Contributing to Scrapy

Important

Double check you are reading the most recent version of this document at http://doc.scrapy.org/en/master/contributing.html

There are many ways to contribute to Scrapy. Here are some of them:

  • Blog about Scrapy. Tell the world how you’re using Scrapy. This will help newcomers with more examples and the Scrapy project to increase its visibility.
  • Report bugs and request features in the issue tracker, trying to follow the guidelines detailed in Reporting bugs below.
  • Submit patches for new functionality and/or bug fixes. Please read Writing patches and Submitting patches below for details on how to write and submit a patch.
  • Join the Scrapy subreddit and share your ideas on how to improve Scrapy. We’re always open to suggestions.

Reporting bugs

Note

Please report security issues only to scrapy-security@googlegroups.com. This is a private list only open to trusted Scrapy developers, and its archives are not public.

Well-written bug reports are very helpful, so keep in mind the following guidelines when reporting a new bug.

  • check the FAQ first to see if your issue is addressed in a well-known question
  • check the open issues to see if it has already been reported. If it has, don’t dismiss the report but check the ticket history and comments, you may find additional useful information to contribute.
  • search the scrapy-users list and Scrapy subreddit to see if it has been discussed there, or if you’re not sure if what you’re seeing is a bug. You can also ask in the #scrapy IRC channel.
  • write complete, reproducible, specific bug reports. The smaller the test case, the better. Remember that other developers won’t have your project to reproduce the bug, so please include all relevant files required to reproduce it. See for example StackOverflow’s guide on creating a Minimal, Complete, and Verifiable example exhibiting the issue.
  • include the output of scrapy version -v so developers working on your bug know exactly which version and platform it occurred on, which is often very helpful for reproducing it, or knowing if it was already fixed.

Writing patches

The better written a patch is, the higher chance that it’ll get accepted and the sooner that will be merged.

Well-written patches should:

  • contain the minimum amount of code required for the specific change. Small patches are easier to review and merge. So, if you’re doing more than one change (or bug fix), please consider submitting one patch per change. Do not collapse multiple changes into a single patch. For big changes consider using a patch queue.
  • pass all unit-tests. See Running tests below.
  • include one (or more) test cases that check the bug fixed or the new functionality added. See Writing tests below.
  • if you’re adding or changing a public (documented) API, please include the documentation changes in the same patch. See Documentation policies below.

Submitting patches

The best way to submit a patch is to issue a pull request on GitHub, optionally creating a new issue first.

Remember to explain what was fixed or the new functionality (what it is, why it’s needed, etc). The more info you include, the easier will be for core developers to understand and accept your patch.

You can also discuss the new functionality (or bug fix) before creating the patch, but it’s always good to have a patch ready to illustrate your arguments and show that you have put some additional thought into the subject. A good starting point is to send a pull request on GitHub. It can be simple enough to illustrate your idea, and leave documentation/tests for later, after the idea has been validated and proven useful. Alternatively, you can start a conversation in the Scrapy subreddit to discuss your idea first. When writing GitHub pull requests, try to keep titles short but descriptive. E.g. For bug #411: “Scrapy hangs if an exception raises in start_requests” prefer “Fix hanging when exception occurs in start_requests (#411)” instead of “Fix for #411”. Complete titles make it easy to skim through the issue tracker.

Finally, try to keep aesthetic changes (PEP 8 compliance, unused imports removal, etc) in separate commits than functional changes. This will make pull requests easier to review and more likely to get merged.

Coding style

Please follow these coding conventions when writing code for inclusion in Scrapy:

  • Unless otherwise specified, follow PEP 8.
  • It’s OK to use lines longer than 80 chars if it improves the code readability.
  • Don’t put your name in the code you contribute. Our policy is to keep the contributor’s name in the AUTHORS file distributed with Scrapy.

Documentation policies

  • Don’t use docstrings for documenting classes, or methods which are already documented in the official (sphinx) documentation. For example, the ItemLoader.add_value() method should be documented in the sphinx documentation, not its docstring.
  • Do use docstrings for documenting functions not present in the official (sphinx) documentation, such as functions from scrapy.utils package and its sub-modules.

Tests

Tests are implemented using the Twisted unit-testing framework, running tests requires tox.

Running tests

Make sure you have a recent enough tox installation:

tox --version

If your version is older than 1.7.0, please update it first:

pip install -U tox

To run all tests go to the root directory of Scrapy source code and run:

tox

To run a specific test (say tests/test_loader.py) use:

tox -- tests/test_loader.py

To see coverage report install coverage (pip install coverage) and run:

coverage report

see output of coverage --help for more options like html or xml report.

Writing tests

All functionality (including new features and bug fixes) must include a test case to check that it works as expected, so please include tests for your patches if you want them to get accepted sooner.

Scrapy uses unit-tests, which are located in the tests/ directory. Their module name typically resembles the full path of the module they’re testing. For example, the item loaders code is in:

scrapy.loader

And their unit-tests are in:

tests/test_loader.py