) and a sample of documents.""" + _environment = _AstraDBEnvironment( + token=token, + api_endpoint=api_endpoint, + environment=environment, + astra_db_client=astra_db_client, + async_astra_db_client=async_astra_db_client, + namespace=namespace, + ) + descriptors = [ + coll_d + for coll_d in _environment.database.list_collections() + if coll_d.name == collection_name + ] + if not descriptors: + return None, [] + descriptor = descriptors[0] + # fetch some documents + document_ite = _environment.database.get_collection(collection_name).find( + filter={}, + projection={"*": True}, + limit=SURVEY_NUMBER_OF_DOCUMENTS, + ) + return (descriptor, list(document_ite)) + + class _AstraDBEnvironment: def __init__( self, diff --git a/libs/astradb/langchain_astradb/utils/encoders.py b/libs/astradb/langchain_astradb/utils/encoders.py deleted file mode 100644 index 62452c2..0000000 --- a/libs/astradb/langchain_astradb/utils/encoders.py +++ /dev/null @@ -1,200 +0,0 @@ -"""Classes to handle encoding of documents on DB for the Vector Store..""" - -from __future__ import annotations - -from abc import ABC, abstractmethod -from typing import Any - -from langchain_core.documents import Document -from typing_extensions import override - -NO_NULL_VECTOR_MSG = "Default encoder cannot receive null vector" -VECTOR_REQUIRED_PREAMBLE_MSG = "DefaultVectorize encoder got a non-null vector" - - -def _default_encode_filter(filter_dict: dict[str, Any]) -> dict[str, Any]: - metadata_filter = {} - for k, v in filter_dict.items(): - # Key in this dict starting with $ are supposedly operators and as such - # should not be nested within the `metadata.` prefix. For instance, - # >>> _default_encode_filter({'a':1, '$or': [{'b':2}, {'c': 3}]}) - # {'metadata.a': 1, '$or': [{'metadata.b': 2}, {'metadata.c': 3}]} - if k and k[0] == "$": - if isinstance(v, list): - metadata_filter[k] = [_default_encode_filter(f) for f in v] - else: - # assume each list item can be fed back to this function - metadata_filter[k] = _default_encode_filter(v) # type: ignore[assignment] - else: - metadata_filter[f"metadata.{k}"] = v - - return metadata_filter - - -class _AstraDBVectorStoreDocumentEncoder(ABC): - """A document encoder for the Astra DB vector store. - - The document encoder contains the information for consistent interaction - with documents as stored on the Astra DB collection. - - Implementations of this class must: - - define how to encode/decode documents consistently to and from - Astra DB collections. The two operations must, so to speak, combine - to the identity on both sides (except for the quirks of their signatures). - - provide the adequate projection dictionaries for running find - operations on Astra DB, with and without the field containing the vector. - - encode IDs to the `_id` field on Astra DB. - - define the name of the field storing the textual content of the Document. - - define whether embeddings are computed server-side (with $vectorize) or not. - """ - - server_side_embeddings: bool - content_field: str - base_projection: dict[str, bool] - full_projection: dict[str, bool] - - @abstractmethod - def encode( - self, - content: str, - document_id: str, - vector: list[float] | None, - metadata: dict | None, - ) -> dict[str, Any]: - """Create a document for storage on Astra DB. - - Args: - content: textual content for the (LangChain) `Document`. - document_id: unique ID for the (LangChain) `Document`. - vector: a vector associated to the (LangChain) `Document`. This - parameter must be None for and only for server-side embeddings. - metadata: a metadata dictionary for the (LangChain) `Document`. - - Returns: - a dictionary ready for storage onto Astra DB. - """ - - @abstractmethod - def decode(self, astra_document: dict[str, Any]) -> Document: - """Create a LangChain Document instance from a document retrieved from Astra DB. - - Args: - astra_document: a dictionary as retrieved from Astra DB. - - Returns: - a (langchain) Document corresponding to the input. - """ - - @abstractmethod - def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: - """Encode a LangChain filter for use in Astra DB queries. - - Make a LangChain filter into a filter clause suitable for operations - against the Astra DB collection, consistently with the encoding scheme. - - Args: - filter_dict: a filter in the standardized metadata-filtering form - used throughout LangChain. - - Returns: - an equivalent filter clause for use in Astra DB's find queries. - """ - - -class _DefaultVSDocumentEncoder(_AstraDBVectorStoreDocumentEncoder): - """Encoder for the default vector store usage with client-side embeddings. - - This encoder expresses how document are stored for collections created - and entirely managed by the AstraDBVectorStore class. - """ - - server_side_embeddings = False - content_field = "content" - - def __init__(self) -> None: - """Initialize a new DefaultVSDocumentEncoder.""" - self.base_projection = {"_id": True, "content": True, "metadata": True} - self.full_projection = { - "_id": True, - "content": True, - "metadata": True, - "$vector": True, - } - - @override - def encode( - self, - content: str, - document_id: str, - vector: list[float] | None, - metadata: dict | None, - ) -> dict[str, Any]: - if vector is None: - raise ValueError(NO_NULL_VECTOR_MSG) - return { - "content": content, - "_id": document_id, - "$vector": vector, - "metadata": metadata, - } - - @override - def decode(self, astra_document: dict[str, Any]) -> Document: - return Document( - page_content=astra_document["content"], - metadata=astra_document["metadata"], - ) - - @override - def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: - return _default_encode_filter(filter_dict) - - -class _DefaultVectorizeVSDocumentEncoder(_AstraDBVectorStoreDocumentEncoder): - """Encoder for the default vector store usage with server-side embeddings. - - This encoder expresses how document are stored for collections created - and entirely managed by the AstraDBVectorStore class, for the case of - server-side embeddings (aka $vectorize). - """ - - server_side_embeddings = True - content_field = "$vectorize" - - def __init__(self) -> None: - """Initialize a new DefaultVectorizeVSDocumentEncoder.""" - self.base_projection = {"_id": True, "$vectorize": True, "metadata": True} - self.full_projection = { - "_id": True, - "$vectorize": True, - "metadata": True, - "$vector": True, - } - - @override - def encode( - self, - content: str, - document_id: str, - vector: list[float] | None, - metadata: dict | None, - ) -> dict[str, Any]: - if vector is not None: - msg = f"{VECTOR_REQUIRED_PREAMBLE_MSG}: {vector}" - raise ValueError(msg) - return { - "$vectorize": content, - "_id": document_id, - "metadata": metadata, - } - - @override - def decode(self, astra_document: dict[str, Any]) -> Document: - return Document( - page_content=astra_document["$vectorize"], - metadata=astra_document["metadata"], - ) - - @override - def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: - return _default_encode_filter(filter_dict) diff --git a/libs/astradb/langchain_astradb/utils/vector_store_autodetect.py b/libs/astradb/langchain_astradb/utils/vector_store_autodetect.py new file mode 100644 index 0000000..c79c0fc --- /dev/null +++ b/libs/astradb/langchain_astradb/utils/vector_store_autodetect.py @@ -0,0 +1,130 @@ +"""Utilities for AstraDB vector store autodetect mode.""" + +from __future__ import annotations + +import logging +from collections import Counter +from operator import itemgetter +from typing import ( + Any, +) + +from langchain_astradb.utils.vector_store_codecs import ( + _AstraDBVectorStoreDocumentCodec, + _DefaultVectorizeVSDocumentCodec, + _DefaultVSDocumentCodec, + _FlatVectorizeVSDocumentCodec, + _FlatVSDocumentCodec, +) + +logger = logging.getLogger(__name__) + + +def _detect_document_flatness(document: dict[str, Any]) -> bool | None: + """Try to guess, when possible, if this document has metadata-as-a-dict or not.""" + _metadata = document.get("metadata") + _vector = document.get("$vector") + _regularfields = set(document.keys()) - {"_id", "$vector"} + _regularfields_m = _regularfields - {"metadata"} + # cannot determine if ... + if _vector is None: + return None + # now a determination + if isinstance(_metadata, dict) and _regularfields_m: + return False + if isinstance(_metadata, dict) and not _regularfields_m: + # this document should not contribute to the survey + return None + str_regularfields = { + k for k, v in document.items() if isinstance(v, str) if k in _regularfields + } + if str_regularfields: + # Note: even if the only string field is "metadata" + return True + return None + + +def _detect_documents_flatness(documents: list[dict[str, Any]]) -> bool: + flatness_survey = [_detect_document_flatness(document) for document in documents] + n_flats = flatness_survey.count(True) + n_deeps = flatness_survey.count(False) + if n_flats > 0 and n_deeps > 0: + msg = "Mixed document shapes detected on collection during autodetect." + raise ValueError(msg) + + # in absence of clues, 0 < 0 is False and default is NON FLAT (i.e. native) + return n_deeps < n_flats + + +def _detect_document_content_field(document: dict[str, Any]) -> str | None: + """Try to guess the content field by inspecting the passed document.""" + strlen_map = { + k: len(v) for k, v in document.items() if k != "_id" if isinstance(v, str) + } + if not strlen_map: + return None + return sorted(strlen_map.items(), key=itemgetter(1), reverse=True)[0][0] + + +def _detect_documents_content_field( + documents: list[dict[str, Any]], + requested_content_field: str, +) -> str: + if requested_content_field == "*": + # guess content_field by docs inspection + content_fields = [ + _detect_document_content_field(document) for document in documents + ] + valid_content_fields = [cf for cf in content_fields if cf is not None] + logger.info( + "vector store autodetect: inferring content_field from %i documents", + len(valid_content_fields), + ) + cf_stats = Counter(valid_content_fields) + if not cf_stats: + msg = "Could not infer content_field name from sampled documents." + raise ValueError(msg) + return cf_stats.most_common(1)[0][0] + + return requested_content_field + + +def _detect_document_codec( + documents: list[dict[str, Any]], + *, + has_vectorize: bool, + ignore_invalid_documents: bool, + norm_content_field: str, +) -> _AstraDBVectorStoreDocumentCodec: + logger.info("vector store autodetect: inspecting %i documents", len(documents)) + # survey and determine flatness + is_flat = _detect_documents_flatness(documents) + logger.info("vector store autodetect: is_flat = %s", is_flat) + + final_content_field = _detect_documents_content_field( + documents=documents, + requested_content_field=norm_content_field, + ) + logger.info( + "vector store autodetect: final_content_field = %s", final_content_field + ) + + if has_vectorize: + if is_flat: + return _FlatVectorizeVSDocumentCodec( + ignore_invalid_documents=ignore_invalid_documents, + ) + + return _DefaultVectorizeVSDocumentCodec( + ignore_invalid_documents=ignore_invalid_documents, + ) + # no vectorize: + if is_flat: + return _FlatVSDocumentCodec( + content_field=final_content_field, + ignore_invalid_documents=ignore_invalid_documents, + ) + return _DefaultVSDocumentCodec( + content_field=final_content_field, + ignore_invalid_documents=ignore_invalid_documents, + ) diff --git a/libs/astradb/langchain_astradb/utils/vector_store_codecs.py b/libs/astradb/langchain_astradb/utils/vector_store_codecs.py new file mode 100644 index 0000000..68f1a7b --- /dev/null +++ b/libs/astradb/langchain_astradb/utils/vector_store_codecs.py @@ -0,0 +1,389 @@ +"""Classes to handle encoding of documents on DB for the Vector Store..""" + +from __future__ import annotations + +import logging +import warnings +from abc import ABC, abstractmethod +from typing import Any + +from langchain_core.documents import Document +from typing_extensions import override + +NO_NULL_VECTOR_MSG = "Default (non-vectorize) codec cannot encode null vector." +VECTOR_REQUIRED_PREAMBLE_MSG = ( + "Default vectorize codec got a non-null vector to encode." +) +FLATTEN_CONFLICT_MSG = "Cannot flatten metadata: field name overlap for '{field}'." + +logger = logging.getLogger(__name__) + + +def _default_encode_filter(filter_dict: dict[str, Any]) -> dict[str, Any]: + metadata_filter = {} + for k, v in filter_dict.items(): + # Key in this dict starting with $ are supposedly operators and as such + # should not be nested within the `metadata.` prefix. For instance, + # >>> _default_encode_filter({'a':1, '$or': [{'b':2}, {'c': 3}]}) + # {'metadata.a': 1, '$or': [{'metadata.b': 2}, {'metadata.c': 3}]} + if k and k[0] == "$": + if isinstance(v, list): + metadata_filter[k] = [_default_encode_filter(f) for f in v] + else: + # assume each list item can be fed back to this function + metadata_filter[k] = _default_encode_filter(v) # type: ignore[assignment] + else: + metadata_filter[f"metadata.{k}"] = v + + return metadata_filter + + +class _AstraDBVectorStoreDocumentCodec(ABC): + """A document codec for the Astra DB vector store. + + The document codec contains the information for consistent interaction + with documents as stored on the Astra DB collection. + + Implementations of this class must: + - define how to encode/decode documents consistently to and from + Astra DB collections. The two operations must, so to speak, combine + to the identity on both sides (except for the quirks of their signatures). + - provide the adequate projection dictionaries for running find + operations on Astra DB, with and without the field containing the vector. + - encode IDs to the `_id` field on Astra DB. + - define the name of the field storing the textual content of the Document. + - define whether embeddings are computed server-side (with $vectorize) or not. + """ + + server_side_embeddings: bool + content_field: str + base_projection: dict[str, bool] + full_projection: dict[str, bool] + ignore_invalid_documents: bool + + @abstractmethod + def encode( + self, + content: str, + document_id: str, + vector: list[float] | None, + metadata: dict | None, + ) -> dict[str, Any]: + """Create a document for storage on Astra DB. + + Args: + content: textual content for the (LangChain) `Document`. + document_id: unique ID for the (LangChain) `Document`. + vector: a vector associated to the (LangChain) `Document`. This + parameter must be None for and only for server-side embeddings. + metadata: a metadata dictionary for the (LangChain) `Document`. + + Returns: + a dictionary ready for storage onto Astra DB. + """ + + @abstractmethod + def decode(self, astra_document: dict[str, Any]) -> Document | None: + """Create a LangChain Document instance from a document retrieved from Astra DB. + + Args: + astra_document: a dictionary as retrieved from Astra DB. + + Returns: + a (langchain) Document corresponding to the input. + """ + + @abstractmethod + def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: + """Encode a LangChain filter for use in Astra DB queries. + + Make a LangChain filter into a filter clause suitable for operations + against the Astra DB collection, consistently with the encoding scheme. + + Args: + filter_dict: a filter in the standardized metadata-filtering form + used throughout LangChain. + + Returns: + an equivalent filter clause for use in Astra DB's find queries. + """ + + +class _DefaultVSDocumentCodec(_AstraDBVectorStoreDocumentCodec): + """Codec for the default vector store usage with client-side embeddings. + + This codec expresses how document are stored for collections created + and entirely managed by the AstraDBVectorStore class. + """ + + server_side_embeddings = False + + def __init__(self, content_field: str, *, ignore_invalid_documents: bool) -> None: + """Initialize a new DefaultVSDocumentCodec. + + Args: + content_field: name of the (top-level) field for textual content. + ignore_invalid_documents: if True, noncompliant inputs to `decode` + are logged and a None is returned (instead of raising an exception). + """ + self.content_field = content_field + self.base_projection = {"_id": True, self.content_field: True, "metadata": True} + self.full_projection = { + "_id": True, + self.content_field: True, + "metadata": True, + "$vector": True, + } + self.ignore_invalid_documents = ignore_invalid_documents + + @override + def encode( + self, + content: str, + document_id: str, + vector: list[float] | None, + metadata: dict | None, + ) -> dict[str, Any]: + if vector is None: + raise ValueError(NO_NULL_VECTOR_MSG) + return { + self.content_field: content, + "_id": document_id, + "$vector": vector, + "metadata": metadata or {}, + } + + @override + def decode(self, astra_document: dict[str, Any]) -> Document | None: + _invalid_doc = ( + "metadata" not in astra_document or self.content_field not in astra_document + ) + if _invalid_doc and self.ignore_invalid_documents: + invalid_doc_warning = ( + "Ignoring document with _id = " + f"{astra_document.get('_id', '(no _id)')}. " + "Reason: missing required fields." + ) + logger.warning(invalid_doc_warning) + return None + return Document( + page_content=astra_document[self.content_field], + metadata=astra_document["metadata"], + ) + + @override + def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: + return _default_encode_filter(filter_dict) + + +class _DefaultVectorizeVSDocumentCodec(_AstraDBVectorStoreDocumentCodec): + """Codec for the default vector store usage with server-side embeddings. + + This codec expresses how document are stored for collections created + and entirely managed by the AstraDBVectorStore class, for the case of + server-side embeddings (aka $vectorize). + """ + + server_side_embeddings = True + content_field = "$vectorize" + + def __init__(self, *, ignore_invalid_documents: bool) -> None: + """Initialize a new DefaultVectorizeVSDocumentCodec. + + Args: + ignore_invalid_documents: if True, noncompliant inputs to `decode` + are logged and a None is returned (instead of raising an exception). + """ + self.base_projection = {"_id": True, "$vectorize": True, "metadata": True} + self.full_projection = { + "_id": True, + "$vectorize": True, + "metadata": True, + "$vector": True, + } + self.ignore_invalid_documents = ignore_invalid_documents + + @override + def encode( + self, + content: str, + document_id: str, + vector: list[float] | None, + metadata: dict | None, + ) -> dict[str, Any]: + if vector is not None: + msg = f"{VECTOR_REQUIRED_PREAMBLE_MSG}: {vector}" + raise ValueError(msg) + return { + "$vectorize": content, + "_id": document_id, + "metadata": metadata or {}, + } + + @override + def decode(self, astra_document: dict[str, Any]) -> Document | None: + _invalid_doc = ( + "metadata" not in astra_document or "$vectorize" not in astra_document + ) + if _invalid_doc and self.ignore_invalid_documents: + invalid_doc_warning = ( + "Ignoring document with _id = " + f"{astra_document.get('_id', '(no _id)')}. " + "Reason: missing required fields." + ) + warnings.warn( + invalid_doc_warning, + stacklevel=2, + ) + return None + return Document( + page_content=astra_document["$vectorize"], + metadata=astra_document["metadata"], + ) + + @override + def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: + return _default_encode_filter(filter_dict) + + +class _FlatVSDocumentCodec(_AstraDBVectorStoreDocumentCodec): + """Codec for collections populated externally, with client-side embeddings. + + This codec manages document structured as a flat key-value map, with one + field being the textual content and the other implicitly forming the "metadata". + """ + + server_side_embeddings = False + + def __init__(self, content_field: str, *, ignore_invalid_documents: bool) -> None: + """Initialize a new DefaultVSDocumentCodec. + + Args: + content_field: name of the (top-level) field for textual content. + ignore_invalid_documents: if True, noncompliant inputs to `decode` + are logged and a None is returned (instead of raising an exception). + """ + self.content_field = content_field + self.base_projection = {"_id": True, "$vector": False} + self.full_projection = {"*": True} + self.ignore_invalid_documents = ignore_invalid_documents + self._non_md_fields = { + "_id", + "$vector", + "$vectorize", + self.content_field, + "$similarity", + } + + @override + def encode( + self, + content: str, + document_id: str, + vector: list[float] | None, + metadata: dict | None, + ) -> dict[str, Any]: + if vector is None: + raise ValueError(NO_NULL_VECTOR_MSG) + if self.content_field in (metadata or {}): + msg = FLATTEN_CONFLICT_MSG.format(field=self.content_field) + raise ValueError(msg) + return { + self.content_field: content, + "_id": document_id, + "$vector": vector, + **(metadata or {}), + } + + @override + def decode(self, astra_document: dict[str, Any]) -> Document | None: + if self.content_field not in astra_document and self.ignore_invalid_documents: + invalid_doc_warning = ( + "Ignoring document with _id = " + f"{astra_document.get('_id', '(no _id)')}. " + "Reason: missing required fields." + ) + warnings.warn( + invalid_doc_warning, + stacklevel=2, + ) + return None + _metadata = { + k: v for k, v in astra_document.items() if k not in self._non_md_fields + } + return Document( + page_content=astra_document[self.content_field], + metadata=_metadata, + ) + + @override + def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: + return filter_dict + + +class _FlatVectorizeVSDocumentCodec(_AstraDBVectorStoreDocumentCodec): + """Codec for collections populated externally, with server-side embeddings. + + This codec manages document structured as a flat key-value map, with one + field being the textual content and the other implicitly forming the "metadata". + """ + + server_side_embeddings = True + content_field = "$vectorize" + + def __init__(self, *, ignore_invalid_documents: bool) -> None: + """Initialize a new DefaultVectorizeVSDocumentCodec. + + Args: + ignore_invalid_documents: if True, noncompliant inputs to `decode` + are logged and a None is returned (instead of raising an exception). + """ + self.base_projection = {"_id": True, "$vector": False, "$vectorize": True} + self.full_projection = {"*": True} + self.ignore_invalid_documents = ignore_invalid_documents + self._non_md_fields = {"_id", "$vector", "$vectorize", "$similarity"} + + @override + def encode( + self, + content: str, + document_id: str, + vector: list[float] | None, + metadata: dict | None, + ) -> dict[str, Any]: + if vector is not None: + msg = f"{VECTOR_REQUIRED_PREAMBLE_MSG}: {vector}" + raise ValueError(msg) + if "$vectorize" in (metadata or {}): + msg = FLATTEN_CONFLICT_MSG.format(field="$vectorize") + raise ValueError(msg) + return { + "$vectorize": content, + "_id": document_id, + **(metadata or {}), + } + + @override + def decode(self, astra_document: dict[str, Any]) -> Document | None: + if "$vectorize" not in astra_document and self.ignore_invalid_documents: + invalid_doc_warning = ( + "Ignoring document with _id = " + f"{astra_document.get('_id', '(no _id)')}. " + "Reason: missing required fields." + ) + warnings.warn( + invalid_doc_warning, + stacklevel=2, + ) + return None + _metadata = { + k: v for k, v in astra_document.items() if k not in self._non_md_fields + } + return Document( + page_content=astra_document["$vectorize"], + metadata=_metadata, + ) + + @override + def encode_filter(self, filter_dict: dict[str, Any]) -> dict[str, Any]: + return filter_dict diff --git a/libs/astradb/langchain_astradb/vectorstores.py b/libs/astradb/langchain_astradb/vectorstores.py index 26bf65b..cfb2cf6 100644 --- a/libs/astradb/langchain_astradb/vectorstores.py +++ b/libs/astradb/langchain_astradb/vectorstores.py @@ -4,6 +4,7 @@ import asyncio import inspect +import logging import uuid import warnings from concurrent.futures import ThreadPoolExecutor @@ -31,13 +32,17 @@ MAX_CONCURRENT_DOCUMENT_REPLACEMENTS, SetupMode, _AstraDBCollectionEnvironment, -) -from langchain_astradb.utils.encoders import ( - _AstraDBVectorStoreDocumentEncoder, - _DefaultVectorizeVSDocumentEncoder, - _DefaultVSDocumentEncoder, + _survey_collection, ) from langchain_astradb.utils.mmr import maximal_marginal_relevance +from langchain_astradb.utils.vector_store_autodetect import ( + _detect_document_codec, +) +from langchain_astradb.utils.vector_store_codecs import ( + _AstraDBVectorStoreDocumentCodec, + _DefaultVectorizeVSDocumentCodec, + _DefaultVSDocumentCodec, +) if TYPE_CHECKING: from astrapy.authentication import EmbeddingHeadersProvider, TokenProvider @@ -59,6 +64,8 @@ # indexing options when creating a collection DEFAULT_INDEXING_OPTIONS = {"allow": ["metadata"]} +logger = logging.getLogger(__name__) + def _unique_list(lst: list[T], key: Callable[[T], U]) -> list[T]: visited_keys: set[U] = set() @@ -71,13 +78,77 @@ def _unique_list(lst: list[T], key: Callable[[T], U]) -> list[T]: return new_lst +def _normalize_content_field( + content_field: str | None, + *, + is_autodetect: bool, + has_vectorize: bool, +) -> str: + if has_vectorize: + if content_field is not None: + msg = "content_field is not configurable for vectorize collections." + raise ValueError(msg) + return "$vectorize" + + if content_field is None: + return "*" if is_autodetect else "content" + + if content_field == "*": + if not is_autodetect: + msg = "content_field='*' illegal if autodetect_collection is False." + raise ValueError(msg) + return content_field + + return content_field + + +def _validate_autodetect_init_params( + *, + metric: str | None = None, + setup_mode: SetupMode | None, + pre_delete_collection: bool, + metadata_indexing_include: Iterable[str] | None, + metadata_indexing_exclude: Iterable[str] | None, + collection_indexing_policy: dict[str, Any] | None, + collection_vector_service_options: CollectionVectorServiceOptions | None, +) -> None: + """Check that the passed parameters do not violate the autodetect constraints.""" + forbidden_parameters = [ + p_name + for p_name, p_value in ( + ("metric", metric), + ("metadata_indexing_include", metadata_indexing_include), + ("metadata_indexing_exclude", metadata_indexing_exclude), + ("collection_indexing_policy", collection_indexing_policy), + ("collection_vector_service_options", collection_vector_service_options), + ) + if p_value is not None + ] + fp_error: str | None = None + if forbidden_parameters: + fp_error = ( + f"Parameter(s) {', '.join(forbidden_parameters)}. were provided " + "but cannot be passed." + ) + pd_error: str | None = None + if pre_delete_collection: + pd_error = "Parameter `pre_delete_collection` cannot be True." + sm_error: str | None = None + if setup_mode is not None: + sm_error = "Parameter `setup_mode` not allowed." + am_errors = [err_s for err_s in (fp_error, pd_error, sm_error) if err_s is not None] + if am_errors: + msg = f"Invalid parameters for autodetect mode: {'; '.join(am_errors)}" + raise ValueError(msg) + + class AstraDBVectorStore(VectorStore): """AstraDB vector store integration. Setup: Install the ``langchain-astradb`` package and head to the `AstraDB website `, create an account, create a - new database and `create an application token `. + new database and `create an application token `. .. code-block:: bash @@ -117,6 +188,24 @@ class AstraDBVectorStore(VectorStore): token=ASTRA_DB_APPLICATION_TOKEN, ) + Have the vector store figure out its configuration (documents scheme on DB) + from an existing collection, in the case of `server-side-embeddings `: + + .. code-block:: python + + import getpass + from langchain_astradb import AstraDBVectorStore + + ASTRA_DB_API_ENDPOINT = getpass.getpass("ASTRA_DB_API_ENDPOINT = ") + ASTRA_DB_APPLICATION_TOKEN = getpass.getpass("ASTRA_DB_APPLICATION_TOKEN = ") + + vector_store = AstraDBVectorStore( + collection_name="astra_vector_langchain", + api_endpoint=ASTRA_DB_API_ENDPOINT, + token=ASTRA_DB_APPLICATION_TOKEN, + autodetect_collection=True, + ) + Add Documents: .. code-block:: python @@ -215,7 +304,7 @@ def _filter_to_metadata(self, filter_dict: dict[str, Any] | None) -> dict[str, A if filter_dict is None: return {} - return self.document_encoder.encode_filter(filter_dict) + return self.document_codec.encode_filter(filter_dict) @staticmethod def _normalize_metadata_indexing_policy( @@ -275,36 +364,39 @@ def __init__( bulk_insert_batch_concurrency: int | None = None, bulk_insert_overwrite_concurrency: int | None = None, bulk_delete_concurrency: int | None = None, - setup_mode: SetupMode = SetupMode.SYNC, + setup_mode: SetupMode | None = None, pre_delete_collection: bool = False, metadata_indexing_include: Iterable[str] | None = None, metadata_indexing_exclude: Iterable[str] | None = None, collection_indexing_policy: dict[str, Any] | None = None, collection_vector_service_options: CollectionVectorServiceOptions | None = None, collection_embedding_api_key: str | EmbeddingHeadersProvider | None = None, + content_field: str | None = None, + ignore_invalid_documents: bool = False, + autodetect_collection: bool = False, ) -> None: """Wrapper around DataStax Astra DB for vector-store workloads. For quickstart and details, visit - https://docs.datastax.com/en/astra/astra-db-vector/ + https://docs.datastax.com/en/astra-db-serverless/index.html Args: embedding: the embeddings function or service to use. This enables client-side embedding functions or calls to external - embedding providers. If `embedding` is provided, arguments - `collection_vector_service_options` and - `collection_embedding_api_key` cannot be provided. + embedding providers. If ``embedding`` is provided, arguments + ``collection_vector_service_options`` and + ``collection_embedding_api_key`` cannot be provided. collection_name: name of the Astra DB collection to create/use. token: API token for Astra DB usage, either in the form of a string - or a subclass of `astrapy.authentication.TokenProvider`. + or a subclass of ``astrapy.authentication.TokenProvider``. If not provided, the environment variable ASTRA_DB_APPLICATION_TOKEN is inspected. api_endpoint: full URL to the API endpoint, such as - `https://-us-east1.apps.astra.datastax.com`. If not provided, + ``https://-us-east1.apps.astra.datastax.com``. If not provided, the environment variable ASTRA_DB_API_ENDPOINT is inspected. environment: a string specifying the environment of the target Data API. If omitted, defaults to "prod" (Astra DB production). - Other values are in `astrapy.constants.Environment` enum class. + Other values are in ``astrapy.constants.Environment`` enum class. astra_db_client: *DEPRECATED starting from version 0.3.5.