%global _empty_manifest_terminate_build 0 Name: python-meteostat Version: 1.6.5 Release: 1 Summary: Access and analyze historical weather and climate data with Python. License: MIT URL: https://github.com/meteostat/meteostat-python Source0: https://mirrors.nju.edu.cn/pypi/web/packages/87/4e/7c657eaa0e11f76238ee87c157ff673ecd7a00a8f7cf177eb8e001cdf1b9/meteostat-1.6.5.tar.gz BuildArch: noarch Requires: python3-pandas Requires: python3-pytz Requires: python3-numpy %description # Meteostat Python Package The Meteostat Python library provides a simple API for accessing open weather and climate data. The historical observations and statistics are collected by [Meteostat](https://meteostat.net) from different public interfaces, most of which are governmental. Among the data sources are national weather services like the National Oceanic and Atmospheric Administration (NOAA) and Germany's national meteorological service (DWD). Are you looking for a **hosted solution**? Try our [JSON API](https://rapidapi.com/meteostat/api/meteostat/). ## Installation The Meteostat Python package is available through [PyPI](https://pypi.org/project/meteostat/): ```sh pip install meteostat ``` Meteostat **requires Python 3.6** or higher. If you want to visualize data, please install Matplotlib, too. ## Documentation The Meteostat Python library is divided into multiple classes which provide access to the actual data. The [documentation](https://dev.meteostat.net/python/) covers all aspects of the library: * **Selecting Locations** * [Geographical Point](https://dev.meteostat.net/python/point.html) * [Weather Stations](https://dev.meteostat.net/python/stations.html) * **Time Series** * [Hourly Data](https://dev.meteostat.net/python/hourly.html) * [Daily Data](https://dev.meteostat.net/python/daily.html) * [Monthly Data](https://dev.meteostat.net/python/monthly.html) * **Miscellaneous Data** * [Climate Normals](https://dev.meteostat.net/python/normals.html) * **Library** * [Contributing](https://dev.meteostat.net/python/contributing.html) * [Formats & Units](https://dev.meteostat.net/formats.html) * [Data Sources](https://dev.meteostat.net/sources.html) * [Terms & License](https://dev.meteostat.net/terms.html) ## Example Let's plot 2018 temperature data for Vancouver, BC: ```python # Import Meteostat library and dependencies from datetime import datetime import matplotlib.pyplot as plt from meteostat import Point, Daily # Set time period start = datetime(2018, 1, 1) end = datetime(2018, 12, 31) # Create Point for Vancouver, BC location = Point(49.2497, -123.1193, 70) # Get daily data for 2018 data = Daily(location, start, end) data = data.fetch() # Plot line chart including average, minimum and maximum temperature data.plot(y=['tavg', 'tmin', 'tmax']) plt.show() ``` Take a look at the expected output: ![2018 temperature data for Vancouver, BC](https://dev.meteostat.net/assets/img/py-example-chart.046f8b8e.png) ## Contributing Instructions on building and testing the Meteostat Python package can be found in the [documentation](https://dev.meteostat.net/python/contributing.html). More information about the Meteostat bulk data interface is available [here](https://dev.meteostat.net/bulk/). ## Donating If you want to support the project financially, you can make a donation using one of the following services: * [GitHub](https://github.com/sponsors/clampr) * [Patreon](https://www.patreon.com/meteostat) * [PayPal](https://www.paypal.com/donate?hosted_button_id=MQ67WRDC8EW38) ## Data License Meteorological data is provided under the terms of the [Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/legalcode). You may build upon the material for any purpose, even commercially. However, you are not allowed to redistribute Meteostat data "as-is" for commercial purposes. By using the Meteostat Python library you agree to our [terms of service](https://dev.meteostat.net/terms.html). All meteorological data sources used by the Meteostat project are listed [here](https://dev.meteostat.net/sources.html). ## Code License The code of this library is available under the [MIT license](https://opensource.org/licenses/MIT). %package -n python3-meteostat Summary: Access and analyze historical weather and climate data with Python. Provides: python-meteostat BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-meteostat # Meteostat Python Package The Meteostat Python library provides a simple API for accessing open weather and climate data. The historical observations and statistics are collected by [Meteostat](https://meteostat.net) from different public interfaces, most of which are governmental. Among the data sources are national weather services like the National Oceanic and Atmospheric Administration (NOAA) and Germany's national meteorological service (DWD). Are you looking for a **hosted solution**? Try our [JSON API](https://rapidapi.com/meteostat/api/meteostat/). ## Installation The Meteostat Python package is available through [PyPI](https://pypi.org/project/meteostat/): ```sh pip install meteostat ``` Meteostat **requires Python 3.6** or higher. If you want to visualize data, please install Matplotlib, too. ## Documentation The Meteostat Python library is divided into multiple classes which provide access to the actual data. The [documentation](https://dev.meteostat.net/python/) covers all aspects of the library: * **Selecting Locations** * [Geographical Point](https://dev.meteostat.net/python/point.html) * [Weather Stations](https://dev.meteostat.net/python/stations.html) * **Time Series** * [Hourly Data](https://dev.meteostat.net/python/hourly.html) * [Daily Data](https://dev.meteostat.net/python/daily.html) * [Monthly Data](https://dev.meteostat.net/python/monthly.html) * **Miscellaneous Data** * [Climate Normals](https://dev.meteostat.net/python/normals.html) * **Library** * [Contributing](https://dev.meteostat.net/python/contributing.html) * [Formats & Units](https://dev.meteostat.net/formats.html) * [Data Sources](https://dev.meteostat.net/sources.html) * [Terms & License](https://dev.meteostat.net/terms.html) ## Example Let's plot 2018 temperature data for Vancouver, BC: ```python # Import Meteostat library and dependencies from datetime import datetime import matplotlib.pyplot as plt from meteostat import Point, Daily # Set time period start = datetime(2018, 1, 1) end = datetime(2018, 12, 31) # Create Point for Vancouver, BC location = Point(49.2497, -123.1193, 70) # Get daily data for 2018 data = Daily(location, start, end) data = data.fetch() # Plot line chart including average, minimum and maximum temperature data.plot(y=['tavg', 'tmin', 'tmax']) plt.show() ``` Take a look at the expected output: ![2018 temperature data for Vancouver, BC](https://dev.meteostat.net/assets/img/py-example-chart.046f8b8e.png) ## Contributing Instructions on building and testing the Meteostat Python package can be found in the [documentation](https://dev.meteostat.net/python/contributing.html). More information about the Meteostat bulk data interface is available [here](https://dev.meteostat.net/bulk/). ## Donating If you want to support the project financially, you can make a donation using one of the following services: * [GitHub](https://github.com/sponsors/clampr) * [Patreon](https://www.patreon.com/meteostat) * [PayPal](https://www.paypal.com/donate?hosted_button_id=MQ67WRDC8EW38) ## Data License Meteorological data is provided under the terms of the [Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/legalcode). You may build upon the material for any purpose, even commercially. However, you are not allowed to redistribute Meteostat data "as-is" for commercial purposes. By using the Meteostat Python library you agree to our [terms of service](https://dev.meteostat.net/terms.html). All meteorological data sources used by the Meteostat project are listed [here](https://dev.meteostat.net/sources.html). ## Code License The code of this library is available under the [MIT license](https://opensource.org/licenses/MIT). %package help Summary: Development documents and examples for meteostat Provides: python3-meteostat-doc %description help # Meteostat Python Package The Meteostat Python library provides a simple API for accessing open weather and climate data. The historical observations and statistics are collected by [Meteostat](https://meteostat.net) from different public interfaces, most of which are governmental. Among the data sources are national weather services like the National Oceanic and Atmospheric Administration (NOAA) and Germany's national meteorological service (DWD). Are you looking for a **hosted solution**? Try our [JSON API](https://rapidapi.com/meteostat/api/meteostat/). ## Installation The Meteostat Python package is available through [PyPI](https://pypi.org/project/meteostat/): ```sh pip install meteostat ``` Meteostat **requires Python 3.6** or higher. If you want to visualize data, please install Matplotlib, too. ## Documentation The Meteostat Python library is divided into multiple classes which provide access to the actual data. The [documentation](https://dev.meteostat.net/python/) covers all aspects of the library: * **Selecting Locations** * [Geographical Point](https://dev.meteostat.net/python/point.html) * [Weather Stations](https://dev.meteostat.net/python/stations.html) * **Time Series** * [Hourly Data](https://dev.meteostat.net/python/hourly.html) * [Daily Data](https://dev.meteostat.net/python/daily.html) * [Monthly Data](https://dev.meteostat.net/python/monthly.html) * **Miscellaneous Data** * [Climate Normals](https://dev.meteostat.net/python/normals.html) * **Library** * [Contributing](https://dev.meteostat.net/python/contributing.html) * [Formats & Units](https://dev.meteostat.net/formats.html) * [Data Sources](https://dev.meteostat.net/sources.html) * [Terms & License](https://dev.meteostat.net/terms.html) ## Example Let's plot 2018 temperature data for Vancouver, BC: ```python # Import Meteostat library and dependencies from datetime import datetime import matplotlib.pyplot as plt from meteostat import Point, Daily # Set time period start = datetime(2018, 1, 1) end = datetime(2018, 12, 31) # Create Point for Vancouver, BC location = Point(49.2497, -123.1193, 70) # Get daily data for 2018 data = Daily(location, start, end) data = data.fetch() # Plot line chart including average, minimum and maximum temperature data.plot(y=['tavg', 'tmin', 'tmax']) plt.show() ``` Take a look at the expected output: ![2018 temperature data for Vancouver, BC](https://dev.meteostat.net/assets/img/py-example-chart.046f8b8e.png) ## Contributing Instructions on building and testing the Meteostat Python package can be found in the [documentation](https://dev.meteostat.net/python/contributing.html). More information about the Meteostat bulk data interface is available [here](https://dev.meteostat.net/bulk/). ## Donating If you want to support the project financially, you can make a donation using one of the following services: * [GitHub](https://github.com/sponsors/clampr) * [Patreon](https://www.patreon.com/meteostat) * [PayPal](https://www.paypal.com/donate?hosted_button_id=MQ67WRDC8EW38) ## Data License Meteorological data is provided under the terms of the [Creative Commons Attribution-NonCommercial 4.0 International Public License (CC BY-NC 4.0)](https://creativecommons.org/licenses/by-nc/4.0/legalcode). You may build upon the material for any purpose, even commercially. However, you are not allowed to redistribute Meteostat data "as-is" for commercial purposes. By using the Meteostat Python library you agree to our [terms of service](https://dev.meteostat.net/terms.html). All meteorological data sources used by the Meteostat project are listed [here](https://dev.meteostat.net/sources.html). ## Code License The code of this library is available under the [MIT license](https://opensource.org/licenses/MIT). %prep %autosetup -n meteostat-1.6.5 %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-meteostat -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Fri May 05 2023 Python_Bot - 1.6.5-1 - Package Spec generated