makepy 0.0.19

makepy: Handsfree Python Module Programming

makepy: Handsfree Python Module Programming

This project provides:

makepy: A command line tool to simplify Python project setup, installation, and testing.
makepy.mainlog: A module for making logging and structlog setup less cumbersome and less error-prone.
makepy.argparse: A module providing a drop-in ArgumentParser for writing better readable argparse code.

Install via pip install --user makepy.

mainlog module

As the name suggest, use makepy.mainlog only in your main module. Do not setup logging outside of main modules! The module's main function is mainlog.setup_logging:

import logging
from makepy import mainlog

log = logging.getLogger('pimp-test')

def main(argv=None):
    level = logging.INFO
    mainlog.setup_logging(level=level, mode='json')
    log.info('Hello %s!', 'makepy', extra={'v':1})

main()
# {"message": "Hello makepy!", "v": 1}

The currently supported logging modes are json and console (default). Using mode='console' or no mode will produce regular stdlib logs like:

INFO:pimp-test:Hello makepy!

Use mainlog.setup_logging(level=level, use_structlog=True) to setup structlog logging. If struclog is not installed, stdlib logging is used as fallback. The predefined structlog settings will format stdlib logs as follows.

[info     ] info msg 1                     [stdlib]
[debug    ] debug msg 2                    [stdlib]
[error    ] error msg 3                    [stdlib]

If you use structlog loggers in your modules you also get key-value pairs.

[info     ] info msg                       [structlog] a=[1, 2, 3] v=1
[debug    ] debug msg                      [structlog] b=('a', 'b', 'c') v=2
[error    ] error msg                      [structlog] c={'x': 1} v=3

If colorama is installed, the logs will be nicely colored.

argparse module

For readability makepy.argparse provides a compatible ArgumentParser that uses the 4-letter opti and flag methods instead the clumsy add_argument.

from makepy import argparse
desc = 'My CLI Tool'
p = argparse.ArgumentParser(description=desc)
p.flag('--json',          help='use json output format')
p.flag('--dry_run',       help='perform dry run')
p.opti('--num',     '-n', help='number of iterations', metavar='N', type=int, default=1)
p.opti('--file',    '-f', help='input file',           required=True)
p.opti('command',         help='command to run',       choices=['upper','lower'])

Using shorter names and nice alignment allows argparse code to be much more readable. Yes I know, to allow for such multi-column-based coding, you need to disable some linter rules. But it's worth it, not just for argparse code, but for better readable Python code in general. makepy's ArgumentParser also provides a few shortcuts to setup commonly used related modules directly via the following flags:

• with_debug: adds --debug flag
• with_logging: automatically sets up logging using makepy.mainlog after parsing args
• with_input: adds --input option, defaulting to - (aka. stdin)
• with_protected_spaces: will replace spaces in all help texts with protected spaces to prevent argparse from stripping them. This way, you do not need to setup a special help formatter to achive aligned table-like help texts on the command line. You can just align them in the code! See makep/cli.py as an example.

To setup debug and logging I usually use this one-liner in my parsers:

p = argparse.ArgumentParser(description=desc).with_logging(use_structlog=True).with_debug()

If you do not like one-liners, you can also break lines.

p = argparse.ArgumentParser(description=desc)
p.with_logging(use_structlog=True)
p.with_debug()
p.with_input()

Using the with_logging and optionally using with_debug allows you to quickly setup logging or structlog loggers with human-readable console output. Therefore, with_logging supports the same mode and use_structlog key-value args as used by mainlog.setup_logging described above.

makepy command

There is also a makepy command that I use to automate project creation, incremental building, testing via tox, and uploading to PyPi.

Here are some commands supported by makepy:

makepy init --trg ~/workspace/newproject # setup new python project
cd ~/workspace/newproject                # enter new project

makepy backport   # backport project to python2
tox -e py3        # install the current version in testenv and run tests
tox               # install and test in all testenvs
makepy            # install and test the default testenv
makepy clean      # cleanup test environments

makepy dist       # build python wheel for project
makepy install    # install the wheel in the system (may require sudo)
makepy uninstall  # uninstall current project from all pips

The makepy command uses a custom project.cfg, tox.ini, setup.cfg, and a generic py2-py3+ compatible setup.py, as found in this project. It can also be combined with make.

Run makepy init --trg PATH_TO_NEW_PROJECT to setup all required files; use -f to allow overwriting existing files. See makepy --help for more options.

makepy + make

Some makepy functionality is still only available via make, using the make/project.mk, [make/vars.mk][make_vars], etc. include files. You can still use these in your project. Just copy them to a make dir in your project and include them in your Makefile, as done by this project. See each mk-file for details and help.

Goals

In general the project aims to provide a few flexible tools and modules that should help with daily Python programming tasks, when developing your own Python modules, libaries, and command line tools. It aims to capture best practices and make them reusable, allowing you to write less and more readable code, without breaking flexibility or compatibility of the enhanced modules.

Motivation

Most Python programmers know argparse, logging or structlog, tox and pip, and many also use twine, setuptools, and others. However, in my projects I have used the same or very similar code and build chains over and over again when using these tools and modules. And since I do not like to repeat myself, I wanted to extract the most common practices from my projects and make them available for my next projects and for others to use.

I will keep makepy updated, with future learning and I am happy to welcome pull requests.

Have fun!