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HPI/doc/SETUP.org
Dima Gerasimov e351c8ba49 cli: add 'config init' command
2020-05-25 12:25:41 +01:00

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Please don't be shy and raise issues if something in the instructions is unclear. You'd be really helping me, I want to make the setup as straightforward as possible!

TOC

Few notes

I understand people may not super familiar with Python, PIP or generally unix, so here are some useful notes:

  • only python3 is supported, and more specifically, python >= 3.6.
  • I'm using pip3 command, but on your system you might only have pip. If your pip --version says python 3, feel free to use pip.
  • similarly, I'm using python3 in the documentation, but if your python --version says python3, it's okay to use python
  • when you are using pip install, always pass --user, and never install third party packages with sudo (unless you know what you are doing)
  • throughout the guide I'm assuming the user config directory is ~/.config, but it's different on Mac/Windows. See this if you're not sure what's your user config dir.

Install main HPI package

This is a required step

You can choose one of the following options:

option 1: install from PIP

This is the easiest way:

pip3 install --user HPI

option 2: local/editable install

This is convenient if you're planning to add new modules or change the existing ones.

  1. Clone the repository: git clone git@github.com:karlicoss/HPI.git /path/to/hpi
  2. Go into the project directory: cd /path/to/hpi
  3. Run pip3 install --user -e . This will install the package in 'editable mode'. It means that any changes to /path/to/hpi will be immediately reflected without need to reinstall anything. It's extremely convenient for developing and debugging.

option 3: use without installing

This is less convenient, but gives you more control.

  1. Clone the repository: git clone git@github.com:karlicoss/HPI.git /path/to/hpi
  2. Go into the project directory: cd /path/to/hpi
  3. Install the dependencies: python3 setup.py --dependencies-only

  4. Use with_my script to get access to my. modules.

    For example:

    /path/to/hpi/with_my python3 -c 'from my.pinboard import bookmarks; print(list(bookmarks()))'

    It's also convenient to put a symlink to with_my somewhere in your system path so you can run it from anywhere, or add an alias in your bashrc:

    alias with_my='/path/to/hpi/with_my'

    After that, you can wrap your command in with_my to give it access to my. modules, e.g. see examples.

The benefit of this way is that you get a bit more control, explicitly allowing your scripts to use your data.

appendix: optional packages

You can also install some opional packages

pip3 install 'HPI[optional]'

They aren't necessary, but will improve your experience. At the moment these are:

  • cachew: automatic caching library, which can greatly speedup data access
  • logzero: a nice logging library, supporting colors
  • mypy: mypy is used for checking configs and troubleshooting

Setting up modules

This is an optional step as few modules work without extra setup. But it depends on the specific module.

See MODULES to read documentation on specific modules that interest you.

You might also find interesting to read CONFIGURING, where I'm elaborating on some technical rationales behind the current configuration system.

private configuration (my.config)

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.

The configuration contains paths to the data on your disks, links to external repositories, etc. The config is simply a python package (named my.config), expected to be in ~/.config/my.

Since it's a Python package, generally it's very flexible and there are many ways to set it up.

  • The simplest way

    After installing HPI, run hpi config init.

    This will create an empty config file for you (usually, in ~/.config/my), which you can edit. Example configuration:

    import pytz # yes, you can use any Python stuff in the config

class emfit:
    export_path = '/data/exports/emfit'
    tz = pytz.timezone('Europe/London')
    excluded_sids = []
    cache_path  = '/tmp/emfit.cache'

class instapaper:
    export_path = '/data/exports/instapaper'

class roamresearch:
    export_path = '/data/exports/roamresearch'
    username    = 'karlicoss'

    To find out which attributes you need to specify:

    • check in MODULES
    • if there is nothing there, the easiest is perhaps to skim through the code of the module and to search for config. uses. For example, if you search for config. in emfit module, you'll see that it's using export_path, tz, excluded_sids and cache_path.
    • or you can just try running them and fill in the attributes Python complains about!

