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|
%global _empty_manifest_terminate_build 0
Name: python-GameBenchAPI-PyClient-BigFish
Version: 1.0.3
Release: 1
Summary: A GameBench API Client Library.
License: BSD License
URL: https://github.com/bigfishgames/GameBenchAPI-PyClient
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/93/2f/150f8e2f76c28c0f8a2f28d4a0fb5004ec689a871a216c99df0ca52f2d00/GameBenchAPI-PyClient-BigFish-1.0.3.tar.gz
BuildArch: noarch
Requires: python3-pandas
Requires: python3-urllib3
Requires: python3-requests
%description
A Python Client for the GameBench API
[](https://travis-ci.com/bigfishgames/GameBenchAPI-PyClient)
[](https://sonarcloud.io/dashboard?id=bigfishgames_GameBenchAPI)
[](https://sonarcloud.io/dashboard?id=bigfishgames_GameBenchAPI)
[](https://bettercodehub.com/)
[](https://gitter.im/bigfishgames/GameBench-API-PyClient?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
Please check out our [ZenHub Board](https://app.zenhub.com/workspaces/gamebenchapi-pyclient-5cabf535a736c27636b0283d/board?repos=180245554) for open issues and feature
requests.
Repository: [GitHub](https://github.com/bigfishgames/GameBenchAPI-PyClient)
For full documentation, go to the [ReadtheDocs](https://gamebenchapi-pyclient.readthedocs.io/) page.
[PyPi](https://pypi.org/project/GameBenchAPI-PyClient-BigFish/#description)
## Overview
To install, run `pip install GameBenchAPI-PyClient-BigFish`
The GameBench API Client library supplies a high-level object-oriented interface to the GameBench API. It is built in
Python 3.7 and uses the Requests library and Pandas data frames to easily integrate into data analysis software.
The library has two main architectural components; the models and API packages. The API package is responsible for
URL requests and dealing with the responses. The models are the objects representing the data returned. A mediator
provides the glue between the api and the models.
As a user of the library, you should only ever need to interact with the models creator class and the model objects
it can return.
Right now, the models are very thin. They only contain a property that has the data frame assigned. Over time we
would like to add common functionality, like aggregates, to these classes.
## The Basics
To make a request, import the ModelCreator class.
Instantiating the ModelCreator requires two arguments. The first is a CamelCase style 'model'
named after the metric that you are looking for; the model is dynamically imported based on this
name. The second argument is a dictionary that must include specific key/value pairs for
querying the GameBench API.
```python
from gamebench_api_client.models.creator.model_creator import ModelCreator
time_series_request = {
'session_id': '66d926f47ff5a7a5d853d1058c6305614e1ae6a5'
}
creator = ModelCreator('Cpu', time_series_request)
cpu_time_series = creator.get_model()
results = cpu_time_series.data
print(results)
"""
appUsage daemonUsage gbUsage timestamp totalCpuUsage
0 1372571.375 0 12.658228 5257 39.688461
"""
```
%package -n python3-GameBenchAPI-PyClient-BigFish
Summary: A GameBench API Client Library.
Provides: python-GameBenchAPI-PyClient-BigFish
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-GameBenchAPI-PyClient-BigFish
A Python Client for the GameBench API
[](https://travis-ci.com/bigfishgames/GameBenchAPI-PyClient)
[](https://sonarcloud.io/dashboard?id=bigfishgames_GameBenchAPI)
[](https://sonarcloud.io/dashboard?id=bigfishgames_GameBenchAPI)
[](https://bettercodehub.com/)
[](https://gitter.im/bigfishgames/GameBench-API-PyClient?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
Please check out our [ZenHub Board](https://app.zenhub.com/workspaces/gamebenchapi-pyclient-5cabf535a736c27636b0283d/board?repos=180245554) for open issues and feature
requests.
Repository: [GitHub](https://github.com/bigfishgames/GameBenchAPI-PyClient)
For full documentation, go to the [ReadtheDocs](https://gamebenchapi-pyclient.readthedocs.io/) page.
