Saravanan666/pypi-org huggingface dataset:
Package: crillab-metrics
mETRICS - rEproducible sofTware peRformance analysIs in perfeCt SimplicityAuthorsThibault Falque - Exakis NeliteRomain Wallon - CRIL, Univ Artois & CNRSHugues Wattez - Laboratoire d'Informatique de l'X (LIX), École PolytechniqueAboutMetricsMetricsis an open-source Python library developed atCRIL, designed to facilitate the conduction of
experiments and their analysis.The main objective ofMetricsis to provide a complete toolchain from
the execution of software programs to the analysis of their performance.
In particular, the development ofMetricsstarted with the observation
that, in the SAT community, the process of experimenting solver remains
mostly the same: everybody collects almost the same statistics about the
solver execution.
However, there are probably as many scripts as researchers in the domain
for retrieving experimental data and drawing figures.
There is thus clearly a need for a tool that unifies and makes easier the
analysis of solver experiments.The ambition of Metrics is thus to simplify the retrieval of experimental data
from many different kinds of inputs (including the solver's output), and
provide a nice interface for drawing commonly used plots, computing statistics
about the execution of the solver, and effortlessly organizing them.
In the end, the main purpose of Metrics is to favor the sharing and
reproducibility of experimental results and their analysis.InstallationTo executeMetricson your computer, you first need to installPython(at least version3.8).You may installMetricsusingpip, as themetricslibrary isavailable on PyPI.pipinstallcrillab-metricsNote that, depending on your Python installation, you may need to usepip3to install it, or to executepipas a module, as follows.python3-mpipinstallcrillab-metricsTo improve the reproducibility of the experiments, we highly recommend to use
avirtual environmentfor
each analysis you create withMetrics, and thus to install themetricslibrary in this virtual environment rather than with a system-wide
installation.UsingMetricsYou may find more information on how to useMetricsin thedocumentationwe provide for the package.CitingMetricsIf you are usingMetricsin your papers, we kindly ask you to either refer to
this repository or to one of the following papers:Metrics : Mission Expérimentations.Thibault Falque, Romain Wallon and Hugues Wattez.
16es Journées Francophones de Programmation par Contraintes (JFPC'21), 2021.Metrics: Towards a Unified Library for Experimenting Solvers.
Thibault Falque, Romain Wallon and Hugues Wattez.
11th International Workshop on Pragmatics of SAT (POS'20), 2020.
Package: crime-hotspots-uk
# Crime Hotspots UK
A python module that identifies and produces graphs of assult hotspots within the UK.For full documentation click [here](https://crime-hotspots-uk.readthedocs.io/en/latest/?)## About
This module has been programmed by organisers of Reclaim The Night Leeds. We hope it will be a useful tool for feminist and political activism groups in the UK. We do not necessarily any groups who have used this software.## How to use
View the demo.ipynb Jupyter Notebook file for demonstration of how to use this module. We advise using the [anaconda toolkit](https://www.anaconda.com/) to install and run Jupyter Notebook.You can also view the notebook online [here](https://github.com/Tasty213/crime-hotspots-uk/blob/main/demo.ipynb) however then you cannot change any of the variables.## Contribute
We welcom pull requests, issues and feature suggestions. To colloborate with us on publishing data you have produced using this or any other tool email us at RTNLeeds[at]gmail.com.