* *Please use 'token', 'api_endpoint' and optionally 'environment'.* @@ -341,25 +433,59 @@ def __init__( collection_indexing_policy: a full "indexing" specification for what fields should be indexed for later filtering in searches. This dict must conform to to the API specifications - (see docs.datastax.com/en/astra/astra-db-vector/api-reference/ - data-api-commands.html#advanced-feature-indexing-clause-on-createcollection) + (see https://docs.datastax.com/en/astra-db-serverless/api-reference/collections.html#the-indexing-option) collection_vector_service_options: specifies the use of server-side - embeddings within Astra DB. If passing this parameter, `embedding` + embeddings within Astra DB. If passing this parameter, ``embedding`` cannot be provided. collection_embedding_api_key: for usage of server-side embeddings within Astra DB. With this parameter one can supply an API Key that will be passed to Astra DB with each data request. This parameter can be either a string or a subclass of - `astrapy.authentication.EmbeddingHeadersProvider`. + ``astrapy.authentication.EmbeddingHeadersProvider``. This is useful when the service is configured for the collection, but no corresponding secret is stored within Astra's key management system. This parameter cannot be provided without - specifying `collection_vector_service_options`. + specifying ``collection_vector_service_options``. + content_field: name of the field containing the textual content + in the documents when saved on Astra DB. For vectorize collections, + this cannot be specified; for non-vectorize collection, defaults + to "content". + The special value "*" can be passed only if autodetect_collection=True. + In this case, the actual name of the key for the textual content is + guessed by inspection of a few documents from the collection, under the + assumption that the longer strings are the most likely candidates. + Please understand the limitations of this method and get some + understanding of your data before passing ``"*"`` for this parameter. + ignore_invalid_documents: if False (default), exceptions are raised + when a document is found on the Astra DB collectin that does + not have the expected shape. If set to True, such results + from the database are ignored and a warning is issued. Note + that in this case a similarity search may end up returning fewer + results than the required ``k``. + autodetect_collection: if True, turns on autodetect behavior. + The store will look for an existing collection of the provided name + and infer the store settings from it. Default is False. + In autodetect mode, ``content_field`` can be given as ``"*"``, meaning + that an attempt will be made to determine it by inspection (unless + vectorize is enabled, in which case ``content_field`` is ignored). + In autodetect mode, the store not only determines whether embeddings + are client- or server-side, but - most importantly - switches + automatically between "nested" and "flat" representations of documents + on DB (i.e. having the metadata key-value pairs grouped in a + ``metadata`` field or spread at the documents' top-level). The former + scheme is the native mode of the AstraDBVectorStore; the store resorts + to the latter in case of vector collections populated with external + means (such as a third-party data import tool) before applying + an AstraDBVectorStore to them. + Note that the following parameters cannot be used if this is True: + ``metric``, ``setup_mode``, ``metadata_indexing_include``, + ``metadata_indexing_exclude``, ``collection_indexing_policy``, + ``collection_vector_service_options``. Note: - For concurrency in synchronous :meth:`~add_texts`:, as a rule of thumb, on a - typical client machine it is suggested to keep the quantity + For concurrency in synchronous :meth:`~add_texts`:, as a rule of thumb, + on a typical client machine it is suggested to keep the quantity bulk_insert_batch_concurrency * bulk_insert_overwrite_concurrency much below 1000 to avoid exhausting the client multithreading/networking resources. The hardcoded defaults are somewhat conservative to meet @@ -374,47 +500,23 @@ def __init__( Remember you can pass concurrency settings to individual calls to :meth:`~add_texts` and :meth:`~add_documents` as well. """ - # Embedding and the server-side embeddings are mutually exclusive, - # as both specify how to produce embeddings - if embedding is None and collection_vector_service_options is None: - msg = ( - "Either an `embedding` or a `collection_vector_service_options` " - "must be provided." - ) - raise ValueError(msg) - - if embedding is not None and collection_vector_service_options is not None: - msg = ( - "Only one of `embedding` or `collection_vector_service_options` " - "can be provided." - ) - raise ValueError(msg) - - if ( - collection_vector_service_options is None - and collection_embedding_api_key is not None - ): - msg = ( - "`collection_embedding_api_key` cannot be provided unless" - " `collection_vector_service_options` is also passed." - ) - raise ValueError(msg) - - self.embedding_dimension: int | None = None - self.embedding = embedding + # general collection settings self.collection_name = collection_name self.token = token self.api_endpoint = api_endpoint self.environment = environment self.namespace = namespace - self.collection_vector_service_options = collection_vector_service_options - self.document_encoder: _AstraDBVectorStoreDocumentEncoder - if self.collection_vector_service_options is not None: - self.document_encoder = _DefaultVectorizeVSDocumentEncoder() - else: - self.document_encoder = _DefaultVSDocumentEncoder() + self.indexing_policy: dict[str, Any] + self.autodetect_collection = autodetect_collection + # vector-related settings + self.embedding_dimension: int | None = None + self.embedding = embedding + self.metric = metric self.collection_embedding_api_key = collection_embedding_api_key - # Concurrency settings + self.collection_vector_service_options = collection_vector_service_options + # DB-encoding settings: + self.document_codec: _AstraDBVectorStoreDocumentCodec + # concurrency settings self.batch_size: int | None = batch_size or DEFAULT_DOCUMENT_CHUNK_SIZE self.bulk_insert_batch_concurrency: int = ( bulk_insert_batch_concurrency or MAX_CONCURRENT_DOCUMENT_INSERTIONS @@ -425,21 +527,111 @@ def __init__( self.bulk_delete_concurrency: int = ( bulk_delete_concurrency or MAX_CONCURRENT_DOCUMENT_DELETIONS ) - # "vector-related" settings - self.metric = metric - embedding_dimension_m: int | Awaitable[int] | None = None - if self.embedding is not None: - if setup_mode == SetupMode.ASYNC: - embedding_dimension_m = self._aget_embedding_dimension() - elif setup_mode in (SetupMode.SYNC, SetupMode.OFF): - embedding_dimension_m = self._get_embedding_dimension() - - # indexing policy setting - self.indexing_policy: dict[str, Any] = self._normalize_metadata_indexing_policy( - metadata_indexing_include=metadata_indexing_include, - metadata_indexing_exclude=metadata_indexing_exclude, - collection_indexing_policy=collection_indexing_policy, - ) + + _setup_mode: SetupMode + _embedding_dimension: int | Awaitable[int] | None + + if not self.autodetect_collection: + logger.info( + "vector store default init, collection '%s'", self.collection_name + ) + _setup_mode = SetupMode.SYNC if setup_mode is None else setup_mode + _embedding_dimension = self._prepare_embedding_dimension(_setup_mode) + # determine vectorize/nonvectorize + has_vectorize = self.collection_vector_service_options is not None + _content_field = _normalize_content_field( + content_field, + is_autodetect=False, + has_vectorize=has_vectorize, + ) + + if self.collection_vector_service_options is not None: + self.document_codec = _DefaultVectorizeVSDocumentCodec( + ignore_invalid_documents=ignore_invalid_documents, + ) + else: + self.document_codec = _DefaultVSDocumentCodec( + content_field=_content_field, + ignore_invalid_documents=ignore_invalid_documents, + ) + # indexing policy setting + self.indexing_policy = self._normalize_metadata_indexing_policy( + metadata_indexing_include=metadata_indexing_include, + metadata_indexing_exclude=metadata_indexing_exclude, + collection_indexing_policy=collection_indexing_policy, + ) + else: + logger.info( + "vector store autodetect init, collection '%s'", self.collection_name + ) + # specific checks for autodetect logic + _validate_autodetect_init_params( + metric=self.metric, + setup_mode=setup_mode, + pre_delete_collection=pre_delete_collection, + metadata_indexing_include=metadata_indexing_include, + metadata_indexing_exclude=metadata_indexing_exclude, + collection_indexing_policy=collection_indexing_policy, + collection_vector_service_options=self.collection_vector_service_options, + ) + _setup_mode = SetupMode.OFF + + # fetch collection intelligence + c_descriptor, c_documents = _survey_collection( + collection_name=self.collection_name, + token=self.token, + api_endpoint=self.api_endpoint, + environment=self.environment, + astra_db_client=astra_db_client, + async_astra_db_client=async_astra_db_client, + namespace=self.namespace, + ) + if c_descriptor is None: + msg = f"Collection '{self.collection_name}' not found." + raise ValueError(msg) + # use the collection info to set the store properties + self.indexing_policy = self._normalize_metadata_indexing_policy( + metadata_indexing_include=None, + metadata_indexing_exclude=None, + collection_indexing_policy=c_descriptor.options.indexing, + ) + if c_descriptor.options.vector is None: + msg = "Non-vector collection detected." + raise ValueError(msg) + _embedding_dimension = c_descriptor.options.vector.dimension + self.collection_vector_service_options = c_descriptor.options.vector.service + has_vectorize = self.collection_vector_service_options is not None + logger.info("vector store autodetect: has_vectorize = %s", has_vectorize) + norm_content_field = _normalize_content_field( + content_field, + is_autodetect=True, + has_vectorize=has_vectorize, + ) + self.document_codec = _detect_document_codec( + c_documents, + has_vectorize=has_vectorize, + ignore_invalid_documents=ignore_invalid_documents, + norm_content_field=norm_content_field, + ) + + # validate embedding/vectorize compatibility and such. + # Embedding and the server-side embeddings are mutually exclusive, + # as both specify how to produce embeddings. + # Also API key makes no sense unless vectorize. + if self.embedding is None and not self.document_codec.server_side_embeddings: + msg = "Embedding is required for non-vectorize collections." + raise ValueError(msg) + + if self.embedding is not None and self.document_codec.server_side_embeddings: + msg = "Embedding cannot be provided for vectorize collections." + raise ValueError(msg) + + if ( + not self.document_codec.server_side_embeddings + and self.collection_embedding_api_key is not None + ): + msg = "Embedding API Key cannot be provided for non-vectorize collections." + raise ValueError(msg) self.astra_env = _AstraDBCollectionEnvironment( collection_name=collection_name, @@ -449,9 +641,9 @@ def __init__( astra_db_client=astra_db_client, async_astra_db_client=async_astra_db_client, namespace=self.namespace, - setup_mode=setup_mode, + setup_mode=_setup_mode, pre_delete_collection=pre_delete_collection, - embedding_dimension=embedding_dimension_m, + embedding_dimension=_embedding_dimension, metric=self.metric, requested_indexing_policy=self.indexing_policy, default_indexing_policy=DEFAULT_INDEXING_OPTIONS, @@ -465,19 +657,28 @@ def _get_safe_embedding(self) -> Embeddings: raise ValueError(msg) return self.embedding - def _get_embedding_dimension(self) -> int: - if self.embedding_dimension is None: - self.embedding_dimension = len( - self._get_safe_embedding().embed_query( - text="This is a sample sentence." - ) - ) - return self.embedding_dimension + def _prepare_embedding_dimension( + self, setup_mode: SetupMode + ) -> int | Awaitable[int] | None: + """Return the right kind of object for the astra_env to use.""" + if self.embedding is None: + return None + if setup_mode == SetupMode.ASYNC: + # in this case, we wrap the computation as an awaitable + async def _aget_embedding_dimension() -> int: + if self.embedding_dimension is None: + self.embedding_dimension = len( + await self._get_safe_embedding().aembed_query( + text="This is a sample sentence." + ) + ) + return self.embedding_dimension - async def _aget_embedding_dimension(self) -> int: + return _aget_embedding_dimension() + # case of setup_mode = SetupMode.SYNC, SetupMode.OFF if self.embedding_dimension is None: self.embedding_dimension = len( - await self._get_safe_embedding().aembed_query( + self._get_safe_embedding().embed_query( text="This is a sample sentence." ) ) @@ -648,7 +849,7 @@ def _get_documents_to_insert( if metadatas is None: metadatas = [{} for _ in texts] documents_to_insert = [ - self.document_encoder.encode( + self.document_codec.encode( content=b_txt, document_id=b_id, vector=b_emb, @@ -731,9 +932,9 @@ def add_texts( Note: There are constraints on the allowed field names in the metadata dictionaries, coming from the underlying Astra DB API. - For instance, the `$` (dollar sign) cannot be used in the dict keys. + For instance, the ``$`` (dollar sign) cannot be used in the dict keys. See this document for details: - https://docs.datastax.com/en/astra/astra-db-vector/api-reference/data-api.html + https://docs.datastax.com/en/astra-db-serverless/api-reference/overview.html#limits Returns: The list of ids of the added texts. @@ -748,7 +949,7 @@ def add_texts( self.astra_env.ensure_db_setup() embedding_vectors: Sequence[list[float] | None] - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: embedding_vectors = [None for _ in list(texts)] else: embedding_vectors = self._get_safe_embedding().embed_documents(list(texts)) @@ -853,9 +1054,9 @@ async def aadd_texts( Note: There are constraints on the allowed field names in the metadata dictionaries, coming from the underlying Astra DB API. - For instance, the `$` (dollar sign) cannot be used in the dict keys. + For instance, the ``$`` (dollar sign) cannot be used in the dict keys. See this document for details: - https://docs.datastax.com/en/astra/astra-db-vector/api-reference/data-api.html + https://docs.datastax.com/en/astra-db-serverless/api-reference/overview.html#limits Returns: The list of ids of the added texts. @@ -870,7 +1071,7 @@ async def aadd_texts( await self.astra_env.aensure_db_setup() embedding_vectors: Sequence[list[float] | None] - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: embedding_vectors = [None for _ in list(texts)] else: embedding_vectors = await self._get_safe_embedding().aembed_documents( @@ -1013,7 +1214,7 @@ def similarity_search_with_score_id( Returns: The list of (Document, score, id), the most similar to the query. """ - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: sort = {"$vectorize": query} return self._similarity_search_with_score_id_by_sort( sort=sort, @@ -1097,7 +1298,7 @@ def similarity_search_with_score_id_by_vector( Returns: The list of (Document, score, id), the most similar to the query vector. """ - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: msg = ( "Searching by vector on a Vector Store that uses server-side " "embeddings is not allowed." @@ -1121,18 +1322,22 @@ def _similarity_search_with_score_id_by_sort( metadata_parameter = self._filter_to_metadata(filter) hits_ite = self.astra_env.collection.find( filter=metadata_parameter, - projection=self.document_encoder.base_projection, + projection=self.document_codec.base_projection, limit=k, include_similarity=True, sort=sort, ) return [ - ( - self.document_encoder.decode(hit), - hit["$similarity"], - hit["_id"], + (doc, sim, did) + for (doc, sim, did) in ( + ( + self.document_codec.decode(hit), + hit["$similarity"], + hit["_id"], + ) + for hit in hits_ite ) - for hit in hits_ite + if doc is not None ] @override @@ -1205,7 +1410,7 @@ async def asimilarity_search_with_score_id( Returns: The list of (Document, score, id), the most similar to the query. """ - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: sort = {"$vectorize": query} return await self._asimilarity_search_with_score_id_by_sort( sort=sort, @@ -1289,7 +1494,7 @@ async def asimilarity_search_with_score_id_by_vector( Returns: The list of (Document, score, id), the most similar to the query vector. """ - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: msg = ( "Searching by vector on a Vector Store that uses server-side " "embeddings is not allowed." @@ -1312,18 +1517,22 @@ async def _asimilarity_search_with_score_id_by_sort( await self.astra_env.aensure_db_setup() metadata_parameter = self._filter_to_metadata(filter) return [ - ( - self.document_encoder.decode(hit), - hit["$similarity"], - hit["_id"], - ) - async for hit in self.astra_env.async_collection.find( - filter=metadata_parameter, - projection=self.document_encoder.base_projection, - limit=k, - include_similarity=True, - sort=sort, + (doc, sim, did) + async for (doc, sim, did) in ( + ( + self.document_codec.decode(hit), + hit["$similarity"], + hit["_id"], + ) + async for hit in self.astra_env.async_collection.find( + filter=metadata_parameter, + projection=self.document_codec.base_projection, + limit=k, + include_similarity=True, + sort=sort, + ) ) + if doc is not None ] def _run_mmr_query_by_sort( @@ -1336,7 +1545,7 @@ def _run_mmr_query_by_sort( ) -> list[Document]: prefetch_cursor = self.astra_env.collection.find( filter=metadata_parameter, - projection=self.document_encoder.full_projection, + projection=self.document_codec.full_projection, limit=fetch_k, include_similarity=True, include_sort_vector=True, @@ -1361,7 +1570,7 @@ async def _arun_mmr_query_by_sort( ) -> list[Document]: prefetch_cursor = self.astra_env.async_collection.find( filter=metadata_parameter, - projection=self.document_encoder.full_projection, + projection=self.document_codec.full_projection, limit=fetch_k, include_similarity=True, include_sort_vector=True, @@ -1394,7 +1603,11 @@ def _get_mmr_hits( for prefetch_index, prefetch_hit in enumerate(prefetch_hits) if prefetch_index in mmr_chosen_indices ] - return [self.document_encoder.decode(hit) for hit in mmr_hits] + return [ + doc + for doc in (self.document_codec.decode(hit) for hit in mmr_hits) + if doc is not None + ] @override def max_marginal_relevance_search_by_vector( @@ -1502,7 +1715,7 @@ def max_marginal_relevance_search( Returns: The list of Documents selected by maximal marginal relevance. """ - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: # this case goes directly to the "_by_sort" method # (and does its own filter normalization, as it cannot # use the path for the with-embedding mmr querying) @@ -1553,7 +1766,7 @@ async def amax_marginal_relevance_search( Returns: The list of Documents selected by maximal marginal relevance. """ - if self.document_encoder.server_side_embeddings: + if self.document_codec.server_side_embeddings: # this case goes directly to the "_by_sort" method # (and does its own filter normalization, as it cannot # use the path for the with-embedding mmr querying) @@ -1619,12 +1832,13 @@ def from_texts( metadatas: metadata dicts for the texts. ids: ids to associate to the texts. **kwargs: you can pass any argument that you would - to :meth:`~add_texts` and/or to the 'AstraDBVectorStore' constructor - (see these methods for details). These arguments will be + to :meth:`~add_texts` and/or to the + ``AstraDBVectorStore`` constructor (see these methods for + details). These arguments will be routed to the respective methods as they are. Returns: - an `AstraDBVectorStore` vectorstore. + an ``AstraDBVectorStore`` vectorstore. """ _add_texts_inspection = inspect.getfullargspec(AstraDBVectorStore.add_texts) _method_args = ( @@ -1663,12 +1877,12 @@ async def afrom_texts( metadatas: metadata dicts for the texts. ids: ids to associate to the texts. **kwargs: you can pass any argument that you would - to :meth:`~aadd_texts` and/or to the 'AstraDBVectorStore' constructor - (see these methods for details). These arguments will be - routed to the respective methods as they are. + to :meth:`~aadd_texts` and/or to the ``AstraDBVectorStore`` + constructor (see these methods for details). These arguments + will be routed to the respective methods as they are. Returns: - an `AstraDBVectorStore` vectorstore. + an ``AstraDBVectorStore`` vectorstore. """ _aadd_texts_inspection = inspect.getfullargspec(AstraDBVectorStore.aadd_texts) _method_args = ( @@ -1699,13 +1913,20 @@ def from_documents( ) -> AstraDBVectorStore: """Create an Astra DB vectorstore from a document list. - Utility method that defers to 'from_texts' (see that one). + Utility method that defers to :meth:`from_texts` (see that one). - Args: see 'from_texts', except here you have to supply 'documents' - in place of 'texts' and 'metadatas'. + Args: + texts: the texts to insert. + documents: a list of `Document` objects for insertion in the store. + embedding: the embedding function to use in the store. + **kwargs: you can pass any argument that you would + to :meth:`~add_texts` and/or to the + ``AstraDBVectorStore`` constructor (see these methods for + details). These arguments will be + routed to the respective methods as they are. Returns: - an `AstraDBVectorStore` vectorstore. + an ``AstraDBVectorStore`` vectorstore. """ texts = [d.page_content for d in documents] metadatas = [d.metadata for d in documents] @@ -1725,13 +1946,13 @@ async def afrom_documents( ) -> AstraDBVectorStore: """Create an Astra DB vectorstore from a document list. - Utility method that defers to 'afrom_texts' (see that one). + Utility method that defers to :meth:`afrom_texts` (see that one). - Args: see 'afrom_texts', except here you have to supply 'documents' - in place of 'texts' and 'metadatas'. + Args: see :meth:`afrom_texts`, except here you have to supply ``documents`` + in place of ``texts`` and ``metadatas``. Returns: - an `AstraDBVectorStore` vectorstore. + an ``AstraDBVectorStore`` vectorstore. """ texts = [d.page_content for d in documents] metadatas = [d.metadata for d in documents] diff --git a/libs/astradb/poetry.lock b/libs/astradb/poetry.lock index 990b637..f859124 100644 --- a/libs/astradb/poetry.lock +++ b/libs/astradb/poetry.lock @@ -1,91 +1,118 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. + +[[package]] +name = "aiohappyeyeballs" +version = "2.4.0" +description = "Happy Eyeballs for asyncio" +optional = false +python-versions = ">=3.8" +files = [ + {file = "aiohappyeyeballs-2.4.0-py3-none-any.whl", hash = "sha256:7ce92076e249169a13c2f49320d1967425eaf1f407522d707d59cac7628d62bd"}, + {file = "aiohappyeyeballs-2.4.0.tar.gz", hash = "sha256:55a1714f084e63d49639800f95716da97a1f173d46a16dfcfda0016abb93b6b2"}, +] [[package]] name = "aiohttp" -version = "3.9.5" +version = "3.10.5" description = "Async http client/server framework (asyncio)" optional = false python-versions = ">=3.8" files = [ - {file = "aiohttp-3.9.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:fcde4c397f673fdec23e6b05ebf8d4751314fa7c24f93334bf1f1364c1c69ac7"}, - {file = "aiohttp-3.9.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:5d6b3f1fabe465e819aed2c421a6743d8debbde79b6a8600739300630a01bf2c"}, - {file = "aiohttp-3.9.