%global _empty_manifest_terminate_build 0 Name: python-pyairnow Version: 1.2.1 Release: 1 Summary: A lightweight Python wrapper for EPA AirNow Air Quality API License: MIT URL: https://github.com/asymworks/pyairnow Source0: https://mirrors.nju.edu.cn/pypi/web/packages/92/02/9f81110037dafaf7e3e8e421580516a49d8e7288b386deb271ec5de3d1bb/pyairnow-1.2.1.tar.gz BuildArch: noarch Requires: python3-aiohttp %description # pyairnow: a thin Python wrapper for the AirNow API [![CI](https://github.com/asymworks/pyairnow/workflows/CI/badge.svg)](https://github.com/asymworks/pyairnow/actions) [![PyPi](https://img.shields.io/pypi/v/pyairnow.svg)](https://pypi.python.org/pypi/pyairnow) [![Version](https://img.shields.io/pypi/pyversions/pyairnow.svg)](https://pypi.python.org/pypi/pyairnow) [![License](https://img.shields.io/pypi/l/pyairnow.svg)](https://github.com/asymworks/pyairnow/blob/master/LICENSE) [![Code Coverage](https://codecov.io/gh/asymworks/pyairnow/branch/master/graph/badge.svg)](https://codecov.io/gh/asymworks/pyairnow) `pyairnow` is a simple, tested, thin client library for interacting with the [AirNow](https://www.airnow.gov) United States EPA Air Quality Index API. - [Python Versions](#python-versions) - [Installation](#installation) - [API Key](#api-key) - [Usage](#usage) - [Contributing](#contributing) # Python Versions `pyairnow` is currently supported and tested on: * Python 3.8 * Python 3.9 * Python 3.10 * Python 3.11 # Installation ```python pip install pyairnow ``` # API Key You can get an AirNow API key from [the AirNow API site](https://docs.airnowapi.org/account/request/). Ensure you read and understand the expectations and limitations of API usage, which can be found at [the AirNow FAQ](https://docs.airnowapi.org/faq). # Usage ```python import asyncio import datetime from pyairnow import WebServiceAPI async def main() -> None: client = WebServiceAPI('your-api-key') # Get current observational data based on a zip code data = await client.observations.zipCode( '90001', # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) # Get current observational data based on a latitude and longitude data = await client.observations.latLong( 34.053718, -118.244842, # if there are no observation stations at this location, optionally # provide a radius to search (in miles) distance=50, ) # Get forecast data based on a zip code data = await client.forecast.zipCode( '90001', # to get a forecast for a certain day, provide a date in yyyy-mm-dd, # if not specified the current day will be used date='2020-09-01', # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) # Get forecast data based on a latitude and longitude data = await client.forecast.latLong( # Lat/Long may be strings or floats '34.053718', '-118.244842', # forecast dates may also be datetime.date or datetime.datetime objects date=datetime.date(2020, 9, 1), # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) asyncio.run(main()) ``` By default, the library creates a new connection to AirNow with each coroutine. If you are calling a large number of coroutines (or merely want to squeeze out every second of runtime savings possible), an [`aiohttp`](https://github.com/aio-libs/aiohttp) `ClientSession` can be used for connection pooling: ```python import asyncio import datetime from aiohttp import ClientSession from pyairnow import WebServiceAPI async def main() -> None: async with ClientSession() as session: client = WebServiceAPI('your-api-key', session=session) # ... asyncio.run(main()) ``` The library provides two convenience functions to convert between AQI and pollutant concentrations. See [this EPA document](https://www.airnow.gov/sites/default/files/2020-05/aqi-technical-assistance-document-sept2018.pdf) for more details. ```python from pyairnow.conv import aqi_to_concentration, concentration_to_aqi # Supported Pollutants # -------------------- # Ozone ('O3'): ppm # pm2.5 ('PM2.5'): ug/m^3 # pm10 ('PM10'): ug/m^3 # Carbon Monoxide ('CO'): ppm # Sulfur Dioxide ('SO2'): ppm # Nitrogen Dioxide ('NO2'): ppm # Returns AQI = 144 for pm2.5 of 53.0 ug/m^3 aqi_to_concentration(144, 'PM2.5') # Returns Cp = 53.0 ug/m^3 concentration_to_aqi(53.0, 'PM2.5') ``` # Contributing 1. [Check for open features/bugs](https://github.com/asymworks/pyairnow/issues) or [start a discussion on one](https://github.com/asymworks/pyairnow/issues/new). 2. [Fork the repository](https://github.com/asymworks/pyairnow/fork). 3. Install [Poetry](https://python-poetry.org/) and set up the development workspace: `poetry install` 4. Code your new feature or bug fix. 5. Write tests that cover your new functionality. 6. Run tests and ensure 100% code coverage: `make test` 7. Run the linter to ensure 100% code style correctness: `make lint` 8. Update `README.md` with any new documentation. 