PyPI 官网下载 | indice_pollution-0.15.4.tar.gz

# Indice pollution This package give you access to air pollution level in France. You can instantiate a small website with a search bar, to search the air pollution level for a specific city, or you can use it as a lib. ## Website Make a new virtual environment, and install the package with ``` pip install indice_pollution ``` And then run flask ``` flask run ``` Access it at `http://localhost:5000` ## As a lib Make a new virtual environment, and install the package with ``` pip install indice_pollution ``` And then you can use it with ``` from indice_pollution import forecast forecast(75101) ``` ## Usage ### Forecast #### Request `GET` `/forecast?insee=${insee}` #### Response ```json { "data": [ { "date":"2020-08-10", "date_ech":1597017600000, "indice":7, "qualif":"M\u00e9diocre", "val_no2":0, "val_o3":0, "val_pm10":0, "val_pm25":0, "val_so2":0, "valeur":7 } ], "metadata": { "region": { "website": "http://www.atmonormandie.fr/", "nom": "Normandie", } } } ``` ##### data The array may contains several objects. Typically, one for the current day and potentially one forecast object for one or a couple of next days. - `date` is the date for the forecast provided in `YYYY-MM-DD` format - `indice` is the general "indice ATMO" as standardized by l'État Français (`1` is good air quality, `10` is terrible air quality) - (optional) `date_ech` is ? - (optional) `val_<pollutant>` are each the "indice AMTO" for each pollutant as standardized by l'État Français (`0` is a mistake value) - (optional) `qualif` is a word qualifying the general "indice ATMO" as standardized by l'État Français. One of `Très bon`, `Bon`, `Moyen`, `Médiocre`, `Mauvais`, - (optional) `valeur`. Same thing than `indice` ##### metadata Currently, it only has a `region` property. This property is an object with: - `nom` France Région name - `website` corresponding AASQUA website ## Test A test instanced is deployed at https://app-ed2e0e03-0bd3-4eb4-8326-000288aeb6a0.cleverapps.io/ Query example: https://app-ed2e0e03-0bd3-4eb4-8326-000288aeb6a0.cleverapps.io/forecast?insee=76717