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        "author": "Maxime Mouchet",
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        "description": "# atlas_df: a dataframe-oriented interface to RIPE Atlas\n\n[![Python Version](https://img.shields.io/badge/python-3-blue.svg?style=flat)](#)\n[![License](https://img.shields.io/badge/license-MIT-blue.svg?style=flat)](https://github.com/maxmouchet/atlas_df/blob/master/LICENSE)\n[![Build Status](https://travis-ci.org/maxmouchet/atlas_df.svg?branch=master)](https://travis-ci.org/maxmouchet/atlas_df)\n[![Documentation Status](https://readthedocs.org/projects/atlas_df/badge/?version=latest)](https://atlas-df.readthedocs.io/en/latest/)\n[![Coverage Status](https://coveralls.io/repos/github/maxmouchet/atlas_df/badge.svg?branch=master)](https://coveralls.io/github/maxmouchet/atlas_df?branch=master)\n\n[![Example Map](https://github.com/maxmouchet/atlas_df/blob/master/examples/1001_map.png)](#)\n\natlas_df is an interface to the RIPE Atlas API built on top of the official client ([ripe-atlas-cousteau](https://github.com/RIPE-NCC/ripe-atlas-cousteau)). It converts Atlas resources to [pandas](https://github.com/pandas-dev/pandas) and [geopandas](https://github.com/geopandas/geopandas) DataFrames/Series. This makes the use of the Python scientific ecosystem (matplotlib, seaborn, numpy, scikit-learn, ...) with Atlas data very easy.\n\n**Features:**\n- Conversion of RIPE Atlas resources to `DataFrame` and `Series` objects.\n- [Caching](#cache) of API requests.\n- geo plot/queries ...\nTODO: logging, computation of geo distance between anchors/probes, ...\n\n## Table of Contents\n\n- [Install](#install)\n- [Usage](#usage)\n- [Development](#development)\n- [Maintainers](#maintainers)\n- [Contribute](#contribute)\n- [License](#license)\n\n## Install\n\natlas_df is a Python 3 library, depending on your setup, you may want to use `pip` or `pip3`.\n\n```bash\npip install atlas_df\n```\n\n## Usage\n\nA comprehensive (TODO) documentation is on [Read the Docs](https://atlas-df.readthedocs.io/en/latest/).\n\n```python\nfrom atlas_df.dataframes import AnchorDataFrame\n\nanchors = AnchorDataFrame.from_api()\nmeasurements = anchors.loc[1029].fetch_mesh_measurements()\n```\n\n\n### Anchoring\n\n```python\nimport datetime as dt\nfrom atlas_df.anchoring import AnchoringMesh\n\nanchoring_mesh = AnchoringMesh()\n\nanchor_fqdn_a = 'al-tia-as42409.anchors.atlas.ripe.net'\nanchor_fqdn_b = 'nc-nou-as56055.anchors.atlas.ripe.net'\nstart_datetime = dt.datetime(2018, 5, 1)\nstop_datetime  = dt.datetime(2018, 5, 7)\naf = 4\n\ntraceroute_ab, traceroute_ba = anchoring_mesh.fetch_results(anchor_fqdn_a, anchor_fqdn_b, af, 'traceroute', {'start': START_DATETIME, 'stop': STOP_DATETIME})\n```\n\n### Cache\n\n```python\nimport atlas_df\natlas_df.CACHE_DIR = '.atlas_df'\natlas_df.CACHE_ENABLED = True\n```\n\n## Development\n\n```bash\ngit clone https://github.com/maxmouchet/atlas_df.git\ncd atlas_df\npip install -e .\n```\n\nCode is formatted using [yapf](https://github.com/google/yapf).\n\n### Building documentation\n\n```bash\npip install sphinx sphinx-rtd-theme\nsphinx-apidoc -f -o docs/source/ atlas_df\ncd docs; make html\n```\n\n### Running tests\n\n```bash\npip install -U pytest pytest-cov\npy.test --cov=atlas_df tests/\n```\n\n## Maintainers\n\n[@maxmouchet](https://github.com/maxmouchet)\n\n## Contribute\n\nPRs accepted.\n\n## License\n\nMIT \u00a9 2018 Maxime Mouchet",
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