Saravanan666/pypi-org huggingface dataset:
Package: halfapi
HalfAPIBase tools to develop complex API with rights management.This project was developped by Maxime Alves and Joël Maïzi. The name was chosen
to referenceHalfORM, a project written by Joël Maïzi.Dependenciespython3python3-piplibgit2-devstarlettePyJWTclickuvicornorjsonpyyamlConfigurationConfigure HalfAPI in the file : .halfapi/config .It's atomlfile that contains at least two sections, project and domains.https://toml.io/en/### ProjectThe main configuration options without which HalfAPI cannot be run.secret: The file containing the secret to decode the user's tokens.port: The port for the test server.loglevel: The log level (info, debug, critical, ...)DomainsSpecify the domains configurations in the following form :[domains.DOMAIN_NAME]
name = "DOMAIN_NAME"
enabled = true
prefix = "/prefix"
module = "domain_name.path.to.api.root"
port = 1002Specific configuration can be done under the "config" section :[domains.DOMAIN_NAME.config]
boolean_option = false
string_value = "String"
answer = 42
listylist = ["hello", "world"]And can be accessed through the app's "config" dictionnary.UsageDevelop an HalfAPI domain by following the examples located in
tests/dummy_domain . An HalfAPI domain should be an importable python module
that is available in the python path.Run the project by using thehalfapi runcommand.You can try the dummy_domain with the following command.PYTHONPATH=$PWD/tests python -m halfapi domain dummy_domainCLI documentationUse the CLI help.python -m halfapi --help
python -m halfapi domain --helpAPI Testing@TODOExampleCheck out thesample projectthat helps you to build your own domain.Development@TODO
Package: halfgeo
GeoGeo is a geospatial management tool for Python. It facilitates the creation of Location objects, and acts as a model for Singapore's urban environment.During my National Service, I was involved in the DRO project, a piece of software used to optimise the placement of ambulances in Singapore. In addition, I further worked with medical, fire alarm and MyResponder data. This started my journey into Geospatial Analytics.After concluding my service, I began exploring different aspects of Singapore's urban geography; I used BeautifulSoup and Selenium to extract data pertaining to Malls, Schools, Services, Transportation, Shops and the like. I further extracted and processed datasets from LTA, URA and GovTech, which I explored using tools such as Tableau and QGis. This eventually led me to creating my MALLS Card Game, utilising as much of the data collected as possible to produce a strategic card game.This Python package details some of the ways I have managed this data, and applied programming principles learned from my Computer Science modules. Through this project, I hope to display strong concepts in Object Oriented Progamming, Generics, Immutability and Tree Data Structures.Link to website post about the projectGeometryThe "geom" submodule contains classes representing different aspects of a location in Singapore, including points, lines and shapes. It also includes a dynamic distance calculator as well as one for elevation.StructuresThe "structures" submodule contains data structures to facilitate certain operations. In it, I have implemented many data structures learned from my modules, such as the AVLTree, KDTree, Priority Queue and the Median Finding Algorithm. But I've also implemented my own Bounds Tree, which stores multiple shapes.LocationsUsing the two submodules mentioned previously, the "locations" submodule contains objects representing locations in Singapore. Be it MRT, Bus, Land Lots, Malls, Planning Areas, Roads or Schools, the objects have been optimised to handle queries much more quickly. The objects facilitate filtering, mapping, sorting, grouping, regex searching, distance querying, iterating and many more.
