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Remotely control a telescope while it polls for tasks, collects and edge processes data, and delivers results and data for further processing.

This project has been archived.

The maintainers of this project have marked this project as archived. No new releases are expected.

Project description

CitraScope

Pytest Publish Python Package

Remotely control a telescope while it polls for tasks, collects observations, and delivers data for further processing.

Features

  • Offers a web UI to configure hardware and connect to Citra.space's api
  • Connects to Citra.space's API and identifies itself as an online telescope
  • Connects to configured telescope and camera hardware
  • Acts as a task daemon carrying out and remitting photography tasks

Documentation

Full documentation is available at docs.citra.space.

Documentation source is maintained in the citra-space/docs repository.

Installation

Important: CitraScope requires Python 3.10, 3.11, or 3.12.

Check Your Python Version

python3 --version

If you don't have a compatible version, install one with pyenv:

pyenv install 3.12.0
pyenv local 3.12.0  # Sets Python 3.12.0 for the current directory

Install CitraScope

Recommended: Using pip in a virtual environment

python3 -m venv citrascope-env
source citrascope-env/bin/activate  # On Windows: citrascope-env\Scripts\activate
pip install citrascope

Optional Dependencies

For Linux-based telescope control (INDI):

pip install citrascope[indi]

This provides the citrascope command-line tool. To see available commands:

citrascope --help

Usage

Starting the Daemon

Run the daemon with:

citrascope

By default, this starts the web interface on http://localhost:24872. You can customize the port:

citrascope --web-port 8080

Developer Setup

If you are developing on macOS or Windows, use the provided VS Code Dev Container setup. The devcontainer provides a full Linux environment, which is required for the pyindi-client dependency to work. This is necessary because pyindi-client only works on Linux, and will not function natively on Mac or Windows.

By opening this project in VS Code and choosing "Reopen in Container" (or using the Dev Containers extension), you can develop and run the project seamlessly, regardless of your host OS.

The devcontainer also ensures all required system dependencies (like cmake) are installed automatically.

Python Version

This project requires Python 3.10 or higher, up to Python 3.12. A .python-version file is included specifying Python 3.12 as the recommended version. If you use pyenv, it will automatically use this version when you enter the project directory.

If not using the dev container:

python -m venv .venv
source .venv/bin/activate

Installing Development Dependencies

To install development dependencies (for code style, linting, and pre-commit hooks):

pip install '.[dev]'

Setting up Pre-commit Hooks

This project uses pre-commit to run code quality checks (like Flake8, Black, isort, etc.) automatically before each commit.

After installing the dev dependencies, enable the hooks with:

pre-commit install

You can manually run all pre-commit checks on all files with:

pre-commit run --all-files

This ensures code style and quality checks are enforced for all contributors.

Releasing a New Version

To bump the version and create a release:

bump-my-version bump patch  # 0.1.3 → 0.1.4
bump-my-version bump minor  # 0.1.3 → 0.2.0
bump-my-version bump major  # 0.1.3 → 1.0.0
git push && git push --tags

Then create a release in the GitHub UI from the new tag. This triggers automatic PyPI publishing.

Running and Debugging with VS Code

If you are using Visual Studio Code, you can run or debug the project directly using the pre-configured launch options in .vscode/launch.json:

  • Python: citrascope — Runs the daemon with default settings
  • Python: citrascope (custom port) — Runs with web interface on port 8080

To use these, open the Run and Debug panel in VS Code, select the desired configuration, and click the Run or Debug button.

Running Tests

This project uses pytest for unit testing. All tests are located in the tests/ directory.

To run unit tests within your devcontainer:

pytest

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