Saravanan666/pypi-org huggingface dataset:
Package: s5cmdpy
s5cmd-pythonpython binding for using s5cmd to download and upload files to s3 efficientlyTheS5CmdRunnerclass provides a Python interface for interacting withs5cmd, a command-line tool designed for efficient data transfer to and from Amazon S3.For more information about s5cmd, please refer to the originals5cmdrepository.FeaturesCheck for the presence ofs5cmdand download it if necessary.Executes5cmdcommandscp,mv, andrun.Handle file downloads from URLs and S3 URIs.Generate command files for batch operations withs5cmd.Simplify operations like copying and moving files between local paths and S3 URIs.InstallationTo useS5CmdRunner, ensure that Python 3.10 or higher is installed. The project itself can be installed from pip:pipinstalls5cmdpyor from source:gitclone<repourl>cds5cmd-python
pipinstall-e.UsageHere are some examples of how to use theS5CmdRunnerclass:Initialize S5CmdRunnerfroms5cmdpyimportS5CmdRunnerrunner=S5CmdRunner()Run s5cmd with a Local Command File# local_txt: `cp s3://dataset-artstation-uw2/artists/__andrey__/1841730##GZGgW.json .`local_txt_path="s5cmd_test.txt"runner.run(local_txt_path)Run s5cmd with a Command File from S3# Useful in environments like SageMaker or for reproducibility;# Extends `s5cmd run something.txt` to support command files stored in S3txt_s3_uri="s3://dataset-artstation-uw2/s5cmd_test.txt"runner.run(txt_s3_uri)Download Multiple Files from S3# Input a series of S3 URIs to create the necessary commands.txt for `s5cmd run`,# then execute `s5cmd run <commands.txt>`s3_uris=['s3://dataset-artstation-uw2/artists/__andrey__/1841730##GZGgW.json','s3://dataset-artstation-uw2/artists/__andrey__/2249992##q5Y22.json']destination_dir='/home/ubuntu/datasets/s5cmd_test'runner.download_from_s3_list(s3_uris,destination_dir)Download a file from internet and upload to S3cpcommand also works with a file from internet:# Download a file from internet and upload to S3target_url="https://huggingface.co/kiriyamaX/mld-caformer/resolve/main/ml_caformer_m36_dec-5-97527.onnx"dst_s3_uri="s3://dataset-artstation-uw2/_dev/"runner.cp(target_url,dst_s3_uri)LicenseS5cmd itself is MIT licensed. This project is also MIT licensed.
Package: s5-pytorch
S5: Simplified State Space Layers for Sequence ModelingThis is a ported version derived fromhttps://github.com/lindermanlab/S5andhttps://github.com/kavorite/S5.
It includes a bunch of functions ported from jax/lax/flax/whatever since they didn't exist yet.Jax is required because it relies on the pytree structure but it's not used for any computation.
Pytorch 1.13 or later is required because it makes heavy use offunctorch.vampto substitute it's jax counterpart.
Python 3.10 or later is required due to usage of thematchkeyword---Update:In my experiments it follows the results found in theHyena Hierarchy(& H3) paper that the state spaces alone lack the recall capabilities required for LLM but seem work well for regular sequence feature extraction and linear complexity.You can use variable step-size as described in the paper using a 1D tensor forstep_scalehowever this takesa lot of memorydue to a lot of intermediate values needing to be held (which I believe is true for the official S5 repo, but not mentioned in the paper unless I missed it).Installpipinstalls5-pytorchExamplefroms5importS5,S5Block# Raw S5 operatorx=torch.rand([2,256,32])model=S5(32,32)model(x)# [2, 256, 32]# S5-former block (S5+FFN-GLU w/ layernorm, dropout & residual)model=S5Block(32,32,False)model(x)# [2, 256, 32]
Package: s6r-hubspot
s6r-hubspotInstallationpipinstalls6r-hubspotUsagefroms6r_hubspotimportHubspotConnectionhubspot=HubspotConnection('your_access_token')owners=hubspot.get_owners()LicenseThis project is licensed under theGNU Lesser General Public License (LGPL) Version 3.ContributingContributions are welcome! If you find any issues or have suggestions for improvements,
please open an issue or submit a pull request.GitHub Repository:ScalizerOrg/s6r-hubspotContributorsDavid Halgand -GitHubMorgane Goujon -GitHubKhalid Bentaleb -GitHubMichel Perrocheau -GitHubMaintainerThis software is maintained byScalizer.