Package: halfjson
## 目标修复残破的 json## 修复原理根据异常提示来做一些操作, json 预期啥给啥根据文本前后,删除一些 BadCase## 当前测试`bash ./runtest.sh # 查看准确率 seq 1 10|xargs-I{} ./runtest.sh|grep ratio: |awk '{t += $3; h+=$6}{printh/t}'|tail-1`## HitRatio
1. 0.4269, 0.4287, 0.4303   # 实现完 12 条规则
2. 0.5037, 0.5084, 0.5077   # string 的 “ 补充在末尾
3. 0.5259, 0.5224, 0.5187   # Array 需要 pos - 2
4. 0.5433, 0.5311, 0.5381   # Array 细化一下 [, 的情况
5. 0.7192, 0.7216, 0.7265   # 大改进, FIX 之前的 Bug( parser 被冲掉了)
6. 0.7732, 0.7686, 0.7701   # case: {“a”:1 –> 补充 }## 目前的缺点 && 发现从前往后扫描, 不容易识别 pair 在前面缺失的 –>  {}]靠异常比较难拿到当时的 Value, nextchar 和 end 倒是好拿数字的支持比较弱 –> -02 / 0. / .0还不支持回溯 –> [{]同一个 case, 处理空白的情况也许可以统计 [] {} “” 的配合情况## TODO考虑尽量改成回溯的方式来试探解析缺失的 JSON 常量## BadCase{}]  / []]00
Package: halfling
halflingSmall, practical build and task automation system written in Python.Installation$pip3installhalflingIntroductionFor some strange reason I felt the urge to create my own build system. Halfling currently supports C and C++ builds out of the box (with incremental builds based on file modified times), but adding your own builder is as simple as subclassinghalfling.builders.Builder(seehalfling/builders/cxx.pyfor an example).Halfling is not intended to be feature rich, free of bugs, or particularly fast. On my machine, builds with halfling are marginally slower than builds with make.The biggest advantage to halfling is extensibility. The halfling CLI (invoked withhalfling) will attempt to load a file namedhalfling.pyin the current directory. Thishalfling.pyfile acts as an extension file; it can be used to configure your builds, add tasks to the CLI, and/or execute any arbitrary python code.Example extension file (halfling/examples/shotgun/halfling.py):frompathlibimportPathimporthalfling# Common build options used by all typesbuild_options=halfling.builders.CxxBuildOptions(executable_name="shotgun.out",compiler="g++",build_dir=Path(__file__).parent/"hbuild",sources=["src/main.cpp","src/add.cpp","src/sub.cpp",],obj_dir="hobj",flags=["-Wall"],include_paths=["lib/mul/inc"],defines=["DEFINED_IN_PY","ALSO_DEFINED_IN_PY"],lib_paths=["lib/mul"],libs=["mul"])# Add build and clean tasks to halflinghalfling.shortcuts.add_build_and_clean_tasks(halfling.builders.CxxBuilder(build_options),# The build_types_dict allows users to specify custom build types which can be selected with# the -t/--type CLI option. The default will be the first build type specified in the dict# (if you're using python 3.7+, and most likely if you're using python 3.6).## Each build type must provide a function which takes one argument (the build options data# structure).## The build_types_dict defaults to None, in which case, there will be no -t/--type CLI option.build_types_dict={"debug":lambdaoptions:options.flags.extend(["-g"]),"release":lambdaoptions:options.flags.extend(["-O2"])})# Add a custom taskdefmy_task(args):print(f"echo:{args.echo}")defsetup_my_task_args(parser):parser.add_argument("echo",type=str,help="string to echo back")halfling.tasks.add_task("my_task",my_task,setup_my_task_args)# Execute arbitrary code at load time. This probably isn't useful, its more for the sake of# demonstrating that this is just normal python code.print("Extension file loaded.")
Package: halftone
halftoneHalftoning in Python.pipinstallhalftoneimport halftone as ht
import PIL.Image

img = PIL.Image.open('foo.png')

halftoned = ht.halftone(img, ht.euclid_dot(spacing=8, angle=30))

halftoned.save('bar.png)Check the example notebook:notebooks/halftoning.ipynb.
Package: halftones
Halftones Packagehalftonesis a Python package for generating halftone versions of images. It provides an easy-to-use interface for transforming images into their halftone representations.Example OutputExample of a halftone image generated by thehalftonespackage.InstallationInstall the package using pip:pipinstallhalftonesExample UsageHere's a simple example to demonstrate how to use the halftones package:importhalftonesashtfromPILimportImage# Load your image (replace 'path/to/your/image.jpg' with your image file)image=Image.open('path/to/your/image.jpg')# Generate a halftone version of the imageimage_color_info=ht.generate_halftone_image(image,display_flag=True,grid_width=5)# The resulting 'image_color_info' contains information about the processed imageThis example demonstrates loading an image using the PIL library, processing it with the halftones package, and retrieving the result.FeaturesThehalftonespackage offers a range of functionalities for creating and manipulating halftone images. Here are some of the key features:Halftone Pattern Generation: Generate halftone patterns from images, a popular artistic effect that simulates continuous tone imagery through the use of dots.Flexible Grid and Tile Configurations: Create grids and tiles with user-specified angles and distances, offering flexibility in designing the halftone effect.Command-Line Interface: In addition to being a library,halftonescan be used as a command-line tool, making it easy to process images directly from the terminal.Customizable Halftone Effects: Parameters for adjusting the halftone effect, such as alpha transparency and black channel threshold, allow for a wide range of artistic expressions.These features makehalftonesa versatile tool for artists, designers, and anyone interested in image processing and halftone art.LicenseThehalftonespackage is open-source software licensed under the MIT License.ContactEmail hi@eotles.comfor questions.