9. Add yourself to `AUTHORS.md`. 10. Submit a pull request! %package -n python3-pyairnow Summary: A lightweight Python wrapper for EPA AirNow Air Quality API Provides: python-pyairnow BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-pyairnow # pyairnow: a thin Python wrapper for the AirNow API [![CI](https://github.com/asymworks/pyairnow/workflows/CI/badge.svg)](https://github.com/asymworks/pyairnow/actions) [![PyPi](https://img.shields.io/pypi/v/pyairnow.svg)](https://pypi.python.org/pypi/pyairnow) [![Version](https://img.shields.io/pypi/pyversions/pyairnow.svg)](https://pypi.python.org/pypi/pyairnow) [![License](https://img.shields.io/pypi/l/pyairnow.svg)](https://github.com/asymworks/pyairnow/blob/master/LICENSE) [![Code Coverage](https://codecov.io/gh/asymworks/pyairnow/branch/master/graph/badge.svg)](https://codecov.io/gh/asymworks/pyairnow) `pyairnow` is a simple, tested, thin client library for interacting with the [AirNow](https://www.airnow.gov) United States EPA Air Quality Index API. - [Python Versions](#python-versions) - [Installation](#installation) - [API Key](#api-key) - [Usage](#usage) - [Contributing](#contributing) # Python Versions `pyairnow` is currently supported and tested on: * Python 3.8 * Python 3.9 * Python 3.10 * Python 3.11 # Installation ```python pip install pyairnow ``` # API Key You can get an AirNow API key from [the AirNow API site](https://docs.airnowapi.org/account/request/). Ensure you read and understand the expectations and limitations of API usage, which can be found at [the AirNow FAQ](https://docs.airnowapi.org/faq). # Usage ```python import asyncio import datetime from pyairnow import WebServiceAPI async def main() -> None: client = WebServiceAPI('your-api-key') # Get current observational data based on a zip code data = await client.observations.zipCode( '90001', # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) # Get current observational data based on a latitude and longitude data = await client.observations.latLong( 34.053718, -118.244842, # if there are no observation stations at this location, optionally # provide a radius to search (in miles) distance=50, ) # Get forecast data based on a zip code data = await client.forecast.zipCode( '90001', # to get a forecast for a certain day, provide a date in yyyy-mm-dd, # if not specified the current day will be used date='2020-09-01', # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) # Get forecast data based on a latitude and longitude data = await client.forecast.latLong( # Lat/Long may be strings or floats '34.053718', '-118.244842', # forecast dates may also be datetime.date or datetime.datetime objects date=datetime.date(2020, 9, 1), # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) asyncio.run(main()) ``` By default, the library creates a new connection to AirNow with each coroutine. If you are calling a large number of coroutines (or merely want to squeeze out every second of runtime savings possible), an [`aiohttp`](https://github.com/aio-libs/aiohttp) `ClientSession` can be used for connection pooling: ```python import asyncio import datetime from aiohttp import ClientSession from pyairnow import WebServiceAPI async def main() -> None: async with ClientSession() as session: client = WebServiceAPI('your-api-key', session=session) # ... asyncio.run(main()) ``` The library provides two convenience functions to convert between AQI and pollutant concentrations. See [this EPA document](https://www.airnow.gov/sites/default/files/2020-05/aqi-technical-assistance-document-sept2018.pdf) for more details. ```python from pyairnow.conv import aqi_to_concentration, concentration_to_aqi # Supported Pollutants # -------------------- # Ozone ('O3'): ppm # pm2.5 ('PM2.5'): ug/m^3 # pm10 ('PM10'): ug/m^3 # Carbon Monoxide ('CO'): ppm # Sulfur Dioxide ('SO2'): ppm # Nitrogen Dioxide ('NO2'): ppm # Returns AQI = 144 for pm2.5 of 53.0 ug/m^3 aqi_to_concentration(144, 'PM2.5') # Returns Cp = 53.0 ug/m^3 concentration_to_aqi(53.0, 'PM2.5') ``` # Contributing 1. [Check for open features/bugs](https://github.com/asymworks/pyairnow/issues) or [start a discussion on one](https://github.com/asymworks/pyairnow/issues/new). 2. [Fork the repository](https://github.com/asymworks/pyairnow/fork). 3. Install [Poetry](https://python-poetry.org/) and set up the development workspace: `poetry install` 4. Code your new feature or bug fix. 5. Write tests that cover your new functionality. 6. Run tests and ensure 100% code coverage: `make test` 7. Run the linter to ensure 100% code style correctness: `make lint` 8. Update `README.md` with any new documentation. 9. Add yourself to `AUTHORS.md`. 