Package: s6r-odoo
s6r-odooInstallationpipinstalls6r-odooUsagefroms6r_odooimportOdooConnectionodoo_cli=OdooConnection(url='http://odoo.localhost',dbname='odoo',user='admin',password='admin')partners=odoo_cli.read_search('res.partner',[])forpartnerinpartners:print(partner)LicenseThis project is licensed under theGNU Lesser General Public License (LGPL) Version 3.ContributingContributions are welcome! If you find any issues or have suggestions for improvements,
please open an issue or submit a pull request.GitHub Repository:ScalizerOrg/s6r-odooContributorsDavid Halgand -GitHubMichel Perrocheau -GitHubMaintainerThis software is maintained byScalizer.
Package: sa11y
The Selenium Accessibility PackageGet basic accessibility information using
theaxe-core npm libraryon websites visited usingSelenium.ContactDequefor more information about axe™ functionality and results.Note: This project does not support all of the features available in axe™, but is
provided for the flexibility and convenience of Ruby users.PrerequisitesInstallpythonInstallpipInstallnpmInstalling$ pip install sa11yUsageJust pass in a valid driver instance to theAnalyzeclass constructor and call the#resultsmethod.driver = webdriver.Chrome()
Analyze(driver).results()By default, sa11y inspects elements in all frames and iframes on the page.
If your site does not use frames, you can improve performance slightly by turning off frame checks:driver = webdriver.Chrome()
analyze = Analyze(driver, frames=false)
analyze.results()By default, sa11y does not inspect frames from cross origins. If you need to analyze frames
originating from a different domain, you need to turn this on:driver = webdriver.Chrome()
analyze = Analyze(driver, cross_origin=false)
analyze.results()This gem comes packaged with the latest axe™ version at release. If you want to change this, specify the JS library you want to use:driver = webdriver.Chrome()
js_lib = open(“tests/resources/old.axe.min.js”, “r”).read()
Analyze(driver, js_lib=js_lib).results()DevelopmentThis project will be developed in Python 3.x so please create avirtual environment:python3 -m venv venvsource venv/bin/activateTo install dependencies, do the following:pip install -r requirements.txtTo install required scripts:python setup.py npm_installDeploymentThe project needs to include a dynamically generatedaxe.min.jsfile, and can be built with this command:python setup.py npm_install install sdistTo release, makes sure you have twine installed and run:twine upload -r  pypi dist/*ContributingPlease read [CONTRIBUTING.md](../CONTRIBUTING.md) for details on our process for submitting pull requests to us,
and please ensure you follow the [CODE_OF_CONDUCT.md](../CODE_OF_CONDUCT.md).VersioningWe use [SemVer](http://semver.org/) for versioning. For the versions available,
see the [tags on this repository](https://github.com/saucelabs/sa11y/tags).License and CopyrightThis project is licensed under the MPL-2.0 License - see the [LICENSE.md](LICENSE.md) file for details
Copyright (c) 2021 Sauce LabsAcknowledgmentsThanks to [@dequelabs](https://github.com/dequelabs) for their contributions to accessibility with the axe™ projectThanks to [@seleniumhq](https://github.com/seleniumhq) for their contributions to browser automation with the Selenium projectTestingTo run all tests, run the following:pytest
Package: sa2-seed-key
