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Binder Project generated with PyScaffold

Curso de cálculo astronomico

Codigo con rutinas para cálculo astronómico escritas en python implementando las técnicas y algoritmos estudiados en el curso.

Siguiendo el temario desarrollado a lo largo del curso de cálculo astronómico de la FAAE, se irán implementando en un paquete las rutinas y funciones dentro del directorio src/calculoastronomico/. Los programas y cuadernos de jupyter que llaman a estas rutinas se incluirán en scripts/ y notebooks/, respectivamente.

Installation

In order to set up the necessary environment:

  1. review and uncomment what you need in environment.yml and create an environment calculoastronomico with the help of conda: 
    conda env create -f environment.yml
  2. activate the new environment with: 
    conda activate calculoastronomico

NOTE: The conda environment will have calculoastronomico installed in editable mode. Some changes, e.g. in setup.cfg, might require you to run pip install -e . again.

Optional and needed only once after git clone:

  1. install several pre-commit git hooks with:

    pre-commit install
# You might also want to run `pre-commit autoupdate`

    and checkout the configuration under .pre-commit-config.yaml. The -n, --no-verify flag of git commit can be used to deactivate pre-commit hooks temporarily. For Windows, an error might appear while importin ctypes. The only solution I could find was downgrading pre-commits with a different channel.

    conda install -c conda-forge/label/gcc7 pre_commit

  2. install nbstripout git hooks to remove the output cells of committed notebooks with:

    nbstripout --install --attributes notebooks/.gitattributes

    This is useful to avoid large diffs due to plots in your notebooks. A simple nbstripout --uninstall will revert these changes.

Then take a look into the scripts and notebooks folders.

Dependency Management & Reproducibility

  1. Always keep your abstract (unpinned) dependencies updated in environment.yml and eventually in setup.cfg if you want to ship and install your package via pip later on.
  2. Create concrete dependencies as environment.lock.yml for the exact reproduction of your environment with: 
    conda env export -n calculoastronomico -f environment.lock.yml
    For multi-OS development, consider using --no-builds during the export.
  3. Update your current environment with respect to a new environment.lock.yml using: 
    conda env update -f environment.lock.yml --prune

Project Organization

├── AUTHORS.md              <- List of developers and maintainers.
├── CHANGELOG.md            <- Changelog to keep track of new features and fixes.
├── CONTRIBUTING.md         <- Guidelines for contributing to this project.
├── Dockerfile              <- Build a docker container with `docker build .`.
├── LICENSE.txt             <- License as chosen on the command-line.
├── README.md               <- The top-level README for developers.
├── configs                 <- Directory for configurations of model & application.
├── data
│   ├── external            <- Data from third party sources.
│   ├── interim             <- Intermediate data that has been transformed.
│   ├── processed           <- The final, canonical data sets for modeling.
│   └── raw                 <- The original, immutable data dump.
├── docs                    <- Directory for Sphinx documentation in rst or md.
├── environment.yml         <- The conda environment file for reproducibility.
├── models                  <- Trained and serialized models, model predictions,
│                              or model summaries.
├── notebooks               <- Jupyter notebooks. Naming convention is a number (for
│                              ordering), the creator's initials and a description,
│                              e.g. `1.0-fw-initial-data-exploration`.
├── pyproject.toml          <- Build configuration. Don't change! Use `pip install -e .`
│                              to install for development or to build `tox -e build`.
├── references              <- Data dictionaries, manuals, and all other materials.
├── reports                 <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures             <- Generated plots and figures for reports.
├── scripts                 <- Analysis and production scripts which import the
│                              actual PYTHON_PKG, e.g. train_model.
├── setup.cfg               <- Declarative configuration of your project.
├── setup.py                <- [DEPRECATED] Use `python setup.py develop` to install for
│                              development or `python setup.py bdist_wheel` to build.
├── src
│   └── calculoastronomico  <- Actual Python package where the main functionality goes.
├── tests                   <- Unit tests which can be run with `pytest`.
├── .coveragerc             <- Configuration for coverage reports of unit tests.
├── .isort.cfg              <- Configuration for git hook that sorts imports.
└── .pre-commit-config.yaml <- Configuration of pre-commit git hooks.

Note

This project has been set up using PyScaffold 4.2.1 and the dsproject extension 0.7.1.