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Rich is a Python library for rich text and beautiful formatting in the terminal. The Rich API makes it easy to add color and style to terminal output. Rich can also render pretty tables, progress bars, markdown, syntax highlighted source code, tracebacks, and more — out of the box.
rich-argparse Format argparse and optparse help using rich. rich-argparse improves the look and readability of argparse's help while requiring minimal changes to the code. Table of contents Installation Usage Output styles Colors Group names Highlighting patterns "usage" --version Subparsers Third party formatters (ft. django) Optparse (experimental) Legacy Windows Installation Install from PyPI with pip or your favorite tool. pip install rich-argparse Usage Simply pass formatter_class to the argument parser import argparse from rich_argparse import RichHelpFormatter parser = argparse.ArgumentParser(..., formatter_class=RichHelpFormatter) ... rich-argparse defines equivalents to argparse's built-in formatters: rich_argparse formatter equivalent in argparse RichHelpFormatter HelpFormatter RawDescriptionRichHelpFormatter RawDescriptionHelpFormatter RawTextRichHelpFormatter RawTextHelpFormatter ArgumentDefaultsRichHelpFormatter ArgumentDefaultsHelpFormatter
Richly rendered command line interfaces in click.
Rich DataFrame Create animated and pretty Pandas Dataframe or Pandas Series, as shown below: Installation pip install rich-dataframe Usage Minimal example from sklearn.datasets import fetch_openml from rich_dataframe import prettify speed_dating = fetch_openml(name='SpeedDating', version=1)['frame'] table = prettify(speed_dating) If you want to pass a non-dataframe object, rich_dataframe got it covered too! from rich_dataframe import prettify var = {'a': 1, 'b': 3} prettify(var) Parameters df: pd.DataFrame The data you want to prettify row_limit : int, optional Number of rows to show, by default 20 col_limit : int, optional Number of columns to show, by default 10 first_rows : bool, optional Whether to show first n rows or last n rows, by default True. If this is set to False, show last n rows. first_cols : bool, optional Whether to show first n columns or last n columns, by default True. If this is set to False, show last n rows. delay_time : int, optional How fast is the
serpy is a super simple object serialization framework built for speed. serpy serializes complex datatypes (Django Models, custom classes, ...) to simple native types (dicts, lists, strings, ...). The native types can easily be converted to JSON or any other format needed. The goal of serpy is to be able to do this simply, reliably, and quickly. Since serializers are class based, they can be combined, extended and customized with very little code duplication. Compared to other popular Python serialization frameworks like marshmallow or Django Rest Framework Serializers serpy is at least an order of magnitude faster. Python 3 version.
This is a metapackage bringing in completion extras requires for python3-trytond. It makes sure the dependencies are installed.
This is a metapackage bringing in data extras requires for python3-trytond-currency. It makes sure the dependencies are installed.
Boto3 is the Amazon Web Services (AWS) Software Development Kit (SDK) for Python, which allows Python developers to write software that makes use of services like Amazon S3 and Amazon EC2.
Bottle is a fast and simple micro-framework for small web-applications. It offers request dispatching (Routes) with URL parameter support, Templates, a built-in HTTP Server and adapters for many third party WSGI/HTTP-server and template engines. All in a single file and with no dependencies other than the Python Standard Library.
A collection of cache libraries with a common API. Extracted from Werkzeug.