Package: halib
Helper package for coding and automationVersion 0.1.24renamesystosystemto avoid conflict with built-insysmoduleaddtele_notimodule to send notification to telegram after a specific interval for training progress monitoringVersion 0.1.22addcuda.pymodule to check CUDA availability (for both pytorch and tensorflow)Version 0.1.21usingnetworkxandomegaconfto allow yaml file inheritance and overrideVersion 0.1.15__init__.py: add common logging library; alsoconsole_logdecorator to log function (start and end)Version 0.1.10filesys: fix typo on "is_exit" to "is_exist"gdrive: now support uploading file to folder and return direct link (shareable link)Version 0.1.9add dependencies requirement.txtVersion 0.1.8Fix bugs:[performance] instead of inserting directly new rows into table dataframe, first insert it into in-memoryrow_pool_dict, that fill data in that dict into the actual dataframe when needed.Version 0.1.7Fix bugs:fix insert into table so slow by allowing insert multiple rows at onceVersion 0.1.6New features:add DFCreator for manipulating table (DataFrame) - create, insert row, display, write to fileVersion 0.1.5New Featuresadd cmd modulenew package structureVersion 0.1.4New Featuresadd support to create Bitbucket Project from templateVersion 0.1.2New Featuresadd support to upload local to google drive.
Package: halig
halig(R)ageencrypted note-taking CLI app.haligopens, using your favorite$EDITOR, an in-memory copy of a file and upon save-and-exit,
it encrypts the new contents into anagefile that
you can store,relativelysafe, anywhere.FeaturesSimple notebooks management with paths autocompletionPassphrase-less, fully-encrypted notes, compatible with existing SSH keysNo externalagebinary neededAlmost allageadvantages, like having multiple keys for encryption and decryptionRemote (HTTP) public keys import: e.g: github.com/<username>.keysInstallpipxinstallhalig# or pipSetup TLDRset-e
ssh-keygen-ted25519
mkdir-p"${XDG_CONFIG_HOME:-$HOME/.config}/halig"cat<< EOF > "${XDG_CONFIG_HOME:-$HOME/.config}/halig/halig.yml"---notebooks_root_path: ~/Documents/Notebooksidentity_paths:- ~/.ssh/id_ed25519recipient_paths:- ~/.ssh/id_ed25519.pub- https://github.com/<username>.keys- https://gitlab.com/<username>.keysEOFUsage TLDRhaligeditsome_notebook# edit today's note relative to <notebooks_root_path>/some_notebookhaligeditsome_notebook/foo# edit  <notebooks_root_path>/some_notebook/foo.agehalignotebooks# list current notebooks
Package: hall
Probability theory using pythonic and (almost) mathematical notation.HelpSeedocumentationfor more details.A simple example: Intelligence quotient>>>fromhallimportP,E,Std,Normal,sample>>>IQ=~Normal()*100+15>>>E[IQ]100.0>>>Std[IQ]15.0>>>P(IQ>=130)0.0227501319481792>>>print("IQ test outcome:",sample(IQ))IQ test outcome: 116.309834872963So the chance of having an IQ (normally distributed with μ=100 and σ=15) of at
least 130 is approximately 2.3%.A simple example: MontyPythonHallTODOContributingFor guidance on setting up a development environment and how to make a
contribution tohall, seeContributing to hall.
