Metadata-Version: 2.1
Name: traffic
Version: 2.6
Summary: A toolbox for manipulating and analysing air traffic data
Home-page: https://github.com/xoolive/traffic/
Author: Xavier Olive
Author-email: git@xoolive.org
License: MIT
Description: # A toolbox for processing and analysing air traffic data
        
        [![Documentation Status](https://github.com/xoolive/traffic/workflows/docs/badge.svg)](https://traffic-viz.github.io/)
        [![tests](https://github.com/xoolive/traffic/actions/workflows/run-tests.yml/badge.svg?branch=master&event=push)](https://github.com/xoolive/traffic/actions/workflows/run-tests.yml)
        [![Code Coverage](https://img.shields.io/codecov/c/github/xoolive/traffic.svg)](https://codecov.io/gh/xoolive/traffic)
        [![Codacy Badge](https://img.shields.io/codacy/grade/eea673ed15304f1b93490726295d6de0)](https://www.codacy.com/manual/xoolive/traffic)\
        [![Checked with mypy](https://img.shields.io/badge/mypy-checked-blue.svg)](https://mypy.readthedocs.io/)
        [![Code style: black](https://img.shields.io/badge/code%20style-black-black.svg)](https://github.com/psf/black)
        ![License](https://img.shields.io/pypi/l/traffic.svg)
        [![Join the chat at https://gitter.im/xoolive/traffic](https://badges.gitter.im/xoolive/traffic.svg)](https://gitter.im/xoolive/traffic?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\
        [![JOSS paper](http://joss.theoj.org/papers/10.21105/joss.01518/status.svg)](https://doi.org/10.21105/joss.01518)
        ![PyPI version](https://img.shields.io/pypi/v/traffic)
        [![PyPI downloads](https://img.shields.io/pypi/dm/traffic)](https://pypi.org/project/traffic)
        [![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/traffic-viz/traffic_static/blob/master/notebooks/quickstart.ipynb)
        
        The traffic library helps working with common sources of air traffic data.
        
        Its main purpose is to offer basic cumbersome data analysis methods commonly
        applied to trajectories and ATC sectors. When a specific function is not
        provided, the access to the underlying structure is direct, through an attribute
        pointing to a pandas dataframe.
        
        The library also offers facilities to parse and/or access traffic data from open
        sources of ADS-B traffic like the [OpenSky Network](https://opensky-network.org/)
        or Eurocontrol DDR files. It is designed to be easily extendable to other
        sources of data.
        
        Static visualisation (images) exports are accessible via Matplotlib/Cartopy.
        More dynamic visualisation frameworks are easily accessible in Jupyter
        environments with [ipyleaflet](http://ipyleaflet.readthedocs.io/) and
        [altair](http://altair-viz.github.io/); or through exports to other formats,
        including CesiumJS or Google Earth.
        
        ## Installation
        
        Latest release:
        
        ```sh
        pip install --upgrade traffic
        ```
        
        Development version:
        
        ```sh
        pip install git+https://github.com/xoolive/traffic
        ```
        
        **Warning:** `cartes` and `shapely` have strong dependencies to dynamic
        libraries which may not be available on your system by default.
        
        Before reporting an issue, please try to use an Anaconda environment. Other
        installations (You may check them in the `.travis.yml` configuration file.)
        should work but the Anaconda way proved to work smoothly.
        
        ```sh
        conda install cartopy shapely
        ```
        
        For troubleshootings, refer to the appropriate
        [documentation section](https://traffic-viz.github.io/installation.html#troubleshooting).
        
        ## Credits
        
        [![JOSS badge](http://joss.theoj.org/papers/10.21105/joss.01518/status.svg)](https://doi.org/10.21105/joss.01518)
        
        If you find this project useful for your research and use it in an academic
        work, you may cite it as:
        
        ```bibtex
        @article{olive2019traffic,
            author={Xavier {Olive}},
            journal={Journal of Open Source Software},
            title={traffic, a toolbox for processing and analysing air traffic data},
            year={2019},
            volume={4},
            pages={1518},
            doi={10.21105/joss.01518},
            issn={2475-9066},
        }
        ```
        
        Additionally, you may consider adding a star to the repository. This token of appreciation is often interpreted as a positive feedback and improves the visibility of the library.
        