Package: crime-news-classifer-spanish
domestic-violence-news-classifer-spanishTo install itpip install domestic-violence-news-classifer-spanishyou will also need tensorflow and keras to run this package sopip install tensorflow kerasImport the packagefrom domestic_violence_news_classifer_spanish import domestic_violence_classifierwe will use the following text to test it:text_new = "Una mujer de 39 años murió en las últimas horas en un hospital de Santa Fe luego de agonizar desde el 11 de marzo, cuando su hijo la roció con nafta y la prendió fuego, en la localidad de Bella Italia, lindante con Rafaela, informaron hoy fuentes policiales. Los voceros identificaron a la víctima como Romina Esther Leiva (39), en tanto el acusado del ataque es su hijo Miguel Ángel Beresvilj (25), quien está detenido a la espera del juicio. Leiva murió mientras era asistida en la sala de terapia intensiva del hospital José María Cullen de la capital santafesina, luego de sufrir graves quemaduras en el 80 por ciento de su cuerpo que le afectaron el rostro, tórax, brazos y la pierna izquierda. La mujer resultó quemada en el marco de un violento episodio en su casa, situada en calle Córdoba al 100, de Bella Italia, localidad ubicada unos 95 kilómetros al oeste de la ciudad de Santa Fe. Luego del ataque, Beresvilj escapó en su motocicleta y horas después fue atrapado por la policía en la localidad de Frontera, en el límite con la provincia de Córdoba. En el domicilio donde ocurrió la agresión la Policía de Investigaciones secuestró dos bidones de cinco litros con restos de nafta. La versión del muchacho ante la Justicia es que su intención era quemar el automóvil de la pareja de su madre, con quien mantenía una mala relación, y que su madre se interpuso y resultó quemada por accidente. La fiscal de la Unidad de Violencia de Género, Familiar y Sexual del Ministerio Público de la Acusación (MPA), Ángela Capitanio, imputó a Beresvilj por el delito de ?homicidio agravado por el vínculo y por mediar violencia de género, en grado de tentativa, aunque ahora cambiará de figura penal ante la muerte de la mujer. El acusado se encuentra detenido con prisión preventiva sin plazos por orden del juez Osvaldo Carlos. Voceros judiciales indicaron que en la audiencia donde se fijó la prisión preventiva, el acusado dijo que jamás tuvo la intención de lastimar a su madre y que solo quería arruinarle el auto a (Roberto) Mansilla, el esposo de Leiva. Romina Leiva tenía, además de Beresvilj, cuatro hijos, dos mellizos de 13 años y otros dos de 9, producto de una relación anterior."run the classifier:classifier = domestic_violence_classifier.DomesticViolenceClassifier()
print(classifier.domestic_violence_subject_probability(text_new))you will see that it outputs0.9789301
Package: crimes
CrimesBlur the line between C and Python.First, write some C code:/* hello.c */#include<stdio.h>voidhello(void){printf("Hello world from C!\n");}Then import that C code into Python:importcrimescrimes.commit()fromhelloimporthellohello()# prints "Hello world from C!"All you had to do is callcrimes.commit()!What if I am a terrible C programmer?Not to worry!crimeswill print your syntax errors as part of the normal Python traceback:/* hello.c */#include<stdio.h>/* missing ')' on the next line: */voidhello(void{printf("Hello world from C!\n");}importcrimescrimes.commit()fromhelloimporthello# raises an error hereGives you this error:Traceback (most recent call last):
  File "/tmp/example.py", line 6, in <module>
    from hello import hello  # type: ignore
    ^^^^^^^^^^^^^^^^^^^^^^^
  File "/tmp/hello.c", line 5, in hello.c
    void hello(void {
                    ^
crimes.exceptions.CCompileError: expected ';', ',' or ')' before '{' tokenInstall[!WARNING] This is currently pretty hacky.
I provide absolutely no guarantee that this will work on your machine.
Here's how I got it working on my machine, which running macOS.
I highly doubt this library works at all on Windows.First, install the library:pipinstallcrimesNext, make sure you have a compatible version of GCC.
Any version of GCC 9.0 or greater should work. On most Linux distros,
you probably already have this installed. On macOS though... Apple
thought it was a good idea to symlinkgcctoclang. This does not
work. So first, installactualGCC using brew:brewinstallgcc@13Next, before using this module, make sure thatCCis set to usegcc-13. You can do this universally like this:exportCC=gcc-13...but I prefer to do it per-process:envCC=gcc-13python3my-program-that-commits-crimes.pyCopyingCopyright © 2023 Eddie Antonio Santos. Apache-2.0 licensed. SeeLICENSEfor details.Especiallythe Disclaimer of Warranty!