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:6ae79c1bc12c34082d92bf9422764f799aee4746fd7a392db46b7fd357d4a17a"}, - {file = "aiohttp-3.9.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4d3ebb9e1316ec74277d19c5f482f98cc65a73ccd5430540d6d11682cd857430"}, - {file = "aiohttp-3.9.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:84dabd95154f43a2ea80deffec9cb44d2e301e38a0c9d331cc4aa0166fe28ae3"}, - {file = "aiohttp-3.9.5-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c8a02fbeca6f63cb1f0475c799679057fc9268b77075ab7cf3f1c600e81dd46b"}, - {file = "aiohttp-3.9.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c26959ca7b75ff768e2776d8055bf9582a6267e24556bb7f7bd29e677932be72"}, - {file = "aiohttp-3.9.5-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:714d4e5231fed4ba2762ed489b4aec07b2b9953cf4ee31e9871caac895a839c0"}, - {file = "aiohttp-3.9.5-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:e7a6a8354f1b62e15d48e04350f13e726fa08b62c3d7b8401c0a1314f02e3558"}, - {file = "aiohttp-3.9.5-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:c413016880e03e69d166efb5a1a95d40f83d5a3a648d16486592c49ffb76d0db"}, - {file = "aiohttp-3.9.5-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:ff84aeb864e0fac81f676be9f4685f0527b660f1efdc40dcede3c251ef1e867f"}, - {file = "aiohttp-3.9.5-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:ad7f2919d7dac062f24d6f5fe95d401597fbb015a25771f85e692d043c9d7832"}, - {file = "aiohttp-3.9.5-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:702e2c7c187c1a498a4e2b03155d52658fdd6fda882d3d7fbb891a5cf108bb10"}, - {file = "aiohttp-3.9.5-cp310-cp310-win32.whl", hash = "sha256:67c3119f5ddc7261d47163ed86d760ddf0e625cd6246b4ed852e82159617b5fb"}, - {file = "aiohttp-3.9.5-cp310-cp310-win_amd64.whl", hash = "sha256:471f0ef53ccedec9995287f02caf0c068732f026455f07db3f01a46e49d76bbb"}, - {file = "aiohttp-3.9.5-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:e0ae53e33ee7476dd3d1132f932eeb39bf6125083820049d06edcdca4381f342"}, - {file = "aiohttp-3.9.5-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c088c4d70d21f8ca5c0b8b5403fe84a7bc8e024161febdd4ef04575ef35d474d"}, - {file = "aiohttp-3.9.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:639d0042b7670222f33b0028de6b4e2fad6451462ce7df2af8aee37dcac55424"}, - {file = "aiohttp-3.9.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f26383adb94da5e7fb388d441bf09c61e5e35f455a3217bfd790c6b6bc64b2ee"}, - {file = "aiohttp-3.9.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:66331d00fb28dc90aa606d9a54304af76b335ae204d1836f65797d6fe27f1ca2"}, - {file = "aiohttp-3.9.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4ff550491f5492ab5ed3533e76b8567f4b37bd2995e780a1f46bca2024223233"}, - {file = "aiohttp-3.9.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f22eb3a6c1080d862befa0a89c380b4dafce29dc6cd56083f630073d102eb595"}, - {file = "aiohttp-3.9.5-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:a81b1143d42b66ffc40a441379387076243ef7b51019204fd3ec36b9f69e77d6"}, - {file = "aiohttp-3.9.5-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:f64fd07515dad67f24b6ea4a66ae2876c01031de91c93075b8093f07c0a2d93d"}, - {file = "aiohttp-3.9.5-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:93e22add827447d2e26d67c9ac0161756007f152fdc5210277d00a85f6c92323"}, - {file = "aiohttp-3.9.5-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:55b39c8684a46e56ef8c8d24faf02de4a2b2ac60d26cee93bc595651ff545de9"}, - {file = "aiohttp-3.9.5-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:4715a9b778f4293b9f8ae7a0a7cef9829f02ff8d6277a39d7f40565c737d3771"}, - {file = "aiohttp-3.9.5-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:afc52b8d969eff14e069a710057d15ab9ac17cd4b6753042c407dcea0e40bf75"}, - {file = "aiohttp-3.9.5-cp311-cp311-win32.whl", hash = "sha256:b3df71da99c98534be076196791adca8819761f0bf6e08e07fd7da25127150d6"}, - {file = "aiohttp-3.9.5-cp311-cp311-win_amd64.whl", hash = "sha256:88e311d98cc0bf45b62fc46c66753a83445f5ab20038bcc1b8a1cc05666f428a"}, - {file = "aiohttp-3.9.5-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:c7a4b7a6cf5b6eb11e109a9755fd4fda7d57395f8c575e166d363b9fc3ec4678"}, - {file = "aiohttp-3.9.5-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:0a158704edf0abcac8ac371fbb54044f3270bdbc93e254a82b6c82be1ef08f3c"}, - {file = "aiohttp-3.9.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:d153f652a687a8e95ad367a86a61e8d53d528b0530ef382ec5aaf533140ed00f"}, - {file = "aiohttp-3.9.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:82a6a97d9771cb48ae16979c3a3a9a18b600a8505b1115cfe354dfb2054468b4"}, - {file = "aiohttp-3.9.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:60cdbd56f4cad9f69c35eaac0fbbdf1f77b0ff9456cebd4902f3dd1cf096464c"}, - {file = "aiohttp-3.9.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8676e8fd73141ded15ea586de0b7cda1542960a7b9ad89b2b06428e97125d4fa"}, - {file = "aiohttp-3.9.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da00da442a0e31f1c69d26d224e1efd3a1ca5bcbf210978a2ca7426dfcae9f58"}, - {file = "aiohttp-3.9.5-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:18f634d540dd099c262e9f887c8bbacc959847cfe5da7a0e2e1cf3f14dbf2daf"}, - {file = "aiohttp-3.9.5-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:320e8618eda64e19d11bdb3bd04ccc0a816c17eaecb7e4945d01deee2a22f95f"}, - {file = "aiohttp-3.9.5-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:2faa61a904b83142747fc6a6d7ad8fccff898c849123030f8e75d5d967fd4a81"}, - {file = "aiohttp-3.9.5-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:8c64a6dc3fe5db7b1b4d2b5cb84c4f677768bdc340611eca673afb7cf416ef5a"}, - {file = "aiohttp-3.9.5-cp312-cp312-musllinux_1_1_s390x.whl", hash = "sha256:393c7aba2b55559ef7ab791c94b44f7482a07bf7640d17b341b79081f5e5cd1a"}, - {file = "aiohttp-3.9.5-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:c671dc117c2c21a1ca10c116cfcd6e3e44da7fcde37bf83b2be485ab377b25da"}, - {file = "aiohttp-3.9.5-cp312-cp312-win32.whl", hash = "sha256:5a7ee16aab26e76add4afc45e8f8206c95d1d75540f1039b84a03c3b3800dd59"}, - {file = "aiohttp-3.9.5-cp312-cp312-win_amd64.whl", hash = "sha256:5ca51eadbd67045396bc92a4345d1790b7301c14d1848feaac1d6a6c9289e888"}, - {file = "aiohttp-3.9.5-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:694d828b5c41255e54bc2dddb51a9f5150b4eefa9886e38b52605a05d96566e8"}, - {file = "aiohttp-3.9.5-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:0605cc2c0088fcaae79f01c913a38611ad09ba68ff482402d3410bf59039bfb8"}, - {file = "aiohttp-3.9.5-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4558e5012ee03d2638c681e156461d37b7a113fe13970d438d95d10173d25f78"}, - {file = "aiohttp-3.9.5-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9dbc053ac75ccc63dc3a3cc547b98c7258ec35a215a92bd9f983e0aac95d3d5b"}, - {file = "aiohttp-3.9.5-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4109adee842b90671f1b689901b948f347325045c15f46b39797ae1bf17019de"}, - {file = "aiohttp-3.9.5-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a6ea1a5b409a85477fd8e5ee6ad8f0e40bf2844c270955e09360418cfd09abac"}, - {file = "aiohttp-3.9.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f3c2890ca8c59ee683fd09adf32321a40fe1cf164e3387799efb2acebf090c11"}, - {file = "aiohttp-3.9.5-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3916c8692dbd9d55c523374a3b8213e628424d19116ac4308e434dbf6d95bbdd"}, - {file = "aiohttp-3.9.5-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:8d1964eb7617907c792ca00b341b5ec3e01ae8c280825deadbbd678447b127e1"}, - {file = "aiohttp-3.9.5-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:d5ab8e1f6bee051a4bf6195e38a5c13e5e161cb7bad83d8854524798bd9fcd6e"}, - {file = "aiohttp-3.9.5-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:52c27110f3862a1afbcb2af4281fc9fdc40327fa286c4625dfee247c3ba90156"}, - {file = "aiohttp-3.9.5-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:7f64cbd44443e80094309875d4f9c71d0401e966d191c3d469cde4642bc2e031"}, - {file = "aiohttp-3.9.5-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:8b4f72fbb66279624bfe83fd5eb6aea0022dad8eec62b71e7bf63ee1caadeafe"}, - {file = "aiohttp-3.9.5-cp38-cp38-win32.whl", hash = "sha256:6380c039ec52866c06d69b5c7aad5478b24ed11696f0e72f6b807cfb261453da"}, - {file = "aiohttp-3.9.5-cp38-cp38-win_amd64.whl", hash = "sha256:da22dab31d7180f8c3ac7c7635f3bcd53808f374f6aa333fe0b0b9e14b01f91a"}, - {file = "aiohttp-3.9.5-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:1732102949ff6087589408d76cd6dea656b93c896b011ecafff418c9661dc4ed"}, - {file = "aiohttp-3.9.5-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c6021d296318cb6f9414b48e6a439a7f5d1f665464da507e8ff640848ee2a58a"}, - {file = "aiohttp-3.9.5-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:239f975589a944eeb1bad26b8b140a59a3a320067fb3cd10b75c3092405a1372"}, - {file = "aiohttp-3.9.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3b7b30258348082826d274504fbc7c849959f1989d86c29bc355107accec6cfb"}, - {file = "aiohttp-3.9.5-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:cd2adf5c87ff6d8b277814a28a535b59e20bfea40a101db6b3bdca7e9926bc24"}, - {file = "aiohttp-3.9.5-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e9a3d838441bebcf5cf442700e3963f58b5c33f015341f9ea86dcd7d503c07e2"}, - {file = "aiohttp-3.9.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9e3a1ae66e3d0c17cf65c08968a5ee3180c5a95920ec2731f53343fac9bad106"}, - {file = "aiohttp-3.9.5-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:9c69e77370cce2d6df5d12b4e12bdcca60c47ba13d1cbbc8645dd005a20b738b"}, - {file = "aiohttp-3.9.5-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:0cbf56238f4bbf49dab8c2dc2e6b1b68502b1e88d335bea59b3f5b9f4c001475"}, - {file = "aiohttp-3.9.5-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:d1469f228cd9ffddd396d9948b8c9cd8022b6d1bf1e40c6f25b0fb90b4f893ed"}, - {file = "aiohttp-3.9.5-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:45731330e754f5811c314901cebdf19dd776a44b31927fa4b4dbecab9e457b0c"}, - {file = "aiohttp-3.9.5-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:3fcb4046d2904378e3aeea1df51f697b0467f2aac55d232c87ba162709478c46"}, - {file = "aiohttp-3.9.5-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:8cf142aa6c1a751fcb364158fd710b8a9be874b81889c2bd13aa8893197455e2"}, - {file = "aiohttp-3.9.5-cp39-cp39-win32.whl", hash = "sha256:7b179eea70833c8dee51ec42f3b4097bd6370892fa93f510f76762105568cf09"}, - {file = "aiohttp-3.9.5-cp39-cp39-win_amd64.whl", hash = "sha256:38d80498e2e169bc61418ff36170e0aad0cd268da8b38a17c4cf29d254a8b3f1"}, - {file = "aiohttp-3.9.5.tar.gz", hash = "sha256:edea7d15772ceeb29db4aff55e482d4bcfb6ae160ce144f2682de02f6d693551"}, + {file = "aiohttp-3.10.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:18a01eba2574fb9edd5f6e5fb25f66e6ce061da5dab5db75e13fe1558142e0a3"}, + {file = "aiohttp-3.10.5-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:94fac7c6e77ccb1ca91e9eb4cb0ac0270b9fb9b289738654120ba8cebb1189c6"}, + {file = "aiohttp-3.10.5-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2f1f1c75c395991ce9c94d3e4aa96e5c59c8356a15b1c9231e783865e2772699"}, + {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4f7acae3cf1a2a2361ec4c8e787eaaa86a94171d2417aae53c0cca6ca3118ff6"}, + {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:94c4381ffba9cc508b37d2e536b418d5ea9cfdc2848b9a7fea6aebad4ec6aac1"}, + {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c31ad0c0c507894e3eaa843415841995bf8de4d6b2d24c6e33099f4bc9fc0d4f"}, + {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0912b8a8fadeb32ff67a3ed44249448c20148397c1ed905d5dac185b4ca547bb"}, + {file = "aiohttp-3.10.5-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0d93400c18596b7dc4794d48a63fb361b01a0d8eb39f28800dc900c8fbdaca91"}, + {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d00f3c5e0d764a5c9aa5a62d99728c56d455310bcc288a79cab10157b3af426f"}, + {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:d742c36ed44f2798c8d3f4bc511f479b9ceef2b93f348671184139e7d708042c"}, + {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:814375093edae5f1cb31e3407997cf3eacefb9010f96df10d64829362ae2df69"}, + {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:8224f98be68a84b19f48e0bdc14224b5a71339aff3a27df69989fa47d01296f3"}, + {file = "aiohttp-3.10.5-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:d9a487ef090aea982d748b1b0d74fe7c3950b109df967630a20584f9a99c0683"}, + {file = "aiohttp-3.10.5-cp310-cp310-win32.whl", hash = "sha256:d9ef084e3dc690ad50137cc05831c52b6ca428096e6deb3c43e95827f531d5ef"}, + {file = "aiohttp-3.10.5-cp310-cp310-win_amd64.whl", hash = "sha256:66bf9234e08fe561dccd62083bf67400bdbf1c67ba9efdc3dac03650e97c6088"}, + {file = "aiohttp-3.10.5-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:8c6a4e5e40156d72a40241a25cc226051c0a8d816610097a8e8f517aeacd59a2"}, + {file = "aiohttp-3.10.5-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2c634a3207a5445be65536d38c13791904fda0748b9eabf908d3fe86a52941cf"}, + {file = "aiohttp-3.10.5-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:4aff049b5e629ef9b3e9e617fa6e2dfeda1bf87e01bcfecaf3949af9e210105e"}, + {file = "aiohttp-3.10.5-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1942244f00baaacaa8155eca94dbd9e8cc7017deb69b75ef67c78e89fdad3c77"}, + {file = "aiohttp-3.10.5-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:e04a1f2a65ad2f93aa20f9ff9f1b672bf912413e5547f60749fa2ef8a644e061"}, + {file = "aiohttp-3.10.5-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7f2bfc0032a00405d4af2ba27f3c429e851d04fad1e5ceee4080a1c570476697"}, + {file = "aiohttp-3.10.5-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:424ae21498790e12eb759040bbb504e5e280cab64693d14775c54269fd1d2bb7"}, + {file = "aiohttp-3.10.5-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:975218eee0e6d24eb336d0328c768ebc5d617609affaca5dbbd6dd1984f16ed0"}, + {file = "aiohttp-3.10.5-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:4120d7fefa1e2d8fb6f650b11489710091788de554e2b6f8347c7a20ceb003f5"}, + {file = "aiohttp-3.10.5-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:b90078989ef3fc45cf9221d3859acd1108af7560c52397ff4ace8ad7052a132e"}, + {file = "aiohttp-3.10.5-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:ba5a8b74c2a8af7d862399cdedce1533642fa727def0b8c3e3e02fcb52dca1b1"}, + {file = "aiohttp-3.10.5-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:02594361128f780eecc2a29939d9dfc870e17b45178a867bf61a11b2a4367277"}, + {file = "aiohttp-3.10.5-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:8fb4fc029e135859f533025bc82047334e24b0d489e75513144f25408ecaf058"}, + {file = "aiohttp-3.10.5-cp311-cp311-win32.whl", hash = "sha256:e1ca1ef5ba129718a8fc827b0867f6aa4e893c56eb00003b7367f8a733a9b072"}, + {file = "aiohttp-3.10.5-cp311-cp311-win_amd64.whl", hash = "sha256:349ef8a73a7c5665cca65c88ab24abe75447e28aa3bc4c93ea5093474dfdf0ff"}, + {file = "aiohttp-3.10.5-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:305be5ff2081fa1d283a76113b8df7a14c10d75602a38d9f012935df20731487"}, + {file = "aiohttp-3.10.5-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:3a1c32a19ee6bbde02f1cb189e13a71b321256cc1d431196a9f824050b160d5a"}, + {file = "aiohttp-3.10.5-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:61645818edd40cc6f455b851277a21bf420ce347baa0b86eaa41d51ef58ba23d"}, + {file = "aiohttp-3.10.5-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6c225286f2b13bab5987425558baa5cbdb2bc925b2998038fa028245ef421e75"}, + {file = "aiohttp-3.10.5-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8ba01ebc6175e1e6b7275c907a3a36be48a2d487549b656aa90c8a910d9f3178"}, + {file = "aiohttp-3.10.5-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8eaf44ccbc4e35762683078b72bf293f476561d8b68ec8a64f98cf32811c323e"}, + {file = "aiohttp-3.10.5-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b1c43eb1ab7cbf411b8e387dc169acb31f0ca0d8c09ba63f9eac67829585b44f"}, + {file = "aiohttp-3.10.5-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:de7a5299827253023c55ea549444e058c0eb496931fa05d693b95140a947cb73"}, + {file = "aiohttp-3.10.5-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:4790f0e15f00058f7599dab2b206d3049d7ac464dc2e5eae0e93fa18aee9e7bf"}, + {file = "aiohttp-3.10.5-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:44b324a6b8376a23e6ba25d368726ee3bc281e6ab306db80b5819999c737d820"}, + {file = "aiohttp-3.10.5-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:0d277cfb304118079e7044aad0b76685d30ecb86f83a0711fc5fb257ffe832ca"}, + {file = "aiohttp-3.10.5-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:54d9ddea424cd19d3ff6128601a4a4d23d54a421f9b4c0fff740505813739a91"}, + {file = "aiohttp-3.10.5-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:4f1c9866ccf48a6df2b06823e6ae80573529f2af3a0992ec4fe75b1a510df8a6"}, + {file = "aiohttp-3.10.5-cp312-cp312-win32.whl", hash = "sha256:dc4826823121783dccc0871e3f405417ac116055bf184ac04c36f98b75aacd12"}, + {file = "aiohttp-3.10.5-cp312-cp312-win_amd64.whl", hash = "sha256:22c0a23a3b3138a6bf76fc553789cb1a703836da86b0f306b6f0dc1617398abc"}, + {file = "aiohttp-3.10.5-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:7f6b639c36734eaa80a6c152a238242bedcee9b953f23bb887e9102976343092"}, + {file = "aiohttp-3.10.5-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:f29930bc2921cef955ba39a3ff87d2c4398a0394ae217f41cb02d5c26c8b1b77"}, + {file = "aiohttp-3.10.5-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:f489a2c9e6455d87eabf907ac0b7d230a9786be43fbe884ad184ddf9e9c1e385"}, + {file = "aiohttp-3.10.5-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:123dd5b16b75b2962d0fff566effb7a065e33cd4538c1692fb31c3bda2bfb972"}, + {file = "aiohttp-3.10.5-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b98e698dc34966e5976e10bbca6d26d6724e6bdea853c7c10162a3235aba6e16"}, + {file = "aiohttp-3.10.5-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c3b9162bab7e42f21243effc822652dc5bb5e8ff42a4eb62fe7782bcbcdfacf6"}, + {file = "aiohttp-3.10.5-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1923a5c44061bffd5eebeef58cecf68096e35003907d8201a4d0d6f6e387ccaa"}, + {file = "aiohttp-3.10.5-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d55f011da0a843c3d3df2c2cf4e537b8070a419f891c930245f05d329c4b0689"}, + {file = "aiohttp-3.10.5-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:afe16a84498441d05e9189a15900640a2d2b5e76cf4efe8cbb088ab4f112ee57"}, + {file = "aiohttp-3.10.5-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:f8112fb501b1e0567a1251a2fd0747baae60a4ab325a871e975b7bb67e59221f"}, + {file = "aiohttp-3.10.5-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:1e72589da4c90337837fdfe2026ae1952c0f4a6e793adbbfbdd40efed7c63599"}, + {file = "aiohttp-3.10.5-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:4d46c7b4173415d8e583045fbc4daa48b40e31b19ce595b8d92cf639396c15d5"}, + {file = "aiohttp-3.10.5-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:33e6bc4bab477c772a541f76cd91e11ccb6d2efa2b8d7d7883591dfb523e5987"}, + {file = "aiohttp-3.10.5-cp313-cp313-win32.whl", hash = "sha256:c58c6837a2c2a7cf3133983e64173aec11f9c2cd8e87ec2fdc16ce727bcf1a04"}, + {file = "aiohttp-3.10.5-cp313-cp313-win_amd64.whl", hash = "sha256:38172a70005252b6893088c0f5e8a47d173df7cc2b2bd88650957eb84fcf5022"}, + {file = "aiohttp-3.10.5-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:f6f18898ace4bcd2d41a122916475344a87f1dfdec626ecde9ee802a711bc569"}, + {file = "aiohttp-3.10.5-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:5ede29d91a40ba22ac1b922ef510aab871652f6c88ef60b9dcdf773c6d32ad7a"}, + {file = "aiohttp-3.10.5-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:673f988370f5954df96cc31fd99c7312a3af0a97f09e407399f61583f30da9bc"}, + {file = "aiohttp-3.10.5-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:58718e181c56a3c02d25b09d4115eb02aafe1a732ce5714ab70326d9776457c3"}, + {file = "aiohttp-3.10.5-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:4b38b1570242fbab8d86a84128fb5b5234a2f70c2e32f3070143a6d94bc854cf"}, + {file = "aiohttp-3.10.5-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:074d1bff0163e107e97bd48cad9f928fa5a3eb4b9d33366137ffce08a63e37fe"}, + {file = "aiohttp-3.10.5-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fd31f176429cecbc1ba499d4aba31aaccfea488f418d60376b911269d3b883c5"}, + {file = "aiohttp-3.10.5-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7384d0b87d4635ec38db9263e6a3f1eb609e2e06087f0aa7f63b76833737b471"}, + {file = "aiohttp-3.10.5-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:8989f46f3d7ef79585e98fa991e6ded55d2f48ae56d2c9fa5e491a6e4effb589"}, + {file = "aiohttp-3.10.5-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:c83f7a107abb89a227d6c454c613e7606c12a42b9a4ca9c5d7dad25d47c776ae"}, + {file = "aiohttp-3.10.5-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:cde98f323d6bf161041e7627a5fd763f9fd829bcfcd089804a5fdce7bb6e1b7d"}, + {file = "aiohttp-3.10.5-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:676f94c5480d8eefd97c0c7e3953315e4d8c2b71f3b49539beb2aa676c58272f"}, + {file = "aiohttp-3.10.5-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:2d21ac12dc943c68135ff858c3a989f2194a709e6e10b4c8977d7fcd67dfd511"}, + {file = "aiohttp-3.10.5-cp38-cp38-win32.whl", hash = "sha256:17e997105bd1a260850272bfb50e2a328e029c941c2708170d9d978d5a30ad9a"}, + {file = "aiohttp-3.10.5-cp38-cp38-win_amd64.whl", hash = "sha256:1c19de68896747a2aa6257ae4cf6ef59d73917a36a35ee9d0a6f48cff0f94db8"}, + {file = "aiohttp-3.10.5-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:7e2fe37ac654032db1f3499fe56e77190282534810e2a8e833141a021faaab0e"}, + {file = "aiohttp-3.10.5-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:f5bf3ead3cb66ab990ee2561373b009db5bc0e857549b6c9ba84b20bc462e172"}, + {file = "aiohttp-3.10.5-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1b2c16a919d936ca87a3c5f0e43af12a89a3ce7ccbce59a2d6784caba945b68b"}, + {file = "aiohttp-3.10.5-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ad146dae5977c4dd435eb31373b3fe9b0b1bf26858c6fc452bf6af394067e10b"}, + {file = "aiohttp-3.10.5-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8c5c6fa16412b35999320f5c9690c0f554392dc222c04e559217e0f9ae244b92"}, + {file = "aiohttp-3.10.5-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:95c4dc6f61d610bc0ee1edc6f29d993f10febfe5b76bb470b486d90bbece6b22"}, + {file = "aiohttp-3.10.5-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da452c2c322e9ce0cfef392e469a26d63d42860f829026a63374fde6b5c5876f"}, + {file = "aiohttp-3.10.5-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:898715cf566ec2869d5cb4d5fb4be408964704c46c96b4be267442d265390f32"}, + {file = "aiohttp-3.10.5-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:391cc3a9c1527e424c6865e087897e766a917f15dddb360174a70467572ac6ce"}, + {file = "aiohttp-3.10.5-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:380f926b51b92d02a34119d072f178d80bbda334d1a7e10fa22d467a66e494db"}, + {file = "aiohttp-3.10.5-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:ce91db90dbf37bb6fa0997f26574107e1b9d5ff939315247b7e615baa8ec313b"}, + {file = "aiohttp-3.10.5-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:9093a81e18c45227eebe4c16124ebf3e0d893830c6aca7cc310bfca8fe59d857"}, + {file = "aiohttp-3.10.5-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:ee40b40aa753d844162dcc80d0fe256b87cba48ca0054f64e68000453caead11"}, + {file = "aiohttp-3.10.5-cp39-cp39-win32.whl", hash = "sha256:03f2645adbe17f274444953bdea69f8327e9d278d961d85657cb0d06864814c1"}, + {file = "aiohttp-3.10.5-cp39-cp39-win_amd64.whl", hash = "sha256:d17920f18e6ee090bdd3d0bfffd769d9f2cb4c8ffde3eb203777a3895c128862"}, + {file = "aiohttp-3.10.5.tar.gz", hash = "sha256:f071854b47d39591ce9a17981c46790acb30518e2f83dfca8db2dfa091178691"}, ] [package.dependencies] +aiohappyeyeballs = ">=2.3.0" aiosignal = ">=1.1.2" async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""} attrs = ">=17.3.0" @@ -94,7 +121,7 @@ multidict = ">=4.5,<7.0" yarl = ">=1.0,<2.0" [package.extras] -speedups = ["Brotli", "aiodns", "brotlicffi"] +speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"] [[package]] name = "aiosignal" @@ -148,20 +175,20 @@ trio = ["trio (>=0.23)"] [[package]] name = "astrapy" -version = "1.4.0" +version = "1.4.1" description = "AstraPy is a Pythonic SDK for DataStax Astra and its Data API" optional = false python-versions = "<4.0.0,>=3.8.0" files = [ - {file = "astrapy-1.4.0-py3-none-any.whl", hash = "sha256:6decf0619daf3fe1daca61a18b897fe51d8a64d52dd4a9d1261aa8dd31c4667e"}, - {file = "astrapy-1.4.0.tar.gz", hash = "sha256:336292bc43bacb356877639e456a056165f3240a0caf861630daa73587819db8"}, + {file = "astrapy-1.4.1-py3-none-any.whl", hash = "sha256:f2f6ca3a19cfab9422f306b3941401079fb940e286f3d17c776b71ff76eb9f73"}, + {file = "astrapy-1.4.1.tar.gz", hash = "sha256:ea4ed0ec44f9d7281d034c9bd829b0db844438424d492c9c27136456d1a82719"}, ] [package.dependencies] -bson = ">=0.5.10,<0.6.0" cassio = ">=0.1.4,<0.2.0" deprecation = ">=2.1.0,<2.2.0" httpx = {version = ">=0.25.2,<1", extras = ["http2"]} +pymongo = ">=3" toml = ">=0.10.2,<0.11.0" uuid6 = ">=2024.1.12,<2024.2.0" @@ -178,36 +205,22 @@ files = [ [[package]] name = "attrs" -version = "23.2.0" +version = "24.2.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.7" files = [ - {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"}, - {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"}, + {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"}, + {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"}, ] [package.extras] -cov = ["attrs[tests]", "coverage[toml] (>=5.3)"] -dev = ["attrs[tests]", "pre-commit"] -docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"] -tests = ["attrs[tests-no-zope]", "zope-interface"] -tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"] -tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"] - -[[package]] -name = "bson" -version = "0.5.10" -description = "BSON codec for Python" -optional = false -python-versions = "*" -files = [ - {file = "bson-0.5.10.tar.gz", hash = "sha256:d6511b2ab051139a9123c184de1a04227262173ad593429d21e443d6462d6590"}, -] - -[package.dependencies] -python-dateutil = ">=2.4.0" -six = ">=1.9.0" +benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"] +tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] [[package]] name = "cassandra-driver" @@ -274,13 +287,13 @@ requests = ">=2.31.0,<3.0.0" [[package]] name = "certifi" -version = "2024.7.4" +version = "2024.8.30" description = "Python package for providing Mozilla's CA Bundle." optional = false python-versions = ">=3.6" files = [ - {file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"}, - {file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"}, + {file = "certifi-2024.8.30-py3-none-any.whl", hash = "sha256:922820b53db7a7257ffbda3f597266d435245903d80737e34f8a45ff3e3230d8"}, + {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"}, ] [[package]] @@ -438,6 +451,26 @@ files = [ [package.dependencies] packaging = "*" +[[package]] +name = "dnspython" +version = "2.6.1" +description = "DNS toolkit" +optional = false +python-versions = ">=3.8" +files = [ + {file = "dnspython-2.6.1-py3-none-any.whl", hash = "sha256:5ef3b9680161f6fa89daf8ad451b5f1a33b18ae8a1c6778cdf4b43f08c0a6e50"}, + {file = "dnspython-2.6.1.tar.gz", hash = "sha256:e8f0f9c23a7b7cb99ded64e6c3a6f3e701d78f50c55e002b839dea7225cff7cc"}, +] + +[package.extras] +dev = ["black (>=23.1.0)", "coverage (>=7.0)", "flake8 (>=7)", "mypy (>=1.8)", "pylint (>=3)", "pytest (>=7.4)", "pytest-cov (>=4.1.0)", "sphinx (>=7.2.0)", "twine (>=4.0.0)", "wheel (>=0.42.0)"] +dnssec = ["cryptography (>=41)"] +doh = ["h2 (>=4.1.0)", "httpcore (>=1.0.0)", "httpx (>=0.26.0)"] +doq = ["aioquic (>=0.9.25)"] +idna = ["idna (>=3.6)"] +trio = ["trio (>=0.23)"] +wmi = ["wmi (>=1.5.1)"] + [[package]] name = "exceptiongroup" version = "1.2.2" @@ -698,13 +731,13 @@ trio = ["trio (>=0.22.0,<0.26.0)"] [[package]] name = "httpx" -version = "0.27.0" +version = "0.27.2" description = "The next generation HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpx-0.27.0-py3-none-any.whl", hash = "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5"}, - {file = "httpx-0.27.0.tar.gz", hash = "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5"}, + {file = "httpx-0.27.2-py3-none-any.whl", hash = "sha256:7bb2708e112d8fdd7829cd4243970f0c223274051cb35ee80c03301ee29a3df0"}, + {file = "httpx-0.27.2.tar.gz", hash = "sha256:f7c2be1d2f3c3c3160d441802406b206c2b76f5947b11115e6df10c6c65e66c2"}, ] [package.dependencies] @@ -720,6 +753,7 @@ brotli = ["brotli", "brotlicffi"] cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"] http2 = ["h2 (>=3,<5)"] socks = ["socksio (==1.