SA2 Seed KeySA2 Seed/Key authentication is a mechanism for authorizing test / tool clients with Volkswagen Auto Group control units, usually used to unlock a Programming session to re-flash the control units.The SA2 Seed/Key "script" is contained in the FRF or ODX flash container, and consists of a small bytecode machine in which simple opcodes are applied to the "seed" provided by the ECU to generate the "Key".Usage:vs = Sa2SeedKey([0x68, 0x02, 0x81, 0x49, 0x93, 0xa5, 0x5a, 0x55, 0xaa, 0x4a, 0x05, 0x87, 0x81, 0x05, 0x95, 0x26, 0x68, 0x05, 0x82, 0x49, 0x84, 0x5a, 0xa5, 0xaa, 0x55, 0x87, 0x03, 0xf7, 0x80, 0x6a, 0x4c], 0x1a1b1c1d)
result = vs.execute() # 0x6a37f02e
Package: sa818
SA818 ProgrammingUse this software to program the frequency, ctcss, dcs and filters ont
the radio module SA818Installation$ pip install sa818Example$ sa818 radio --frequency 145.230 --offset -.6 --ctcss 100
SA818: INFO: +DMOSETGROUP:0, RX frequency: 145.2300, TX frequency: 144.6300, ctcss: 100.0, squelch: 4, OK

$ sa818 volume --level 5
SA818: INFO: +DMOSETVOLUME:0 Volume level: 5
Package: saagieapi
PresentationInstallationUsageContributingPresentationThesaagieapipython package implements python API wrappers to easily interact with the Saagie platform in python.DocumentationYou can find the documentation of this packagehere.Installingpipinstallsaagieapi==<version>Compatibility with your Saagie platformSaagie platform versionsaagie-api release< 2.2.0< 0.6.0>= 2.2.0>= 0.6.0>= 2023.01>= 2.4.0>= 2023.02>= 2.6.0>= 2023.03>= 2.7.0>= 2023.04>= 2.9.0>= 2023.05>= 2.10.0>= 2024.01>= 2.11.0ContributingThe complete guide to contribute is available here:Contributing:warning: Warning :warning:This library is provided on an experimental basis and is not covered by Saagie support for the moment.
Package: saasops
SaaSOps - SaaS Tracking & Metrics AnalysisTrack Customers, Contracts, Revenue Segments and Invoices for SaaS administration and metrics reporting. Generates recognized revenue, MRR, ARR and associated metrics for chosen time period. Output tables and charts to terminal or export to XLSX or PPTX.ObjectivesOffer a platform for tracking customer and contract activity.Intended primarily for early-stage startup execs and finance leaders.Achieve consensus in SaaS metrics reporting across exec, ops and finance functions, such agreement being critical for reporting to investors.Ensure correct comprehension and use of metrics.All too often users of metrics, and those who report them, don't comprehend the actual defintion and so report inaccurately to stakeholders and investors.Bring the power of expanded metrics tracking to all users.Some of the more complex metrics are challenging to produce reliably in spreadsheet environments, and lend themselves well to implementation in a programmed environment.Design approachWhy Open Source- finance and finance-related functions in startups are mostly dependent upon either closed-source ledger and workflow tools or spreadsheet platforms. With increased availability of coding support and productivity tools it's possible that open source platforms could emerge for managing various aspects of the finance and operations functions in start-up and high-growth businesses.Why CLI?- easy to get to a first working app, and for early-stage B2B startups the volume of contract activity tends to be low enough such that CLI poses little impact on productivity. An API and browser UI/UX can be added later once main platform sufficiently developed.Reconciliation to accounting- standard reports with recognized revenue enable reconciliation to accounting data.FutureTo be added.DocumentationCurrent documentation can be foundhereon GitHub Pages.Demo: Adding Customers, Contracts and Segmentshttps://github.com/birchpoplar/saasops/assets/4149682/c59e6287-323c-464e-a986-887f45488c54Demo: Generating Metrics Reportshttps://github.com/birchpoplar/saasops/assets/4149682/737d23fe-7dd1-4c2a-a443-edd1a7ca68c5Standard AnalyticsThe first three charts are generated from the demonstration contract and segment details entered in the above videos. The fourth chart, showing trailing 12-month cohort analytics for Net and Gross Dollar Retention is on different data.Bookings, ARR & CARRNote: CARR is Contracted ARR.Monthly MRRMRR ChangeChart shows only the changes in MRR each month, without the starting and ending balances.TTM NDR & GDR
