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Change","sub_category":"Climate Data Processing and Analysis","monthly_downloads":61,"total_dependent_repos":0,"total_dependent_packages":0,"readme":"# Free Evaluation System Framework\n\n[![PyPI version](https://badge.fury.io/py/freva.svg)](https://badge.fury.io/py/freva)\n[![Update](https://anaconda.org/conda-forge/freva/badges/latest_release_date.svg)](https://github.com/freva-org/freva-legacy)\n[![Anaconda-Server Badge](https://anaconda.org/conda-forge/freva/badges/version.svg)](https://anaconda.org/conda-forge/freva)\n[![Docs](https://img.shields.io/badge/Freva-Docs-green.svg)](https://freva-org.github.io/freva-legacy)\n[![codecov](https://codecov.io/gh/freva-org/freva/branch/main/graph/badge.svg)](https://codecov.io/gh/freva-org/freva-legacy)\n[![Pipeline](https://github.com/freva-org/freva/actions/workflows/ci_job.yml/badge.svg)](https://github.com/freva-org/freva-legacy/actions)\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/freva-org/freva-legacy/main?labpath=Readme.ipynb)\n[![BSD](https://anaconda.org/conda-forge/freva/badges/license.svg)](https://github.com/freva-org/freva-legacy)\n\n \u003e 💡 The code base is deprecated and should only be used if necessary.\n \u003e  A new version of Freva is on the way! While it’s still under development,\n \u003e  you can already start using it. If your primary focus is searching and\n \u003e  accessing data, we highly recommend trying out the new Freva client\n \u003e  (https://pypi.org/project/freva-client/)\n\n\n\n\u003cimg src=\"docs/source/_static/freva_flowchart-new.jpg\" alt=\"Freva\" width=\"400\"/\u003e\n\n## What is Freva ?\nFreva, the free evaluation system framework, is a data search and analysis\nplatform developed by the atmospheric science community for the atmospheric\nscience community. With help of Freva researchers can:\n\n- quickly and intuitively search for data stored at typical data centers that\n  host many datasets.\n- create a common interface for user defined data analysis tools.\n- apply data analysis tools in a reproducible manner.\n\nData analysis is realised by user developed data analysis plugins. These plugins\nare code agnostic, meaning that users don't have to rewrite the core of their\nplugins to make them work with Freva. All that Freva does is providing a user\ninterface for the plugins.\n\nCurrently Freva comes in three different flavours:\n\n- a python module that allows the usage of Freva in python environments, like\n  jupyter notebooks\n- a command line interface (cli) that allows using Freva from the command\n  lines and shell scripts.\n- a web user interface (web-ui)\n\n\n\n## Where can I find the Freva user documentation?\nA more detailed overview on the usage of freva can be found on the\n[freva user documentation page](https://freva-org.github.io/freva)\n\n\n\n## How can I install Freva at my institution?\n\nDeployment is realised via a dedicated repository that holds code to set up\nthe command line and web user interface as well as all services.\nTo deploy the system in production\nmode consult [deployment docs](https://freva.gitlab-pages.dkrz.de/deployment/index.html).\n\n## How can I set up a local version for development?\n\nTo start development with freva clone the repository and its submodules:\n\n```\ngit clone --recursive https://github.com/freva-org/freva.git\n```\n\nA basic local development setup can be created using\n[Docker](https://docs.docker.com/engine/install/) and\n[`docker-compose`](https://docs.docker.com/compose/install/)\n(Linux users need to install it separately).\n\nThis also requires that the `.envrc` file is sourced.\n\n```\ndocker-compose up -d\n```\n\nDummy data can be injected into a running `docker-compose` environment with\n`make dummy-data`. This will add some example files into solr and run an\nexample plugin a few times to add some history data.\n\nWhen finished, tear down the environment with\n\n```\ndocker-compose down\n```\n\n### Creating a dedicated anaconda dev environment\nWe recommend using anaconda to install all packages that are needed for\ndevelopment. Here we assume that you have a\nworking anaconda version per-installed on your local computer. To install\nthe dev environment simply use the following command:\n\n```\nconda env create -f dev-environment.yml\nsource .envrc\n```\nThis will automatically set environment variables needed for development.\nThe freshly installed environment can be activated:\n```\nconda activate freva-dev\n```\nThe conda environment can be deactivated using the following command:\n```\nconda deactivate\n```\n_Note_: The conda install command can be slow. If you want to speed up the\ninstallation of the environment we recommend to install the `mamba` package in\nthe anaconda `base` environment and use the `mamba` command to create the\nenvironment:\n\n```\nconda install mamba\nmamba env create -f dev-environment.yml\nsource .envrc\n```\n\n### Installing the python package\n\nUse the `pip install` command to install the actual python core packages into\nyour activated environment:\n\n```bash\npip install -e .[test]\n```\n\nThe `-e` flag will link the source code into your python environment, which\ncan be useful for development purpose.\n\n### Running tests and creating a test coverage report\n\nThe system can be tested with a `Makefile`. To run the tests and generate a\nsimple test coverage report simply use the make command:\n\n```bash\nmake test\n```\n\nThe linter testing can be applied by:\n\n```bash\nmake lint\n```\n\n### Usage of pre-commit setup\n\nTo use the pre-commit setup in freva, follow these steps:\n\n1. **Install Pre-commit**:\n   - First, install the `pre-commit` package using pip:\n     ```bash\n     pip install pre-commit\n     ```\n\n2. **Activate Hooks**:\n   - Navigate to the root directory of your repository and run the following command to set up the git hooks:\n     ```bash\n     pre-commit install\n     ```\n\n3. **Automatic Checks**:\n   - Now, each time you attempt to commit changes, the pre-commit hooks will automatically run to ensure your files adhere to the specified standards.\n\n4. **Manual Execution**:\n   - If you want to manually run the hooks on all files, use:\n     ```bash\n     pre-commit run --all-files\n     ```\n","funding_links":[],"readme_doi_urls":[],"works":{},"citation_counts":{},"total_citations":0,"keywords_from_contributors":["earth-science","atmospheric-science","solr-server"],"project_url":"https://ost.ecosyste.ms/api/v1/projects/46096","html_url":"https://ost.ecosyste.ms/projects/46096"}