Package: crime-sim-toolkit
Crime data simulating toolkitThe crime_sim_toolkit is a python package that originated from a jointAlan Turing InstituteandLeeds Institute of Data Analyticsproject formulated byDr. Dan Birksat the University of Leeds. It focuses on generating simulations of crime demand, using alternate methodologies, that can then be used as an input into an agent based model of police supply.The toolkit was envisioned to have three main strategies for data simulation:a simple poisson sampler based on past dataa decision tree using a wide range of predictor variables (TODO)a microsimulation using transition probabilitiesThe data_manipulation folder contains notebooks highlighting how some data sources have been constructed.InstallationInstall via Python package indexThis package is now available viaPyPi.pip install --user crime_sim_toolkitInstall from sourcesYou can also install this package from source by cloning this repository, navigating into thecrime_sim_toolkitdirectory and running the following.python setup.py install --userWikiFind out how to get started using thecrime_sim_toolkitvia ourWikiLicenseMIT LicenseNotes on datafilesThe census_2011_population_hh.csv file is derived fromONS data. Taking data from sheet LSOA and using row 12 as the header row and keeping only rows below with data.TODOBuild method for using Police data APIDecision tree implementation
Package: crimg
crimg usesPillowto crop and resize an image as appropriate for web
presentation.
It is a convenience package that allows image
resizing without aspect ratio distortion.APIcrimg contains one useful function,crimg.crop_resize.
The function takes three arguments:image: aPIL imageobjectsize: a 2-tuple of (width,height);  at least one must be specifiedexact_size: whether to scale up for smaller imagesSeecrimg.crop_resize.__doc__for the function
documentation.crop_resizereturns the cropped and resized PIL image.Command LineThe command line program,crimg, is included in this python
package.  The help for the program is displayed by runningcrimgwith no arguments orcrimg--help.
Package: criminal-dance
犯人在跳舞 0.2.0祝各位新年快乐~基于ayaka的文字版桌游！得益于ayaka，本插件可作为如下机器人框架的插件使用nonebot2(使用onebot11适配器，可兼容qq频道)hoshinononebot1也可将其作为console程序离线运行nonebot2 安装本插件pip install criminal_dancehoshino 安装本插件从github仓库下载安装依赖pip install -r requirements.txt将criminal_dance/criminal_dance文件夹放入hoshino/modules在hoshino/config/__bot__.py中的MODULES_ON里，写入字符串criminal_dance作为console程序离线运行# run.pyimportayaka.adapters.consoleascatimportcriminal_danceif__name__=="__main__":cat.run()python run.py帮助[犯人在跳舞]
3-8人游玩，游玩前请先加bot好友，否则无法发牌。90s内不出牌会被系统强制弃牌（防止挂机）