Package: saat
Welcome to SAATSAAT (Simulated Annealing Allocation Tool) is a tool intended to optimise the allocation of individuals into groups across teams within an organisation.PurposeSuppose we have some employees who want to learn more about their organisation.  Some know about HR, some finance, some marketing and others logistics.  The CEO decides the best way to do this is to put them into groups and get them to talk to one another.  Each employee has their specialism and diary as below:EmployeeSpecialism1pm2pm3pmDaveFinanceBusy--JanetteLogistics-BusyBusyJohnHR-Busy-.........Ideally, the groups would have a good mix of specialisms, all be about the same size and have as many time slots in which the group can meet.  For large numbers, it's not trivial how to best allocate employees into groups; this is the problem which SAAT approaches.DocsInstallLibrarypipinstallsaatJupyter Demosgit clone https://github.com/samuelweller21/SAAT.git
cd SAAT

# Intall [poetry](https://python-poetry.org/docs/#installing-with-the-official-installer)
poetry shell
poetry install

# Jupyter
python3 -m ipykernel install --user --name="SAAT" --display-name="SAAT"Run testspytestSeeTutorialsection for more information orDemofor a notebook example.
Package: saaya
Saaya Framework on Mirai目前最新版本为：2.0.4 devSaaya 以迁移至 mirai-api-http v2，下载时请注意版本此框架目前正在开发中，请暂时使用PyCharm以获得较好的代码内文档体验Saaya是一个为了与群内cdd对抗而开发的基于mirai-api-http的轻量机器人框架，使用语言为Python快速开始Saaya基于mirai-api-http，因此你的第一步应该是安装服务端，这里推荐使用MCL。服务端部署参见MCL提供的教程，安装服务端程序，并运行一次生成对应文件参考mirai-api-http，安装对应的插件运行一次MCL并关闭，修改配置文件，配置qq自动登录并打开mirai-api-http的websocket选项Saaya 配置pip install saaya创建主函数main.py与插件文件夹plugins编写应用逻辑将 Dockerfile 与 docker-compose.yaml 拖到目录中docker-compose up -d你的第一个应用编写主函数main.pyfromsaaya.sessionimportBotfromprivateimportaddress,verifyKey,botqqif__name__=='__main__':bot=Bot(address,verifyKey)# 创建一个 Bot 实例bot.bind(botqq)# 登陆 Bot （注意：需要主程序已登陆对应 qq）bot.registerPlugins([# 'plugins.turing.main','plugins.base.reply'])# 插件注册，规范如上bot.loop()# 开始监听事件循环插件规范在上一步中，我们注册了一个名为plugins.base.reply的插件，在BrickBot中，插件以目录的最深层为终点，也就是说明这个插件的路径应该是plugins/base/reply.py，如下便是一个最简单的插件fromsaaya.utilsimportPluginManagerfromsaaya.eventimportGroupMessagefromprivateimporttest_groups@PluginManager.registerEvent('GroupMessage')asyncdefhello(event:GroupMessage):ifevent.group.uidintest_groups:ifevent.message.getContent()=='ping':event.group.sendMessage('pong')Saaya v2 更新注意，你可能需要类型检查与一些判断来判明消息来源为群还是好友
此外，内置了功能 %help，用来显示命令的帮助当然，你也可以使用CmdManager来简化命令式插件的开发fromsaaya.utilsimportCmdManagerfromsaaya.eventimportGroupMessage,FriendMessagefromtypingimportUnion@CmdManager.registerCommand('hello',alias=['打招呼'],help='进行一个招呼的打')defhello(event:Union[GroupMessage,FriendMessage],param):event.sender.sendMessage('Hello world!')CmdManager默认起始符号为%，因此，在你无论是群聊还是私聊发送消息%hello时，Saaya都会回复你Hello world!Hello world将插件放置到相应的目录，并运行main.py可以看到插件已经成功加载，并且机器人回复了你pong鸣谢Mirai开源项目https://github.com/mamoe/miraimirai-api-http提供的接口支持
Package: sabac
Simple Attribute Based Access ControlDescriptionPython implementation of Attribute Based Access Control (ABAC).
