Skip to main content

Kanji Stroke Order Study Tool

Project description

ksost

ksost logo

ksost stands for Kanji Stroke Order Study Tool. It is a small web application for studying kanji stroke order, written in Python and plain JavaScript.

The server has no runtime Python or JavaScript package dependencies, but there are some dependencies for development and to run the desktop wrapper, as well as some setup steps required to run from source. See Running From Source, Desktop Wrapper and Development.

Dependencies

  • Python >= 3.14
  • SQLite3
  • optional Qt for desktop wrapper

Installing

ksost is currently packaged only as a PyPI package and can be installed by end users by running:

pip install ksost
# To include native desktop dependencies (won't work on Linux):
pip install 'ksost[desktop]'
# To include Qt desktop dependencies:
pip install 'ksost[desktop-qt]'

Running From Source

First initialize the dataset submodules. You can use git submodule for that, but prefer the make bootstrap target, which will also prepare the environment in other ways (see make targets):

make bootstrap

Then activate the venv and start the server using the command installed in it, or call the commands using the venv explicitly:

# Activating the venv
. .venv/bin/activate
ksost

# Without activating the venv
.venv/bin/ksost
# Or
.venv/bin/python -m ksost

These commands start the built-in HTTP server and initialize the configured SQLite database if needed.

If you want to initialize the database explicitly, you can also run:

ksost init-db

Desktop Wrapper

To run the desktop wrapper on Linux you need Qt installed on your system beforehand. The Python-level desktop dependencies are defined in pyproject.toml, and you can install them to your venv manually or with:

make desktop-qt
# In Windows/Mac you can probably use it without Qt, with just:
make desktop

Then run with:

ksost desktop
# Or force Qt:
ksost desktop qt

Configuration

Runtime configuration lives in ksost.toml. ksost looks for that file in this order, using only the first file it finds:

  1. the current working directory
  2. the user config directory
  3. the system config directories

An example commented file is provided at ksost.toml.example.

On Linux, the user config directory is $XDG_CONFIG_HOME/ksost if XDG_CONFIG_HOME is set, otherwise ~/.config/ksost. System config directories are /etc/ksost followed by the entries in XDG_CONFIG_DIRS, or /etc/xdg/ksost if XDG_CONFIG_DIRS is not set.

Development

For development, create a virtual environment and install the dev optional-dependency group from pyproject.toml.

You can do that manually, or use the make target:

make dev

This also creates an untracked local override file at ksost/frontend/pwa.local.js if it does not exist yet. By default it keeps the normal PWA behavior:

export const PWA_ENABLED = true;

For local frontend testing, you can change that to false, which disables the service-worker/PWA behavior, making testing easier when you're constantly changing the static files.

To run the checks:

./scripts/check.sh && ./scripts/test.sh

make targets

You can see in Makefile the complete list of targets. In addition to the actual file targets, there are phony targets that group targets in useful functional groups. The top-level targets are:

  • Bootstrap targets:
    • bootstrap
      • Includes submodules, which initializes git submodules
      • Includes data, which copies important files from submodules to the paths where the application expects them
      • Includes venv, which creates the Python virtual environment in .venv
    • dev
      • Includes bootstrap
      • Includes overrides, which creates the PWA override mentioned in Development
      • Installs the Python extra development dependencies from pyproject.toml
    • desktop
      • Includes bootstrap
      • Installs the Python extra desktop dependencies from pyproject.toml
  • Packaging targets:
    • arch
      • Depends on the Python package artifacts, see below
      • Updates the PKGBUILD source hash
      • Generates .SRCINFO
      • Runs makepkg -s to package for Arch Linux
      • Must be run outside an active Python venv
      • Not currently published on the AUR, PKGBUILD is here as a reference if someone desires to do so
    • python
      • Creates both the python wheel and sdist packages, with our best effort to make both builds reproducible
      • Refuses to build when the git worktree has unstaged or untracked changes
      • Use make ALLOW_DIRTY=1 python to bypass
    • clean-dist
      • Remove all generated artifacts in dist/

License

ksost itself is licensed under MIT. This repository also includes third-party datasets under their own licenses. See LICENSE for the exact boundary and the referenced third-party license files.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ksost-13.tar.gz (21.1 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ksost-13-py3-none-any.whl (21.1 MB view details)

Uploaded Python 3

File details

Details for the file ksost-13.tar.gz.

File metadata

  • Download URL: ksost-13.tar.gz
  • Upload date:
  • Size: 21.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for ksost-13.tar.gz
Algorithm Hash digest
SHA256 76750238332dcf62404ff071c269eee41d99e8d0227a7ce42363390b90847138
MD5 5df1a964f4d432c6efaea0ad6bc99f14
BLAKE2b-256 2567e3f02be927b62f47d0b84d977d62d1d31a9b2ae8c0c26bea93b5b1eaadd2

See more details on using hashes here.

File details

Details for the file ksost-13-py3-none-any.whl.

File metadata

  • Download URL: ksost-13-py3-none-any.whl
  • Upload date:
  • Size: 21.1 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.14.4

File hashes

Hashes for ksost-13-py3-none-any.whl
Algorithm Hash digest
SHA256 37d2c41a29ece1de5a2df120ae64024c06d20cc89b4b7fc7754365a7669d9250
MD5 946a9932c2be8023bc0f0a4cd920a1ce
BLAKE2b-256 aad889fa5641a1116a00e5ab84f8a85fbd4ef972791c7eddc6f49d317239768b

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page