- 犯人在跳舞 唤醒猫猫
[*]
- 卡牌帮助 <卡牌名> 获取相应的帮助
- 详细帮助 
- 牌库规则 
- 绑定私聊 <qq uid> 频道用户请使用该命令
- 退出游戏 
- 局势 查看场面局势
- 手牌 展示手牌
[room]
- 加入 加入房间
- 离开 离开房间
- 房间 查看房间信息
- 开始 开始游戏使用流程所有参与者都要提前加bot的qq好友，以便bot通过私聊发消息给你们发送犯人在跳舞，启动猫猫并创建游戏房间，发起者自动位于1号位频道用户需要额外发送绑定私聊 12345678，绑定自己的qq号随后其他人发送加入，根据加入顺序确定座次人数满足要求后，发送开始开始游戏，bot将通过私聊告知手牌之后在群里发送卡牌名称即可打出此卡！发送退出游戏，关闭猫猫！卡牌帮助[第一发现人] 一切都是由您开始。打出时没有特别效果
[共犯] 打出这张牌成为共犯。当犯人获胜时，您也获得胜利。当犯人输掉游戏时，您也跟着输掉游戏
[犯人] 您是犯人，不能让其他玩家知道。您只能在只剩下这张手牌时才能打出这张牌，如果您要这么做，您获胜
[不在场证明] 只要有了这个，您就不是犯人了。打出时没有特别效果。如果您有犯人和不在场证明，侦探质疑时您可以否认
[侦探] 您的手牌<=2才能打出这张牌。打出时质疑另一位玩家，如果该玩家持有犯人，您获胜
[普通人] 打出时没有特别效果
[谣言] 所有玩家随机抽一张他下家玩家的手牌
[情报交换] 所有玩家把一张牌传给他上家玩家
[目击者] 看另一个玩家的手牌
[交易] 和至少还有1张手牌的玩家交换一张手牌。如果这是您打出的最后一张牌，则没有特别效果
[神犬] 选择一个玩家。该玩家弃掉他其中的一张手牌，并且获得神犬。如果他弃掉一张犯人牌，您获胜
[警部] 手牌<=2时，选定一个玩家放置此牌，若其最终打出犯人牌，您获得游戏胜利详细帮助开局每人4张手牌，轮流出牌，整局游戏的第一张牌必须是{R.第一发现人}（类似扑克规则中的红桃3）

游戏分为好人阵营和坏人阵营，默认都是好人，而最终打出{R.犯人}牌的人作为坏人而胜利
但{R.犯人}牌只有在手牌数为1的时候才能打出，此时打出者作为{R.犯人}而胜利
其他人的目标就是在{R.犯人}逃跑成功之前，通过{R.侦探}、{R.神犬}、{R.警部}等牌抓到{R.犯人}，此时好人阵营胜利
当你打出{R.共犯}牌后，你便加入了坏人阵营，需要协助{R.犯人}获胜
当然，你也可以当个二五仔，若{R.共犯}使用{R.侦探}等牌抓到了{R.犯人}，那么他也视为好人阵营一同胜利

根据参与人数的不同，牌库的牌也不同，具体规则请发送 牌库规则 进一步了解

此外，当游戏进行中时，还有如下命令
局势：获得游戏进行情况等信息
手牌：获得你当前的手牌情况（bot私聊告知）牌库规则3人局，必须有第一发现人、犯人、侦探、不在场证明，加其他任意8张牌
4人局，必须有第一发现人、犯人、侦探、不在场证明、共犯，加其他任意11张牌
5人局，必须有第一发现人、犯人、侦探、不在场证明*2、共犯，加其他任意14张牌
6人局，必须有第一发现人、犯人、侦探*2、不在场证明*2、共犯*2，加其他任意16张牌
7人局，必须有第一发现人、犯人、侦探*2、不在场证明*3、共犯*2，加其他任意19张牌
8人局，加全部配置data/ayaka/犯人在跳舞.json属性意义overtime超时限制，超时后系统会自动出牌，防止挂机auto_card_help自动卡牌帮助，每打出一张牌后bot都会发送帮助，等参与玩家熟悉规则后，可以关闭该配置rename重命名卡牌，为担心和谐的人准备你可以将犯人改名为大老鼠，共犯改成小老鼠，侦探改成猫猫，警部改成捕鼠笼，谣言改成幸运大转盘，例如：{"第一发现人":"第一发现人","犯人":"大老鼠","神犬":"神犬","警部":"捕鼠笼","共犯":"小老鼠","普通人":"普通人","不在场证明":"不在场证明","目击者":"目击者","侦探":"猫猫","谣言":"幸运大转盘","交易":"交易","情报交换":"情报交换"}此时，游戏的启动命令将变成大老鼠在跳舞更新记录0.0.1b2原型阶段，勉强可玩0.0.1重构代码，第一个正式版本，全部功能已实现0.0.2修复BUG：在交易、情报交换等特殊阶段，无法查询手牌、局势0.0.3重构代码，更精简的逻辑结构修复BUG：在关闭猫猫后依旧可以通过私聊控制群聊的猫猫更新依赖 ayaka 0.0.1.40.0.4b0更新退出游戏命令修复BUG：使用强制退出时无法关闭超时机制，请使用退出游戏命令更新依赖 ayaka 0.0.1.5b10.1.0修复BUG：结束游戏后超时机制没有正确关闭修复BUG：神犬、侦探牌打出后没有按预期切换牌权更新依赖 ayaka 0.0.2.00.1.1更新依赖 ayaka 0.0.3.0新特性：支持qq频道0.1.2更严格的依赖约束新特性：新增命令退出优化游戏帮助0.2.0更新依赖修复BUG：修复了侦探指认犯人时，犯人没有被算入游戏失败方的BUG
Package: crimjustsimpy
crimjustsimpyTools for criminal justice simulation.##Introduction
This module contains a few classes that can help with simulating
certain elements of the criminal justice system in the United States.At present, it only simululates cases that have a probabilistic outcome at trial,
with an option to plea bargain that is solely a random choice. In the future,
I hope to add more realistic simulation of how both prosecutors and defendants
make plea bargaining decisions.
