• Setting up
  • my_configuration package for private paths/repositores (optional)
  • with_my helper script
  • Dependencies
• Usage examples
• Linting

https://circleci.com/gh/karlicoss/my/tree/master.svg?style=svg

Python interface into my life and data.

This package deals with abstracting away various data sources and providing nice Python interfaces for them, to make it easier to access, work with and combine data.

This particular setup might not necessarily be convenient for you to use, perhaps it's more of a concept of how you can organize and access your personal data. But it definitely works for me so hopefully that would help you if you're struggling!

This readme is more of a setup manual, I'm writing about motivation and specific usecases here.

Setting up

my_configuration package for private paths/repositores (optional)

If you're not planning to use private configuration (some modules don't need it) you can skip straight to the next step. Still, I'd recommend you to read anyway.

First you need to tell the package where to look for your data and external repositories, which is done though a separate (private) package named my_configuration.

You can see example in my_configuration_template. You can copy it somewhere else and modify to your needs.

Some explanations:

d my_configuration_template/
d my_configuration_template/my_configuration
f my_configuration_template/my_configuration/__init__.py
  ---
  class paths:
      """
      Feel free to remore hypexport if you don't need it/add your own custom settings and use them
      """
      class hypexport:
          export_dir = '/tmp/my_demo/backups/hypothesis'
  ---
d my_configuration_template/my_configuration/repos
l my_configuration_template/my_configuration/repos/hypexport -> /tmp/my_demo/hypothesis_repo

As you can see, generally you specify fixed paths (e.g. to backup directory) in __init__.py. Feel free to add other files as well though to organize better, it's a real python package after all!

Some things (e.g. links to external packages like hypexport) are specified as normal symlinks in repos directory. That way you get easy imports (e.g. import my_configuration.repos.hypexport.model) and proper IDE integration.

with_my helper script

Next, point with_my script to your private configuration:

cp with_my.example with_my
vim with_my # specify path to your my_configuration (if you want to use it)

It's also convenient to put with_my somewhere in your system path so you can run it from anywhere.

Dependencies

Dependencies are different for specific modules you're planning to use, so it's hard to specify. Generally you can just try using the module and then install missing packages via pip install --user, should be fairly straighforward.

Usage examples

If you run your script with with_my wrapper, you'd have my in PYTHONPATH which gives you access to your data from within the script.

• accessing Kobo books

  with_my python3 -c 'import my.books.kobo as kobo; print(kobo.get_todos())'

• if you have orger installed, you can use its Polar module to render all highlights as org-mode file as easy as:

with_my orger/modules/polar.py --to polar.org

• read/run demo.py for a full demonstration of setting up Hypothesis (it uses public annotations data from Github)

Linting

# see https://github.com/python/mypy/issues/1645 for --namespace-packages explanation
with_my mypy --namespace-packages my

or, set up as mypy.ini file:

[mypy]
mypy_path=/path/to/my_configuration_dir