*)"] +zstd = ["zstandard (>=0.18.0)"] [[package]] name = "hyperframe" @@ -734,13 +768,13 @@ files = [ [[package]] name = "idna" -version = "3.7" +version = "3.8" description = "Internationalized Domain Names in Applications (IDNA)" optional = false -python-versions = ">=3.5" +python-versions = ">=3.6" files = [ - {file = "idna-3.7-py3-none-any.whl", hash = "sha256:82fee1fc78add43492d3a1898bfa6d8a904cc97d8427f683ed8e798d07761aa0"}, - {file = "idna-3.7.tar.gz", hash = "sha256:028ff3aadf0609c1fd278d8ea3089299412a7a8b9bd005dd08b9f8285bcb5cfc"}, + {file = "idna-3.8-py3-none-any.whl", hash = "sha256:050b4e5baadcd44d760cedbd2b8e639f2ff89bbc7a5730fcc662954303377aac"}, + {file = "idna-3.8.tar.gz", hash = "sha256:d838c2c0ed6fced7693d5e8ab8e734d5f8fda53a039c0164afb0b82e771e3603"}, ] [[package]] @@ -781,7 +815,7 @@ files = [ [[package]] name = "langchain" -version = "0.2.11" +version = "0.2.16" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.8.1,<4.0" @@ -791,7 +825,7 @@ develop = false [package.dependencies] aiohttp = "^3.8.3" async-timeout = {version = "^4.0.0", markers = "python_version < \"3.11\""} -langchain-core = "^0.2.23" +langchain-core = "^0.2.38" langchain-text-splitters = "^0.2.0" langsmith = "^0.1.17" numpy = [ @@ -808,12 +842,12 @@ tenacity = "^8.1.0,!=8.4.0" type = "git" url = "https://github.com/langchain-ai/langchain.git" reference = "HEAD" -resolved_reference = "01ab2918a29d22d2676ed5c286f1b44ccaaba631" +resolved_reference = "de97d5064437c98f34dae0b0afa3b61162790726" subdirectory = "libs/langchain" [[package]] name = "langchain-core" -version = "0.2.24" +version = "0.2.38" description = "Building applications with LLMs through composability" optional = false python-versions = ">=3.8.1,<4.0" @@ -830,17 +864,18 @@ pydantic = [ ] PyYAML = ">=5.3" tenacity = "^8.1.0,!=8.4.0" +typing-extensions = ">=4.7" [package.source] type = "git" url = "https://github.com/langchain-ai/langchain.git" reference = "HEAD" -resolved_reference = "01ab2918a29d22d2676ed5c286f1b44ccaaba631" +resolved_reference = "de97d5064437c98f34dae0b0afa3b61162790726" subdirectory = "libs/core" [[package]] name = "langchain-text-splitters" -version = "0.2.2" +version = "0.2.4" description = "LangChain text splitting utilities" optional = false python-versions = ">=3.8.1,<4.0" @@ -848,27 +883,28 @@ files = [] develop = false [package.dependencies] -langchain-core = "^0.2.10" +langchain-core = "^0.2.38" [package.source] type = "git" url = "https://github.com/langchain-ai/langchain.git" reference = "HEAD" -resolved_reference = "01ab2918a29d22d2676ed5c286f1b44ccaaba631" +resolved_reference = "de97d5064437c98f34dae0b0afa3b61162790726" subdirectory = "libs/text-splitters" [[package]] name = "langsmith" -version = "0.1.93" +version = "0.1.114" description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform." optional = false python-versions = "<4.0,>=3.8.1" files = [ - {file = "langsmith-0.1.93-py3-none-any.whl", hash = "sha256:811210b9d5f108f36431bd7b997eb9476a9ecf5a2abd7ddbb606c1cdcf0f43ce"}, - {file = "langsmith-0.1.93.tar.gz", hash = "sha256:285b6ad3a54f50fa8eb97b5f600acc57d0e37e139dd8cf2111a117d0435ba9b4"}, + {file = "langsmith-0.1.114-py3-none-any.whl", hash = "sha256:2b6b6b49ddb1cea75f465da107ddc21e60d3c7242813dcc0de90f914e4957249"}, + {file = "langsmith-0.1.114.tar.gz", hash = "sha256:1683e1505d034d1bf7c960067c1357fd0d294172dd20540f913093e4b86857a2"}, ] [package.dependencies] +httpx = ">=0.23.0,<1" orjson = ">=3.9.14,<4.0.0" pydantic = [ {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}, @@ -1120,62 +1156,68 @@ files = [ [[package]] name = "orjson" -version = "3.10.6" +version = "3.10.7" description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy" optional = false python-versions = ">=3.8" files = [ - {file = "orjson-3.10.6-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:fb0ee33124db6eaa517d00890fc1a55c3bfe1cf78ba4a8899d71a06f2d6ff5c7"}, - {file = "orjson-3.10.6-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9c1c4b53b24a4c06547ce43e5fee6ec4e0d8fe2d597f4647fc033fd205707365"}, - {file = "orjson-3.10.6-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:eadc8fd310edb4bdbd333374f2c8fec6794bbbae99b592f448d8214a5e4050c0"}, - {file = "orjson-3.10.6-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:61272a5aec2b2661f4fa2b37c907ce9701e821b2c1285d5c3ab0207ebd358d38"}, - {file = "orjson-3.10.6-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:57985ee7e91d6214c837936dc1608f40f330a6b88bb13f5a57ce5257807da143"}, - {file = "orjson-3.10.6-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:633a3b31d9d7c9f02d49c4ab4d0a86065c4a6f6adc297d63d272e043472acab5"}, - {file = "orjson-3.10.6-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:1c680b269d33ec444afe2bdc647c9eb73166fa47a16d9a75ee56a374f4a45f43"}, - {file = "orjson-3.10.6-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:f759503a97a6ace19e55461395ab0d618b5a117e8d0fbb20e70cfd68a47327f2"}, - {file = "orjson-3.10.6-cp310-none-win32.whl", hash = "sha256:95a0cce17f969fb5391762e5719575217bd10ac5a189d1979442ee54456393f3"}, - {file = "orjson-3.10.6-cp310-none-win_amd64.whl", hash = "sha256:df25d9271270ba2133cc88ee83c318372bdc0f2cd6f32e7a450809a111efc45c"}, - {file = "orjson-3.10.6-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:b1ec490e10d2a77c345def52599311849fc063ae0e67cf4f84528073152bb2ba"}, - {file = "orjson-3.10.6-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:55d43d3feb8f19d07e9f01e5b9be4f28801cf7c60d0fa0d279951b18fae1932b"}, - {file = "orjson-3.10.6-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ac3045267e98fe749408eee1593a142e02357c5c99be0802185ef2170086a863"}, - {file = "orjson-3.10.6-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c27bc6a28ae95923350ab382c57113abd38f3928af3c80be6f2ba7eb8d8db0b0"}, - {file = "orjson-3.10.6-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d27456491ca79532d11e507cadca37fb8c9324a3976294f68fb1eff2dc6ced5a"}, - {file = "orjson-3.10.6-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:05ac3d3916023745aa3b3b388e91b9166be1ca02b7c7e41045da6d12985685f0"}, - {file = "orjson-3.10.6-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:1335d4ef59ab85cab66fe73fd7a4e881c298ee7f63ede918b7faa1b27cbe5212"}, - {file = "orjson-3.10.6-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:4bbc6d0af24c1575edc79994c20e1b29e6fb3c6a570371306db0993ecf144dc5"}, - {file = "orjson-3.10.6-cp311-none-win32.whl", hash = "sha256:450e39ab1f7694465060a0550b3f6d328d20297bf2e06aa947b97c21e5241fbd"}, - {file = "orjson-3.10.6-cp311-none-win_amd64.whl", hash = "sha256:227df19441372610b20e05bdb906e1742ec2ad7a66ac8350dcfd29a63014a83b"}, - {file = "orjson-3.10.6-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:ea2977b21f8d5d9b758bb3f344a75e55ca78e3ff85595d248eee813ae23ecdfb"}, - {file = "orjson-3.10.6-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b6f3d167d13a16ed263b52dbfedff52c962bfd3d270b46b7518365bcc2121eed"}, - {file = "orjson-3.10.6-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f710f346e4c44a4e8bdf23daa974faede58f83334289df80bc9cd12fe82573c7"}, - {file = "orjson-3.10.6-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7275664f84e027dcb1ad5200b8b18373e9c669b2a9ec33d410c40f5ccf4b257e"}, - {file = "orjson-3.10.6-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0943e4c701196b23c240b3d10ed8ecd674f03089198cf503105b474a4f77f21f"}, - {file = "orjson-3.10.6-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:446dee5a491b5bc7d8f825d80d9637e7af43f86a331207b9c9610e2f93fee22a"}, - {file = "orjson-3.10.6-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:64c81456d2a050d380786413786b057983892db105516639cb5d3ee3c7fd5148"}, - {file = "orjson-3.10.6-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:960db0e31c4e52fa0fc3ecbaea5b2d3b58f379e32a95ae6b0ebeaa25b93dfd34"}, - {file = "orjson-3.10.6-cp312-none-win32.whl", hash = "sha256:a6ea7afb5b30b2317e0bee03c8d34c8181bc5a36f2afd4d0952f378972c4efd5"}, - {file = "orjson-3.10.6-cp312-none-win_amd64.whl", hash = "sha256:874ce88264b7e655dde4aeaacdc8fd772a7962faadfb41abe63e2a4861abc3dc"}, - {file = "orjson-3.10.6-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:66680eae4c4e7fc193d91cfc1353ad6d01b4801ae9b5314f17e11ba55e934183"}, - {file = "orjson-3.10.6-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:caff75b425db5ef8e8f23af93c80f072f97b4fb3afd4af44482905c9f588da28"}, - {file = "orjson-3.10.6-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:3722fddb821b6036fd2a3c814f6bd9b57a89dc6337b9924ecd614ebce3271394"}, - {file = "orjson-3.10.6-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c2c116072a8533f2fec435fde4d134610f806bdac20188c7bd2081f3e9e0133f"}, - {file = "orjson-3.10.6-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6eeb13218c8cf34c61912e9df2de2853f1d009de0e46ea09ccdf3d757896af0a"}, - {file = "orjson-3.10.6-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:965a916373382674e323c957d560b953d81d7a8603fbeee26f7b8248638bd48b"}, - {file = "orjson-3.10.6-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:03c95484d53ed8e479cade8628c9cea00fd9d67f5554764a1110e0d5aa2de96e"}, - {file = "orjson-3.10.6-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:e060748a04cccf1e0a6f2358dffea9c080b849a4a68c28b1b907f272b5127e9b"}, - {file = "orjson-3.10.6-cp38-none-win32.whl", hash = "sha256:738dbe3ef909c4b019d69afc19caf6b5ed0e2f1c786b5d6215fbb7539246e4c6"}, - {file = "orjson-3.10.6-cp38-none-win_amd64.whl", hash = "sha256:d40f839dddf6a7d77114fe6b8a70218556408c71d4d6e29413bb5f150a692ff7"}, - {file = "orjson-3.10.6-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:697a35a083c4f834807a6232b3e62c8b280f7a44ad0b759fd4dce748951e70db"}, - {file = "orjson-3.10.6-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fd502f96bf5ea9a61cbc0b2b5900d0dd68aa0da197179042bdd2be67e51a1e4b"}, - {file = "orjson-3.10.6-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f215789fb1667cdc874c1b8af6a84dc939fd802bf293a8334fce185c79cd359b"}, - {file = "orjson-3.10.6-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:a2debd8ddce948a8c0938c8c93ade191d2f4ba4649a54302a7da905a81f00b56"}, - {file = "orjson-3.10.6-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5410111d7b6681d4b0d65e0f58a13be588d01b473822483f77f513c7f93bd3b2"}, - {file = "orjson-3.10.6-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bb1f28a137337fdc18384079fa5726810681055b32b92253fa15ae5656e1dddb"}, - {file = "orjson-3.10.6-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:bf2fbbce5fe7cd1aa177ea3eab2b8e6a6bc6e8592e4279ed3db2d62e57c0e1b2"}, - {file = "orjson-3.10.6-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:79b9b9e33bd4c517445a62b90ca0cc279b0f1f3970655c3df9e608bc3f91741a"}, - {file = "orjson-3.10.6-cp39-none-win32.whl", hash = "sha256:30b0a09a2014e621b1adf66a4f705f0809358350a757508ee80209b2d8dae219"}, - {file = "orjson-3.10.6-cp39-none-win_amd64.whl", hash = "sha256:49e3bc615652617d463069f91b867a4458114c5b104e13b7ae6872e5f79d0844"}, - {file = "orjson-3.10.6.tar.gz", hash = "sha256:e54b63d0a7c6c54a5f5f726bc93a2078111ef060fec4ecbf34c5db800ca3b3a7"}, + {file = "orjson-3.10.7-cp310-cp310-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:74f4544f5a6405b90da8ea724d15ac9c36da4d72a738c64685003337401f5c12"}, + {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:34a566f22c28222b08875b18b0dfbf8a947e69df21a9ed5c51a6bf91cfb944ac"}, + {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bf6ba8ebc8ef5792e2337fb0419f8009729335bb400ece005606336b7fd7bab7"}, + {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ac7cf6222b29fbda9e3a472b41e6a5538b48f2c8f99261eecd60aafbdb60690c"}, + {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:de817e2f5fc75a9e7dd350c4b0f54617b280e26d1631811a43e7e968fa71e3e9"}, + {file = "orjson-3.10.7-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:348bdd16b32556cf8d7257b17cf2bdb7ab7976af4af41ebe79f9796c218f7e91"}, + {file = "orjson-3.10.7-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:479fd0844ddc3ca77e0fd99644c7fe2de8e8be1efcd57705b5c92e5186e8a250"}, + {file = "orjson-3.10.7-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:fdf5197a21dd660cf19dfd2a3ce79574588f8f5e2dbf21bda9ee2d2b46924d84"}, + {file = "orjson-3.10.7-cp310-none-win32.whl", hash = "sha256:d374d36726746c81a49f3ff8daa2898dccab6596864ebe43d50733275c629175"}, + {file = "orjson-3.10.7-cp310-none-win_amd64.whl", hash = "sha256:cb61938aec8b0ffb6eef484d480188a1777e67b05d58e41b435c74b9d84e0b9c"}, + {file = "orjson-3.10.7-cp311-cp311-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:7db8539039698ddfb9a524b4dd19508256107568cdad24f3682d5773e60504a2"}, + {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:480f455222cb7a1dea35c57a67578848537d2602b46c464472c995297117fa09"}, + {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:8a9c9b168b3a19e37fe2778c0003359f07822c90fdff8f98d9d2a91b3144d8e0"}, + {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8de062de550f63185e4c1c54151bdddfc5625e37daf0aa1e75d2a1293e3b7d9a"}, + {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6b0dd04483499d1de9c8f6203f8975caf17a6000b9c0c54630cef02e44ee624e"}, + {file = "orjson-3.10.7-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b58d3795dafa334fc8fd46f7c5dc013e6ad06fd5b9a4cc98cb1456e7d3558bd6"}, + {file = "orjson-3.10.7-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:33cfb96c24034a878d83d1a9415799a73dc77480e6c40417e5dda0710d559ee6"}, + {file = "orjson-3.10.7-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:e724cebe1fadc2b23c6f7415bad5ee6239e00a69f30ee423f319c6af70e2a5c0"}, + {file = "orjson-3.10.7-cp311-none-win32.whl", hash = "sha256:82763b46053727a7168d29c772ed5c870fdae2f61aa8a25994c7984a19b1021f"}, + {file = "orjson-3.10.7-cp311-none-win_amd64.whl", hash = "sha256:eb8d384a24778abf29afb8e41d68fdd9a156cf6e5390c04cc07bbc24b89e98b5"}, + {file = "orjson-3.10.7-cp312-cp312-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:44a96f2d4c3af51bfac6bc4ef7b182aa33f2f054fd7f34cc0ee9a320d051d41f"}, + {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:76ac14cd57df0572453543f8f2575e2d01ae9e790c21f57627803f5e79b0d3c3"}, + {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:bdbb61dcc365dd9be94e8f7df91975edc9364d6a78c8f7adb69c1cdff318ec93"}, + {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b48b3db6bb6e0a08fa8c83b47bc169623f801e5cc4f24442ab2b6617da3b5313"}, + {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:23820a1563a1d386414fef15c249040042b8e5d07b40ab3fe3efbfbbcbcb8864"}, + {file = "orjson-3.10.7-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a0c6a008e91d10a2564edbb6ee5069a9e66df3fbe11c9a005cb411f441fd2c09"}, + {file = "orjson-3.10.7-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:d352ee8ac1926d6193f602cbe36b1643bbd1bbcb25e3c1a657a4390f3000c9a5"}, + {file = "orjson-3.10.7-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:d2d9f990623f15c0ae7ac608103c33dfe1486d2ed974ac3f40b693bad1a22a7b"}, + {file = "orjson-3.10.7-cp312-none-win32.whl", hash = "sha256:7c4c17f8157bd520cdb7195f75ddbd31671997cbe10aee559c2d613592e7d7eb"}, + {file = "orjson-3.10.7-cp312-none-win_amd64.whl", hash = "sha256:1d9c0e733e02ada3ed6098a10a8ee0052dd55774de3d9110d29868d24b17faa1"}, + {file = "orjson-3.10.7-cp313-cp313-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:77d325ed866876c0fa6492598ec01fe30e803272a6e8b10e992288b009cbe149"}, + {file = "orjson-3.10.7-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ea2c232deedcb605e853ae1db2cc94f7390ac776743b699b50b071b02bea6fe"}, + {file = "orjson-3.10.7-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3dcfbede6737fdbef3ce9c37af3fb6142e8e1ebc10336daa05872bfb1d87839c"}, + {file = "orjson-3.10.7-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:11748c135f281203f4ee695b7f80bb1358a82a63905f9f0b794769483ea854ad"}, + {file = "orjson-3.10.7-cp313-none-win32.whl", hash = "sha256:a7e19150d215c7a13f39eb787d84db274298d3f83d85463e61d277bbd7f401d2"}, + {file = "orjson-3.10.7-cp313-none-win_amd64.whl", hash = "sha256:eef44224729e9525d5261cc8d28d6b11cafc90e6bd0be2157bde69a52ec83024"}, + {file = "orjson-3.10.7-cp38-cp38-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:6ea2b2258eff652c82652d5e0f02bd5e0463a6a52abb78e49ac288827aaa1469"}, + {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:430ee4d85841e1483d487e7b81401785a5dfd69db5de01314538f31f8fbf7ee1"}, + {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:4b6146e439af4c2472c56f8540d799a67a81226e11992008cb47e1267a9b3225"}, + {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:084e537806b458911137f76097e53ce7bf5806dda33ddf6aaa66a028f8d43a23"}, + {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4829cf2195838e3f93b70fd3b4292156fc5e097aac3739859ac0dcc722b27ac0"}, + {file = "orjson-3.10.7-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1193b2416cbad1a769f868b1749535d5da47626ac29445803dae7cc64b3f5c98"}, + {file = "orjson-3.10.7-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:4e6c3da13e5a57e4b3dca2de059f243ebec705857522f188f0180ae88badd354"}, + {file = "orjson-3.10.7-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:c31008598424dfbe52ce8c5b47e0752dca918a4fdc4a2a32004efd9fab41d866"}, + {file = "orjson-3.10.7-cp38-none-win32.whl", hash = "sha256:7122a99831f9e7fe977dc45784d3b2edc821c172d545e6420c375e5a935f5a1c"}, + {file = "orjson-3.10.7-cp38-none-win_amd64.whl", hash = "sha256:a763bc0e58504cc803739e7df040685816145a6f3c8a589787084b54ebc9f16e"}, + {file = "orjson-3.10.7-cp39-cp39-macosx_10_15_x86_64.macosx_11_0_arm64.macosx_10_15_universal2.whl", hash = "sha256:e76be12658a6fa376fcd331b1ea4e58f5a06fd0220653450f0d415b8fd0fbe20"}, + {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ed350d6978d28b92939bfeb1a0570c523f6170efc3f0a0ef1f1df287cd4f4960"}, + {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:144888c76f8520e39bfa121b31fd637e18d4cc2f115727865fdf9fa325b10412"}, + {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:09b2d92fd95ad2402188cf51573acde57eb269eddabaa60f69ea0d733e789fe9"}, + {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5b24a579123fa884f3a3caadaed7b75eb5715ee2b17ab5c66ac97d29b18fe57f"}, + {file = "orjson-3.10.7-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e72591bcfe7512353bd609875ab38050efe3d55e18934e2f18950c108334b4ff"}, + {file = "orjson-3.10.7-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:f4db56635b58cd1a200b0a23744ff44206ee6aa428185e2b6c4a65b3197abdcd"}, + {file = "orjson-3.10.7-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:0fa5886854673222618638c6df7718ea7fe2f3f2384c452c9ccedc70b4a510a5"}, + {file = "orjson-3.10.7-cp39-none-win32.whl", hash = "sha256:8272527d08450ab16eb405f47e0f4ef0e5ff5981c3d82afe0efd25dcbef2bcd2"}, + {file = "orjson-3.10.7-cp39-none-win_amd64.whl", hash = "sha256:974683d4618c0c7dbf4f69c95a979734bf183d0658611760017f6e70a145af58"}, + {file = "orjson-3.10.7.tar.gz", hash = "sha256:75ef0640403f945f3a1f9f6400686560dbfb0fb5b16589ad62cd477043c4eee3"}, ] [[package]] @@ -1327,6 +1369,78 @@ files = [ [package.dependencies] typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0" +[[package]] +name = "pymongo" +version = "4.8.0" +description = "Python driver for MongoDB " +optional = false +python-versions = ">=3.8" +files = [ + {file = "pymongo-4.8.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f2b7bec27e047e84947fbd41c782f07c54c30c76d14f3b8bf0c89f7413fac67a"}, + {file = "pymongo-4.8.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3c68fe128a171493018ca5c8020fc08675be130d012b7ab3efe9e22698c612a1"}, + {file = "pymongo-4.8.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:920d4f8f157a71b3cb3f39bc09ce070693d6e9648fb0e30d00e2657d1dca4e49"}, + {file = "pymongo-4.8.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:52b4108ac9469febba18cea50db972605cc43978bedaa9fea413378877560ef8"}, + {file = "pymongo-4.8.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:180d5eb1dc28b62853e2f88017775c4500b07548ed28c0bd9c005c3d7bc52526"}, + {file = "pymongo-4.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aec2b9088cdbceb87e6ca9c639d0ff9b9d083594dda5ca5d3c4f6774f4c81b33"}, + {file = "pymongo-4.8.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d0cf61450feadca81deb1a1489cb1a3ae1e4266efd51adafecec0e503a8dcd84"}, + {file = "pymongo-4.8.0-cp310-cp310-win32.whl", hash = "sha256:8b18c8324809539c79bd6544d00e0607e98ff833ca21953df001510ca25915d1"}, + {file = "pymongo-4.8.0-cp310-cp310-win_amd64.whl", hash = "sha256:e5df28f74002e37bcbdfdc5109799f670e4dfef0fb527c391ff84f078050e7b5"}, + {file = "pymongo-4.8.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6b50040d9767197b77ed420ada29b3bf18a638f9552d80f2da817b7c4a4c9c68"}, + {file = "pymongo-4.8.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:417369ce39af2b7c2a9c7152c1ed2393edfd1cbaf2a356ba31eb8bcbd5c98dd7"}, + {file = "pymongo-4.8.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bf821bd3befb993a6db17229a2c60c1550e957de02a6ff4dd0af9476637b2e4d"}, + {file = "pymongo-4.8.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9365166aa801c63dff1a3cb96e650be270da06e3464ab106727223123405510f"}, + {file = "pymongo-4.8.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cc8b8582f4209c2459b04b049ac03c72c618e011d3caa5391ff86d1bda0cc486"}, + {file = "pymongo-4.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:16e5019f75f6827bb5354b6fef8dfc9d6c7446894a27346e03134d290eb9e758"}, + {file = "pymongo-4.8.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:3b5802151fc2b51cd45492c80ed22b441d20090fb76d1fd53cd7760b340ff554"}, + {file = "pymongo-4.8.0-cp311-cp311-win32.whl", hash = "sha256:4bf58e6825b93da63e499d1a58de7de563c31e575908d4e24876234ccb910eba"}, + {file = "pymongo-4.8.0-cp311-cp311-win_amd64.whl", hash = "sha256:b747c0e257b9d3e6495a018309b9e0c93b7f0d65271d1d62e572747f4ffafc88"}, + {file = "pymongo-4.8.0-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:e6a720a3d22b54183352dc65f08cd1547204d263e0651b213a0a2e577e838526"}, + {file = "pymongo-4.8.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:31e4d21201bdf15064cf47ce7b74722d3e1aea2597c6785882244a3bb58c7eab"}, + {file = "pymongo-4.8.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c6b804bb4f2d9dc389cc9e827d579fa327272cdb0629a99bfe5b83cb3e269ebf"}, + {file = "pymongo-4.8.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f2fbdb87fe5075c8beb17a5c16348a1ea3c8b282a5cb72d173330be2fecf22f5"}, + {file = "pymongo-4.8.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:cd39455b7ee70aabee46f7399b32ab38b86b236c069ae559e22be6b46b2bbfc4"}, + {file = "pymongo-4.8.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:940d456774b17814bac5ea7fc28188c7a1338d4a233efbb6ba01de957bded2e8"}, + {file = "pymongo-4.8.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:236bbd7d0aef62e64caf4b24ca200f8c8670d1a6f5ea828c39eccdae423bc2b2"}, + {file = "pymongo-4.8.0-cp312-cp312-win32.whl", hash = "sha256:47ec8c3f0a7b2212dbc9be08d3bf17bc89abd211901093e3ef3f2adea7de7a69"}, + {file = "pymongo-4.8.0-cp312-cp312-win_amd64.whl", hash = "sha256:e84bc7707492f06fbc37a9f215374d2977d21b72e10a67f1b31893ec5a140ad8"}, + {file = "pymongo-4.8.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:519d1bab2b5e5218c64340b57d555d89c3f6c9d717cecbf826fb9d42415e7750"}, + {file = "pymongo-4.8.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:87075a1feb1e602e539bdb1ef8f4324a3427eb0d64208c3182e677d2c0718b6f"}, + {file = "pymongo-4.8.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:77f53429515d2b3e86dcc83dadecf7ff881e538c168d575f3688698a8707b80a"}, + {file = "pymongo-4.8.0-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:fdc20cd1e1141b04696ffcdb7c71e8a4a665db31fe72e51ec706b3bdd2d09f36"}, + {file = "pymongo-4.8.0-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:284d0717d1a7707744018b0b6ee7801b1b1ff044c42f7be7a01bb013de639470"}, + {file = "pymongo-4.8.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f5bf0eb8b6ef40fa22479f09375468c33bebb7fe49d14d9c96c8fd50355188b0"}, + {file = "pymongo-4.8.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2ecd71b9226bd1d49416dc9f999772038e56f415a713be51bf18d8676a0841c8"}, + {file = "pymongo-4.8.0-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:e0061af6e8c5e68b13f1ec9ad5251247726653c5af3c0bbdfbca6cf931e99216"}, + {file = "pymongo-4.8.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:658d0170f27984e0d89c09fe5c42296613b711a3ffd847eb373b0dbb5b648d5f"}, + {file = "pymongo-4.8.0-cp38-cp38-win32.whl", hash = "sha256:3ed1c316718a2836f7efc3d75b4b0ffdd47894090bc697de8385acd13c513a70"}, + {file = "pymongo-4.8.0-cp38-cp38-win_amd64.whl", hash = "sha256:7148419eedfea9ecb940961cfe465efaba90595568a1fb97585fb535ea63fe2b"}, + {file = "pymongo-4.8.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:e8400587d594761e5136a3423111f499574be5fd53cf0aefa0d0f05b180710b0"}, + {file = "pymongo-4.8.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:af3e98dd9702b73e4e6fd780f6925352237f5dce8d99405ff1543f3771201704"}, + {file = "pymongo-4.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de3a860f037bb51f968de320baef85090ff0bbb42ec4f28ec6a5ddf88be61871"}, + {file = "pymongo-4.8.0-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:0fc18b3a093f3db008c5fea0e980dbd3b743449eee29b5718bc2dc15ab5088bb"}, + {file = "pymongo-4.8.0-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:18c9d8f975dd7194c37193583fd7d1eb9aea0c21ee58955ecf35362239ff31ac"}, + {file = "pymongo-4.