Package: crimm
crimmcrimmstands forChemistry with the ReInvented Macromolecular Mechanics. This project aims to integrate and supplement CHARMM with better object handle and APIsWhy"reinvent the wheel"This is a toolkit that is under active development, where many useful macromolecular modeling routines are selected to be reimplemented. This is an attempt to unify many macromolecular preparation/modeling routine under one platform while offering proper object handles and APIs in python. While currently, we aim to integrate with CHARMM and pyCHARMM, the broader goal is to provide highly usable, integratable, and scriptable python library/platform for simplifying any macromolecular modeling pipelines.Installationscrimm can be installed bypip install crimmcrimm requirespython>=3.8. The main dependencies are biopython, nglview, scipy, and requests. To use the adaptors, the respective packages need to be installed separately (e.g. pyCHARMM, rdkit, etc.)If you are installing crimm on a fresh enviroment, it is recommended to use theenv.yamlfile.conda env create -f env.yamlNoteOpenMMandpyCHARMMstill need to be installed separately in this environment if you require these in your pipeline.If you are using a centralizedJupyterlabinstallation and install the ipython kernel to it, thenglviewversion should match in both environment (crimmenv andjupyterlabenv). Otherwise the ipywidget fornglviewcould break. The requirednglviewversion is currently 3.0.6Base Library and Object HandlesThis library is built upon the excellent Biopython library. The macromolecular entity representations are derived from Biopython's entity classes and follow the same hierarchy. As a result, the entities in this library remain fully compatible with all functions and routines provided in Biopython.Parser ModuleNew and improved mmCIF parser is implemented to allow accurate structure representations and more complete information.Looper ModuleFor a given PDB structure with gaps or missing loops in the chain, this module provides functions to query PDB for the residue sequence and fill in the gaps or missing loop regions with the residues coordinates from the homology models.Structure Alignment/SuperpositionStructure Alignment utilizes Biopython'sSuperimposertool. However, sequence alignment based on the canonical sequence will be performed prior to the superimposition to determine where the residues should be aligned for two polymer chains that are not identical in sequence identity.VisualizationNGLViewis integrated for a direct visualization of structures for Jupyter Notebook/JupuyterLab.
Package: crimpl
Connecting to Compute Resources made Simple(r)pip install crimplIMPORTANT:crimplis currently still under development, is not yet well-tested, and is subject to significant API changes.  Please keep posted until an official release is ready.Read thelatest documentation on readthedocsorbrowse the current documentation.crimplprovides high-level python object-oriented interfaces to manage running scripts within conda environments on remote compute resources.Each type of server implements arun_scriptwhich runs a given set of commands remotely on the server, showing the output, and waiting for completion, andsubmit_scriptwhich starts the script running on the server and detaches while allowing for monitoring its progress remotely.  They also each include as.check_outputfor copying expected output files back to the local machine.Documentation and API DocsThe configuration, options, and capabilities of each type of server are explored inthe latest documentation on readthedocsorbrowse the current documentation.ContributorsKyle ConroyContributions are welcome!  Feel free to file an issue or fork and create a pull-request.
Package: crimson
CrimsonCrimson converts non-standard bioinformatics tool outputs to JSON or YAML.Currently it can convert outputs of the following tools:FastQC(fastqc)FusionCatcher(fusioncatcher)samtoolsflagstat (flagstat)Picardmetrics tools (picard)STARlog file (star)STAR-Fusionhits table (star-fusion)Variant Effect Predictorplain text output (vep)For each conversion, there are two execution options: as command line tool or as a Python
library function. The first alternative usescrimsonas a command-line tool. The second one
requires importing thecrimsonlibrary in your program.InstallationCrimson is available on thePython Package Indexand you can install it viapip:$pipinstallcrimsonIt is also available onBioConda, both through thecondapackage manager or as aDocker container.For Docker execution, you may also usethe GitHub Docker registry. This
registry hosts the latest version, but does not host versions 1.1.0 or earlier.dockerpullghcr.io/bow/crimsonUsageAs a command line toolThe general command iscrimson {tool_name}. By default, the output is written tostdout. For example, to use thepicardparser, you would execute:$crimsonpicard/path/to/a/picard.metricsYou can also write the output to a file by specifying a file name. The following