Design is based on XACML model, but is not its strict implementation.FeaturesExamplefromsabacimportPDP,PAP,DenyBiasedPEP,deny_unless_permit# Creating Policy Administration Pointpap=PAP(deny_unless_permit)# Adding policy to PAPpap.add_item({"description":"Admin permissions","target":{'subject.id':1,},"algorithm":"DENY_UNLESS_PERMIT",'rules':[{"effect":"PERMIT","description":"Allow to manage users","target":{'resource.type':'user','action':{'@in':['create','view','update','erase_personal_data','delete']},},}]})pdp=PDP(pap_instance=pap)# Creating Policy Enforcement Pointpep=DenyBiasedPEP(pdp)# Describing Policy Enforcement Point contextcontext={'resource.type':'user','action':'create','subject.id':1}# Evaluating policyresult=pep.evaluate(context)print(result)# Should return TrueTODOImplement all combining algorithms#ReferencesXACML 3.0 standardhttp://docs.oasis-open.org/xacml/3.0/xacml-3.0-core-spec-os-en.htmlXACML Algorithms combining truth tableshttps://xacml.ioA popular ABAC/XACML introduction in Russianhttps://habr.com/ru/company/custis/blog/258861/#rule
Package: sabacan
Sabacan is a command line interface using various application server APIs.
Currently sabacan support the following server APIs.PlantUML ServerRedPen ServerSabacan has the following design concept:Command line option compatibility. All subcommand options are compatible
to the options of CLI commands corresponding to application servers.
This ease to replace using the commands by sabacan.Minimum dependencies. Sabacan uses only Python standard libraries.
This ease to export sabacan into environments unavailable to use package
managers.InstallationUse pip:pip install sabacanor use setup.py:python3 setup.py installThese will install sabacan command.UsageSabacan command takes a subcommand.Generate UML by PlanUML server:sabacan -u http://localhost/plantuml plantuml -tpng sequence.umlValidate document by RedPen:sabacan -u http://X.X.X.X redpen -r json document.mdEnable to specify the server URL by environment variables:export SABACAN_REDPEN_URL=http://localhost/redpen:8080
sabacan redpen -r plain2 document.rst
sabacan redpen -r xml document.txt
Package: sabaka
What is sabaka?In Belter Creole, in the TV show The Expanse (and in the books on which the show was based), "Sabaka" means"a general-purpose curse; "Dammit!" or "You bastard!", a suitable name for an error messaging package. The purpose ofsabakais to expand options for error messages beyond passed strings to include:a message composed from passed args and kwargs; anda default message.This is done by either using one of the included Exception subclasses or by mixing-in one of the mixin classes which add other messaging options to Python's base exceptions.ExamplesAPIExceptionsException MixinsContributingContributors are always welcome and should findsabakaeasy to work with. The project is highly documented so that users and developers can makesabakawork with their projects. It is designed for Python coders at all levels. Beginners should be able to follow the readable code and internal documentation to understand how it works. More advanced users should find complex and tricky problems addressed through efficient code.