10. Submit a pull request! %package help Summary: Development documents and examples for pyairnow Provides: python3-pyairnow-doc %description help # pyairnow: a thin Python wrapper for the AirNow API [![CI](https://github.com/asymworks/pyairnow/workflows/CI/badge.svg)](https://github.com/asymworks/pyairnow/actions) [![PyPi](https://img.shields.io/pypi/v/pyairnow.svg)](https://pypi.python.org/pypi/pyairnow) [![Version](https://img.shields.io/pypi/pyversions/pyairnow.svg)](https://pypi.python.org/pypi/pyairnow) [![License](https://img.shields.io/pypi/l/pyairnow.svg)](https://github.com/asymworks/pyairnow/blob/master/LICENSE) [![Code Coverage](https://codecov.io/gh/asymworks/pyairnow/branch/master/graph/badge.svg)](https://codecov.io/gh/asymworks/pyairnow) `pyairnow` is a simple, tested, thin client library for interacting with the [AirNow](https://www.airnow.gov) United States EPA Air Quality Index API. - [Python Versions](#python-versions) - [Installation](#installation) - [API Key](#api-key) - [Usage](#usage) - [Contributing](#contributing) # Python Versions `pyairnow` is currently supported and tested on: * Python 3.8 * Python 3.9 * Python 3.10 * Python 3.11 # Installation ```python pip install pyairnow ``` # API Key You can get an AirNow API key from [the AirNow API site](https://docs.airnowapi.org/account/request/). Ensure you read and understand the expectations and limitations of API usage, which can be found at [the AirNow FAQ](https://docs.airnowapi.org/faq). # Usage ```python import asyncio import datetime from pyairnow import WebServiceAPI async def main() -> None: client = WebServiceAPI('your-api-key') # Get current observational data based on a zip code data = await client.observations.zipCode( '90001', # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) # Get current observational data based on a latitude and longitude data = await client.observations.latLong( 34.053718, -118.244842, # if there are no observation stations at this location, optionally # provide a radius to search (in miles) distance=50, ) # Get forecast data based on a zip code data = await client.forecast.zipCode( '90001', # to get a forecast for a certain day, provide a date in yyyy-mm-dd, # if not specified the current day will be used date='2020-09-01', # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) # Get forecast data based on a latitude and longitude data = await client.forecast.latLong( # Lat/Long may be strings or floats '34.053718', '-118.244842', # forecast dates may also be datetime.date or datetime.datetime objects date=datetime.date(2020, 9, 1), # if there are no observation stations in this zip code, optionally # provide a radius to search (in miles) distance=50, ) asyncio.run(main()) ``` By default, the library creates a new connection to AirNow with each coroutine. If you are calling a large number of coroutines (or merely want to squeeze out every second of runtime savings possible), an [`aiohttp`](https://github.com/aio-libs/aiohttp) `ClientSession` can be used for connection pooling: ```python import asyncio import datetime from aiohttp import ClientSession from pyairnow import WebServiceAPI async def main() -> None: async with ClientSession() as session: client = WebServiceAPI('your-api-key', session=session) # ... asyncio.run(main()) ``` The library provides two convenience functions to convert between AQI and pollutant concentrations. See [this EPA document](https://www.airnow.gov/sites/default/files/2020-05/aqi-technical-assistance-document-sept2018.pdf) for more details. ```python from pyairnow.conv import aqi_to_concentration, concentration_to_aqi # Supported Pollutants # -------------------- # Ozone ('O3'): ppm # pm2.5 ('PM2.5'): ug/m^3 # pm10 ('PM10'): ug/m^3 # Carbon Monoxide ('CO'): ppm # Sulfur Dioxide ('SO2'): ppm # Nitrogen Dioxide ('NO2'): ppm # Returns AQI = 144 for pm2.5 of 53.0 ug/m^3 aqi_to_concentration(144, 'PM2.5') # Returns Cp = 53.0 ug/m^3 concentration_to_aqi(53.0, 'PM2.5') ``` # Contributing 1. [Check for open features/bugs](https://github.com/asymworks/pyairnow/issues) or [start a discussion on one](https://github.com/asymworks/pyairnow/issues/new). 2. [Fork the repository](https://github.com/asymworks/pyairnow/fork). 3. Install [Poetry](https://python-poetry.org/) and set up the development workspace: `poetry install` 4. Code your new feature or bug fix. 5. Write tests that cover your new functionality. 6. Run tests and ensure 100% code coverage: `make test` 7. Run the linter to ensure 100% code style correctness: `make lint` 8. Update `README.md` with any new documentation. 9. Add yourself to `AUTHORS.md`. 10. Submit a pull request! %prep %autosetup -n pyairnow-1.2.1 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-pyairnow -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Thu Mar 09 2023 Python_Bot - 1.2.1-1 - Package Spec generated