%global _empty_manifest_terminate_build 0
Name: python-circleguard
Version: 5.4.0
Release: 1
Summary: A utilities library for osu!. Provides support for parsing replays from a file or from the api, as well as support for unstable rate, hits, similarity, and frametime calculations.
License: GNU General Public License v3 (GPLv3)
URL: https://github.com/circleguard/circlecore
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/55/9d/ecb5f191b7d278a6c562b084e90c9035a06c94eca5d20869f6193afb4aa6/circleguard-5.4.0.tar.gz
BuildArch: noarch
Requires: python3-osrparse
Requires: python3-ossapi
Requires: python3-wtc
Requires: python3-numpy
Requires: python3-requests
Requires: python3-slider
Requires: python3-scipy
Requires: python3-matplotlib
%description
[](https://pypi.org/project/circleguard/)
# Circlecore ([documentation](https://circleguard.github.io/circlecore/))
Circlecore is a utilities library for osu!. Features include:
* Unstable Rate calculation
* Judgments calculation (classifying all hitobjects into misses, hit300s, hit100s, hit50s, or sliderbreaks)
* Similarity calculation between two replays, for replay stealing detection
* Frametime calculation, for timewarp detection
* Jerky, suspicious movement detection (called Snaps)
Circlecore is used by [Circleguard](https://github.com/circleguard/circleguard), a replay analysis tool.
Circlecore is developed and maintained by:
* [tybug](https://github.com/tybug)
* [samuelhklumpers](https://github.com/samuelhklumpers)
## Installation
Circlecore can be installed from pip:
```bash
pip install circleguard
```
This documentation refers to the project as `circlecore` to differentiate it from our organization [Circleguard](https://github.com/circleguard) and the replay analysis tool [Circleguard](https://github.com/circleguard/circleguard). However, `circlecore` is installed from pypi with the name `circleguard`, and is imported as such in code (`import circleguard`).
## Links
Github:
Documentation:
Discord:
## Usage
We have a full tutorial and documentation at . If you really want to jump right in, below is a quickstart guide:
```python
from circleguard import *
# replace "key" with your api key
cg = Circleguard("key")
# replay on http://osu.ppy.sh/b/221777 by http://osu.ppy.sh/u/2757689
replay = ReplayMap(221777, 2757689)
print(cg.ur(replay)) # unstable rate
print(cg.frametime(replay)) # average frametime
print(cg.frametimes(replay)) # full frametime list
print(cg.hits(replay)) # where the replay hits hitobjects
print(cg.snaps(replay)) # any jerky/suspicious movement
replay2 = ReplayMap(221777, 4196808)
print(cg.similarity(replay, replay2)) # how similar the replays are
# ReplayMap isn't the only way to represent replays; we can also
# get a beatmap's top 3 plays
map_ = cg.Map(221777, span="1-3")
# or a User's fifteenth and twentieth best plays
user = cg.User(124493, span="15, 20")
# or a local replay
replay3 = ReplayPath("/path/to/local/osr/replay.osr")
# and more. You can find them all at
# https://circleguard.github.io/circlecore/appendix.html#circleguard.loadables.Loadable
# maps and users can be iterated over
for r in map_:
print(cg.ur(r))
```
## Contributing
Join [our discord](https://discord.gg/VNnkTjm) and ask how you can help, or look around for open issues which interest you and tackle those. Pull requests are welcome!
%package -n python3-circleguard
Summary: A utilities library for osu!. Provides support for parsing replays from a file or from the api, as well as support for unstable rate, hits, similarity, and frametime calculations.
Provides: python-circleguard
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-circleguard
[](https://pypi.org/project/circleguard/)
# Circlecore ([documentation](https://circleguard.github.io/circlecore/))
Circlecore is a utilities library for osu!. Features include:
* Unstable Rate calculation
* Judgments calculation (classifying all hitobjects into misses, hit300s, hit100s, hit50s, or sliderbreaks)
* Similarity calculation between two replays, for replay stealing detection
* Frametime calculation, for timewarp detection
* Jerky, suspicious movement detection (called Snaps)
Circlecore is used by [Circleguard](https://github.com/circleguard/circleguard), a replay analysis tool.
Circlecore is developed and maintained by:
* [tybug](https://github.com/tybug)
* [samuelhklumpers](https://github.com/samuelhklumpers)
## Installation
Circlecore can be installed from pip:
```bash
pip install circleguard
```
This documentation refers to the project as `circlecore` to differentiate it from our organization [Circleguard](https://github.com/circleguard) and the replay analysis tool [Circleguard](https://github.com/circleguard/circleguard). However, `circlecore` is installed from pypi with the name `circleguard`, and is imported as such in code (`import circleguard`).
