Project Aspen will glean information from open source-ecosystem data sets that can help drive community- and business-oriented decision making. Using data-analysis tools built by OSPO, as well as community metric tools from Project CHAOSS, Sandiego will enable contributors and participants to ask questions and make data-informed decisions about open source projects and communities.
We have a Matrix room for discussion of anything Sandiego-related. Come chat with us in #sandiego-rh:matrix.org!
Example of config.json file:
{
"connection_string": "sqlite:///:memory:",
"database": "sandiegorh",
"host": "chaoss.tv",
"password": "<<Your Password>>",
"port": 5432,
"schema": "augur_data",
"user": "<<Your Username>>",
"user_type": "read_only"
}
├── LICENSE
├── Makefile <- Makefile with commands like `make data` or `make train`
├── Pipfile <- Pipfile stating package configuration as used by Pipenv.
├── Pipfile.lock <- Pipfile.lock stating a pinned down software stack with as used by Pipenv.
├── 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 number (for ordering),
│ the creator's initials, and a short `-` delimited description, e.g.
│ `1.0-jqp-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 stating direct dependencies if a library
│ is developed.
│
├── 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
│
├── .thoth.yaml <- Thoth's configuration file
├── .aicoe-ci.yaml <- AICoE CI configuration file (https://github.com/AICoE/aicoe-ci)
└── tox.ini <- tox file with settings for running tox; see tox.readthedocs.io
Project based on the cookiecutter data science project template. #cookiecutterdatascience