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:408b2f8fdbeca3c19e4156f28fff1ab11c3efb0407b60687162d49f68075e63c"}, + {file = "pymongo-4.8.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b6564780cafd6abeea49759fe661792bd5a67e4f51bca62b88faab497ab5fe89"}, + {file = "pymongo-4.8.0-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:d18d86bc9e103f4d3d4f18b85a0471c0e13ce5b79194e4a0389a224bb70edd53"}, + {file = "pymongo-4.8.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.whl", hash = "sha256:9097c331577cecf8034422956daaba7ec74c26f7b255d718c584faddd7fa2e3c"}, + {file = "pymongo-4.8.0-cp39-cp39-win32.whl", hash = "sha256:d5428dbcd43d02f6306e1c3c95f692f68b284e6ee5390292242f509004c9e3a8"}, + {file = "pymongo-4.8.0-cp39-cp39-win_amd64.whl", hash = "sha256:ef7225755ed27bfdb18730c68f6cb023d06c28f2b734597480fb4c0e500feb6f"}, + {file = "pymongo-4.8.0.tar.gz", hash = "sha256:454f2295875744dc70f1881e4b2eb99cdad008a33574bc8aaf120530f66c0cde"}, +] + +[package.dependencies] +dnspython = ">=1.16.0,<3.0.0" + +[package.extras] +aws = ["pymongo-auth-aws (>=1.1.0,<2.0.0)"] +docs = ["furo (==2023.9.10)", "readthedocs-sphinx-search (>=0.3,<1.0)", "sphinx (>=5.3,<8)", "sphinx-rtd-theme (>=2,<3)", "sphinxcontrib-shellcheck (>=1,<2)"] +encryption = ["certifi", "pymongo-auth-aws (>=1.1.0,<2.0.0)", "pymongocrypt (>=1.6.0,<2.0.0)"] +gssapi = ["pykerberos", "winkerberos (>=0.5.0)"] +ocsp = ["certifi", "cryptography (>=2.5)", "pyopenssl (>=17.2.0)", "requests (<3.0.0)", "service-identity (>=18.1.0)"] +snappy = ["python-snappy"] +test = ["pytest (>=7)"] +zstd = ["zstandard"] + [[package]] name = "pytest" version = "7.4.4" @@ -1444,61 +1558,64 @@ cli = ["click (>=5.0)"] [[package]] name = "pyyaml" -version = "6.0.1" +version = "6.0.2" description = "YAML parser and emitter for Python" optional = false -python-versions = ">=3.6" +python-versions = ">=3.8" files = [ - {file = "PyYAML-6.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d858aa552c999bc8a8d57426ed01e40bef403cd8ccdd0fc5f6f04a00414cac2a"}, - {file = "PyYAML-6.0.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fd66fc5d0da6d9815ba2cebeb4205f95818ff4b79c3ebe268e75d961704af52f"}, - {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:69b023b2b4daa7548bcfbd4aa3da05b3a74b772db9e23b982788168117739938"}, - {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e0b275a9ecc9c0c0c07b4b90ba548307583c125f54d5b6946cfee6360c733d"}, - {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ba336e390cd8e4d1739f42dfe9bb83a3cc2e80f567d8805e11b46f4a943f5515"}, - {file = "PyYAML-6.0.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:326c013efe8048858a6d312ddd31d56e468118ad4cdeda36c719bf5bb6192290"}, - {file = "PyYAML-6.0.1-cp310-cp310-win32.whl", hash = "sha256:bd4af7373a854424dabd882decdc5579653d7868b8fb26dc7d0e99f823aa5924"}, - {file = "PyYAML-6.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:fd1592b3fdf65fff2ad0004b5e363300ef59ced41c2e6b3a99d4089fa8c5435d"}, - {file = "PyYAML-6.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6965a7bc3cf88e5a1c3bd2e0b5c22f8d677dc88a455344035f03399034eb3007"}, - {file = "PyYAML-6.0.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:f003ed9ad21d6a4713f0a9b5a7a0a79e08dd0f221aff4525a2be4c346ee60aab"}, - {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:42f8152b8dbc4fe7d96729ec2b99c7097d656dc1213a3229ca5383f973a5ed6d"}, - {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:062582fca9fabdd2c8b54a3ef1c978d786e0f6b3a1510e0ac93ef59e0ddae2bc"}, - {file = "PyYAML-6.0.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:d2b04aac4d386b172d5b9692e2d2da8de7bfb6c387fa4f801fbf6fb2e6ba4673"}, - {file = "PyYAML-6.0.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:e7d73685e87afe9f3b36c799222440d6cf362062f78be1013661b00c5c6f678b"}, - {file = "PyYAML-6.0.1-cp311-cp311-win32.whl", hash = "sha256:1635fd110e8d85d55237ab316b5b011de701ea0f29d07611174a1b42f1444741"}, - {file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"}, - {file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"}, - {file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"}, - {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"}, - {file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"}, - {file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"}, - {file = "PyYAML-6.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:0d3304d8c0adc42be59c5f8a4d9e3d7379e6955ad754aa9d6ab7a398b59dd1df"}, - {file = "PyYAML-6.0.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50550eb667afee136e9a77d6dc71ae76a44df8b3e51e41b77f6de2932bfe0f47"}, - {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1fe35611261b29bd1de0070f0b2f47cb6ff71fa6595c077e42bd0c419fa27b98"}, - {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:704219a11b772aea0d8ecd7058d0082713c3562b4e271b849ad7dc4a5c90c13c"}, - {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:afd7e57eddb1a54f0f1a974bc4391af8bcce0b444685d936840f125cf046d5bd"}, - {file = "PyYAML-6.0.1-cp36-cp36m-win32.whl", hash = "sha256:fca0e3a251908a499833aa292323f32437106001d436eca0e6e7833256674585"}, - {file = "PyYAML-6.0.1-cp36-cp36m-win_amd64.whl", hash = "sha256:f22ac1c3cac4dbc50079e965eba2c1058622631e526bd9afd45fedd49ba781fa"}, - {file = "PyYAML-6.0.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:b1275ad35a5d18c62a7220633c913e1b42d44b46ee12554e5fd39c70a243d6a3"}, - {file = "PyYAML-6.0.1-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:18aeb1bf9a78867dc38b259769503436b7c72f7a1f1f4c93ff9a17de54319b27"}, - {file = "PyYAML-6.0.1-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:596106435fa6ad000c2991a98fa58eeb8656ef2325d7e158344fb33864ed87e3"}, - {file = "PyYAML-6.0.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:baa90d3f661d43131ca170712d903e6295d1f7a0f595074f151c0aed377c9b9c"}, - {file = "PyYAML-6.0.1-cp37-cp37m-win32.whl", hash = "sha256:9046c58c4395dff28dd494285c82ba00b546adfc7ef001486fbf0324bc174fba"}, - {file = "PyYAML-6.0.1-cp37-cp37m-win_amd64.whl", hash = "sha256:4fb147e7a67ef577a588a0e2c17b6db51dda102c71de36f8549b6816a96e1867"}, - {file = "PyYAML-6.0.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:1d4c7e777c441b20e32f52bd377e0c409713e8bb1386e1099c2415f26e479595"}, - {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a0cd17c15d3bb3fa06978b4e8958dcdc6e0174ccea823003a106c7d4d7899ac5"}, - {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28c119d996beec18c05208a8bd78cbe4007878c6dd15091efb73a30e90539696"}, - {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e07cbde391ba96ab58e532ff4803f79c4129397514e1413a7dc761ccd755735"}, - {file = "PyYAML-6.0.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:49a183be227561de579b4a36efbb21b3eab9651dd81b1858589f796549873dd6"}, - {file = "PyYAML-6.0.1-cp38-cp38-win32.whl", hash = "sha256:184c5108a2aca3c5b3d3bf9395d50893a7ab82a38004c8f61c258d4428e80206"}, - {file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"}, - {file = "PyYAML-6.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8"}, - {file = "PyYAML-6.0.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:c8098ddcc2a85b61647b2590f825f3db38891662cfc2fc776415143f599bb859"}, - {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"}, - {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b786eecbdf8499b9ca1d697215862083bd6d2a99965554781d0d8d1ad31e13a0"}, - {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"}, - {file = "PyYAML-6.0.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:04ac92ad1925b2cff1db0cfebffb6ffc43457495c9b3c39d3fcae417d7125dc5"}, - {file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"}, - {file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"}, - {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"}, + {file = "PyYAML-6.0.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:0a9a2848a5b7feac301353437eb7d5957887edbf81d56e903999a75a3d743086"}, + {file = "PyYAML-6.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:29717114e51c84ddfba879543fb232a6ed60086602313ca38cce623c1d62cfbf"}, + {file = "PyYAML-6.0.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8824b5a04a04a047e72eea5cec3bc266db09e35de6bdfe34c9436ac5ee27d237"}, + {file = "PyYAML-6.0.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7c36280e6fb8385e520936c3cb3b8042851904eba0e58d277dca80a5cfed590b"}, + {file = "PyYAML-6.0.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ec031d5d2feb36d1d1a24380e4db6d43695f3748343d99434e6f5f9156aaa2ed"}, + {file = "PyYAML-6.0.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:936d68689298c36b53b29f23c6dbb74de12b4ac12ca6cfe0e047bedceea56180"}, + {file = "PyYAML-6.0.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:23502f431948090f597378482b4812b0caae32c22213aecf3b55325e049a6c68"}, + {file = "PyYAML-6.0.2-cp310-cp310-win32.whl", hash = "sha256:2e99c6826ffa974fe6e27cdb5ed0021786b03fc98e5ee3c5bfe1fd5015f42b99"}, + {file = "PyYAML-6.0.2-cp310-cp310-win_amd64.whl", hash = "sha256:a4d3091415f010369ae4ed1fc6b79def9416358877534caf6a0fdd2146c87a3e"}, + {file = "PyYAML-6.0.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:cc1c1159b3d456576af7a3e4d1ba7e6924cb39de8f67111c735f6fc832082774"}, + {file = "PyYAML-6.0.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:1e2120ef853f59c7419231f3bf4e7021f1b936f6ebd222406c3b60212205d2ee"}, + {file = "PyYAML-6.0.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5d225db5a45f21e78dd9358e58a98702a0302f2659a3c6cd320564b75b86f47c"}, + {file = "PyYAML-6.0.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:5ac9328ec4831237bec75defaf839f7d4564be1e6b25ac710bd1a96321cc8317"}, + {file = "PyYAML-6.0.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ad2a3decf9aaba3d29c8f537ac4b243e36bef957511b4766cb0057d32b0be85"}, + {file = "PyYAML-6.0.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:ff3824dc5261f50c9b0dfb3be22b4567a6f938ccce4587b38952d85fd9e9afe4"}, + {file = "PyYAML-6.0.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:797b4f722ffa07cc8d62053e4cff1486fa6dc094105d13fea7b1de7d8bf71c9e"}, + {file = "PyYAML-6.0.2-cp311-cp311-win32.whl", hash = "sha256:11d8f3dd2b9c1207dcaf2ee0bbbfd5991f571186ec9cc78427ba5bd32afae4b5"}, + {file = "PyYAML-6.0.2-cp311-cp311-win_amd64.whl", hash = "sha256:e10ce637b18caea04431ce14fabcf5c64a1c61ec9c56b071a4b7ca131ca52d44"}, + {file = "PyYAML-6.0.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:c70c95198c015b85feafc136515252a261a84561b7b1d51e3384e0655ddf25ab"}, + {file = "PyYAML-6.0.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:ce826d6ef20b1bc864f0a68340c8b3287705cae2f8b4b1d932177dcc76721725"}, + {file = "PyYAML-6.0.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1f71ea527786de97d1a0cc0eacd1defc0985dcf6b3f17bb77dcfc8c34bec4dc5"}, + {file = "PyYAML-6.0.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:9b22676e8097e9e22e36d6b7bda33190d0d400f345f23d4065d48f4ca7ae0425"}, + {file = "PyYAML-6.0.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:80bab7bfc629882493af4aa31a4cfa43a4c57c83813253626916b8c7ada83476"}, + {file = "PyYAML-6.0.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:0833f8694549e586547b576dcfaba4a6b55b9e96098b36cdc7ebefe667dfed48"}, + {file = "PyYAML-6.0.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8b9c7197f7cb2738065c481a0461e50ad02f18c78cd75775628afb4d7137fb3b"}, + {file = "PyYAML-6.0.2-cp312-cp312-win32.whl", hash = "sha256:ef6107725bd54b262d6dedcc2af448a266975032bc85ef0172c5f059da6325b4"}, + {file = "PyYAML-6.0.2-cp312-cp312-win_amd64.whl", hash = "sha256:7e7401d0de89a9a855c839bc697c079a4af81cf878373abd7dc625847d25cbd8"}, + {file = "PyYAML-6.0.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:efdca5630322a10774e8e98e1af481aad470dd62c3170801852d752aa7a783ba"}, + {file = "PyYAML-6.0.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:50187695423ffe49e2deacb8cd10510bc361faac997de9efef88badc3bb9e2d1"}, + {file = "PyYAML-6.0.2-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0ffe8360bab4910ef1b9e87fb812d8bc0a308b0d0eef8c8f44e0254ab3b07133"}, + {file = "PyYAML-6.0.2-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:17e311b6c678207928d649faa7cb0d7b4c26a0ba73d41e99c4fff6b6c3276484"}, + {file = "PyYAML-6.0.2-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70b189594dbe54f75ab3a1acec5f1e3faa7e8cf2f1e08d9b561cb41b845f69d5"}, + {file = "PyYAML-6.0.2-cp313-cp313-musllinux_1_1_aarch64.whl", hash = "sha256:41e4e3953a79407c794916fa277a82531dd93aad34e29c2a514c2c0c5fe971cc"}, + {file = "PyYAML-6.0.2-cp313-cp313-musllinux_1_1_x86_64.whl", hash = "sha256:68ccc6023a3400877818152ad9a1033e3db8625d899c72eacb5a668902e4d652"}, + {file = "PyYAML-6.0.2-cp313-cp313-win32.whl", hash = "sha256:bc2fa7c6b47d6bc618dd7fb02ef6fdedb1090ec036abab80d4681424b84c1183"}, + {file = "PyYAML-6.0.2-cp313-cp313-win_amd64.whl", hash = "sha256:8388ee1976c416731879ac16da0aff3f63b286ffdd57cdeb95f3f2e085687563"}, + {file = "PyYAML-6.0.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:24471b829b3bf607e04e88d79542a9d48bb037c2267d7927a874e6c205ca7e9a"}, + {file = "PyYAML-6.0.2-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7fded462629cfa4b685c5416b949ebad6cec74af5e2d42905d41e257e0869f5"}, + {file = "PyYAML-6.0.2-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d84a1718ee396f54f3a086ea0a66d8e552b2ab2017ef8b420e92edbc841c352d"}, + {file = "PyYAML-6.0.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9056c1ecd25795207ad294bcf39f2db3d845767be0ea6e6a34d856f006006083"}, + {file = "PyYAML-6.0.2-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:82d09873e40955485746739bcb8b4586983670466c23382c19cffecbf1fd8706"}, + {file = "PyYAML-6.0.2-cp38-cp38-win32.whl", hash = "sha256:43fa96a3ca0d6b1812e01ced1044a003533c47f6ee8aca31724f78e93ccc089a"}, + {file = "PyYAML-6.0.2-cp38-cp38-win_amd64.whl", hash = "sha256:01179a4a8559ab5de078078f37e5c1a30d76bb88519906844fd7bdea1b7729ff"}, + {file = "PyYAML-6.0.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:688ba32a1cffef67fd2e9398a2efebaea461578b0923624778664cc1c914db5d"}, + {file = "PyYAML-6.0.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:a8786accb172bd8afb8be14490a16625cbc387036876ab6ba70912730faf8e1f"}, + {file = "PyYAML-6.0.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d8e03406cac8513435335dbab54c0d385e4a49e4945d2909a581c83647ca0290"}, + {file = "PyYAML-6.0.2-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:f753120cb8181e736c57ef7636e83f31b9c0d1722c516f7e86cf15b7aa57ff12"}, + {file = "PyYAML-6.0.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3b1fdb9dc17f5a7677423d508ab4f243a726dea51fa5e70992e59a7411c89d19"}, + {file = "PyYAML-6.0.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:0b69e4ce7a131fe56b7e4d770c67429700908fc0752af059838b1cfb41960e4e"}, + {file = "PyYAML-6.0.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:a9f8c2e67970f13b16084e04f134610fd1d374bf477b17ec1599185cf611d725"}, + {file = "PyYAML-6.0.2-cp39-cp39-win32.whl", hash = "sha256:6395c297d42274772abc367baaa79683958044e5d3835486c16da75d2a694631"}, + {file = "PyYAML-6.0.2-cp39-cp39-win_amd64.whl", hash = "sha256:39693e1f8320ae4f43943590b49779ffb98acb81f788220ea932a6b6c51004d8"}, + {file = "pyyaml-6.0.2.tar.gz", hash = "sha256:d584d9ec91ad65861cc08d42e834324ef890a082e591037abe114850ff7bbc3e"}, ] [[package]] @@ -1524,29 +1641,29 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"] [[package]] name = "ruff" -version = "0.6.2" +version = "0.6.3" description = "An extremely fast Python linter and code formatter, written in Rust." optional = false python-versions = ">=3.7" files = [ - {file = "ruff-0.6.2-py3-none-linux_armv6l.whl", hash = "sha256:5c8cbc6252deb3ea840ad6a20b0f8583caab0c5ef4f9cca21adc5a92b8f79f3c"}, - {file = "ruff-0.6.2-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:17002fe241e76544448a8e1e6118abecbe8cd10cf68fde635dad480dba594570"}, - {file = "ruff-0.6.2-py3-none-macosx_11_0_arm64.whl", hash = "sha256:3dbeac76ed13456f8158b8f4fe087bf87882e645c8e8b606dd17b0b66c2c1158"}, - {file = "ruff-0.6.2-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:094600ee88cda325988d3f54e3588c46de5c18dae09d683ace278b11f9d4d534"}, - {file = "ruff-0.6.2-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:316d418fe258c036ba05fbf7dfc1f7d3d4096db63431546163b472285668132b"}, - {file = "ruff-0.6.2-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d72b8b3abf8a2d51b7b9944a41307d2f442558ccb3859bbd87e6ae9be1694a5d"}, - {file = "ruff-0.6.2-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:2aed7e243be68487aa8982e91c6e260982d00da3f38955873aecd5a9204b1d66"}, - {file = "ruff-0.6.2-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d371f7fc9cec83497fe7cf5eaf5b76e22a8efce463de5f775a1826197feb9df8"}, - {file = "ruff-0.6.2-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a8f310d63af08f583363dfb844ba8f9417b558199c58a5999215082036d795a1"}, - {file = "ruff-0.6.2-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7db6880c53c56addb8638fe444818183385ec85eeada1d48fc5abe045301b2f1"}, - {file = "ruff-0.6.2-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:1175d39faadd9a50718f478d23bfc1d4da5743f1ab56af81a2b6caf0a2394f23"}, - {file = "ruff-0.6.2-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:5b939f9c86d51635fe486585389f54582f0d65b8238e08c327c1534844b3bb9a"}, - {file = "ruff-0.6.2-py3-none-musllinux_1_2_i686.whl", hash = "sha256:d0d62ca91219f906caf9b187dea50d17353f15ec9bb15aae4a606cd697b49b4c"}, - {file = "ruff-0.6.2-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:7438a7288f9d67ed3c8ce4d059e67f7ed65e9fe3aa2ab6f5b4b3610e57e3cb56"}, - {file = "ruff-0.6.2-py3-none-win32.whl", hash = "sha256:279d5f7d86696df5f9549b56b9b6a7f6c72961b619022b5b7999b15db392a4da"}, - {file = "ruff-0.6.2-py3-none-win_amd64.whl", hash = "sha256:d9f3469c7dd43cd22eb1c3fc16926fb8258d50cb1b216658a07be95dd117b0f2"}, - {file = "ruff-0.6.2-py3-none-win_arm64.whl", hash = "sha256:f28fcd2cd0e02bdf739297516d5643a945cc7caf09bd9bcb4d932540a5ea4fa9"}, - {file = "ruff-0.6.2.tar.gz", hash = "sha256:239ee6beb9e91feb8e0ec384204a763f36cb53fb895a1a364618c6abb076b3be"}, + {file = "ruff-0.6.3-py3-none-linux_armv6l.whl", hash = "sha256:97f58fda4e309382ad30ede7f30e2791d70dd29ea17f41970119f55bdb7a45c3"}, + {file = "ruff-0.6.3-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:3b061e49b5cf3a297b4d1c27ac5587954ccb4ff601160d3d6b2f70b1622194dc"}, + {file = "ruff-0.6.3-py3-none-macosx_11_0_arm64.whl", hash = "sha256:34e2824a13bb8c668c71c1760a6ac7d795ccbd8d38ff4a0d8471fdb15de910b1"}, + {file = "ruff-0.6.3-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bddfbb8d63c460f4b4128b6a506e7052bad4d6f3ff607ebbb41b0aa19c2770d1"}, + {file = "ruff-0.6.3-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:ced3eeb44df75353e08ab3b6a9e113b5f3f996bea48d4f7c027bc528ba87b672"}, + {file = "ruff-0.6.3-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:47021dff5445d549be954eb275156dfd7c37222acc1e8014311badcb9b4ec8c1"}, + {file = "ruff-0.6.3-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:7d7bd20dc07cebd68cc8bc7b3f5ada6d637f42d947c85264f94b0d1cd9d87384"}, + {file = "ruff-0.6.3-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:500f166d03fc6d0e61c8e40a3ff853fa8a43d938f5d14c183c612df1b0d6c58a"}, + {file = "ruff-0.6.3-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:42844ff678f9b976366b262fa2d1d1a3fe76f6e145bd92c84e27d172e3c34500"}, + {file = "ruff-0.6.3-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70452a10eb2d66549de8e75f89ae82462159855e983ddff91bc0bce6511d0470"}, + {file = "ruff-0.6.3-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:65a533235ed55f767d1fc62193a21cbf9e3329cf26d427b800fdeacfb77d296f"}, + {file = "ruff-0.6.3-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:d2e2c23cef30dc3cbe9cc5d04f2899e7f5e478c40d2e0a633513ad081f7361b5"}, + {file = "ruff-0.6.3-py3-none-musllinux_1_2_i686.whl", hash = "sha256:d8a136aa7d228975a6aee3dd8bea9b28e2b43e9444aa678fb62aeb1956ff2351"}, + {file = "ruff-0.6.3-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:f92fe93bc72e262b7b3f2bba9879897e2d58a989b4714ba6a5a7273e842ad2f8"}, + {file = "ruff-0.6.3-py3-none-win32.whl", hash = "sha256:7a62d3b5b0d7f9143d94893f8ba43aa5a5c51a0ffc4a401aa97a81ed76930521"}, + {file = "ruff-0.6.3-py3-none-win_amd64.whl", hash = "sha256:746af39356fee2b89aada06c7376e1aa274a23493d7016059c3a72e3b296befb"}, + {file = "ruff-0.6.3-py3-none-win_arm64.whl", hash = "sha256:14a9528a8b70ccc7a847637c29e56fd1f9183a9db743bbc5b8e0c4ad60592a82"}, + {file = "ruff-0.6.3.tar.gz", hash = "sha256:183b99e9edd1ef63be34a3b51fee0a9f4ab95add123dbf89a71f7b1f0c991983"}, ] [[package]] @@ -1573,60 +1690,60 @@ files = [ [[package]] name = "sqlalchemy" -version = "2.0.31" +version = "2.0.34" description = "Database Abstraction Library" optional = false python-versions = ">=3.7" files = [ - {file = "SQLAlchemy-2.0.31-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:f2a213c1b699d3f5768a7272de720387ae0122f1becf0901ed6eaa1abd1baf6c"}, - {file = "SQLAlchemy-2.0.31-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9fea3d0884e82d1e33226935dac990b967bef21315cbcc894605db3441347443"}, - {file = "SQLAlchemy-2.0.31-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f3ad7f221d8a69d32d197e5968d798217a4feebe30144986af71ada8c548e9fa"}, - {file = "SQLAlchemy-2.0.31-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9f2bee229715b6366f86a95d497c347c22ddffa2c7c96143b59a2aa5cc9eebbc"}, - {file = "SQLAlchemy-2.0.31-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:cd5b94d4819c0c89280b7c6109c7b788a576084bf0a480ae17c227b0bc41e109"}, - {file = "SQLAlchemy-2.0.31-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:750900a471d39a7eeba57580b11983030517a1f512c2cb287d5ad0fcf3aebd58"}, - {file = "SQLAlchemy-2.0.31-cp310-cp310-win32.whl", hash = "sha256:7bd112be780928c7f493c1a192cd8c5fc2a2a7b52b790bc5a84203fb4381c6be"}, - {file = "SQLAlchemy-2.0.31-cp310-cp310-win_amd64.whl", hash = "sha256:5a48ac4d359f058474fadc2115f78a5cdac9988d4f99eae44917f36aa1476327"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:f68470edd70c3ac3b6cd5c2a22a8daf18415203ca1b036aaeb9b0fb6f54e8298"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:2e2c38c2a4c5c634fe6c3c58a789712719fa1bf9b9d6ff5ebfce9a9e5b89c1ca"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:bd15026f77420eb2b324dcb93551ad9c5f22fab2c150c286ef1dc1160f110203"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:2196208432deebdfe3b22185d46b08f00ac9d7b01284e168c212919891289396"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:352b2770097f41bff6029b280c0e03b217c2dcaddc40726f8f53ed58d8a85da4"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:56d51ae825d20d604583f82c9527d285e9e6d14f9a5516463d9705dab20c3740"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-win32.whl", hash = "sha256:6e2622844551945db81c26a02f27d94145b561f9d4b0c39ce7bfd2fda5776dac"}, - {file = "SQLAlchemy-2.0.31-cp311-cp311-win_amd64.whl", hash = "sha256:ccaf1b0c90435b6e430f5dd30a5aede4764942a695552eb3a4ab74ed63c5b8d3"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:3b74570d99126992d4b0f91fb87c586a574a5872651185de8297c6f90055ae42"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:6f77c4f042ad493cb8595e2f503c7a4fe44cd7bd59c7582fd6d78d7e7b8ec52c"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cd1591329333daf94467e699e11015d9c944f44c94d2091f4ac493ced0119449"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:74afabeeff415e35525bf7a4ecdab015f00e06456166a2eba7590e49f8db940e"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:b9c01990d9015df2c6f818aa8f4297d42ee71c9502026bb074e713d496e26b67"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:66f63278db425838b3c2b1c596654b31939427016ba030e951b292e32b99553e"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-win32.whl", hash = "sha256:0b0f658414ee4e4b8cbcd4a9bb0fd743c5eeb81fc858ca517217a8013d282c96"}, - {file = "SQLAlchemy-2.0.31-cp312-cp312-win_amd64.whl", hash = "sha256:fa4b1af3e619b5b0b435e333f3967612db06351217c58bfb50cee5f003db2a5a"}, - {file = "SQLAlchemy-2.0.31-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:f43e93057cf52a227eda401251c72b6fbe4756f35fa6bfebb5d73b86881e59b0"}, - {file = "SQLAlchemy-2.0.31-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d337bf94052856d1b330d5fcad44582a30c532a2463776e1651bd3294ee7e58b"}, - {file = "SQLAlchemy-2.0.31-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c06fb43a51ccdff3b4006aafee9fcf15f63f23c580675f7734245ceb6b6a9e05"}, - {file = "SQLAlchemy-2.0.31-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:b6e22630e89f0e8c12332b2b4c282cb01cf4da0d26795b7eae16702a608e7ca1"}, - {file = "SQLAlchemy-2.0.31-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:79a40771363c5e9f3a77f0e28b3302801db08040928146e6808b5b7a40749c88"}, - {file = "SQLAlchemy-2.0.31-cp37-cp37m-win32.whl", hash = "sha256:501ff052229cb79dd4c49c402f6cb03b5a40ae4771efc8bb2bfac9f6c3d3508f"}, - {file = "SQLAlchemy-2.0.31-cp37-cp37m-win_amd64.whl", hash = "sha256:597fec37c382a5442ffd471f66ce12d07d91b281fd474289356b1a0041bdf31d"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:dc6d69f8829712a4fd799d2ac8d79bdeff651c2301b081fd5d3fe697bd5b4ab9"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:23b9fbb2f5dd9e630db70fbe47d963c7779e9c81830869bd7d137c2dc1ad05fb"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2a21c97efcbb9f255d5c12a96ae14da873233597dfd00a3a0c4ce5b3e5e79704"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:26a6a9837589c42b16693cf7bf836f5d42218f44d198f9343dd71d3164ceeeac"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:dc251477eae03c20fae8db9c1c23ea2ebc47331bcd73927cdcaecd02af98d3c3"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:2fd17e3bb8058359fa61248c52c7b09a97cf3c820e54207a50af529876451808"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-win32.whl", hash = "sha256:c76c81c52e1e08f12f4b6a07af2b96b9b15ea67ccdd40ae17019f1c373faa227"}, - {file = "SQLAlchemy-2.0.31-cp38-cp38-win_amd64.whl", hash = "sha256:4b600e9a212ed59355813becbcf282cfda5c93678e15c25a0ef896b354423238"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:5b6cf796d9fcc9b37011d3f9936189b3c8074a02a4ed0c0fbbc126772c31a6d4"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:78fe11dbe37d92667c2c6e74379f75746dc947ee505555a0197cfba9a6d4f1a4"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2fc47dc6185a83c8100b37acda27658fe4dbd33b7d5e7324111f6521008ab4fe"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8a41514c1a779e2aa9a19f67aaadeb5cbddf0b2b508843fcd7bafdf4c6864005"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:afb6dde6c11ea4525318e279cd93c8734b795ac8bb5dda0eedd9ebaca7fa23f1"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:3f9faef422cfbb8fd53716cd14ba95e2ef655400235c3dfad1b5f467ba179c8c"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-win32.whl", hash = "sha256:fc6b14e8602f59c6ba893980bea96571dd0ed83d8ebb9c4479d9ed5425d562e9"}, - {file = "SQLAlchemy-2.0.31-cp39-cp39-win_amd64.whl", hash = "sha256:3cb8a66b167b033ec72c3812ffc8441d4e9f5f78f5e31e54dcd4c90a4ca5bebc"}, - {file = "SQLAlchemy-2.0.31-py3-none-any.whl", hash = "sha256:69f3e3c08867a8e4856e92d7afb618b95cdee18e0bc1647b77599722c9a28911"}, - {file = "SQLAlchemy-2.0.31.tar.gz", hash = "sha256:b607489dd4a54de56984a0c7656247504bd5523d9d0ba799aef59d4add009484"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:95d0b2cf8791ab5fb9e3aa3d9a79a0d5d51f55b6357eecf532a120ba3b5524db"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:243f92596f4fd4c8bd30ab8e8dd5965afe226363d75cab2468f2c707f64cd83b"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:9ea54f7300553af0a2a7235e9b85f4204e1fc21848f917a3213b0e0818de9a24"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:173f5f122d2e1bff8fbd9f7811b7942bead1f5e9f371cdf9e670b327e6703ebd"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:196958cde924a00488e3e83ff917be3b73cd4ed8352bbc0f2989333176d1c54d"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:bd90c221ed4e60ac9d476db967f436cfcecbd4ef744537c0f2d5291439848768"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-win32.whl", hash = "sha256:3166dfff2d16fe9be3241ee60ece6fcb01cf8e74dd7c5e0b64f8e19fab44911b"}, + {file = "SQLAlchemy-2.0.34-cp310-cp310-win_amd64.whl", hash = "sha256:6831a78bbd3c40f909b3e5233f87341f12d0b34a58f14115c9e94b4cdaf726d3"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:c7db3db284a0edaebe87f8f6642c2b2c27ed85c3e70064b84d1c9e4ec06d5d84"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:430093fce0efc7941d911d34f75a70084f12f6ca5c15d19595c18753edb7c33b"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:79cb400c360c7c210097b147c16a9e4c14688a6402445ac848f296ade6283bbc"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fb1b30f31a36c7f3fee848391ff77eebdd3af5750bf95fbf9b8b5323edfdb4ec"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8fddde2368e777ea2a4891a3fb4341e910a056be0bb15303bf1b92f073b80c02"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:80bd73ea335203b125cf1d8e50fef06be709619eb6ab9e7b891ea34b5baa2287"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-win32.whl", hash = "sha256:6daeb8382d0df526372abd9cb795c992e18eed25ef2c43afe518c73f8cccb721"}, + {file = "SQLAlchemy-2.0.34-cp311-cp311-win_amd64.whl", hash = "sha256:5bc08e75ed11693ecb648b7a0a4ed80da6d10845e44be0c98c03f2f880b68ff4"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:53e68b091492c8ed2bd0141e00ad3089bcc6bf0e6ec4142ad6505b4afe64163e"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:bcd18441a49499bf5528deaa9dee1f5c01ca491fc2791b13604e8f972877f812"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:165bbe0b376541092bf49542bd9827b048357f4623486096fc9aaa6d4e7c59a2"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c3330415cd387d2b88600e8e26b510d0370db9b7eaf984354a43e19c40df2e2b"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:97b850f73f8abbffb66ccbab6e55a195a0eb655e5dc74624d15cff4bfb35bd74"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:7cee4c6917857fd6121ed84f56d1dc78eb1d0e87f845ab5a568aba73e78adf83"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-win32.whl", hash = "sha256:fbb034f565ecbe6c530dff948239377ba859420d146d5f62f0271407ffb8c580"}, + {file = "SQLAlchemy-2.0.34-cp312-cp312-win_amd64.whl", hash = "sha256:707c8f44931a4facd4149b52b75b80544a8d824162602b8cd2fe788207307f9a"}, + {file = "SQLAlchemy-2.0.34-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:24af3dc43568f3780b7e1e57c49b41d98b2d940c1fd2e62d65d3928b6f95f021"}, + {file = "SQLAlchemy-2.0.34-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:e60ed6ef0a35c6b76b7640fe452d0e47acc832ccbb8475de549a5cc5f90c2c06"}, + {file = "SQLAlchemy-2.0.34-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:413c85cd0177c23e32dee6898c67a5f49296640041d98fddb2c40888fe4daa2e"}, + {file = "SQLAlchemy-2.0.34-cp37-cp37m-musllinux_1_2_aarch64.whl", hash = "sha256:25691f4adfb9d5e796fd48bf1432272f95f4bbe5f89c475a788f31232ea6afba"}, + {file = "SQLAlchemy-2.0.34-cp37-cp37m-musllinux_1_2_x86_64.whl", hash = "sha256:526ce723265643dbc4c7efb54f56648cc30e7abe20f387d763364b3ce7506c82"}, + {file = "SQLAlchemy-2.0.34-cp37-cp37m-win32.whl", hash = "sha256:13be2cc683b76977a700948411a94c67ad8faf542fa7da2a4b167f2244781cf3"}, + {file = "SQLAlchemy-2.0.34-cp37-cp37m-win_amd64.whl", hash = "sha256:e54ef33ea80d464c3dcfe881eb00ad5921b60f8115ea1a30d781653edc2fd6a2"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:43f28005141165edd11fbbf1541c920bd29e167b8bbc1fb410d4fe2269c1667a"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:b68094b165a9e930aedef90725a8fcfafe9ef95370cbb54abc0464062dbf808f"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6a1e03db964e9d32f112bae36f0cc1dcd1988d096cfd75d6a588a3c3def9ab2b"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:203d46bddeaa7982f9c3cc693e5bc93db476ab5de9d4b4640d5c99ff219bee8c"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:ae92bebca3b1e6bd203494e5ef919a60fb6dfe4d9a47ed2453211d3bd451b9f5"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:9661268415f450c95f72f0ac1217cc6f10256f860eed85c2ae32e75b60278ad8"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-win32.whl", hash = "sha256:895184dfef8708e15f7516bd930bda7e50ead069280d2ce09ba11781b630a434"}, + {file = "SQLAlchemy-2.0.34-cp38-cp38-win_amd64.whl", hash = "sha256:6e7cde3a2221aa89247944cafb1b26616380e30c63e37ed19ff0bba5e968688d"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:dbcdf987f3aceef9763b6d7b1fd3e4ee210ddd26cac421d78b3c206d07b2700b"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ce119fc4ce0d64124d37f66a6f2a584fddc3c5001755f8a49f1ca0a177ef9796"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a17d8fac6df9835d8e2b4c5523666e7051d0897a93756518a1fe101c7f47f2f0"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9ebc11c54c6ecdd07bb4efbfa1554538982f5432dfb8456958b6d46b9f834bb7"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:2e6965346fc1491a566e019a4a1d3dfc081ce7ac1a736536367ca305da6472a8"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:220574e78ad986aea8e81ac68821e47ea9202b7e44f251b7ed8c66d9ae3f4278"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-win32.whl", hash = "sha256:b75b00083e7fe6621ce13cfce9d4469c4774e55e8e9d38c305b37f13cf1e874c"}, + {file = "SQLAlchemy-2.0.34-cp39-cp39-win_amd64.whl", hash = "sha256:c29d03e0adf3cc1a8c3ec62d176824972ae29b67a66cbb18daff3062acc6faa8"}, + {file = "SQLAlchemy-2.0.34-py3-none-any.whl", hash = "sha256:7286c353ee6475613d8beff83167374006c6b3e3f0e6491bfe8ca610eb1dec0f"}, + {file = "sqlalchemy-2.0.34.tar.gz", hash = "sha256:10d8f36990dd929690666679b0f42235c159a7051534adb135728ee52828dd22"}, ] [package.dependencies] @@ -1660,13 +1777,13 @@ sqlcipher = ["sqlcipher3_binary"] [[package]] name = "syrupy" -version = "4.6.1" +version = "4.7.1" description = "Pytest Snapshot Test Utility" optional = false -python-versions = ">=3.8.1,<4" +python-versions = ">=3.8.1" files = [ - {file = "syrupy-4.6.1-py3-none-any.whl", hash = "sha256:203e52f9cb9fa749cf683f29bd68f02c16c3bc7e7e5fe8f2fc59bdfe488ce133"}, - {file = "syrupy-4.6.1.tar.gz", hash = "sha256:37a835c9ce7857eeef86d62145885e10b3cb9615bc6abeb4ce404b3f18e1bb36"}, + {file = "syrupy-4.7.1-py3-none-any.whl", hash = "sha256:be002267a512a4bedddfae2e026c93df1ea928ae10baadc09640516923376d41"}, + {file = "syrupy-4.7.1.tar.gz", hash = "sha256:f9d4485f3f27d0e5df6ed299cac6fa32eb40a441915d988e82be5a4bdda335c8"}, ] [package.dependencies] @@ -1750,43 +1867,46 @@ files = [ [[package]] name = "watchdog" -version = "4.0.1" +version = "4.0.2" description = "Filesystem events monitoring" optional = false python-versions = ">=3.8" files = [ - {file = "watchdog-4.0.1-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:da2dfdaa8006eb6a71051795856bedd97e5b03e57da96f98e375682c48850645"}, - {file = "watchdog-4.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e93f451f2dfa433d97765ca2634628b789b49ba8b504fdde5837cdcf25fdb53b"}, - {file = "watchdog-4.0.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:ef0107bbb6a55f5be727cfc2ef945d5676b97bffb8425650dadbb184be9f9a2b"}, - {file = "watchdog-4.0.1-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:17e32f147d8bf9657e0922c0940bcde863b894cd871dbb694beb6704cfbd2fb5"}, - {file = "watchdog-4.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:03e70d2df2258fb6cb0e95bbdbe06c16e608af94a3ffbd2b90c3f1e83eb10767"}, - {file = "watchdog-4.0.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:123587af84260c991dc5f62a6e7ef3d1c57dfddc99faacee508c71d287248459"}, - {file = "watchdog-4.0.1-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:093b23e6906a8b97051191a4a0c73a77ecc958121d42346274c6af6520dec175"}, - {file = "watchdog-4.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:611be3904f9843f0529c35a3ff3fd617449463cb4b73b1633950b3d97fa4bfb7"}, - {file = "watchdog-4.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:62c613ad689ddcb11707f030e722fa929f322ef7e4f18f5335d2b73c61a85c28"}, - {file = "watchdog-4.0.1-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:d4925e4bf7b9bddd1c3de13c9b8a2cdb89a468f640e66fbfabaf735bd85b3e35"}, - {file = "watchdog-4.0.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:cad0bbd66cd59fc474b4a4376bc5ac3fc698723510cbb64091c2a793b18654db"}, - {file = "watchdog-4.0.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:a3c2c317a8fb53e5b3d25790553796105501a235343f5d2bf23bb8649c2c8709"}, - {file = "watchdog-4.0.1-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:c9904904b6564d4ee8a1ed820db76185a3c96e05560c776c79a6ce5ab71888ba"}, - {file = "watchdog-4.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:667f3c579e813fcbad1b784db7a1aaa96524bed53437e119f6a2f5de4db04235"}, - {file = "watchdog-4.0.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:d10a681c9a1d5a77e75c48a3b8e1a9f2ae2928eda463e8d33660437705659682"}, - {file = "watchdog-4.0.1-pp310-pypy310_pp73-macosx_10_9_x86_64.whl", hash = "sha256:0144c0ea9997b92615af1d94afc0c217e07ce2c14912c7b1a5731776329fcfc7"}, - {file = "watchdog-4.0.1-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:998d2be6976a0ee3a81fb8e2777900c28641fb5bfbd0c84717d89bca0addcdc5"}, - {file = "watchdog-4.0.1-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:e7921319fe4430b11278d924ef66d4daa469fafb1da679a2e48c935fa27af193"}, - {file = "watchdog-4.0.1-pp38-pypy38_pp73-macosx_11_0_arm64.whl", hash = "sha256:f0de0f284248ab40188f23380b03b59126d1479cd59940f2a34f8852db710625"}, - {file = "watchdog-4.0.1-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:bca36be5707e81b9e6ce3208d92d95540d4ca244c006b61511753583c81c70dd"}, - {file = "watchdog-4.0.1-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:ab998f567ebdf6b1da7dc1e5accfaa7c6992244629c0fdaef062f43249bd8dee"}, - {file = "watchdog-4.0.1-py3-none-manylinux2014_aarch64.whl", hash = "sha256:dddba7ca1c807045323b6af4ff80f5ddc4d654c8bce8317dde1bd96b128ed253"}, - {file = "watchdog-4.0.1-py3-none-manylinux2014_armv7l.whl", hash = "sha256:4513ec234c68b14d4161440e07f995f231be21a09329051e67a2118a7a612d2d"}, - {file = "watchdog-4.0.1-py3-none-manylinux2014_i686.whl", hash = "sha256:4107ac5ab936a63952dea2a46a734a23230aa2f6f9db1291bf171dac3ebd53c6"}, - {file = "watchdog-4.0.1-py3-none-manylinux2014_ppc64.whl", hash = "sha256:6e8c70d2cd745daec2a08734d9f63092b793ad97612470a0ee4cbb8f5f705c57"}, - {file = "watchdog-4.0.1-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:f27279d060e2ab24c0aa98363ff906d2386aa6c4dc2f1a374655d4e02a6c5e5e"}, - {file = "watchdog-4.0.1-py3-none-manylinux2014_s390x.whl", hash = "sha256:f8affdf3c0f0466e69f5b3917cdd042f89c8c63aebdb9f7c078996f607cdb0f5"}, - {file = "watchdog-4.0.1-py3-none-manylinux2014_x86_64.whl", hash = "sha256:ac7041b385f04c047fcc2951dc001671dee1b7e0615cde772e84b01fbf68ee84"}, - {file = "watchdog-4.0.1-py3-none-win32.whl", hash = "sha256:206afc3d964f9a233e6ad34618ec60b9837d0582b500b63687e34011e15bb429"}, - {file = "watchdog-4.0.1-py3-none-win_amd64.whl", hash = "sha256:7577b3c43e5909623149f76b099ac49a1a01ca4e167d1785c76eb52fa585745a"}, - {file = "watchdog-4.0.1-py3-none-win_ia64.whl", hash = "sha256:d7b9f5f3299e8dd230880b6c55504a1f69cf1e4316275d1b215ebdd8187ec88d"}, - {file = "watchdog-4.0.1.tar.gz", hash = "sha256:eebaacf674fa25511e8867028d281e602ee6500045b57f43b08778082f7f8b44"}, + {file = "watchdog-4.0.2-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:ede7f010f2239b97cc79e6cb3c249e72962404ae3865860855d5cbe708b0fd22"}, + {file = "watchdog-4.0.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a2cffa171445b0efa0726c561eca9a27d00a1f2b83846dbd5a4f639c4f8ca8e1"}, + {file = "watchdog-4.0.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c50f148b31b03fbadd6d0b5980e38b558046b127dc483e5e4505fcef250f9503"}, + {file = "watchdog-4.0.2-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:7c7d4bf585ad501c5f6c980e7be9c4f15604c7cc150e942d82083b31a7548930"}, + {file = "watchdog-4.0.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:914285126ad0b6eb2258bbbcb7b288d9dfd655ae88fa28945be05a7b475a800b"}, + {file = "watchdog-4.0.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:984306dc4720da5498b16fc037b36ac443816125a3705dfde4fd90652d8028ef"}, + {file = "watchdog-4.0.2-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:1cdcfd8142f604630deef34722d695fb455d04ab7cfe9963055df1fc69e6727a"}, + {file = "watchdog-4.0.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:d7ab624ff2f663f98cd03c8b7eedc09375a911794dfea6bf2a359fcc266bff29"}, + {file = "watchdog-4.0.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:132937547a716027bd5714383dfc40dc66c26769f1ce8a72a859d6a48f371f3a"}, + {file = "watchdog-4.0.2-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:cd67c7df93eb58f360c43802acc945fa8da70c675b6fa37a241e17ca698ca49b"}, + {file = "watchdog-4.0.2-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:bcfd02377be80ef3b6bc4ce481ef3959640458d6feaae0bd43dd90a43da90a7d"}, + {file = "watchdog-4.0.2-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:980b71510f59c884d684b3663d46e7a14b457c9611c481e5cef08f4dd022eed7"}, + {file = "watchdog-4.0.2-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:aa160781cafff2719b663c8a506156e9289d111d80f3387cf3af49cedee1f040"}, + {file = "watchdog-4.0.2-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:f6ee8dedd255087bc7fe82adf046f0b75479b989185fb0bdf9a98b612170eac7"}, + {file = "watchdog-4.0.2-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:0b4359067d30d5b864e09c8597b112fe0a0a59321a0f331498b013fb097406b4"}, + {file = "watchdog-4.0.2-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:770eef5372f146997638d737c9a3c597a3b41037cfbc5c41538fc27c09c3a3f9"}, + {file = "watchdog-4.0.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:eeea812f38536a0aa859972d50c76e37f4456474b02bd93674d1947cf1e39578"}, + {file = "watchdog-4.0.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:b2c45f6e1e57ebb4687690c05bc3a2c1fb6ab260550c4290b8abb1335e0fd08b"}, + {file = "watchdog-4.0.2-pp310-pypy310_pp73-macosx_10_15_x86_64.whl", hash = "sha256:10b6683df70d340ac3279eff0b2766813f00f35a1d37515d2c99959ada8f05fa"}, + {file = "watchdog-4.0.2-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:f7c739888c20f99824f7aa9d31ac8a97353e22d0c0e54703a547a218f6637eb3"}, + {file = "watchdog-4.0.2-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:c100d09ac72a8a08ddbf0629ddfa0b8ee41740f9051429baa8e31bb903ad7508"}, + {file = "watchdog-4.0.2-pp38-pypy38_pp73-macosx_11_0_arm64.whl", hash = "sha256:f5315a8c8dd6dd9425b974515081fc0aadca1d1d61e078d2246509fd756141ee"}, + {file = "watchdog-4.0.2-pp39-pypy39_pp73-macosx_10_15_x86_64.whl", hash = "sha256:2d468028a77b42cc685ed694a7a550a8d1771bb05193ba7b24006b8241a571a1"}, + {file = "watchdog-4.0.2-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:f15edcae3830ff20e55d1f4e743e92970c847bcddc8b7509bcd172aa04de506e"}, + {file = "watchdog-4.0.2-py3-none-manylinux2014_aarch64.whl", hash = "sha256:936acba76d636f70db8f3c66e76aa6cb5136a936fc2a5088b9ce1c7a3508fc83"}, + {file = "watchdog-4.0.2-py3-none-manylinux2014_armv7l.whl", hash = "sha256:e252f8ca942a870f38cf785aef420285431311652d871409a64e2a0a52a2174c"}, + {file = "watchdog-4.0.2-py3-none-manylinux2014_i686.whl", hash = "sha256:0e83619a2d5d436a7e58a1aea957a3c1ccbf9782c43c0b4fed80580e5e4acd1a"}, + {file = "watchdog-4.0.2-py3-none-manylinux2014_ppc64.whl", hash = "sha256:88456d65f207b39f1981bf772e473799fcdc10801062c36fd5ad9f9d1d463a73"}, + {file = "watchdog-4.0.2-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:32be97f3b75693a93c683787a87a0dc8db98bb84701539954eef991fb35f5fbc"}, + {file = "watchdog-4.0.2-py3-none-manylinux2014_s390x.whl", hash = "sha256:c82253cfc9be68e3e49282831afad2c1f6593af80c0daf1287f6a92657986757"}, + {file = "watchdog-4.0.2-py3-none-manylinux2014_x86_64.whl", hash = "sha256:c0b14488bd336c5b1845cee83d3e631a1f8b4e9c5091ec539406e4a324f882d8"}, + {file = "watchdog-4.0.2-py3-none-win32.whl", hash = "sha256:0d8a7e523ef03757a5aa29f591437d64d0d894635f8a50f370fe37f913ce4e19"}, + {file = "watchdog-4.0.2-py3-none-win_amd64.whl", hash = "sha256:c344453ef3bf875a535b0488e3ad28e341adbd5a9ffb0f7d62cefacc8824ef2b"}, + {file = "watchdog-4.0.2-py3-none-win_ia64.whl", hash = "sha256:baececaa8edff42cd16558a639a9b0ddf425f93d892e8392a56bf904f5eff22c"}, + {file = "watchdog-4.0.2.tar.gz", hash = "sha256:b4dfbb6c49221be4535623ea4474a4d6ee0a9cef4a80b20c28db4d858b64e270"}, ] [package.extras] @@ -1794,101 +1914,103 @@ watchmedo = ["PyYAML (>=3.10)"] [[package]] name = "yarl" -version = "1.9.4" +version = "1.9.11" description = "Yet another URL library" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "yarl-1.9.4-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:a8c1df72eb746f4136fe9a2e72b0c9dc1da1cbd23b5372f94b5820ff8ae30e0e"}, - {file = "yarl-1.9.4-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a3a6ed1d525bfb91b3fc9b690c5a21bb52de28c018530ad85093cc488bee2dd2"}, - {file = "yarl-1.9.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:c38c9ddb6103ceae4e4498f9c08fac9b590c5c71b0370f98714768e22ac6fa66"}, - {file = "yarl-1.9.4-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d9e09c9d74f4566e905a0b8fa668c58109f7624db96a2171f21747abc7524234"}, - {file = "yarl-1.9.4-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:b8477c1ee4bd47c57d49621a062121c3023609f7a13b8a46953eb6c9716ca392"}, - {file = "yarl-1.9.4-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:d5ff2c858f5f6a42c2a8e751100f237c5e869cbde669a724f2062d4c4ef93551"}, - {file = "yarl-1.9.4-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:357495293086c5b6d34ca9616a43d329317feab7917518bc97a08f9e55648455"}, - {file = "yarl-1.9.4-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:54525ae423d7b7a8ee81ba189f131054defdb122cde31ff17477951464c1691c"}, - {file = "yarl-1.9.4-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:801e9264d19643548651b9db361ce3287176671fb0117f96b5ac0ee1c3530d53"}, - {file = "yarl-1.9.4-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:e516dc8baf7b380e6c1c26792610230f37147bb754d6426462ab115a02944385"}, - {file = "yarl-1.9.4-cp310-cp310-musllinux_1_1_ppc64le.whl", hash = "sha256:7d5aaac37d19b2904bb9dfe12cdb08c8443e7ba7d2852894ad448d4b8f442863"}, - {file = "yarl-1.9.4-cp310-cp310-musllinux_1_1_s390x.whl", hash = "sha256:54beabb809ffcacbd9d28ac57b0db46e42a6e341a030293fb3185c409e626b8b"}, - {file = "yarl-1.9.4-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:bac8d525a8dbc2a1507ec731d2867025d11ceadcb4dd421423a5d42c56818541"}, - {file = "yarl-1.9.4-cp310-cp310-win32.whl", hash = "sha256:7855426dfbddac81896b6e533ebefc0af2f132d4a47340cee6d22cac7190022d"}, - {file = "yarl-1.9.4-cp310-cp310-win_amd64.whl", hash = "sha256:848cd2a1df56ddbffeb375535fb62c9d1645dde33ca4d51341378b3f5954429b"}, - {file = "yarl-1.9.4-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:35a2b9396879ce32754bd457d31a51ff0a9d426fd9e0e3c33394bf4b9036b099"}, - {file = "yarl-1.9.4-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:4c7d56b293cc071e82532f70adcbd8b61909eec973ae9d2d1f9b233f3d943f2c"}, - {file = "yarl-1.9.4-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:d8a1c6c0be645c745a081c192e747c5de06e944a0d21245f4cf7c05e457c36e0"}, - {file = "yarl-1.9.4-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4b3c1ffe10069f655ea2d731808e76e0f452fc6c749bea04781daf18e6039525"}, - {file = "yarl-1.9.4-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:549d19c84c55d11687ddbd47eeb348a89df9cb30e1993f1b128f4685cd0ebbf8"}, - {file = "yarl-1.9.4-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a7409f968456111140c1c95301cadf071bd30a81cbd7ab829169fb9e3d72eae9"}, - {file = "yarl-1.9.4-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e23a6d84d9d1738dbc6e38167776107e63307dfc8ad108e580548d1f2c587f42"}, - {file = "yarl-1.9.4-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:d8b889777de69897406c9fb0b76cdf2fd0f31267861ae7501d93003d55f54fbe"}, - {file = "yarl-1.9.4-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:03caa9507d3d3c83bca08650678e25364e1843b484f19986a527630ca376ecce"}, - {file = "yarl-1.9.4-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:4e9035df8d0880b2f1c7f5031f33f69e071dfe72ee9310cfc76f7b605958ceb9"}, - {file = "yarl-1.9.4-cp311-cp311-musllinux_1_1_ppc64le.whl", hash = "sha256:c0ec0ed476f77db9fb29bca17f0a8fcc7bc97ad4c6c1d8959c507decb22e8572"}, - {file = "yarl-1.9.4-cp311-cp311-musllinux_1_1_s390x.whl", hash = "sha256:ee04010f26d5102399bd17f8df8bc38dc7ccd7701dc77f4a68c5b8d733406958"}, - {file = "yarl-1.9.4-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:49a180c2e0743d5d6e0b4d1a9e5f633c62eca3f8a86ba5dd3c471060e352ca98"}, - {file = "yarl-1.9.4-cp311-cp311-win32.whl", hash = "sha256:81eb57278deb6098a5b62e88ad8281b2ba09f2f1147c4767522353eaa6260b31"}, - {file = "yarl-1.9.4-cp311-cp311-win_amd64.whl", hash = "sha256:d1d2532b340b692880261c15aee4dc94dd22ca5d61b9db9a8a361953d36410b1"}, - {file = "yarl-1.9.4-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:0d2454f0aef65ea81037759be5ca9947539667eecebca092733b2eb43c965a81"}, - {file = "yarl-1.9.4-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:44d8ffbb9c06e5a7f529f38f53eda23e50d1ed33c6c869e01481d3fafa6b8142"}, - {file = "yarl-1.9.4-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:aaaea1e536f98754a6e5c56091baa1b6ce2f2700cc4a00b0d49eca8dea471074"}, - {file = "yarl-1.9.4-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:3777ce5536d17989c91696db1d459574e9a9bd37660ea7ee4d3344579bb6f129"}, - {file = "yarl-1.9.4-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9fc5fc1eeb029757349ad26bbc5880557389a03fa6ada41703db5e068881e5f2"}, - {file = "yarl-1.9.4-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ea65804b5dc88dacd4a40279af0cdadcfe74b3e5b4c897aa0d81cf86927fee78"}, - {file = "yarl-1.9.4-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa102d6d280a5455ad6a0f9e6d769989638718e938a6a0a2ff3f4a7ff8c62cc4"}, - {file = "yarl-1.9.4-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:09efe4615ada057ba2d30df871d2f668af661e971dfeedf0c159927d48bbeff0"}, - {file = "yarl-1.9.4-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:008d3e808d03ef28542372d01057fd09168419cdc8f848efe2804f894ae03e51"}, - {file = "yarl-1.9.4-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:6f5cb257bc2ec58f437da2b37a8cd48f666db96d47b8a3115c29f316313654ff"}, - {file = "yarl-1.9.4-cp312-cp312-musllinux_1_1_ppc64le.whl", hash = "sha256:992f18e0ea248ee03b5a6e8b3b4738850ae7dbb172cc41c966462801cbf62cf7"}, - {file = "yarl-1.9.4-cp312-cp312-musllinux_1_1_s390x.whl", hash = "sha256:0e9d124c191d5b881060a9e5060627694c3bdd1fe24c5eecc8d5d7d0eb6faabc"}, - {file = "yarl-1.9.4-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:3986b6f41ad22988e53d5778f91855dc0399b043fc8946d4f2e68af22ee9ff10"}, - {file = "yarl-1.9.4-cp312-cp312-win32.whl", hash = "sha256:4b21516d181cd77ebd06ce160ef8cc2a5e9ad35fb1c5930882baff5ac865eee7"}, - {file = "yarl-1.9.4-cp312-cp312-win_amd64.whl", hash = "sha256:a9bd00dc3bc395a662900f33f74feb3e757429e545d831eef5bb280252631984"}, - {file = "yarl-1.9.4-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:63b20738b5aac74e239622d2fe30df4fca4942a86e31bf47a81a0e94c14df94f"}, - {file = "yarl-1.9.4-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7d7f7de27b8944f1fee2c26a88b4dabc2409d2fea7a9ed3df79b67277644e17"}, - {file = "yarl-1.9.4-cp37-cp37m-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c74018551e31269d56fab81a728f683667e7c28c04e807ba08f8c9e3bba32f14"}, - {file = "yarl-1.9.4-cp37-cp37m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ca06675212f94e7a610e85ca36948bb8fc023e458dd6c63ef71abfd482481aa5"}, - {file = "yarl-1.9.4-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5aef935237d60a51a62b86249839b51345f47564208c6ee615ed2a40878dccdd"}, - {file = "yarl-1.9.4-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:2b134fd795e2322b7684155b7855cc99409d10b2e408056db2b93b51a52accc7"}, - {file = "yarl-1.9.4-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:d25039a474c4c72a5ad4b52495056f843a7ff07b632c1b92ea9043a3d9950f6e"}, - {file = "yarl-1.9.4-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:f7d6b36dd2e029b6bcb8a13cf19664c7b8e19ab3a58e0fefbb5b8461447ed5ec"}, - {file = "yarl-1.9.4-cp37-cp37m-musllinux_1_1_ppc64le.whl", hash = "sha256:957b4774373cf6f709359e5c8c4a0af9f6d7875db657adb0feaf8d6cb3c3964c"}, - {file = "yarl-1.9.4-cp37-cp37m-musllinux_1_1_s390x.whl", hash = "sha256:d7eeb6d22331e2fd42fce928a81c697c9ee2d51400bd1a28803965883e13cead"}, - {file = "yarl-1.9.4-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:6a962e04b8f91f8c4e5917e518d17958e3bdee71fd1d8b88cdce74dd0ebbf434"}, - {file = "yarl-1.9.4-cp37-cp37m-win32.whl", hash = "sha256:f3bc6af6e2b8f92eced34ef6a96ffb248e863af20ef4fde9448cc8c9b858b749"}, - {file = "yarl-1.9.4-cp37-cp37m-win_amd64.whl", hash = "sha256:ad4d7a90a92e528aadf4965d685c17dacff3df282db1121136c382dc0b6014d2"}, - {file = "yarl-1.9.4-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:ec61d826d80fc293ed46c9dd26995921e3a82146feacd952ef0757236fc137be"}, - {file = "yarl-1.9.4-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:8be9e837ea9113676e5754b43b940b50cce76d9ed7d2461df1af39a8ee674d9f"}, - {file = "yarl-1.9.4-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:bef596fdaa8f26e3d66af846bbe77057237cb6e8efff8cd7cc8dff9a62278bbf"}, - {file = "yarl-1.9.4-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2d47552b6e52c3319fede1b60b3de120fe83bde9b7bddad11a69fb0af7db32f1"}, - {file = "yarl-1.9.4-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:84fc30f71689d7fc9168b92788abc977dc8cefa806909565fc2951d02f6b7d57"}, - {file = "yarl-1.9.4-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4aa9741085f635934f3a2583e16fcf62ba835719a8b2b28fb2917bb0537c1dfa"}, - {file = "yarl-1.9.4-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:206a55215e6d05dbc6c98ce598a59e6fbd0c493e2de4ea6cc2f4934d5a18d130"}, - {file = "yarl-1.9.4-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:07574b007ee20e5c375a8fe4a0789fad26db905f9813be0f9fef5a68080de559"}, - {file = "yarl-1.9.4-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:5a2e2433eb9344a163aced6a5f6c9222c0786e5a9e9cac2c89f0b28433f56e23"}, - {file = "yarl-1.9.4-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:6ad6d10ed9b67a382b45f29ea028f92d25bc0bc1daf6c5b801b90b5aa70fb9ec"}, - {file = "yarl-1.9.4-cp38-cp38-musllinux_1_1_ppc64le.whl", hash = "sha256:6fe79f998a4052d79e1c30eeb7d6c1c1056ad33300f682465e1b4e9b5a188b78"}, - {file = "yarl-1.9.4-cp38-cp38-musllinux_1_1_s390x.whl", hash = "sha256:a825ec844298c791fd28ed14ed1bffc56a98d15b8c58a20e0e08c1f5f2bea1be"}, - {file = "yarl-1.9.4-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:8619d6915b3b0b34420cf9b2bb6d81ef59d984cb0fde7544e9ece32b4b3043c3"}, - {file = "yarl-1.9.4-cp38-cp38-win32.whl", hash = "sha256:686a0c2f85f83463272ddffd4deb5e591c98aac1897d65e92319f729c320eece"}, - {file = "yarl-1.9.4-cp38-cp38-win_amd64.whl", hash = "sha256:a00862fb23195b6b8322f7d781b0dc1d82cb3bcac346d1e38689370cc1cc398b"}, - {file = "yarl-1.9.4-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:604f31d97fa493083ea21bd9b92c419012531c4e17ea6da0f65cacdcf5d0bd27"}, - {file = "yarl-1.9.4-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8a854227cf581330ffa2c4824d96e52ee621dd571078a252c25e3a3b3d94a1b1"}, - {file = "yarl-1.9.4-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:ba6f52cbc7809cd8d74604cce9c14868306ae4aa0282016b641c661f981a6e91"}, - {file = "yarl-1.9.4-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a6327976c7c2f4ee6816eff196e25385ccc02cb81427952414a64811037bbc8b"}, - {file = "yarl-1.9.4-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8397a3817d7dcdd14bb266283cd1d6fc7264a48c186b986f32e86d86d35fbac5"}, - {file = "yarl-1.9.4-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e0381b4ce23ff92f8170080c97678040fc5b08da85e9e292292aba67fdac6c34"}, - {file = "yarl-1.9.4-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:23d32a2594cb5d565d358a92e151315d1b2268bc10f4610d098f96b147370136"}, - {file = "yarl-1.9.