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waze-tools

Common python tools to deal with waze data

Start Coding

There is a ready workspace at a server with all libraries needed to work with geodata in python. To connect just

go to 200.20.164.155:8080 in you browser

the password has to be asked to @joaocarabetta.

Otherwise, you can run it locally with docker with two steps:

sudo docker build -t wazetools .
sudo docker run -d     
            -p 8888:8080     
            -v $projdir:/home/jovyan/work     
            --user root     
            -e GRANT_SUDO=yes     
            wazetools:latest

and connect to it at

localhost:8080

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── 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               <- A default Sphinx project; see sphinx-doc.org for details
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. Naming convention is a 
│                         tag describing its use, accepted tags: [dev], [example], [analysis];
│                         number (for ordering) if needed;
│                         the creator's name, not needed for examples;  
│                         short `-` delimited description.
│                         `[analysis] c1.0-joaoc-initial-data-exploration`.
│
├── references         <- Data dictionaries, manuals, and all other explanatory materials.
│
├── reports            <- Generated analysis as HTML, PDF, LaTeX, etc.
│   └── figures        <- Generated graphics and figures to be used in reporting
│
├── requirements.txt   <- The requirements file for reproducing the analysis environment, e.g.
│                         generated with `pip freeze > requirements.txt`
│
├── setup.py           <- makes project pip installable (pip install -e .) so src can be imported
├── src                <- Source code for use in this project.
│   ├── __init__.py    <- Makes src a Python module
│   │
│   ├── data           <- Scripts to download or generate data
│   │   └── make_dataset.py
│   │
│   ├── features       <- Scripts to turn raw data into features for modeling
│   │   └── build_features.py
│   │
│   ├── models         <- Scripts to train models and then use trained models to make
│   │   │                 predictions
│   │   ├── predict_model.py
│   │   └── train_model.py
│   │
│   └── visualization  <- Scripts to create exploratory and results oriented visualizations
│       └── visualize.py
│
├── tox.ini            <- tox file with settings for running tox; see tox.testrun.org
|
└── Dockerfile         <- Builds geoprocessing enviorinment

Project based on the cookiecutter data science project template. #cookiecutterdatascience

Acknowledgements

Repo based on previou work of @JoaoCarabetta

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