## Links
Github:
Documentation:
Discord:
## Usage
We have a full tutorial and documentation at . If you really want to jump right in, below is a quickstart guide:
```python
from circleguard import *
# replace "key" with your api key
cg = Circleguard("key")
# replay on http://osu.ppy.sh/b/221777 by http://osu.ppy.sh/u/2757689
replay = ReplayMap(221777, 2757689)
print(cg.ur(replay)) # unstable rate
print(cg.frametime(replay)) # average frametime
print(cg.frametimes(replay)) # full frametime list
print(cg.hits(replay)) # where the replay hits hitobjects
print(cg.snaps(replay)) # any jerky/suspicious movement
replay2 = ReplayMap(221777, 4196808)
print(cg.similarity(replay, replay2)) # how similar the replays are
# ReplayMap isn't the only way to represent replays; we can also
# get a beatmap's top 3 plays
map_ = cg.Map(221777, span="1-3")
# or a User's fifteenth and twentieth best plays
user = cg.User(124493, span="15, 20")
# or a local replay
replay3 = ReplayPath("/path/to/local/osr/replay.osr")
# and more. You can find them all at
# https://circleguard.github.io/circlecore/appendix.html#circleguard.loadables.Loadable
# maps and users can be iterated over
for r in map_:
print(cg.ur(r))
```
## Contributing
Join [our discord](https://discord.gg/VNnkTjm) and ask how you can help, or look around for open issues which interest you and tackle those. Pull requests are welcome!
%package help
Summary: Development documents and examples for circleguard
Provides: python3-circleguard-doc
%description help
[](https://pypi.org/project/circleguard/)
# Circlecore ([documentation](https://circleguard.github.io/circlecore/))
Circlecore is a utilities library for osu!. Features include:
* Unstable Rate calculation
* Judgments calculation (classifying all hitobjects into misses, hit300s, hit100s, hit50s, or sliderbreaks)
* Similarity calculation between two replays, for replay stealing detection
* Frametime calculation, for timewarp detection
* Jerky, suspicious movement detection (called Snaps)
Circlecore is used by [Circleguard](https://github.com/circleguard/circleguard), a replay analysis tool.
Circlecore is developed and maintained by:
* [tybug](https://github.com/tybug)
* [samuelhklumpers](https://github.com/samuelhklumpers)
## Installation
Circlecore can be installed from pip:
```bash
pip install circleguard
```
This documentation refers to the project as `circlecore` to differentiate it from our organization [Circleguard](https://github.com/circleguard) and the replay analysis tool [Circleguard](https://github.com/circleguard/circleguard). However, `circlecore` is installed from pypi with the name `circleguard`, and is imported as such in code (`import circleguard`).
## Links
Github:
Documentation:
Discord:
## Usage
We have a full tutorial and documentation at . If you really want to jump right in, below is a quickstart guide:
```python
from circleguard import *
# replace "key" with your api key
cg = Circleguard("key")
# replay on http://osu.ppy.sh/b/221777 by http://osu.ppy.sh/u/2757689
replay = ReplayMap(221777, 2757689)
print(cg.ur(replay)) # unstable rate
print(cg.frametime(replay)) # average frametime
print(cg.frametimes(replay)) # full frametime list
print(cg.hits(replay)) # where the replay hits hitobjects
print(cg.snaps(replay)) # any jerky/suspicious movement
replay2 = ReplayMap(221777, 4196808)
print(cg.similarity(replay, replay2)) # how similar the replays are
# ReplayMap isn't the only way to represent replays; we can also
# get a beatmap's top 3 plays
map_ = cg.Map(221777, span="1-3")
# or a User's fifteenth and twentieth best plays
user = cg.User(124493, span="15, 20")
# or a local replay
replay3 = ReplayPath("/path/to/local/osr/replay.osr")
# and more. You can find them all at
# https://circleguard.github.io/circlecore/appendix.html#circleguard.loadables.Loadable
# maps and users can be iterated over
for r in map_:
print(cg.ur(r))
```
## Contributing
Join [our discord](https://discord.gg/VNnkTjm) and ask how you can help, or look around for open issues which interest you and tackle those. Pull requests are welcome!
%prep
%autosetup -n circleguard-5.4.0
%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-circleguard -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed May 17 2023 Python_Bot - 5.4.0-1
- Package Spec generated