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:ddb2a5c08a4eaaba605340fdee8fc08e406c56617566d9643ad8bf6852778fc7"}, - {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:26a1dc6285e03f3cc9e839a2da83bcbf31dcb0d004c72d0730e755b33466c30e"}, - {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:18580f672e44ce1238b82f7fb87d727c4a131f3a9d33a5e0e82b793362bf18b4"}, - {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:29e0f83f37610f173eb7e7b5562dd71467993495e568e708d99e9d1944f561ec"}, - {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:1f23e4fe1e8794f74b6027d7cf19dc25f8b63af1483d91d595d4a07eca1fb26c"}, - {file = "yarl-1.9.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:db8e58b9d79200c76956cefd14d5c90af54416ff5353c5bfd7cbe58818e26ef0"}, - {file = "yarl-1.9.4-cp39-cp39-win32.whl", hash = "sha256:c7224cab95645c7ab53791022ae77a4509472613e839dab722a72abe5a684575"}, - {file = "yarl-1.9.4-cp39-cp39-win_amd64.whl", hash = "sha256:824d6c50492add5da9374875ce72db7a0733b29c2394890aef23d533106e2b15"}, - {file = "yarl-1.9.4-py3-none-any.whl", hash = "sha256:928cecb0ef9d5a7946eb6ff58417ad2fe9375762382f1bf5c55e61645f2c43ad"}, - {file = "yarl-1.9.4.tar.gz", hash = "sha256:566db86717cf8080b99b58b083b773a908ae40f06681e87e589a976faf8246bf"}, + {file = "yarl-1.9.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:79e08c691deae6fcac2fdde2e0515ac561dd3630d7c8adf7b1e786e22f1e193b"}, + {file = "yarl-1.9.11-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:752f4b5cf93268dc73c2ae994cc6d684b0dad5118bc87fbd965fd5d6dca20f45"}, + {file = "yarl-1.9.11-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:441049d3a449fb8756b0535be72c6a1a532938a33e1cf03523076700a5f87a01"}, + {file = "yarl-1.9.11-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b3dfe17b4aed832c627319da22a33f27f282bd32633d6b145c726d519c89fbaf"}, + {file = "yarl-1.9.11-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:67abcb7df27952864440c9c85f1c549a4ad94afe44e2655f77d74b0d25895454"}, + {file = "yarl-1.9.11-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:6de3fa29e76fd1518a80e6af4902c44f3b1b4d7fed28eb06913bba4727443de3"}, + {file = "yarl-1.9.11-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fee45b3bd4d8d5786472e056aa1359cc4dc9da68aded95a10cd7929a0ec661fe"}, + {file = "yarl-1.9.11-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c59b23886234abeba62087fd97d10fb6b905d9e36e2f3465d1886ce5c0ca30df"}, + {file = "yarl-1.9.11-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:d93c612b2024ac25a3dc01341fd98fdd19c8c5e2011f3dcd084b3743cba8d756"}, + {file = "yarl-1.9.11-cp310-cp310-musllinux_1_2_i686.whl", hash = "sha256:4d368e3b9ecd50fa22017a20c49e356471af6ae91c4d788c6e9297e25ddf5a62"}, + {file = "yarl-1.9.11-cp310-cp310-musllinux_1_2_ppc64le.whl", hash = "sha256:5b593acd45cdd4cf6664d342ceacedf25cd95263b83b964fddd6c78930ea5211"}, + {file = "yarl-1.9.11-cp310-cp310-musllinux_1_2_s390x.whl", hash = "sha256:224f8186c220ff00079e64bf193909829144d4e5174bb58665ef0da8bf6955c4"}, + {file = "yarl-1.9.11-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:91c478741d7563a12162f7a2db96c0d23d93b0521563f1f1f0ece46ea1702d33"}, + {file = "yarl-1.9.11-cp310-cp310-win32.whl", hash = "sha256:1cdb8f5bb0534986776a43df84031da7ff04ac0cf87cb22ae8a6368231949c40"}, + {file = "yarl-1.9.11-cp310-cp310-win_amd64.whl", hash = "sha256:498439af143b43a2b2314451ffd0295410aa0dcbdac5ee18fc8633da4670b605"}, + {file = "yarl-1.9.11-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:9e290de5db4fd4859b4ed57cddfe793fcb218504e65781854a8ac283ab8d5518"}, + {file = "yarl-1.9.11-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:e5f50a2e26cc2b89186f04c97e0ec0ba107ae41f1262ad16832d46849864f914"}, + {file = "yarl-1.9.11-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:b4a0e724a28d7447e4d549c8f40779f90e20147e94bf949d490402eee09845c6"}, + {file = "yarl-1.9.11-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:85333d38a4fa5997fa2ff6fd169be66626d814b34fa35ec669e8c914ca50a097"}, + {file = "yarl-1.9.11-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:6ff184002ee72e4b247240e35d5dce4c2d9a0e81fdbef715dde79ab4718aa541"}, + {file = "yarl-1.9.11-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:675004040f847c0284827f44a1fa92d8baf425632cc93e7e0aa38408774b07c1"}, + {file = "yarl-1.9.11-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b30703a7ade2b53f02e09a30685b70cd54f65ed314a8d9af08670c9a5391af1b"}, + {file = "yarl-1.9.11-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:7230007ab67d43cf19200ec15bc6b654e6b85c402f545a6fc565d254d34ff754"}, + {file = "yarl-1.9.11-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:8c2cf0c7ad745e1c6530fe6521dfb19ca43338239dfcc7da165d0ef2332c0882"}, + {file = "yarl-1.9.11-cp311-cp311-musllinux_1_2_i686.whl", hash = "sha256:4567cc08f479ad80fb07ed0c9e1bcb363a4f6e3483a490a39d57d1419bf1c4c7"}, + {file = "yarl-1.9.11-cp311-cp311-musllinux_1_2_ppc64le.whl", hash = "sha256:95adc179a02949c4560ef40f8f650a008380766eb253d74232eb9c024747c111"}, + {file = "yarl-1.9.11-cp311-cp311-musllinux_1_2_s390x.whl", hash = "sha256:755ae9cff06c429632d750aa8206f08df2e3d422ca67be79567aadbe74ae64cc"}, + {file = "yarl-1.9.11-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:94f71d54c5faf715e92c8434b4a0b968c4d1043469954d228fc031d51086f143"}, + {file = "yarl-1.9.11-cp311-cp311-win32.whl", hash = "sha256:4ae079573efeaa54e5978ce86b77f4175cd32f42afcaf9bfb8a0677e91f84e4e"}, + {file = "yarl-1.9.11-cp311-cp311-win_amd64.whl", hash = "sha256:9fae7ec5c9a4fe22abb995804e6ce87067dfaf7e940272b79328ce37c8f22097"}, + {file = "yarl-1.9.11-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:614fa50fd0db41b79f426939a413d216cdc7bab8d8c8a25844798d286a999c5a"}, + {file = "yarl-1.9.11-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:ff64f575d71eacb5a4d6f0696bfe991993d979423ea2241f23ab19ff63f0f9d1"}, + {file = "yarl-1.9.11-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:5c23f6dc3d7126b4c64b80aa186ac2bb65ab104a8372c4454e462fb074197bc6"}, + {file = "yarl-1.9.11-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b8f847cc092c2b85d22e527f91ea83a6cf51533e727e2461557a47a859f96734"}, + {file = "yarl-1.9.11-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:63a5dc2866791236779d99d7a422611d22bb3a3d50935bafa4e017ea13e51469"}, + {file = "yarl-1.9.11-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:c335342d482e66254ae94b1231b1532790afb754f89e2e0c646f7f19d09740aa"}, + {file = "yarl-1.9.11-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e4a8c3dedd081cca134a21179aebe58b6e426e8d1e0202da9d1cafa56e01af3c"}, + {file = "yarl-1.9.11-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:504d19320c92532cabc3495fb7ed6bb599f3c2bfb45fed432049bf4693dbd6d0"}, + {file = "yarl-1.9.11-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:0b2a8e5eb18181060197e3d5db7e78f818432725c0759bc1e5a9d603d9246389"}, + {file = "yarl-1.9.11-cp312-cp312-musllinux_1_2_i686.whl", hash = "sha256:f568d70b7187f4002b6b500c0996c37674a25ce44b20716faebe5fdb8bd356e7"}, + {file = "yarl-1.9.11-cp312-cp312-musllinux_1_2_ppc64le.whl", hash = "sha256:735b285ea46ca7e86ad261a462a071d0968aade44e1a3ea2b7d4f3d63b5aab12"}, + {file = "yarl-1.9.11-cp312-cp312-musllinux_1_2_s390x.whl", hash = "sha256:2d1c81c3b92bef0c1c180048e43a5a85754a61b4f69d6f84df8e4bd615bef25d"}, + {file = "yarl-1.9.11-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:8d6e1c1562b53bd26efd38e886fc13863b8d904d559426777990171020c478a9"}, + {file = "yarl-1.9.11-cp312-cp312-win32.whl", hash = "sha256:aeba4aaa59cb709edb824fa88a27cbbff4e0095aaf77212b652989276c493c00"}, + {file = "yarl-1.9.11-cp312-cp312-win_amd64.whl", hash = "sha256:569309a3efb8369ff5d32edb2a0520ebaf810c3059f11d34477418c90aa878fd"}, + {file = "yarl-1.9.11-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:4915818ac850c3b0413e953af34398775b7a337babe1e4d15f68c8f5c4872553"}, + {file = "yarl-1.9.11-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:ef9610b2f5a73707d4d8bac040f0115ca848e510e3b1f45ca53e97f609b54130"}, + {file = "yarl-1.9.11-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:47c0a3dc8076a8dd159de10628dea04215bc7ddaa46c5775bf96066a0a18f82b"}, + {file = "yarl-1.9.11-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:545f2fbfa0c723b446e9298b5beba0999ff82ce2c126110759e8dac29b5deaf4"}, + {file = "yarl-1.9.11-cp313-cp313-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:9137975a4ccc163ad5d7a75aad966e6e4e95dedee08d7995eab896a639a0bce2"}, + {file = "yarl-1.9.11-cp313-cp313-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0b0c70c451d2a86f8408abced5b7498423e2487543acf6fcf618b03f6e669b0a"}, + {file = "yarl-1.9.11-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ce2bd986b1e44528677c237b74d59f215c8bfcdf2d69442aa10f62fd6ab2951c"}, + {file = "yarl-1.9.11-cp313-cp313-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:8d7b717f77846a9631046899c6cc730ea469c0e2fb252ccff1cc119950dbc296"}, + {file = "yarl-1.9.11-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:3a26a24bbd19241283d601173cea1e5b93dec361a223394e18a1e8e5b0ef20bd"}, + {file = "yarl-1.9.11-cp313-cp313-musllinux_1_2_i686.whl", hash = "sha256:c189bf01af155ac9882e128d9f3b3ad68a1f2c2f51404afad7201305df4e12b1"}, + {file = "yarl-1.9.11-cp313-cp313-musllinux_1_2_ppc64le.whl", hash = "sha256:0cbcc2c54084b2bda4109415631db017cf2960f74f9e8fd1698e1400e4f8aae2"}, + {file = "yarl-1.9.11-cp313-cp313-musllinux_1_2_s390x.whl", hash = "sha256:30f201bc65941a4aa59c1236783efe89049ec5549dafc8cd2b63cc179d3767b0"}, + {file = "yarl-1.9.11-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:922ba3b74f0958a0b5b9c14ff1ef12714a381760c08018f2b9827632783a590c"}, + {file = "yarl-1.9.11-cp313-cp313-win32.whl", hash = "sha256:17107b4b8c43e66befdcbe543fff2f9c93f7a3a9f8e3a9c9ac42bffeba0e8828"}, + {file = "yarl-1.9.11-cp313-cp313-win_amd64.whl", hash = "sha256:0324506afab4f2e176a93cb08b8abcb8b009e1f324e6cbced999a8f5dd9ddb76"}, + {file = "yarl-1.9.11-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:4e4f820fde9437bb47297194f43d29086433e6467fa28fe9876366ad357bd7bb"}, + {file = "yarl-1.9.11-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:dfa9b9d5c9c0dbe69670f5695264452f5e40947590ec3a38cfddc9640ae8ff89"}, + {file = "yarl-1.9.11-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:e700eb26635ce665c018c8cfea058baff9b843ed0cc77aa61849d807bb82a64c"}, + {file = "yarl-1.9.11-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:c305c1bdf10869b5e51facf50bd5b15892884aeae81962ae4ba061fc11217103"}, + {file = "yarl-1.9.11-cp38-cp38-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:c5b7b307140231ea4f7aad5b69355aba2a67f2d7bc34271cffa3c9c324d35b27"}, + {file = "yarl-1.9.11-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a744bdeda6c86cf3025c94eb0e01ccabe949cf385cd75b6576a3ac9669404b68"}, + {file = "yarl-1.9.11-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8e8ed183c7a8f75e40068333fc185566472a8f6c77a750cf7541e11810576ea5"}, + {file = "yarl-1.9.11-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c1db9a4384694b5d20bdd9cb53f033b0831ac816416ab176c8d0997835015d22"}, + {file = "yarl-1.9.11-cp38-cp38-musllinux_1_2_aarch64.whl", hash = "sha256:70194da6e99713250aa3f335a7fa246b36adf53672a2bcd0ddaa375d04e53dc0"}, + {file = "yarl-1.9.11-cp38-cp38-musllinux_1_2_i686.whl", hash = "sha256:ddad5cfcda729e22422bb1c85520bdf2770ce6d975600573ac9017fe882f4b7e"}, + {file = "yarl-1.9.11-cp38-cp38-musllinux_1_2_ppc64le.whl", hash = "sha256:ca35996e0a4bed28fa0640d9512d37952f6b50dea583bcc167d4f0b1e112ac7f"}, + {file = "yarl-1.9.11-cp38-cp38-musllinux_1_2_s390x.whl", hash = "sha256:61ec0e80970b21a8f3c4b97fa6c6d181c6c6a135dbc7b4a601a78add3feeb209"}, + {file = "yarl-1.9.11-cp38-cp38-musllinux_1_2_x86_64.whl", hash = "sha256:9636e4519f6c7558fdccf8f91e6e3b98df2340dc505c4cc3286986d33f2096c2"}, + {file = "yarl-1.9.11-cp38-cp38-win32.whl", hash = "sha256:58081cea14b8feda57c7ce447520e9d0a96c4d010cce54373d789c13242d7083"}, + {file = "yarl-1.9.11-cp38-cp38-win_amd64.whl", hash = "sha256:7d2dee7d6485807c0f64dd5eab9262b7c0b34f760e502243dd83ec09d647d5e1"}, + {file = "yarl-1.9.11-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:d65ad67f981e93ea11f87815f67d086c4f33da4800cf2106d650dd8a0b79dda4"}, + {file = "yarl-1.9.11-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:752c0d33b4aacdb147871d0754b88f53922c6dc2aff033096516b3d5f0c02a0f"}, + {file = "yarl-1.9.11-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:54cc24be98d7f4ff355ca2e725a577e19909788c0db6beead67a0dda70bd3f82"}, + {file = "yarl-1.9.11-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1c82126817492bb2ebc946e74af1ffa10aacaca81bee360858477f96124be39a"}, + {file = "yarl-1.9.11-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8503989860d7ac10c85cb5b607fec003a45049cf7a5b4b72451e87893c6bb990"}, + {file = "yarl-1.9.11-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:475e09a67f8b09720192a170ad9021b7abf7827ffd4f3a83826317a705be06b7"}, + {file = "yarl-1.9.11-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:afcac5bda602b74ff701e1f683feccd8cce0d5a21dbc68db81bf9bd8fd93ba56"}, + {file = "yarl-1.9.11-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:aaeffcb84faceb2923a94a8a9aaa972745d3c728ab54dd011530cc30a3d5d0c1"}, + {file = "yarl-1.9.11-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:51a6f770ac86477cd5c553f88a77a06fe1f6f3b643b053fcc7902ab55d6cbe14"}, + {file = "yarl-1.9.11-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:3fcd056cb7dff3aea5b1ee1b425b0fbaa2fbf6a1c6003e88caf524f01de5f395"}, + {file = "yarl-1.9.11-cp39-cp39-musllinux_1_2_ppc64le.whl", hash = "sha256:21e56c30e39a1833e4e3fd0112dde98c2abcbc4c39b077e6105c76bb63d2aa04"}, + {file = "yarl-1.9.11-cp39-cp39-musllinux_1_2_s390x.whl", hash = "sha256:0a205ec6349879f5e75dddfb63e069a24f726df5330b92ce76c4752a436aac01"}, + {file = "yarl-1.9.11-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:a5706821e1cf3c70dfea223e4e0958ea354f4e2af9420a1bd45c6b547297fb97"}, + {file = "yarl-1.9.11-cp39-cp39-win32.whl", hash = "sha256:cc295969f8c2172b5d013c0871dccfec7a0e1186cf961e7ea575d47b4d5cbd32"}, + {file = "yarl-1.9.11-cp39-cp39-win_amd64.whl", hash = "sha256:55a67dd29367ce7c08a0541bb602ec0a2c10d46c86b94830a1a665f7fd093dfa"}, + {file = "yarl-1.9.11-py3-none-any.whl", hash = "sha256:c6f6c87665a9e18a635f0545ea541d9640617832af2317d4f5ad389686b4ed3d"}, + {file = "yarl-1.9.11.tar.gz", hash = "sha256:c7548a90cb72b67652e2cd6ae80e2683ee08fde663104528ac7df12d8ef271d2"}, ] [package.dependencies] diff --git a/libs/astradb/pyproject.toml b/libs/astradb/pyproject.toml index 5113f69..535a0c3 100644 --- a/libs/astradb/pyproject.toml +++ b/libs/astradb/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langchain-astradb" -version = "0.3.5" +version = "0.4.0" description = "An integration package connecting Astra DB and LangChain" authors = [] readme = "README.md" diff --git a/libs/astradb/tests/integration_tests/conftest.py b/libs/astradb/tests/integration_tests/conftest.py index 54889c1..9cea801 100644 --- a/libs/astradb/tests/integration_tests/conftest.py +++ b/libs/astradb/tests/integration_tests/conftest.py @@ -7,6 +7,7 @@ import pytest from astrapy import Database from astrapy.db import AstraDB +from astrapy.info import CollectionVectorServiceOptions # Getting the absolute path of the current file's directory ABS_PATH = (Path(__file__)).parent @@ -70,3 +71,24 @@ def core_astra_db(astra_db_credentials: AstraDBCredentials) -> AstraDB: _load_env() + + +OPENAI_VECTORIZE_OPTIONS = CollectionVectorServiceOptions( + provider="openai", + model_name="text-embedding-3-small", + authentication={ + "providerKey": f"{os.environ.get('SHARED_SECRET_NAME_OPENAI', '')}", + }, +) + + +OPENAI_VECTORIZE_OPTIONS_HEADER = CollectionVectorServiceOptions( + provider="openai", + model_name="text-embedding-3-small", +) + + +NVIDIA_VECTORIZE_OPTIONS = CollectionVectorServiceOptions( + provider="nvidia", + model_name="NV-Embed-QA", +) diff --git a/libs/astradb/tests/integration_tests/test_vectorstore_autodetect.py b/libs/astradb/tests/integration_tests/test_vectorstore_autodetect.py new file mode 100644 index 0000000..97fe277 --- /dev/null +++ b/libs/astradb/tests/integration_tests/test_vectorstore_autodetect.py @@ -0,0 +1,429 @@ +"""Test of Astra DB vector store class `AstraDBVectorStore` + +Refer to `test_vectorstores.py` for the requirements to run. +""" + +from __future__ import annotations + +import os +from typing import TYPE_CHECKING, Iterable + +import pytest +from astrapy import DataAPIClient +from astrapy.authentication import StaticTokenProvider +from langchain_core.documents import Document + +from langchain_astradb.utils.astradb import SetupMode +from langchain_astradb.vectorstores import AstraDBVectorStore +from tests.conftest import SomeEmbeddings + +from .conftest import OPENAI_VECTORIZE_OPTIONS, AstraDBCredentials, _has_env_vars + +if TYPE_CHECKING: + from astrapy import Collection + from langchain_core.embeddings import Embeddings + +# Faster testing (no actual collection deletions). Off by default (=full tests) +SKIP_COLLECTION_DELETE = ( + int(os.environ.get("ASTRA_DB_SKIP_COLLECTION_DELETIONS", "0")) != 0 +) + +AD_NOVECTORIZE_COLLECTION = "lc_ad_novectorize" +AD_VECTORIZE_COLLECTION = "lc_ad_vectorize" + + +@pytest.fixture(scope="session") +def provisioned_novectorize_collection( + astra_db_credentials: AstraDBCredentials, +) -> Iterable[Collection]: + """Provision a general-purpose collection for the no-vectorize tests.""" + client = DataAPIClient(environment=astra_db_credentials["environment"]) + database = client.get_database( + astra_db_credentials["api_endpoint"], + token=StaticTokenProvider(astra_db_credentials["token"]), + namespace=astra_db_credentials["namespace"], + ) + collection = database.create_collection( + AD_NOVECTORIZE_COLLECTION, + dimension=2, + check_exists=False, + metric="cosine", + ) + yield collection + + if not SKIP_COLLECTION_DELETE: + collection.drop() + + +@pytest.fixture(scope="session") +def provisioned_vectorize_collection( + astra_db_credentials: AstraDBCredentials, +) -> Iterable[Collection]: + """Provision a general-purpose collection for the vectorize tests.""" + client = DataAPIClient(environment=astra_db_credentials["environment"]) + database = client.get_database( + astra_db_credentials["api_endpoint"], + token=StaticTokenProvider(astra_db_credentials["token"]), + namespace=astra_db_credentials["namespace"], + ) + collection = database.create_collection( + AD_VECTORIZE_COLLECTION, + dimension=2, + check_exists=False, + metric="cosine", + service=OPENAI_VECTORIZE_OPTIONS, + ) + yield collection + + if not SKIP_COLLECTION_DELETE: + collection.drop() + + +@pytest.fixture +def novectorize_collection( + provisioned_novectorize_collection: Collection, +) -> Iterable[Collection]: + provisioned_novectorize_collection.delete_many({}) + yield provisioned_novectorize_collection + + provisioned_novectorize_collection.delete_many({}) + + +@pytest.fixture +def vectorize_collection( + provisioned_vectorize_collection: Collection, +) -> Iterable[Collection]: + provisioned_vectorize_collection.delete_many({}) + yield provisioned_vectorize_collection + + provisioned_vectorize_collection.delete_many({}) + + +@pytest.fixture(scope="session") +def embedding() -> Embeddings: + return SomeEmbeddings(dimension=2) + + +@pytest.fixture +def novectorize_store( + novectorize_collection: Collection, # noqa: ARG001 + astra_db_credentials: AstraDBCredentials, + embedding: Embeddings, +) -> AstraDBVectorStore: + return AstraDBVectorStore( + embedding=embedding, + collection_name=AD_NOVECTORIZE_COLLECTION, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + setup_mode=SetupMode.OFF, + ) + + +@pytest.fixture +def vectorize_store( + vectorize_collection: Collection, # noqa: ARG001 + astra_db_credentials: AstraDBCredentials, +) -> AstraDBVectorStore: + return AstraDBVectorStore( + collection_name=AD_VECTORIZE_COLLECTION, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + setup_mode=SetupMode.OFF, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS, + ) + + +@pytest.mark.skipif(not _has_env_vars(), reason="Missing Astra DB env. vars") +class TestVectorStoreAutodetect: + def test_autodetect_flat_novectorize_crud( + self, + novectorize_collection: Collection, + astra_db_credentials: AstraDBCredentials, + embedding: Embeddings, + ) -> None: + """Test autodetect on a populated flat collection, checking all codecs.""" + novectorize_collection.insert_many( + [ + { + "_id": "1", + "$vector": [0.1, 0.2], + "cont": "Cont1", + "m1": "a", + "m2": "x", + }, + { + "_id": "2", + "$vector": [0.3, 0.4], + "cont": "Cont2", + "m1": "b", + "m2": "y", + }, + { + "_id": "3", + "$vector": [0.5, 0.6], + "cont": "Cont3", + "m1": "c", + "m2": "z", + }, + ] + ) + ad_store = AstraDBVectorStore( + embedding=embedding, + collection_name=AD_NOVECTORIZE_COLLECTION, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + autodetect_collection=True, + ) + + # ANN and the metadata + results = ad_store.similarity_search("query", k=3) + assert {res.page_content for res in results} == {"Cont1", "Cont2", "Cont3"} + assert "m1" in results[0].metadata + assert "m2" in results[0].metadata + + # inserting + pc4 = "Cont4" + md4 = {"q1": "Q1", "q2": "Q2"} + inserted_ids = ad_store.add_texts( + texts=[pc4], + metadatas=[md4], + ids=["4"], + ) + assert inserted_ids == ["4"] + + # reading with filtering + results2 = ad_store.similarity_search("query", k=3, filter={"q2": "Q2"}) + assert results2 == [Document(page_content=pc4, metadata=md4)] + + def test_autodetect_default_novectorize_crud( + self, + novectorize_collection: Collection, # noqa: ARG002 + astra_db_credentials: AstraDBCredentials, + embedding: Embeddings, + novectorize_store: AstraDBVectorStore, + ) -> None: + """Test autodetect on a VS-made collection, checking all codecs.""" + novectorize_store.add_texts( + texts=[ + "Cont1", + "Cont2", + "Cont3", + ], + metadatas=[ + {"m1": "a", "m2": "x"}, + {"m1": "b", "m2": "y"}, + {"m1": "c", "m2": "z"}, + ], + ids=[ + "1", + "2", + "3", + ], + ) + # now with the autodetect + ad_store = AstraDBVectorStore( + embedding=embedding, + collection_name=AD_NOVECTORIZE_COLLECTION, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + autodetect_collection=True, + ) + + # ANN and the metadata + results = ad_store.similarity_search("query", k=3) + assert {res.page_content for res in results} == {"Cont1", "Cont2", "Cont3"} + assert "m1" in results[0].metadata + assert "m2" in results[0].metadata + + # inserting + pc4 = "Cont4" + md4 = {"q1": "Q1", "q2": "Q2"} + inserted_ids = ad_store.add_texts( + texts=[pc4], + metadatas=[md4], + ids=["4"], + ) + assert inserted_ids == ["4"] + + # reading with filtering + results2 = ad_store.similarity_search("query", k=3, filter={"q2": "Q2"}) + assert results2 == [Document(page_content=pc4, metadata=md4)] + + def test_autodetect_flat_vectorize_crud( + self, + vectorize_collection: Collection, + astra_db_credentials: AstraDBCredentials, + ) -> None: + """Test autodetect on a populated flat collection, checking all codecs.""" + vectorize_collection.insert_many( + [ + { + "_id": "1", + "$vectorize": "Cont1", + "m1": "a", + "m2": "x", + }, + { + "_id": "2", + "$vectorize": "Cont2", + "m1": "b", + "m2": "y", + }, + { + "_id": "3", + "$vectorize": "Cont3", + "m1": "c", + "m2": "z", + }, + ] + ) + ad_store = AstraDBVectorStore( + collection_name=AD_VECTORIZE_COLLECTION, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + autodetect_collection=True, + ) + + # ANN and the metadata + results = ad_store.similarity_search("query", k=3) + assert {res.page_content for res in results} == {"Cont1", "Cont2", "Cont3"} + assert "m1" in results[0].metadata + assert "m2" in results[0].metadata + + # inserting + pc4 = "Cont4" + md4 = {"q1": "Q1", "q2": "Q2"} + inserted_ids = ad_store.add_texts( + texts=[pc4], + metadatas=[md4], + ids=["4"], + ) + assert inserted_ids == ["4"] + + # reading with filtering + results2 = ad_store.similarity_search("query", k=3, filter={"q2": "Q2"}) + assert results2 == [Document(page_content=pc4, metadata=md4)] + + def test_autodetect_default_vectorize_crud( + self, + vectorize_collection: Collection, # noqa: ARG002 + astra_db_credentials: AstraDBCredentials, + vectorize_store: AstraDBVectorStore, + ) -> None: + """Test autodetect on a VS-made collection, checking all codecs.""" + vectorize_store.add_texts( + texts=[ + "Cont1", + "Cont2", + "Cont3", + ], + metadatas=[ + {"m1": "a", "m2": "x"}, + {"m1": "b", "m2": "y"}, + {"m1": "c", "m2": "z"}, + ], + ids=[ + "1", + "2", + "3", + ], + ) + # now with the autodetect + ad_store = AstraDBVectorStore( + collection_name=AD_VECTORIZE_COLLECTION, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + autodetect_collection=True, + ) + + # ANN and the metadata + results = ad_store.similarity_search("query", k=3) + assert {res.page_content for res in results} == {"Cont1", "Cont2", "Cont3"} + assert "m1" in results[0].metadata + assert "m2" in results[0].metadata + + # inserting + pc4 = "Cont4" + md4 = {"q1": "Q1", "q2": "Q2"} + inserted_ids = ad_store.add_texts( + texts=[pc4], + metadatas=[md4], + ids=["4"], + ) + assert inserted_ids == ["4"] + + # reading with filtering + results2 = ad_store.similarity_search("query", k=3, filter={"q2": "Q2"}) + assert results2 == [Document(page_content=pc4, metadata=md4)] + + def