[PyPi](https://pypi.org/project/GameBenchAPI-PyClient-BigFish/#description)
## Overview
To install, run `pip install GameBenchAPI-PyClient-BigFish`
The GameBench API Client library supplies a high-level object-oriented interface to the GameBench API. It is built in
Python 3.7 and uses the Requests library and Pandas data frames to easily integrate into data analysis software.
The library has two main architectural components; the models and API packages. The API package is responsible for
URL requests and dealing with the responses. The models are the objects representing the data returned. A mediator
provides the glue between the api and the models.
As a user of the library, you should only ever need to interact with the models creator class and the model objects
it can return.
Right now, the models are very thin. They only contain a property that has the data frame assigned. Over time we
would like to add common functionality, like aggregates, to these classes.
## The Basics
To make a request, import the ModelCreator class.
Instantiating the ModelCreator requires two arguments. The first is a CamelCase style 'model'
named after the metric that you are looking for; the model is dynamically imported based on this
name. The second argument is a dictionary that must include specific key/value pairs for
querying the GameBench API.
```python
from gamebench_api_client.models.creator.model_creator import ModelCreator
time_series_request = {
'session_id': '66d926f47ff5a7a5d853d1058c6305614e1ae6a5'
}
creator = ModelCreator('Cpu', time_series_request)
cpu_time_series = creator.get_model()
results = cpu_time_series.data
print(results)
"""
appUsage daemonUsage gbUsage timestamp totalCpuUsage
0 1372571.375 0 12.658228 5257 39.688461
"""
```
%package help
Summary: Development documents and examples for GameBenchAPI-PyClient-BigFish
Provides: python3-GameBenchAPI-PyClient-BigFish-doc
%description help
A Python Client for the GameBench API
[](https://travis-ci.com/bigfishgames/GameBenchAPI-PyClient)
[](https://sonarcloud.io/dashboard?id=bigfishgames_GameBenchAPI)
[](https://sonarcloud.io/dashboard?id=bigfishgames_GameBenchAPI)
[](https://bettercodehub.com/)
[](https://gitter.im/bigfishgames/GameBench-API-PyClient?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge)
Please check out our [ZenHub Board](https://app.zenhub.com/workspaces/gamebenchapi-pyclient-5cabf535a736c27636b0283d/board?repos=180245554) for open issues and feature
requests.
Repository: [GitHub](https://github.com/bigfishgames/GameBenchAPI-PyClient)
For full documentation, go to the [ReadtheDocs](https://gamebenchapi-pyclient.readthedocs.io/) page.
[PyPi](https://pypi.org/project/GameBenchAPI-PyClient-BigFish/#description)
## Overview
To install, run `pip install GameBenchAPI-PyClient-BigFish`
The GameBench API Client library supplies a high-level object-oriented interface to the GameBench API. It is built in
Python 3.7 and uses the Requests library and Pandas data frames to easily integrate into data analysis software.
The library has two main architectural components; the models and API packages. The API package is responsible for
URL requests and dealing with the responses. The models are the objects representing the data returned. A mediator
provides the glue between the api and the models.
As a user of the library, you should only ever need to interact with the models creator class and the model objects
it can return.
Right now, the models are very thin. They only contain a property that has the data frame assigned. Over time we
would like to add common functionality, like aggregates, to these classes.
## The Basics
To make a request, import the ModelCreator class.
Instantiating the ModelCreator requires two arguments. The first is a CamelCase style 'model'
named after the metric that you are looking for; the model is dynamically imported based on this
name. The second argument is a dictionary that must include specific key/value pairs for
querying the GameBench API.
```python
from gamebench_api_client.models.creator.model_creator import ModelCreator
time_series_request = {
'session_id': '66d926f47ff5a7a5d853d1058c6305614e1ae6a5'
}
creator = ModelCreator('Cpu', time_series_request)
cpu_time_series = creator.get_model()
results = cpu_time_series.data
print(results)
"""
appUsage daemonUsage gbUsage timestamp totalCpuUsage
0 1372571.375 0 12.658228 5257 39.688461
"""
```
%prep
%autosetup -n GameBenchAPI-PyClient-BigFish-1.0.3
%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-GameBenchAPI-PyClient-BigFish -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Tue May 30 2023 Python_Bot <Python_Bot@openeuler.org> - 1.0.3-1
- Package Spec generated
|
