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SpiderChef is a powerful, recipe-based web scraping tool that makes data extraction systematic and reproducible. By defining scraping procedures as "recipes" with sequential "steps," SpiderChef allows you to craft elegant, maintainable data extraction workflows.
- Recipe-Based Architecture: Define extraction workflows as YAML recipes
- Modular Step System: Build complex scraping logic from reusable components
- Async Support: Handle both synchronous and asynchronous extraction steps
- Type Safety: Fully typed for better development experience
- Extensible Design: Easily create custom steps for specialized extraction needs
# If you want to use the cli
pip install spiderchef[cli]
# If you just want the library usage
pip install spiderchef# Run a recipe
spiderchef cook recipes/example.yaml
# Create a new recipe template
spiderchef recipe new my_extractionThe basic usage of this library involves just pulling a local recipe and "cooking" it to get the output data:
import asyncio
from spiderchef import Recipe
# Imports a recipe from a yaml file locally
recipe = Recipe.from_yaml('recipe_example.yaml')
# Run a recipe
asyncio.run(recipe.cook())base_url: https://example.com
name: ProductExtractor
steps:
- type: fetch
name: fetch_product_page
page_type: text
path: /products
params:
category: electronics
sort: price_asc
- type: regex
name: extract_product_urls
expression: '"(\/product\/[^"]+)"'
- type: join_base_url
name: format_urlsLet's say you want to extend the steps available even more with your own custom ones, you can do it like so:
import asyncio
from typing import Any
from spiderchef import STEP_REGISTRY, AsyncStep, Recipe, SyncStep
# You can define your own custom steps like so:
class HelloStep(SyncStep):
# .name is a reserved keyword for steps
person_name: str
def _execute(self, recipe: Recipe, previous_output: Any = None) -> str:
return f"Hello There {self.person_name}"
# Sync or Async is possible.
class SleepStep(AsyncStep):
sleep_time: int = 5
async def _execute(self, recipe: Recipe, previous_output: Any = None) -> Any:
await asyncio.sleep(self.sleep_time)
return previous_output
CUSTOM_STEP_REGISTRY = {**STEP_REGISTRY, "hello": HelloStep, "sleep": SleepStep}
# Overrides the global step registry with your own
Recipe.step_registry = CUSTOM_STEP_REGISTRY
# You can manually initialise a recipe like so, or just use the yaml recipe.
recipe = Recipe(
base_url="https://example.com",
name="Example",
steps=[
HelloStep(name="Saying Hello", person_name="George"),
SleepStep(
name="Sleeping",
),
],
)
# Run a recipe
asyncio.run(recipe.cook())
"""Output:
2025-05-07 16:33:01 [info ] π₯£π₯π₯ Cooking 'Example' recipe!
2025-05-07 16:33:01 [info ] β‘οΈ 1. Saying Hello... step_class=HelloStep
2025-05-07 16:33:01 [info ] β‘οΈ 2. Sleeping... step_class=SleepStep
2025-05-07 16:33:06 [info ] π 'Example' recipe finished output='Hello There George'
"""SpiderChef supports variable replacement in your steps using the ${variable} syntax. Variables can be defined in the Recipe and will be automatically replaced when the step is executed:
recipe = Recipe(
name="Variable Example",
base_url="https://example.com"
# Default variables
variables={
"sort_order": "price_asc",
"category": "smartphones"
},
steps=[
# Variables are replaced automatically before execution
FetchStep(
name="Search Products",
path="/products"
params={
"category":"${category}"
"sort":"${sort_order}"
}
)
]
)
# Uses default variables
await recipe.cook()
# Replace a specific variable, making any recipe extendable
await recipe.cook(category="books")In YAML recipes, you can use the same syntax:
name: ProductExtractor
base_url: https://example.com
variables: # these are defaults
category: electronics
sort_order: price_asc
steps:
- type: fetch
name: fetch_product_page
page_type: text
path: /products
params:
category: ${category}
sort: ${sort_order}You can even save variables within the recipe to be used later using the save step.
name: ProductExtractor
base_url: https://example.com
variables:
category: electronics
sort_order: price_asc
steps:
- type: fetch
name: fetch_product_page
path: /products
params:
category: ${category}
sort: ${sort_order}
- type: xpath
name: extract_title
expression: //h1
- type: save
variable: titleTraditional web scraping often involves writing complex, difficult-to-maintain code that mixes HTTP requests, parsing, and business logic. SpiderChef separates these concerns by:
- Breaking extraction into discrete, reusable steps
- Defining workflows as declarative recipes
- Handling common extraction patterns with built-in steps
- Making scraping procedures reproducible and maintainable
Whether you're scraping product data, monitoring prices, or extracting research information, SpiderChef helps you build structured, reliable data extraction pipelines.
For full documentation, visit spiderchef.readthedocs.io.
The documentation includes:
- Getting started guide
- User guides for basic and advanced usage
- API reference
- Tutorials and examples
- Contributing guidelines
To build the documentation locally:
make docsContributions are welcome! Please feel free to submit a Pull Request.