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https://github.com/os-climate/epa_frs-ingest-pipeline
https://github.com/os-climate/epa_frs-ingest-pipeline
Last synced: 7 days ago
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- Host: GitHub
- URL: https://github.com/os-climate/epa_frs-ingest-pipeline
- Owner: os-climate
- License: apache-2.0
- Created: 2021-11-21T14:43:21.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2024-10-28T20:05:13.000Z (17 days ago)
- Last Synced: 2024-10-28T21:19:55.632Z (16 days ago)
- Language: Jupyter Notebook
- Homepage:
- Size: 912 KB
- Stars: 0
- Watchers: 2
- Forks: 3
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS
Awesome Lists containing this project
README
# EPA_FRS-ingest-pipeline
template for the team to use
## Project Organization
├── 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)
│
├── .github <- GitHub configuration folder
│ ├── PULL_REQUEST_TEMPLATE <- GitHub templates for pull requests
│ │
│ ├── ISSUE_TEMPLATE <- GitHub templates for issues
| ├── {major|minor|patch}_release.md <- If Khebut GitHub App Bot (https://github.com/apps/khebhut) is installed, the issue will trigger a major|minor|patch release.
│ | The bot will open a Pull Request to update the CHANGELOG and fix the opened issue.
│ | NOTE: only users that are allowed to release (a.k.a. maintainers specified in the .thoth.yaml file) should open the issue, otherwise bot will
│ | reject them, commenting and closing the issue.
│ | If AICoE CI GitHub App (https://github.com/apps/aicoe-ci) is installed, once the pull request is merged a new tag is created by the bot
│ | and the pipeline to build and push image starts.
│ |
| └── redeliver_container_image.md <- If the tag exists and AICoE CI GitHub App (https://github.com/apps/aicoe-ci) is installed, the issue will retrigger the pipeline to build and
│ push image container image. NOTE: It should be used if the pipeline triggered with the {major|minor|patch}_release failed for any reason.
|
└── tox.ini <- tox file with settings for running tox; see tox.readthedocs.io---
Project based on the [cookiecutter](https://drivendata.github.io/cookiecutter-data-science/) data science project template