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Provides processors for the itemloaders package, commonly used with scrapy.

Project description

Scrapy Processors

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Scrapy Processors is a collection of Processor classes meant to extend the collection provided in the itemloaders package, commonly used with the scrapy webscraping framework.

https://docs.scrapy.org/en/latest/topics/loaders.html

Repositories

PyPI

GitHub

Installation

To install Scrapy Processors, simply use pip:

$ pip install scrapy-processors

Usage

Here is an overview of the processors available in the package:

  • MapCompose: A processor that allows you to specify a list of callables that will be applied sequentially to a value, or to each value in a list of values. It supports functions (regular functions, lambda or methods), objects with a __call__ method or classes that once initialized return an object with a __call__ method. This class inherits from itemloaders.processors.MapCompose and overrides its constructor and defines __add__.
  • Processor: A base class for creating custom processors. Subclasses of Processor should implement the process_value method.
  • EnsureEncoding: A processor that converts a string to a specified encoding, defaults to utf-8 & ignores errors.
  • NormalizeWhitespace: A processor that normalizes whitespace in a string by removing zero-width spaces, replacing multiple whitespaces with a single whitespace, removing leading whitespace in front of punctuation and finally removing leading/trailing whitespaces. default punctuation=(',', '.', '!', '?', ';', ':')
  • PriceParser: A processor that converts a string representing a price to a Price object using the price_parser library.
  • RemoveHTMLTags: A processor that removes HTML tags from a string using the BeautifulSoup library.
  • Demojize: A processor that replaces Unicode emojis in a string with emoji shortcodes using the emoji library.
  • RemoveEmojis: A processor that removes emojis from a string using the emoji library.
  • StripQuotes: A processor that removes any number of leading/trailing quotes or tick marks from a string.
  • StringToDateTime: A processor that converts a string representing a date and time to a datetime.datetime object. default format='%Y-%m-%d, %H:%M:%S'
  • StringToDate: A processor that converts a string representing a date to a datetime.date object. default format='%Y-%m-%d'
  • StringToTime: A processor that converts a string representing a time to a datetime.time object. default format='%H:%M:%S'
  • TakeAll: A processor that returns all values passed to it. This is a renaming of the built-in Identity processor.
  • TakeAllTruthy: A processor that returns all truthy values passed to it. It also accepts a default value to return if no values are truthy.
# example.py
from scrapy_processors import EnsureEncoding, MapCompose, NormalizeWhitespace, Processor


# Example usage of MapCompose
processor = MapCompose(NormalizeWhitespace, str.upper)
result = processor(['Hello   , World!\n', 'Hi!'])
print(result)  # Output: ['HELLO, WORLD!', 'HI!']

# Example usage of EnsureEncoding processor
processor = EnsureEncoding(encoding='utf-8', ignore=True)
result = processor('Hello')
print(result)  # Output: 'Hello'

# Example usage of custom Processor subclass
class MyProcessor(Processor):
    def process_value(self, value):
        return value + ' processed'

processor = MyProcessor()
result = processor(['Hello', 'World'])
print(result)  # Output: ['Hello processed', 'World processed']

Opening an Issue

If you encounter a problem with the project or have a feature request, you can open an issue to let us know.

To open an issue, please follow these steps:

  1. Go to the Issues tab on the github repository page.
  2. Click on the "New Issue" button.
  3. Provide a descriptive title for the issue.
  4. In the issue description, provide detailed information about the problem you are experiencing or the feature you are requesting.
  5. If applicable, include steps to reproduce the problem or any relevant code examples.
  6. Add appropriate labels to categorize the issue (e.g., bug, enhancement, documentation).
  7. Click on the "Submit new issue" button to create the issue.

Once you have opened an issue, our team will review it and provide assistance or discuss the requested feature.

Note: Before opening a new issue, please search the existing issues to see if a similar issue has already been reported. This helps avoid duplicates and allows us to focus on resolving existing problems.

Contributing

Thank you for considering contributing to this project! We welcome your contributions to help make this project better.

To contribute to this project, please follow these steps:

  1. Fork the repository by clicking on the "Fork" button at the top of the repository page. This will create a copy of the repository in your GitHub account.

  2. Clone the forked repository to your local machine using Git:

    $ git clone https://github.com/your-username/scrapy-processors.git
    
  3. Create a new branch for your changes:

    $ git checkout -b feature
    
  4. Make your desired changes to the codebase.

  5. Commit your changes with descriptive commit messages:

    $ git commit -m "Add new feature"
    
  6. Push your changes to your forked repository:

    $ git push origin feature
    
  7. Open a pull request (PR) from your forked repository to the original repository's master branch.

  8. Provide a clear and descriptive title for your PR and explain the changes you have made.

  9. Wait for the project maintainers to review your PR. You may need to make additional changes based on their feedback.

  10. Once your PR is approved, it will be merged into the main codebase. Congratulations on your contribution!

If you have any questions or need further assistance, feel free to open an issue or reach out to the project maintainers.

Happy contributing!

License

This project is licensed under the MIT License. See the LICENSE file for more details.

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