.. _topics-item-pipeline: ============= Item Pipeline ============= After an item has been scraped by a spider, it is sent to the Item Pipeline which processes it through several components that are executed sequentially. Each item pipeline component (sometimes referred as just "Item Pipeline") is a Python class that implements a simple method. They receive an item and perform an action over it, also deciding if the item should continue through the pipeline or be dropped and no longer processed. Typical uses of item pipelines are: * cleansing HTML data * validating scraped data (checking that the items contain certain fields) * checking for duplicates (and dropping them) * storing the scraped item in a database Writing your own item pipeline ============================== Each item pipeline is a :ref:`component ` that must implement the following method: .. method:: process_item(self, item) This method is called for every item pipeline component. `item` is an :ref:`item object `, see :ref:`supporting-item-types`. :meth:`process_item` must either return an :ref:`item object ` or raise a :exc:`~scrapy.exceptions.DropItem` exception. Dropped items are no longer processed by further pipeline components. :param item: the scraped item :type item: :ref:`item object ` Additionally, they may also implement the following methods: .. method:: open_spider(self) This method is called when the spider is opened. .. method:: close_spider(self) This method is called when the spider is closed. Any of these methods may be defined as a coroutine function (``async def``). Item pipeline example ===================== .. _price-pipeline-example: Price validation and dropping items with no prices -------------------------------------------------- Let's take a look at the following hypothetical pipeline that adjusts the ``price`` attribute for those items that do not include VAT (``price_excludes_vat`` attribute), and drops those items which don't contain a price: .. code-block:: python from itemadapter import ItemAdapter from scrapy.exceptions import DropItem class PricePipeline: vat_factor = 1.15 def process_item(self, item): adapter = ItemAdapter(item) if adapter.get("price"): if adapter.get("price_excludes_vat"): adapter["price"] = adapter["price"] * self.vat_factor return item else: raise DropItem("Missing price") Write items to a JSON lines file -------------------------------- The following pipeline stores all scraped items (from all spiders) into a single ``items.jsonl`` file, containing one item per line serialized in JSON format: .. code-block:: python import json from itemadapter import ItemAdapter class JsonWriterPipeline: def open_spider(self): self.file = open("items.jsonl", "w") def close_spider(self): self.file.close() def process_item(self, item): line = json.dumps(ItemAdapter(item).asdict()) + "\n" self.file.write(line) return item .. note:: The purpose of JsonWriterPipeline is just to introduce how to write item pipelines. If you really want to store all scraped items into a JSON file you should use the :ref:`Feed exports `. Write items to MongoDB ---------------------- In this example we'll write items to MongoDB_ using pymongo_. MongoDB address and database name are specified in Scrapy settings; MongoDB collection is specified in a class attribute. The main point of this example is to show how to :ref:`get the crawler ` and how to clean up the resources properly. .. skip: next .. code-block:: python import pymongo from itemadapter import ItemAdapter class MongoPipeline: collection_name = "scrapy_items" def __init__(self, mongo_uri, mongo_db): self.mongo_uri = mongo_uri self.mongo_db = mongo_db @classmethod def from_crawler(cls, crawler): return cls( mongo_uri=crawler.settings.get("MONGO_URI"), mongo_db=crawler.settings.get("MONGO_DATABASE", "items"), ) def open_spider(self): self.client = pymongo.MongoClient(self.mongo_uri) self.db = self.client[self.mongo_db] def close_spider(self): self.client.close() def process_item(self, item): self.db[self.collection_name].insert_one(ItemAdapter(item).asdict()) return item .. _MongoDB: https://www.mongodb.com/ .. _pymongo: https://pymongo.readthedocs.io/en/stable/ .. _ScreenshotPipeline: Take screenshot of item ----------------------- This example demonstrates how to use :doc:`coroutine syntax ` in the :meth:`process_item` method. This item pipeline makes a request to a locally-running instance of Splash_ to render a screenshot of the item URL. After the request response is downloaded, the item pipeline saves the screenshot to a file and adds the filename to the item. .. code-block:: python import hashlib from pathlib import Path from urllib.parse import quote import scrapy from itemadapter import ItemAdapter from scrapy.http.request import NO_CALLBACK class ScreenshotPipeline: """Pipeline that uses Splash to render screenshot of every Scrapy item.""" SPLASH_URL = "http://localhost:8050/render.png?url={}" def __init__(self, crawler): self.crawler = crawler @classmethod def from_crawler(cls, crawler): return cls(crawler) async def process_item(self, item): adapter = ItemAdapter(item) encoded_item_url = quote(adapter["url"]) screenshot_url = self.SPLASH_URL.format(encoded_item_url) request = scrapy.Request(screenshot_url, callback=NO_CALLBACK) response = await self.crawler.engine.download_async(request) if response.status != 200: # Error happened, return item. return item # Save screenshot to file, filename will be hash of url. url = adapter["url"] url_hash = hashlib.md5(url.encode("utf8")).hexdigest() filename = f"{url_hash}.png" Path(filename).write_bytes(response.body) # Store filename in item. adapter["screenshot_filename"] = filename return item .. _Splash: https://splash.readthedocs.io/en/stable/ Duplicates filter ----------------- A filter that looks for duplicate items, and drops those items that were already processed. Let's say that our items have a unique id, but our spider returns multiples items with the same id: .. code-block:: python from itemadapter import ItemAdapter from scrapy.exceptions import DropItem class DuplicatesPipeline: def __init__(self): self.ids_seen = set() def process_item(self, item): adapter = ItemAdapter(item) if adapter["id"] in self.ids_seen: raise DropItem(f"Item ID already seen: {adapter['id']}") else: self.ids_seen.add(adapter["id"]) return item .. _activating-item-pipeline: Activating an Item Pipeline component ===================================== To activate an Item Pipeline component you must add its class to the :setting:`ITEM_PIPELINES` setting, like in the following example: .. code-block:: python ITEM_PIPELINES = { "myproject.pipelines.PricePipeline": 300, "myproject.pipelines.JsonWriterPipeline": 800, } The integer values you assign to classes in this setting determine the order in which they run: items go through from lower valued to higher valued classes. It's customary to define these numbers in the 0-1000 range. A complete example ================== The examples above show item pipeline components on their own. In a project, a pipeline is one of four pieces that work together: the :ref:`item ` your spider produces, the :ref:`spider ` that yields it, the pipeline that processes it, and the :setting:`ITEM_PIPELINES` setting that enables the pipeline. The following example wires those pieces together to validate the price of books scraped from `books.toscrape.com`_, reusing the ``PricePipeline`` from :ref:`price-pipeline-example` above. Define the item in ``myproject/items.py``: .. code-block:: python from dataclasses import dataclass @dataclass class BookItem: title: str price: float Yield instances of that item from your spider, e.g. in ``myproject/spiders/books.py``: .. skip: next .. code-block:: python import scrapy from myproject.items import BookItem class BooksSpider(scrapy.Spider): name = "books" start_urls = ["https://books.toscrape.com/"] def parse(self, response): for book in response.css("article.product_pod"): yield BookItem( title=book.css("h3 a::attr(title)").get(), price=float(book.css("p.price_color::text").re_first(r"[\d.]+")), ) Put the ``PricePipeline`` shown earlier in ``myproject/pipelines.py``, and enable it in ``myproject/settings.py``: .. code-block:: python ITEM_PIPELINES = { "myproject.pipelines.PricePipeline": 300, } With these pieces in place, every ``BookItem`` that ``BooksSpider`` yields passes through ``PricePipeline`` before it reaches the :ref:`feed exports ` or any other output. .. _books.toscrape.com: https://books.toscrape.com/ Common pitfalls =============== The pipeline does not run ------------------------- A pipeline component only runs if its class is listed in the :setting:`ITEM_PIPELINES` setting, normally in your project's :file:`settings.py` file (see :ref:`activating-item-pipeline`). Adding it to the spider or elsewhere has no effect. To confirm that Scrapy loaded your pipeline, look for a line like this near the start of the crawl log:: [scrapy.middleware] INFO: Enabled item pipelines: ['myproject.pipelines.PricePipeline'] If your pipeline is missing from that list, check that its import path matches the :setting:`ITEM_PIPELINES` entry, and that the setting is not being overridden, for example by :attr:`~scrapy.Spider.custom_settings` or by a redefinition of :setting:`ITEM_PIPELINES` in :file:`settings.py`. The item is not returned ------------------------ :meth:`process_item` must return the item (or raise :exc:`~scrapy.exceptions.DropItem`). A common mistake is to modify the item but forget to return it: .. code-block:: python def process_item(self, item): ItemAdapter(item)["price"] *= 1.15 # Bug: returns None, so the next component gets None instead of the item. Return the item so that the next component, and the rest of Scrapy, can keep processing it: .. code-block:: python def process_item(self, item): ItemAdapter(item)["price"] *= 1.15 return item