  • Another example is in example_config:

    dir     | example_config/
dir     | example_config/my
dir     | example_config/my/config
file    | example_config/my/config/__init__.py
          ---
          """
          Feel free to remove this if you don't need it/add your own custom settings and use them
          """

          class hypothesis:
              # expects outputs from https://github.com/karlicoss/hypexport
              # (it's just the standard Hypothes.is export format)
              export_path = '/path/to/hypothesis/data'
          ---
dir     | example_config/my/config/repos
symlink | example_config/my/config/repos/hypexport -> /tmp/my_demo/hypothesis_repo

As you can see, generally you specify fixed paths (e.g. to your backups 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 ordinary symlinks in repos directory. That way you get easy imports (e.g. import my.config.repos.hypexport.model) and proper IDE integration.

  • my own config layout is a bit more complicated:

    ~/.config/my/my/config/__init__.py
~/.config/my/my/config/locations.py
~/.config/my/my/config/repos
~/.config/my/my/config/repos/endoexport
~/.config/my/my/config/repos/fbmessengerexport
~/.config/my/my/config/repos/kobuddy
~/.config/my/my/config/repos/monzoexport
~/.config/my/my/config/repos/pockexport
~/.config/my/my/config/repos/rexport

module 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 pip3 install --user, should be fairly straightforward.

Troubleshooting

HPI comes with a command line tool that can help you detect potential issues. Run:

hpi doctor
# alternatively, for more output:
hpi doctor --verbose

If you only have few modules set up, lots of them will error for you, which is expected, so check the ones you expect to work.

If you have any ideas on how to improve it, please let me know!

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.

End-to-end Roam Research setup

In this post you can trace all steps:

  • learn how to export your raw data
  • integrate it with HPI package

  • benefit from HPI integration

If you want to set up a new data source, it could be a good learning reference.

Polar

Polar doesn't require any setup as it accesses the highlights on your filesystem (usually in ~/.polar).

You can try if it works with:

python3 -c 'import my.reading.polar as polar; print(polar.get_entries())'

Google Takeout

If you have zip Google Takeout archives, you can use HPI to access it:

  • prepare the config ~/.config/my/my/config.py

    class google:
    # you can pass the directory, a glob, or a single zip file
    takeout_path = '/data/takeouts/*.zip'

  • use it:

    $ python3 -c 'import my.media.youtube as yt; print(yt.get_watched()[-1])'
Watched(url='https://www.youtube.com/watch?v=p0t0J_ERzHM', title='Monster magnet meets monster magnet...', when=datetime.datetime(2020, 1, 22, 20, 34, tzinfo=<UTC>))

Kobo reader

Kobo module allows you to access the books you've read along with the highlights and notes. It uses exports provided by kobuddy package.

  • prepare the config

    1. Point ln -sfT /path/to/kobuddy ~/.config/my/my/config/repos/kobuddy

    2. Add kobo config to ~/.config/my/my/config/__init__.py

      class kobo:
    export_dir = 'path/to/kobo/exports'

After that you should be able to use it:

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

Orger

You can use orger to get Org-mode representations of your data.

Some examples (assuming you've installed Orger):

Orger + Polar

This will mirror Polar highlights as org-mode:

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

demo.py

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

Adding/modifying modules

The easiest is just to run HPI via with_my wrapper or with an editable PIP install. That way your changes will be reflected immediately, and you will be able to quickly iterate/fix bugs/add new methods.

The "proper way" (unless you want to contribute to the upstream) is to create a separate file hierarchy and add your module to PYTHONPATH.

For example, if you want to add an awesomedatasource, it could be:

custom_module
└── my
    └──awesomedatasource.py

You can use all existing HPI modules in awesomedatasource.py, for example, my.config, or everything from my.core.

But also, you can use override the builtin HPI modules too:

custom_reddit_overlay
└── my
    └──reddit.py

Now if you add my_reddit_overlay in the front of PYTHONPATH, all the downstream scripts using my.reddit will load it from custom_reddit_overlay instead.

This could be useful to monkey patch some behaviours, or dynamically add some extra data sources – anything that comes to your mind.

I'll put up a better guide on this, in the meantime see "namespace packages" for more info.