test_failed_docs_autodetect_flat_novectorize_crud( + self, + novectorize_collection: Collection, + astra_db_credentials: AstraDBCredentials, + embedding: Embeddings, + ) -> None: + """Test autodetect + skipping failing documents.""" + novectorize_collection.insert_many( + [ + { + "_id": "1", + "$vector": [0.1, 0.2], + "cont": "Cont1", + "m1": "a", + "m2": "x", + }, + ] + ) + ad_store_e = AstraDBVectorStore( + collection_name=AD_NOVECTORIZE_COLLECTION, + embedding=embedding, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + autodetect_collection=True, + ignore_invalid_documents=False, + ) + ad_store_w = AstraDBVectorStore( + collection_name=AD_NOVECTORIZE_COLLECTION, + embedding=embedding, + token=StaticTokenProvider(astra_db_credentials["token"]), + api_endpoint=astra_db_credentials["api_endpoint"], + namespace=astra_db_credentials["namespace"], + environment=astra_db_credentials["environment"], + autodetect_collection=True, + ignore_invalid_documents=True, + ) + + results_e = ad_store_e.similarity_search("query", k=3) + assert len(results_e) == 1 + + results_w = ad_store_w.similarity_search("query", k=3) + assert len(results_w) == 1 + + novectorize_collection.insert_one( + { + "_id": "2", + "$vector": [0.1, 0.2], + "m1": "invalid:", + "m2": "no $vector!", + } + ) + + with pytest.raises(KeyError): + ad_store_e.similarity_search("query", k=3) + + results_w_post = ad_store_w.similarity_search("query", k=3) + assert len(results_w_post) == 1 diff --git a/libs/astradb/tests/integration_tests/test_vectorstores.py b/libs/astradb/tests/integration_tests/test_vectorstores.py index a13a505..f841631 100644 --- a/libs/astradb/tests/integration_tests/test_vectorstores.py +++ b/libs/astradb/tests/integration_tests/test_vectorstores.py @@ -28,14 +28,19 @@ import pytest from astrapy.authentication import EmbeddingAPIKeyHeaderProvider, StaticTokenProvider -from astrapy.info import CollectionVectorServiceOptions from langchain_core.documents import Document from langchain_astradb.utils.astradb import SetupMode from langchain_astradb.vectorstores import AstraDBVectorStore from tests.conftest import ParserEmbeddings, SomeEmbeddings -from .conftest import AstraDBCredentials, _has_env_vars +from .conftest import ( + NVIDIA_VECTORIZE_OPTIONS, + OPENAI_VECTORIZE_OPTIONS, + OPENAI_VECTORIZE_OPTIONS_HEADER, + AstraDBCredentials, + _has_env_vars, +) if TYPE_CHECKING: from astrapy import Database @@ -54,23 +59,6 @@ MATCH_EPSILON = 0.0001 - -openai_vectorize_options = CollectionVectorServiceOptions( - provider="openai", - model_name="text-embedding-3-small", - authentication={ - "providerKey": f"{os.environ.get('SHARED_SECRET_NAME_OPENAI', '')}", - }, -) -openai_vectorize_options_header = CollectionVectorServiceOptions( - provider="openai", - model_name="text-embedding-3-small", -) -nvidia_vectorize_options = CollectionVectorServiceOptions( - provider="nvidia", - model_name="NV-Embed-QA", -) - INCOMPATIBLE_INDEXING_MSG = "is detected as having the following indexing policy" @@ -166,7 +154,7 @@ def vectorize_store( pytest.skip("OpenAI SHARED_SECRET key not set for KMS vectorize") v_store = AstraDBVectorStore( - collection_vector_service_options=openai_vectorize_options, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS, collection_name=COLLECTION_NAME_VECTORIZE_OPENAI, token=astra_db_credentials["token"], api_endpoint=astra_db_credentials["api_endpoint"], @@ -190,7 +178,7 @@ def vectorize_store_w_header( pytest.skip("OpenAI key not available") v_store = AstraDBVectorStore( - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, collection_embedding_api_key=os.environ["OPENAI_API_KEY"], token=astra_db_credentials["token"], @@ -217,7 +205,7 @@ def vectorize_store_w_header_and_provider( pytest.skip("OpenAI key not available") v_store = AstraDBVectorStore( - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, collection_embedding_api_key=EmbeddingAPIKeyHeaderProvider( os.environ["OPENAI_API_KEY"], @@ -244,7 +232,7 @@ def vectorize_store_nvidia( pytest.skip("vectorize/nvidia unavailable") v_store = AstraDBVectorStore( - collection_vector_service_options=nvidia_vectorize_options, + collection_vector_service_options=NVIDIA_VECTORIZE_OPTIONS, collection_name=COLLECTION_NAME_VECTORIZE_NVIDIA, token=astra_db_credentials["token"], api_endpoint=astra_db_credentials["api_endpoint"], @@ -286,7 +274,7 @@ def test_astradb_vectorstore_create_delete_vectorize_sync( ) -> None: """Create and delete with vectorize option.""" v_store = AstraDBVectorStore( - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, token=astra_db_credentials["token"], api_endpoint=astra_db_credentials["api_endpoint"], @@ -315,7 +303,7 @@ async def test_astradb_vectorstore_create_delete_vectorize_async( ) -> None: """Create and delete with vectorize option.""" v_store = AstraDBVectorStore( - collection_vector_service_options=openai_vectorize_options, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS, collection_name=COLLECTION_NAME_VECTORIZE_OPENAI, token=astra_db_credentials["token"], api_endpoint=astra_db_credentials["api_endpoint"], @@ -510,7 +498,7 @@ def test_astradb_vectorstore_from_x_vectorize_sync( ) -> None: """from_texts and from_documents methods with vectorize.""" AstraDBVectorStore( - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_embedding_api_key=os.environ["OPENAI_API_KEY"], collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, token=astra_db_credentials["token"], @@ -522,7 +510,7 @@ def test_astradb_vectorstore_from_x_vectorize_sync( # from_texts v_store = AstraDBVectorStore.from_texts( texts=["Hi", "Ho"], - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_embedding_api_key=os.environ["OPENAI_API_KEY"], collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, token=astra_db_credentials["token"], @@ -541,7 +529,7 @@ def test_astradb_vectorstore_from_x_vectorize_sync( Document(page_content="Hee"), Document(page_content="Hoi"), ], - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_embedding_api_key=os.environ["OPENAI_API_KEY"], collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, token=astra_db_credentials["token"], @@ -662,7 +650,7 @@ async def test_astradb_vectorstore_from_x_vectorize_async( # from_text with vectorize v_store = await AstraDBVectorStore.afrom_texts( texts=["Haa", "Huu"], - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_embedding_api_key=os.environ["OPENAI_API_KEY"], collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, token=astra_db_credentials["token"], @@ -683,7 +671,7 @@ async def test_astradb_vectorstore_from_x_vectorize_async( Document(page_content="HeeH"), Document(page_content="HooH"), ], - collection_vector_service_options=openai_vectorize_options_header, + collection_vector_service_options=OPENAI_VECTORIZE_OPTIONS_HEADER, collection_embedding_api_key=os.environ["OPENAI_API_KEY"], collection_name=COLLECTION_NAME_VECTORIZE_OPENAI_HEADER, token=astra_db_credentials["token"], diff --git a/libs/astradb/tests/unit_tests/test_vectorstores.py b/libs/astradb/tests/unit_tests/test_vectorstores.py index 02f8124..f0a2fab 100644 --- a/libs/astradb/tests/unit_tests/test_vectorstores.py +++ b/libs/astradb/tests/unit_tests/test_vectorstores.py @@ -60,8 +60,7 @@ def test_initialization(self) -> None: # embedding and vectorize => error with pytest.raises( ValueError, - match="Only one of `embedding` or `collection_vector_service_options` can " - "be provided.", + match="Embedding cannot be provided for vectorize collections", ): AstraDBVectorStore( embedding=embedding, @@ -76,8 +75,7 @@ def test_initialization(self) -> None: # no embedding and no vectorize => error with pytest.raises( ValueError, - match="Either an `embedding` or a `collection_vector_service_options` " - "must be provided.", + match="Embedding is required for non-vectorize collections", ): AstraDBVectorStore( collection_name="mock_coll_name", diff --git a/libs/astradb/tests/unit_tests/test_vs_autodetect_inferences.py b/libs/astradb/tests/unit_tests/test_vs_autodetect_inferences.py new file mode 100644 index 0000000..457cd16 --- /dev/null +++ b/libs/astradb/tests/unit_tests/test_vs_autodetect_inferences.py @@ -0,0 +1,193 @@ +from __future__ import annotations + +import json +from typing import Any + +import pytest + +from langchain_astradb.utils.vector_store_autodetect import ( + _detect_document_content_field, + _detect_document_flatness, + _detect_documents_content_field, + _detect_documents_flatness, +) + +FLAT_DOCUMENT = {"$vector": [0], "metadata": "m", "_id": "a", "x": "x"} +DEEP_DOCUMENT = {"$vector": [0], "metadata": {}, "_id": "a", "x": "x"} +UNKNOWN_FLATNESS_DOCUMENT = {"metadata": {}, "_id": "a", "$vectorize": "a", "x": "x"} +DOCUMENT_WITH_CF_X = {"x": "LL", "y": "s", "_id": "a"} +DOCUMENT_WITH_CF_Y = {"x": 1234, "y": "s", "_id": "a"} +DOCUMENT_WITH_UNKNOWN_CF = {"x": 1234, "y": 987, "_id": "a"} + +# Test-case assets: +DOC_FLATNESS_PAIRS = [ + (UNKNOWN_FLATNESS_DOCUMENT, None), + ({"$vector": [0], "metadata": {}, "_id": "a"}, None), + ( + { + "$vector": [0], + "metadata": {}, + "_id": "a", + "$vectorize": "a", + "x": "x", + }, + False, + ), + (DEEP_DOCUMENT, False), + ({"$vector": [0], "metadata": "m", "_id": "a"}, True), + (FLAT_DOCUMENT, True), + ({"$vector": [0], "metadata": "m", "_id": "a", "x": 9}, True), + ( + { + "$vector": [0], + "metadata": "m", + "_id": "a", + "$vectorize": "a", + "x": "x", + }, + True, + ), + ( + { + "$vector": [0], + "metadata": "m", + "_id": "a", + "$vectorize": "a", + "x": 9, + }, + True, + ), + ({"$vector": [0], "metadata": 9, "_id": "a"}, None), + ({"$vector": [0], "metadata": 9, "_id": "a", "x": "x"}, True), + ({"$vector": [0], "metadata": 9, "_id": "a", "x": 9}, None), + ( + { + "$vector": [0], + "metadata": 9, + "_id": "a", + "$vectorize": "a", + "x": "x", + }, + True, + ), + ({"$vector": [0], "metadata": 9, "_id": "a", "$vectorize": "a", "x": 9}, True), + ({"$vector": [0], "_id": "a"}, None), + ({"$vector": [0], "_id": "a", "x": "x"}, True), + ({"$vector": [0], "_id": "a", "x": 9}, None), + ({"$vector": [0], "_id": "a", "$vectorize": "a", "x": "x"}, True), + ({"$vector": [0], "_id": "a", "$vectorize": "a", "x": 9}, True), +] +DOC_FLATNESS_TEST_IDS = [f"DOC=<{json.dumps(doc)}>" for doc, _ in DOC_FLATNESS_PAIRS] + +ff = FLAT_DOCUMENT +df = DEEP_DOCUMENT # noqa: PD901 +uf = UNKNOWN_FLATNESS_DOCUMENT +DOCS_FLATNESS_TEST_PARAMS = [ + pytest.param([], False, id=" docs=[] "), + pytest.param([uf], False, id=" docs=[u] "), + pytest.param([uf, uf], False, id=" docs=[u, u] "), + pytest.param([df], False, id=" docs=[d] "), + pytest.param([df, df], False, id=" docs=[d, d] "), + pytest.param([df, uf], False, id=" docs=[d, u] "), + pytest.param([ff], True, id=" docs=[f] "), + pytest.param([ff, ff], True, id=" docs=[f, f] "), + pytest.param([ff, uf], True, id=" docs=[f, u] "), + pytest.param([ff, df], ValueError(), id=" docs=[f, d] "), +] + +DOC_CF_TEST_PARAMS = [ + pytest.param(DOCUMENT_WITH_CF_X, "x", id="cf=x"), + pytest.param(DOCUMENT_WITH_CF_Y, "y", id="cf=y"), + pytest.param(DOCUMENT_WITH_UNKNOWN_CF, None, id="unknown-cf"), + pytest.param({"x": "LL", "_id": "a"}, "x", id="only-x"), + pytest.param({"x": 1234, "_id": "a"}, None, id="x-is-number"), + pytest.param({"_id": "a"}, None, id="no-fields"), +] + +xc = DOCUMENT_WITH_CF_X +yc = DOCUMENT_WITH_CF_Y +uc = DOCUMENT_WITH_UNKNOWN_CF +DOCS_CF_TEST_PARAMS = [ + pytest.param([], "q", "q", id=" [],req='q' "), + pytest.param([xc], "q", "q", id=" [x],req='q' "), + pytest.param([xc, xc, yc], "q", "q", id=" [x, x, y],req='q' "), + pytest.param([uc, uc], "q", "q", id=" [u, u],req='q' "), + pytest.param([xc, uc, uc], "q", "q", id=" [x, u, u],req='q' "), + pytest.param([xc, xc, yc, uc, uc, uc], "q", "q", id=" [x, x, y, u, u, u],req='q' "), + pytest.param([], "*", ValueError, id=" [],req='*' "), + pytest.param([xc], "*", "x", id=" [x],req='*' "), + pytest.param([xc, xc, yc], "*", "x", id=" [x, x, y],req='*' "), + pytest.param([uc, uc], "*", ValueError, id=" [u, u],req='*' "), + pytest.param([xc, uc, uc], "*", "x", id=" [x, u, u],req='*' "), + pytest.param([xc, xc, yc, uc, uc, uc], "*", "x", id=" [x, x, y, u, u, u],req='*' "), +] + + +class TestVSAutodetectInferences: + @pytest.mark.parametrize( + ("document", "expected_flatness"), DOC_FLATNESS_PAIRS, ids=DOC_FLATNESS_TEST_IDS + ) + def test_detect_document_flatness( + self, + document: dict[str, Any], + expected_flatness: bool | None, + ) -> None: + """Test expected results for flatness detection.""" + assert _detect_document_flatness(document) is expected_flatness + + @pytest.mark.parametrize( + ("documents", "expected_flatness"), + DOCS_FLATNESS_TEST_PARAMS, + ) + def test_detect_documents_flatness( + self, + documents: list[dict[str, Any]], + expected_flatness: bool | Exception, + ) -> None: + """Test flatness detection from a list of documents.""" + if isinstance(expected_flatness, bool): + assert _detect_documents_flatness(documents) is expected_flatness + else: + with pytest.raises(ValueError, match="Mixed"): + _detect_documents_flatness(documents) + + @pytest.mark.parametrize( + ("document", "expected_content_field"), + DOC_CF_TEST_PARAMS, + ) + def test_detect_document_content_field( + self, + document: dict[str, Any], + expected_content_field: str | None, + ) -> None: + """Test content-field detection on a document.""" + if isinstance(expected_content_field, str): + assert _detect_document_content_field(document) == expected_content_field + elif expected_content_field is None: + assert _detect_document_content_field(document) is None + else: + raise NotImplementedError + + @pytest.mark.parametrize( + ("documents", "requested_content_field", "expected_content_field"), + DOCS_CF_TEST_PARAMS, + ) + def test_detect_documents_content_field( + self, + documents: list[dict[str, Any]], + requested_content_field: str, + expected_content_field: str | Exception, + ) -> None: + """Test content-field detection on a list of document.""" + if isinstance(expected_content_field, str): + detected_cf = _detect_documents_content_field( + documents=documents, + requested_content_field=requested_content_field, + ) + assert detected_cf == expected_content_field + else: + with pytest.raises(ValueError, match="not infer"): + _detect_documents_content_field( + documents=documents, + requested_content_field=requested_content_field, + ) diff --git a/libs/astradb/tests/unit_tests/test_vs_doc_codecs.py b/libs/astradb/tests/unit_tests/test_vs_doc_codecs.py new file mode 100644 index 0000000..e3619de --- /dev/null +++ b/libs/astradb/tests/unit_tests/test_vs_doc_codecs.py @@ -0,0 +1,285 @@ +from __future__ import annotations + +import re +from typing import Any + +import pytest +from langchain_core.documents import Document + +from langchain_astradb.utils.vector_store_codecs import ( + NO_NULL_VECTOR_MSG, + VECTOR_REQUIRED_PREAMBLE_MSG, + _DefaultVectorizeVSDocumentCodec, + _DefaultVSDocumentCodec, + _FlatVectorizeVSDocumentCodec, + _FlatVSDocumentCodec, +) + +METADATA: dict[str, Any] = {"m1": 1, "m2": "two"} +CONTENT = "The content" +VECTOR: list[float] = [1, 2, 3] +DOCUMENT_ID = "the_id" +LC_DOCUMENT = Document(page_content=CONTENT, metadata=METADATA) +LC_FILTER = {"a0": 0, "$or": [{"b1": 1}, {"b2": 2}]} + +ASTRA_DEFAULT_DOCUMENT_NOVECTORIZE = { + "_id": DOCUMENT_ID, + "content_x": CONTENT, + "metadata": METADATA, + "$vector": VECTOR, +} +ASTRA_DEFAULT_DOCUMENT_VECTORIZE = { + "_id": DOCUMENT_ID, + "$vectorize": CONTENT, + "metadata": METADATA, +} +ASTRA_DEFAULT_FILTER = { + "metadata.a0": 0, + "$or": [{"metadata.b1": 1}, {"metadata.b2": 2}], +} + +ASTRA_FLAT_DOCUMENT_NOVECTORIZE = { + "_id": DOCUMENT_ID, + "content_x": CONTENT, + "$vector": VECTOR, + **METADATA, +} +ASTRA_FLAT_DOCUMENT_VECTORIZE_WRITTEN: dict[str, Any] = { + "_id": DOCUMENT_ID, + "$vectorize": CONTENT, + **METADATA, +} +ASTRA_FLAT_DOCUMENT_VECTORIZE_READ = { + "$vector": VECTOR, + **ASTRA_FLAT_DOCUMENT_VECTORIZE_WRITTEN, +} +ASTRA_FLAT_FILTER = LC_FILTER + + +class TestVSDocCodecs: + def test_default_novectorize_encoding(self) -> None: + """Test encoding for default, no-vectorize.""" + codec = _DefaultVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + encoded_doc = codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=VECTOR, + metadata=METADATA, + ) + assert encoded_doc == ASTRA_DEFAULT_DOCUMENT_NOVECTORIZE + + def test_default_novectorize_vector_passed(self) -> None: + """Test vector is required for default encoding, no-vectorize.""" + codec = _DefaultVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + with pytest.raises( + ValueError, + match=re.escape(NO_NULL_VECTOR_MSG), + ): + codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=None, + metadata=METADATA, + ) + + def test_default_novectorize_decoding(self) -> None: + """Test decoding for default, no-vectorize.""" + codec = _DefaultVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + decoded_doc = codec.decode(ASTRA_DEFAULT_DOCUMENT_NOVECTORIZE) + assert decoded_doc == LC_DOCUMENT + + def test_default_novectorize_decoding_invalid( + self, + caplog: pytest.LogCaptureFixture, + ) -> None: + """Test decoding for invalid documents, no-vectorize.""" + codec_e = _DefaultVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + with pytest.raises(KeyError): + codec_e.decode({"_id": 0}) + codec_w = _DefaultVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=True + ) + decoded_doc = codec_w.decode({"_id": 0}) + assert decoded_doc is None + assert "Ignoring document with _id = " in caplog.text + + codec_w.decode({"_id": 0, "content_x": "a", "metadata": {"k": "v"}}) + codec_e.decode({"_id": 0, "content_x": "a", "metadata": {"k": "v"}}) + + def test_default_novectorize_filtering(self) -> None: + """Test filter-encoding for default, no-vectorize.""" + codec = _DefaultVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + encoded_flt = codec.encode_filter(LC_FILTER) + assert encoded_flt == ASTRA_DEFAULT_FILTER + + def test_default_vectorize_encoding(self) -> None: + """Test encoding for default, vectorize.""" + codec = _DefaultVectorizeVSDocumentCodec(ignore_invalid_documents=False) + encoded_doc = codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=None, + metadata=METADATA, + ) + assert encoded_doc == ASTRA_DEFAULT_DOCUMENT_VECTORIZE + + def test_default_vectorize_vector_passed(self) -> None: + """Test vector is not allowed for default encoding, vectorize.""" + codec = _DefaultVectorizeVSDocumentCodec(ignore_invalid_documents=False) + with pytest.raises( + ValueError, + match=VECTOR_REQUIRED_PREAMBLE_MSG, + ): + codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=VECTOR, + metadata=METADATA, + ) + + def test_default_vectorize_decoding(self) -> None: + """Test decoding for default, vectorize.""" + codec = _DefaultVectorizeVSDocumentCodec(ignore_invalid_documents=False) + decoded_doc = codec.decode(ASTRA_DEFAULT_DOCUMENT_VECTORIZE) + assert decoded_doc == LC_DOCUMENT + + def test_default_vectorize_decoding_invalid(self) -> None: + """Test decoding for invalid documents, no-vectorize.""" + codec_e = _DefaultVectorizeVSDocumentCodec(ignore_invalid_documents=False) + with pytest.raises(KeyError): + codec_e.decode({"_id": 0}) + codec_w = _DefaultVectorizeVSDocumentCodec(ignore_invalid_documents=True) + with pytest.warns(UserWarning) as rec_warnings: + decoded_doc = codec_w.decode({"_id": 0}) + codec_w.decode({"_id": 0, "$vectorize": "a", "metadata": {"k": "v"}}) + codec_e.decode({"_id": 0, "$vectorize": "a", "metadata": {"k": "v"}}) + assert len(rec_warnings) == 1 + assert decoded_doc is None + + def test_default_vectorize_filtering(self) -> None: + """Test filter-encoding for default, vectorize.""" + codec = _DefaultVectorizeVSDocumentCodec(ignore_invalid_documents=False) + encoded_flt = codec.encode_filter(LC_FILTER) + assert encoded_flt == ASTRA_DEFAULT_FILTER + + def test_flat_novectorize_encoding(self) -> None: + """Test encoding for flat, no-vectorize.""" + codec = _FlatVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + encoded_doc = codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=VECTOR, + metadata=METADATA, + ) + assert encoded_doc == ASTRA_FLAT_DOCUMENT_NOVECTORIZE + + def test_flat_novectorize_vector_passed(self) -> None: + """Test vector is required for flat encoding, no-vectorize.""" + codec = _FlatVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + with pytest.raises( + ValueError, + match=re.escape(NO_NULL_VECTOR_MSG), + ): + codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=None, + metadata=METADATA, + ) + + def test_flat_novectorize_decoding(self) -> None: + """Test decoding for flat, no-vectorize.""" + codec = _FlatVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + decoded_doc = codec.decode(ASTRA_FLAT_DOCUMENT_NOVECTORIZE) + assert decoded_doc == LC_DOCUMENT + + def test_flat_novectorize_decoding_invalid(self) -> None: + """Test decoding for invalid documents, no-vectorize.""" + codec_e = _FlatVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + with pytest.raises(KeyError): + codec_e.decode({"_id": 0}) + codec_w = _FlatVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=True + ) + with pytest.warns(UserWarning) as rec_warnings: + decoded_doc = codec_w.decode({"_id": 0}) + codec_w.decode({"_id": 0, "content_x": "a", "m": "v"}) + codec_e.decode({"_id": 0, "content_x": "a", "m": "v"}) + assert len(rec_warnings) == 1 + assert decoded_doc is None + + def test_flat_novectorize_filtering(self) -> None: + """Test filter-encoding for flat, no-vectorize.""" + codec = _FlatVSDocumentCodec( + content_field="content_x", ignore_invalid_documents=False + ) + encoded_flt = codec.encode_filter(LC_FILTER) + assert encoded_flt == ASTRA_FLAT_FILTER + + def test_flat_vectorize_encoding(self) -> None: + """Test encoding for flat, vectorize.""" + codec = _FlatVectorizeVSDocumentCodec(ignore_invalid_documents=False) + encoded_doc = codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=None, + metadata=METADATA, + ) + assert encoded_doc == ASTRA_FLAT_DOCUMENT_VECTORIZE_WRITTEN + + def test_flat_vectorize_vector_passed(self) -> None: + """Test vector is forbidden for flat encoding, vectorize.""" + codec = _FlatVectorizeVSDocumentCodec(ignore_invalid_documents=False) + with pytest.raises( + ValueError, + match=VECTOR_REQUIRED_PREAMBLE_MSG, + ): + codec.encode( + content=CONTENT, + document_id=DOCUMENT_ID, + vector=VECTOR, + metadata=METADATA, + ) + + def test_flat_vectorize_decoding(self) -> None: + """Test decoding for flat, vectorize.""" + codec = _FlatVectorizeVSDocumentCodec(ignore_invalid_documents=False) + decoded_doc = codec.decode(ASTRA_FLAT_DOCUMENT_VECTORIZE_READ) + assert decoded_doc == LC_DOCUMENT + + def test_flat_vectorize_decoding_invalid(self) -> None: + """Test decoding for invalid documents, vectorize.""" + codec_e = _FlatVectorizeVSDocumentCodec(ignore_invalid_documents=False) + with pytest.raises(KeyError): + codec_e.decode({"_id": 0}) + codec_w = _FlatVectorizeVSDocumentCodec(ignore_invalid_documents=True) + with pytest.warns(UserWarning) as rec_warnings: + decoded_doc = codec_w.decode({"_id": 0}) + codec_w.decode({"_id": 0, "$vectorize": "a", "m": "v"}) + codec_e.decode({"_id": 0, "$vectorize": "a", "m": "v"}) + assert len(rec_warnings) == 1 + assert decoded_doc is None + + def test_flat_vectorize_filtering(self) -> None: + """Test filter-encoding for flat, vectorize.""" + codec = _FlatVectorizeVSDocumentCodec(ignore_invalid_documents=False) + encoded_flt = codec.encode_filter(LC_FILTER) + assert encoded_flt == ASTRA_FLAT_FILTER diff --git a/libs/astradb/tests/unit_tests/test_vs_doc_encoders.py b/libs/astradb/tests/unit_tests/test_vs_doc_encoders.py deleted file mode 100644 index 0460755..0000000 --- a/libs/astradb/tests/unit_tests/test_vs_doc_encoders.py +++ /dev/null @@ -1,109 +0,0 @@ -from __future__ import annotations - -import pytest -from langchain_core.documents import Document - -from langchain_astradb.utils.encoders import ( - NO_NULL_VECTOR_MSG, - VECTOR_REQUIRED_PREAMBLE_MSG, - _DefaultVectorizeVSDocumentEncoder, - _DefaultVSDocumentEncoder, -) - -METADATA = {"m1": 1, "m2": "two"} -CONTENT = "The content" -VECTOR: list[float] = [1, 2, 3] -DOCUMENT_ID = "the_id" -LC_DOCUMENT = Document(page_content=CONTENT, metadata=METADATA) -ASTRA_DEFAULT_DOCUMENT_NOVECTORIZE = { - "_id": DOCUMENT_ID, - "content": CONTENT, - "metadata": METADATA, - "$vector": VECTOR, -} -ASTRA_DEFAULT_DOCUMENT_VECTORIZE = { - "_id": DOCUMENT_ID, - "$vectorize": CONTENT, - "metadata": METADATA, -} -LC_FILTER = {"a0": 0, "$or": [{"b1": 1}, {"b2": 2}]} -ASTRA_DEFAULT_FILTER = { - "metadata.a0": 0, - "$or": [{"metadata.b1": 1}, {"metadata.b2": 2}], -} - - -class TestVSDocEncoders: - def test_default_novectorize_encoding(self) -> None: - """Test encoding for default, no-vectorize.""" - encoder = _DefaultVSDocumentEncoder() - encoded_doc = encoder.encode( - content=CONTENT, - document_id=DOCUMENT_ID, - vector=VECTOR, - metadata=METADATA, - ) - assert encoded_doc == ASTRA_DEFAULT_DOCUMENT_NOVECTORIZE - - def test_default_novectorize_vector_required(self) -> None: - """Test vector is required for default encoding, no-vectorize.""" - encoder = _DefaultVSDocumentEncoder() - with pytest.raises( - ValueError, - match=NO_NULL_VECTOR_MSG, - ): - encoder.encode( - content=CONTENT, - document_id=DOCUMENT_ID, - vector=None, - metadata=METADATA, - ) - - def test_default_novectorize_decoding(self) -> None: - """Test decoding for default, no-vectorize.""" - encoder = _DefaultVSDocumentEncoder() - decoded_doc = encoder.decode(ASTRA_DEFAULT_DOCUMENT_NOVECTORIZE) - assert decoded_doc == LC_DOCUMENT - - def test_default_novectorize_filtering(self) -> None: - """Test filter-encoding for default, no-vectorize.""" - encoder = _DefaultVSDocumentEncoder() - encoded_flt = encoder.encode_filter(LC_FILTER) - assert encoded_flt == ASTRA_DEFAULT_FILTER - - def test_default_vectorize_encoding(self) -> None: - """Test encoding for default, vectorize.""" - encoder = _DefaultVectorizeVSDocumentEncoder() - encoded_doc = encoder.encode( - content=CONTENT, - document_id=DOCUMENT_ID, - vector=None, - metadata=METADATA, - ) - assert encoded_doc == ASTRA_DEFAULT_DOCUMENT_VECTORIZE - - def test_default_vectorize_vector_forbidden(self) -> None: - """Test vector is not allowed for default encoding, vectorize.""" - encoder = _DefaultVectorizeVSDocumentEncoder() - with pytest.raises( - ValueError, - match=VECTOR_REQUIRED_PREAMBLE_MSG, - ): - encoder.encode( - content=CONTENT, - document_id=DOCUMENT_ID, - vector=VECTOR, - metadata=METADATA, - ) - - def test_default_vectorize_decoding(self) -> None: - """Test decoding for default, vectorize.""" - encoder = _DefaultVectorizeVSDocumentEncoder() - decoded_doc = encoder.decode(ASTRA_DEFAULT_DOCUMENT_VECTORIZE) - assert decoded_doc == LC_DOCUMENT - - def test_default_vectorize_filtering(self) -> None: - """Test filter-encoding for default, vectorize.""" - encoder = _DefaultVectorizeVSDocumentEncoder() - encoded_flt = encoder.encode_filter(LC_FILTER) - assert encoded_flt == ASTRA_DEFAULT_FILTER