Package: sabana
SabanaThis package has the following helper classes to allow programmatic interaction with Sabana from python:Instance: handler to an instance deployed in the platform.Program: constructs the series of steps to be executed in an instance deployed in the platform.Build (from sabana.cc): provides compilation of C programs for RISC-V processors.SupportCheckout ourdocumentation pages.For support get in touch with us via ourDiscordserver, or alternatively viaSabana.io.Sign upGet in touch in order to get access to Sabana via the followingform.LicensingThe Sabana package is distributed under the terms of theApache 2.0 license.TermsBy using Sabana you agree to our Terms of Service and Privacy Policy. These are available at ourterms portal.
Package: sabcalculatorpy
## README
## Usage## – make sure you have the current version of the python interpreter## –Run the following command in cmd## pip install sabcalculatorpy## Example 2## import sabcalculatorpy as calc## calc.add(3,8)## Output## 11## Example 2## import sabcalculatorpy as calc## calc.det()## enter the no of rows/columns 3## enter the value 1## enter the value 2## enter the value 3## enter the value 4## enter the value 5## enter the value 6## enter the value 7## enter the value 8## enter the value 9## output## 0## example 3## import sabcalculatorpy as cal## cal.solve2()## enter the a1 value in a1*x + b1*y= c1## 1## enter the b1 value in a1*x + b1*y= c1## 2## enter the c1 value in a1*x + b1*y= c1## 3## enter the a2 value in a2*x + b2*y= c2## 4## enter the b2 value in a2*x + b2*y= c2## 5## enter the c2 value in a2*x + b2*y= c2## 8## output## x= 0.3333333333333333## y=1.3333333333333333
Package: sabcom
The Spatial Agent-Based Covid-19 Model (SABCOM)SABCOM is an open source, easy-to-use-and-adapt, spatial network, multi-agent, model that can be used to simulate the effects of different lockdown policy measures on the spread of the Covid-19 virus in several (South African) cities.InstallationUsing Pip$pipinstallsabcomor, alternatively$pip3installsabcomManual$gitclonehttps://github.com/blackrhinoabm/sabcom$cdsabcom$pythonsetup.pyinstallUsageThe application can be used to simulate the progression of Covid-19 over a city of choice. Before running
the application, the user needs that make sure that all dependencies are installed. This can be done by
installing the files in the requirements.txt file on Github or on your system if you did a manual installation.
Given that you are in the folder that contains this file use:$python-mpipinstall-rrequirements.txtNext, there are two options. Simulating the model (using an existing initialisation) or initialising a new model environment that can be
used for the simulation.SimulationFive arguments need to be provided to simulate the model: a path for the input folder (-i), a path for the output
folder (-o), a seed (-s), a data output mode (-d), and a scenario (-sc).simulate -i <input folder path> -o <output folder path> -s <seed> -d <data output mode> -sc <scenario>For example, say you want to simulate the model using input folderexample_data,
output folderexample_data/output_data, seed2, data output modecsv-light, and scenariono-intervention.
First, make sure that all the files and folders are in your current location. Next, you type in the command line:$sabcomsimulate-iexample_data-oexample_data/output_data-s2-dcsv-light-scno-interventionThis will simulate a no_intervention scenario for the seed_2.pkl initialisation. input files for the city of your choice,
and output a csv light data file in the specified output folder.Note how this assumes that there is already an initialisation file. If this is not the case,
sabcom can be used to produce one given the input files.Initialisationinitialise <input folder path> <seed number>If an initialisation file is not present, you can create one using the sabcom initialise function.
For example, if you want to create an initialisation with the files in input folder (assumed to be in your current working directory)example_data,
Monte Carlo seed 3, the following command can be used:$sabcominitialise-iexample_data-s3As a rule, creating a model initialisation takes much longer than simulating one.RequirementsThe program requires Python 3, and the packages listed in the requirements.txt file.Website and Social Mediahttps://sabcom.co.zahttps://twitter.com/SABCOM5DisclaimerThis software is intended for educational and research purposes. Despite best efforts,
we cannot fully rule out the possibility of errors and bugs. The use of SABCoM
is entirely at your own risk.