{ "info": { "author": "Dennis Terhorst", "author_email": "d.terhorst@fz-juelich.de", "bugtrack_url": null, "classifiers": [ "Development Status :: 2 - Pre-Alpha", "Intended Audience :: Science/Research", "License :: OSI Approved :: BSD License", "Natural Language :: English", "Operating System :: OS Independent", "Programming Language :: Python :: 2", "Programming Language :: Python :: 3", "Topic :: Scientific/Engineering" ], "description": "# Reporter\n\n This tool helps in gathering and formatting of data into a report. The tool\n `reporter.py` basically combines YAML data files with Jinja2-based\n templates. In this way simple markup versions of your report can be\n produced. Together with a format converter like [Pandoc](http://pandoc.org)\n the produced output can then be converted to various target formats (HTML,\n PDF, ...).\n\n To keep a good overview which data is acquired for different parts of the\n report, it is probably a good step to automate the whole workflow with a\n tool like [snakemake](https://snakemake.readthedocs.io/en/stable/) or other\n make-like tools.\n\n\n# Install\n\n The fastest way to install datareport is to use your systems tools:\n\n pip install datareport\n\n To use the latest test version check out the test.pypi server:\n\n pip install --index-url https://test.pypi.org/simple datareport\n\n\n## Requirements\n\n All required packages are listed in `environment.yaml`. In case you\n installed datareport via a package management system like pip, anaconda,\n miniconda, ... all dependencies should already be installed automatically.\n\n\n# Getting Started\n\n For easing your first steps with datareport a small set of [documented\n examples](examples/README.md) can be found in the `examples/` folder. The\n README file gives an overview and you can find the right place to start.\n\n\n## Further reading\n\n For designing reports you need to know about the templating language and\n since you will want to use some automation for the reporting process, also a\n make-like tool is very helpful. Look at the excellent `snakemake` for that!\n\n * [Jinja2](http://jinja.pocoo.org/docs/2.10/) (\u2192 [templating\n language](http://jinja.pocoo.org/docs/2.10/templates/))\n\n * [Snakemake](https://pypi.org/project/snakemake/) (\u2192 [writing\n rules](https://snakemake.readthedocs.io/en/stable/snakefiles/rules.html))\n\n As data inputs you can use different formats. For understanding the details\n about each format you find a lot of information on the web, especially:\n\n * YAML (\u2192 [specification](http://yaml.org/spec/)) and the\n [ruamel.yaml](https://yaml.readthedocs.io/en/latest/basicuse.html)\n package.\n * JSON (\u2192 [specification](https://json.org/))\n\n\n# Developing datareport\n\n Contributions are very welcome! Write issues for feature requests or\n directly file a pull-request with your contribution and/or contact me\n directly!\n\n\n## Tests\n\n This project uses the [PyTest framework](https://docs.pytest.org/en/latest/)\n with tests defined in the [tests/](tests/) sudirectory. It is added into the\n setuptools config, so that it can be run with\n\n python setup.py test\n\n This automatically tests a temporarily packaged version.\n\n Alternatively you can run `pytest` manually with all it [glory\n details](https://docs.pytest.org/en/latest/usage.html).\n\n\n## Releases\n\n The release workflow is mostly automated and is in the [release/](release/)\n folder.", "description_content_type": "", "docs_url": null, "download_url": "", "downloads": { "last_day": -1, "last_month": -1, "last_week": -1 }, "home_page": "https://github.com/INM-6/datareport", "keywords": "", "license": "BSD", "maintainer": "", "maintainer_email": "", "name": "datareport", "package_url": "https://pypi.org/project/datareport/", "platform": "", "project_url": "https://pypi.org/project/datareport/", "project_urls": { "Homepage": "https://github.com/INM-6/datareport" }, "release_url": "https://pypi.org/project/datareport/0.1.7/", "requires_dist": null, "requires_python": "", "summary": "Tool to 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