command writes the output to a file namedconverted.json:$crimsonpicard/path/to/a/picard.metricsconverted.jsonSome parsers may accept additional input formats. The FastQC parser, for example, also
accepts a path to a FastQC output directory as its input:$crimsonfastqc/path/to/a/fastqc/dirIt also accepts a path to a zipped result:$crimsonfastqc/path/to/a/fastqc_result.zipWhen in doubt, use the--helpflag:$crimson--help# for the general help$crimsonfastqc--help# for the parser-specific help, in this case FastQCAs a Python library functionThe specific function to import is generally located atcrimson.{tool_name}.parser. So to
use thepicardparser in your program, you can do:fromcrimsonimportpicard# You can specify the input file name as a string or path-like object...parsed=picard.parse("/path/to/a/picard.metrics")# ... or a file handlewithopen("/path/to/a/picard.metrics")assrc:parsed=picard.parse(src)Why?Not enough tools use standard output formats.Writing and re-writing the same parsers across different scripts is not a productive
way to spend the day.Local DevelopmentSetting up a local development requires that you set up all of the supported Python
versions. We usepyenvfor this.# Clone the repository and cd into it.$gitclonehttps://github.com/bow/crimson
$cdcrimson# Create your local development environment. This command also installs# all supported Python versions using `pyenv`.$makeenv# Run the test and linter suite to verify the setup.$makelinttest# When in doubt, just run `make` without any arguments.$makeContributingIf you are interested, Crimson accepts the following types contribution:Documentation updates / tweaks (if anything seems unclear, feel free to open an issue)Bug reportsSupport for tools' outputs which can be converted to JSON or YAMLFor any of these, feel free to open an issue in theissue
trackeror submit a pull request.LicenseCrimson is BSD-licensed. Refer to theLICENSEfile for the full license.
Package: crio-vault
Installationpip install crio_vaultGet startedHow to fetch keys required by a script from the AWS secret manager vault with this lib:from crio_vault import vaultInstantiatefetch = vault()Call the fetch_and_store methodfetch.fetch_and_store("test100", "prod")
key = json.loads(os.getenv('TEST100_PROD_SHEET_KEY')) # dict
token = os.getenv('TEST100_PROD_TOKEN') # stringPrint and checkprint(key)
print(type(key))
print(token)
print(type(token))
Package: cript
CRIPT Python SDKCRIPT AvailabilityCurrently, CRIPT is only available for users in the USA, and it is equipped with geo-blocking functionality that restricts access for users outside the USA. We are diligently working towards making CRIPT accessible worldwide. We appreciate your patience as we strive to achieve this goal!What is it?The CRIPT Python SDK allows programmatic access to theCRIPT platform. It can help automate uploading your data to CRIPT, and aims to allow for manipulation of your CRIPT data through the python language. This is a perfect tool for users who have python experience and have large amount of data to upload toCRIPT.InstallationCRIPT Python SDK requires Python 3.8+The latest released of CRIPT Python SDK is available onPython Package Index (PyPI)pipinstallcriptDocumentationTo learn more about the CRIPT Python SDK please check theCRIPT Python SDK user documentationTo learn more about the internal workings of the CRIPT Python SDK please check theCRIPT Python SDK internal documentationRelease NotesPlease visit theGitHub Releases pagefor a detailed release notes.We Invite ContributionTo get started, feel free to take a look at ourContribution Guidelinesfor
a detailed guide on how to contribute to our repository and become a part of our community.Whether you want to report a bug, propose a new feature, or submit a pull request, your contribution is highly valued.For development documentation to better understand the Python SDK code please visit thePython SDK Wiki.
If you encounter any issues please let us know viaissues sectionordiscussion sections.To learn more about our great community and all the open source plugins made by our fantastic community available
for theCRIPT Python SDKplease take a look at theplugins section.We appreciate your interest in contributing to our project! Together, let's make it even better! 🚀Happy coding!
Package: criptam
CriptamCriptam is a tool written in Python to easily fetch decryptediOS bootchainfirmware keys(excluding SEPOS) from a connected device.FeaturesAutomatically fetch decrypted bootchain firmware keys for any iOS version, no IPSW download required.RequirementsA UNIX-like OSAn internet connectionA 64-bit device connected in DFU mode vulnerable tocheckm8InstallationCriptam can be installed fromPyPI, or locally (requirespoetry):./install.shUsageOption (short)Option (long)Description-h--helpShows all options avaiable-b BUILDID--buildid BUILDIDiOS build to decrypt firmware keys for-m MAJOR--major MAJORMajor iOS version to decrypt all firmware keys for-a--allDecrypt firmware keys for all versions