        ## Documentation
        
        [![Documentation Status](https://github.com/xoolive/traffic/workflows/docs/badge.svg)](https://traffic-viz.github.io/)
        [![Join the chat at https://gitter.im/xoolive/traffic](https://badges.gitter.im/xoolive/traffic.svg)](https://gitter.im/xoolive/traffic?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
        
        Documentation available at [https://traffic-viz.github.io/](https://traffic-viz.github.io/)\
        Join the Gitter chat: https://gitter.im/xoolive/traffic
        
        ## Tests and code quality
        
        [![tests](https://github.com/xoolive/traffic/actions/workflows/run-tests.yml/badge.svg?branch=master&event=push)](https://github.com/xoolive/traffic/actions/workflows/run-tests.yml)
        [![Code Coverage](https://img.shields.io/codecov/c/github/xoolive/traffic.svg)](https://codecov.io/gh/xoolive/traffic)
        [![Codacy Badge](https://img.shields.io/codacy/grade/eea673ed15304f1b93490726295d6de0)](https://www.codacy.com/manual/xoolive/traffic)
        [![Checked with mypy](https://img.shields.io/badge/mypy-checked-blue.svg)](https://mypy.readthedocs.io/)
        
        Unit and non-regression tests are written in the `tests/` directory. You may
        run `pytest` from the root directory.
        
        Tests are checked on [Github Actions](https://github.com/xoolive/traffic/actions/workflows/run-tests.yml)
        platform upon each commit. Latest status and coverage are displayed with
        standard badges hereabove.
        
        In addition, code is checked against static typing with [mypy](https://mypy.readthedocs.io/)
        ([pre-commit](https://pre-commit.com/) hooks are available in the repository) and
        extra quality checks performed by [Codacy](https://www.codacy.com/manual/xoolive/traffic).
        
        ## Command line tool
        
        The `traffic` tool scripts around the library for common usecases.
        
        The most basic use case revolves around exploring the embedded data. You may check
        the help with `traffic data -h`.
        
        ```
        traffic data -p Tokyo
             altitude country iata  icao   latitude   longitude                                name
        3820       21   Japan  HND  RJTT  35.552250  139.779602  Tokyo Haneda International Airport
        3821      135   Japan  NRT  RJAA  35.764721  140.386307  Tokyo Narita International Airport
        ```
        
        More details in the [documentation](https://traffic-viz.github.io/).
        
        ## Feedback and contribution
        
        Any input, feedback, bug report or contribution is welcome.
        
        Should you encounter any issue, you may want to file it in the [issue](https://github.com/xoolive/traffic/issues/new) section of this repository. Please first activate the `DEBUG` messages recorded using Python logging mechanism with the following snippet:
        
        ```python
        import logging
        logging.basicConfig(level=logging.DEBUG)
        ```
        
        Bug fixes and improvements in the library are also helpful.
        
        If you share a fix together with the issue, I can include it in the code for
        you. But since you did the job, pull requests (PR) let you keep the authorship
        on your additions. For details on creating a PR see GitHub documentation
        [Creating a pull
        request](https://help.github.com/en/articles/creating-a-pull-request). You can
        add more details about your example in the PR such as motivation for the example
        or why you thought it would be a good addition. You will get feedback in the PR
        discussion if anything needs to be changed. To make changes continue to push
        commits made in your local example branch to origin and they will be
        automatically shown in the PR.
        
        You may find the process troublesome but please keep in mind it is actually
        easier that way to keep track of corrections and to remember why things are the
        way they are.
        
        ## Frequently asked questions
        
        [![Join the chat at https://gitter.im/xoolive/traffic](https://badges.gitter.im/xoolive/traffic.svg)](https://gitter.im/xoolive/traffic?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)
        
        - I want to know more about Eurocontrol NM files
        
        We download these files from Eurocontrol [Network Manager Demand Data
        Repository (DDR)](https://www.eurocontrol.int/ddr) under Dataset Files >
        Airspace Environment Datasets. [Access
        conditions](https://www.eurocontrol.int/ddr#access-conditions) are managed by
        EUROCONTROL.
        
        Should you have no such access, basic FIRs are provided in `eurofirs` from
        `traffic.data`.
        
        - I want to know more about Eurocontrol AIXM files
        
        When you import `aixm_airspaces` from `traffic.data`, you need to set a path
        to a directory containing AIRAC files. These are XML files following the
        [AIXM](http://aixm.aero/) standard and produced by Eurocontrol. We download
        these files from Eurocontrol [Network Manager B2B web
        services](https://eurocontrol.int/service/network-manager-business-business-b2b-web-services).
        You have to own a B2B certificate granted by EUROCONTROL to get access to
        this data.
        
        - What does AIRAC mean?
        
        Aeronautical Information Publications are updated every 28 days according to
        fixed calendar. This cycle is known as AIRAC (Aeronautical Information
        Regulation And Control) cycle.
        
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: GIS
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Software Development :: Libraries
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Typing :: Typed
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: dev
