{"id":42503764,"url":"https://github.com/dataforgoodfr/energetic-stress-production","last_synced_at":"2026-01-28T13:37:27.008Z","repository":{"id":234992356,"uuid":"783655846","full_name":"dataforgoodfr/energetic-stress-production","owner":"dataforgoodfr","description":"Forecast the Energy production in France","archived":false,"fork":false,"pushed_at":"2024-11-05T17:24:12.000Z","size":103135,"stargazers_count":1,"open_issues_count":8,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-11-05T18:31:47.784Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://greenforecast-squad.github.io/energetic-stress-production/","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dataforgoodfr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-08T10:11:46.000Z","updated_at":"2024-10-21T13:34:27.000Z","dependencies_parsed_at":"2024-11-05T18:45:04.867Z","dependency_job_id":null,"html_url":"https://github.com/dataforgoodfr/energetic-stress-production","commit_stats":null,"previous_names":["greenforecast-squad/energetic-stress-production","dataforgoodfr/energetic-stress-production"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/dataforgoodfr/energetic-stress-production","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dataforgoodfr%2Fenergetic-stress-production","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dataforgoodfr%2Fenergetic-stress-production/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dataforgoodfr%2Fenergetic-stress-production/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dataforgoodfr%2Fenergetic-stress-production/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dataforgoodfr","download_url":"https://codeload.github.com/dataforgoodfr/energetic-stress-production/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dataforgoodfr%2Fenergetic-stress-production/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28846053,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-28T13:02:32.985Z","status":"ssl_error","status_checked_at":"2026-01-28T13:02:04.945Z","response_time":57,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-01-28T13:37:26.371Z","updated_at":"2026-01-28T13:37:27.001Z","avatar_url":"https://github.com/dataforgoodfr.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Forecast of French electric mix\n\nThe aim of this project is to forecast the French electric mix for the next few days.\n\nThe electric mix is the relative proportion of each energy source used to produce electricity. The main energy sources are: nuclear, wind, solar, hydraulic, coal, gas, bioenergy and waste.\n\nThe Wind and solar energy sources are green, but they are intermittent and depend on the weather. The hydraulic energy source is also dependent on the weather, but to a lesser extent.\n\nHence, the weather directly impacts the CO2 emissions of the electry consumption.\nKnowing the CO2 emission forecast can help plan the time of use of electric devices to reduce the carbon footprint.\n\n## Description of the project\n\nThe project is divided into 2 parts:\n1. Analysis of the historical data\n2. Forecast of the electric mix\n\n### 1. Analysis of the historical data\nWe gathered the data from the French electricity transmission system operator RTE (Réseau de Transport d'Electricité) and the French meteorological service Météo France.\nThe data start in 2022 and end in 2024.\n\nWe used the data to:\n- train a model to predict the electric mix\n- assess the performance of the model\n- identify the main factors influencing the electric mix\n\n### 2. Forecast of the electric mix\nWe will use the model trained in the first part to forecast the electric mix for the next few days.\n\nThe forecast is updated every day.\n\nA website will be created to display the forecast.\n\n## Installation\n\nWe use [hatch](https://hatch.pypa.io) to manage the project.\n\nThere is [a bug](https://github.com/ecmwf/eccodes-python/issues/88) in the current version of `eccodes`, failing the installation.\nInstalling with `conda` first solved the issue for me.\n\nRun the following commands to check if `eccodes` is installed:\n```bash\npython -m eccodes selfcheck\n```\n\n### Interactive mode\n\nYou can use Hatch to activate the virtual environment and install the dependencies with:\n```bash\nhatch shell\n```\nThis will open a shell with the virtual environment activated.\nThe dependencies listed in the `pyproject.toml` file will be installed automatically.\n\n### Run the tests\nYou can run the tests with:\n```bash\nhatch test\n```\nThis will run the tests in the virtual environment.\n\n### Serve the Dashboard\n\nYou can serve the dashboard with:\n```bash\nhatch serve:prod\n```\nThis will serve the dashboard on `http://localhost:8000`.\n\n## The dashboard\nThe dashoard is developed with [Taipy](https://docs.taipy.io/en/latest/).\nLauchind the app will automaticaly\n- Download the weather forecast\n- Download the electricity mix history\n- Display the forecast","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdataforgoodfr%2Fenergetic-stress-production","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdataforgoodfr%2Fenergetic-stress-production","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdataforgoodfr%2Fenergetic-stress-production/lists"}