Package: hallon
hallonhallon is a package for network debugging.requirementsPython >= 3.7InstallationpipinstallhallonUsageGenerate network topologyhallon-nt-cadr47.104.22.0-cusradmin-cpasruijie@123-cprt63275-cenpasruijie@123-upasruijie@123-uprt23-tt5LicenseMITLicenseCopyright (c) 2023 Ryan Alloriadonis
Package: halloumi-cloudwatch-dashboard
Halloumi Cloudwatch DashboardCreate a dashboard in the AWS Cloudwatch using the best practices from Halloumi.InstallFrom pip:pipinstallhalloumi-cloudwatch-dashboardFrom npm:npminstallhalloumi-cloudwatch-dashboardAPI DocumentationCheckAPI DocumentationUsagePythonfromaws_cdkimportcorefromhalloumi-cloudwatch-dashboardimportDashboardapp=core.App()stack=core.Stack(app,'MainStack')...Dashboard(stack,'Dashboard',dashboardName='MyDashboard')Typescriptimport*ascdkfrom'@aws-cdk/core';import{Dashboard}from'@halloumi-cloudwatch-dashboard';exportclassCdkWorkshopStackextendscdk.Stack{constructor(scope:cdk.App,id:string,props?:cdk.StackProps){super(scope,id,props);Dashboard(this,'Dashboard',dashboardName='MyDashboard');}}
Package: halloumi-ses-user
Halloumi SES UserLibrary used to create IAM Users and generates the SES credentials to use with the AWS Simple Email Service (SES).Usage# Example automatically generated without compilation. See https://github.com/aws/jsii/issues/826importaws_cdk.coreascdkimporthalloumi_ses_userashalloumi_ses_userclassSesUserStack(cdk.Stack):def__init__(self,scope,id,*,description=None,env=None,stackName=None,tags=None,synthesizer=None,terminationProtection=None,analyticsReporting=None):super().__init__(scope,id,description=description,env=env,stackName=stackName,tags=tags,synthesizer=synthesizer,terminationProtection=terminationProtection,analyticsReporting=analyticsReporting)halloumi_ses_user.SesUser(self,"SESUser")For more information, please check theAPI Doc
Package: hallo-ut
hallo-utSDK Python Layanan Informasi & Bantuan Universitas TerbukaInstallInstall denganpythonpipinstall--upgradehallo-utPenggunaanPenggunaan sederhanapython-mhallo-ut"pertanyaan anda atau tiket hallo-ut anda"Legal / HukumKode ini sama sekali tidak berafiliasi dengan, diizinkan, dipelihara, disponsori atau didukung olehUniversitas Terbukaatau afiliasi atau anak organisasinya. Ini adalah perangkat lunak yang independen dan tidak resmi. Gunakan dengan risiko Anda sendiri.
Package: hallucination
Travis CIPrerequisitespython-requestsSQLAlchemyUsagePython invocationTo create database tables:proxy_factory=ProxyFactory(config=dict(db_uri='sqlite:///test.db'))proxy_factory.create_db()To import a text file containing a proxy server list:proxy_factory=ProxyFactory(config=dict(db_uri='sqlite:///test.db'))proxy_factory.import_proxies('proxylist.txt')Hallucination supports multiple database backends, as long as supported bySQLAlchemy.proxy_factory=ProxyFactory(config=dict(db_uri='postgres://user:password@host/database'))To make a request:r=proxy_factory.make_request('http://github.com/suminb/hallucination')printr.textYou may specify timeout in seconds:r=proxy_factory.make_request('http://github.com/suminb/hallucination',timeout=5)printr.textShell frontendTo create an SQLite database file:python frontend.py -d proxy.db -cTo import a text file containing a proxy server list:python frontend.py -d proxy.db -i proxylist.txtTo export the proxy server list to a text file:python frontend.py -d proxy.db -x proxylist.txtAn exported file may look like the following:http://84.42.3.3:3128
http://77.94.48.5:80
http://209.62.12.130:8118
http://159.255.160.23:8080
http://50.57.170.105:80
Package: hallux
Hallux - Convenient AI Code Quality AssistantHalluxis a smart console utility to help you with routine code quality tasks.
It may help you with fixing SonarQube issues, linting issues, compilation errors and other code quality problems.
Any annoying issue, requiring a bit more intelligence than usual might be tackled.In order to fix code issues directly in your local filesystem, just typehallux .If you want to fix issues in a orderly manner, where every fix has its owngit commitrunhallux --git .If you wanthalluxto propose you fixes and corrections directly into your Pull-Request, you may add following line into the CIhallux --githubhttps://github.com/ORG_NAME/REPO_NAME/pull/ID.Halluxwill go to Github Web GUI and will send all its findings as comments with code proposals.In order forhalluxto understand your repo you need to provide.halluxconfiguration file, in the repo root folder.For more command-line commands and just type$ halluxInstallationpipinstallhallux

halluxLocal developmentIn order to setup Python virtual environment run./scripts/setup-venv.shFor activating environment runcd /path/to/hallux && source activate.shFolder structurebinmain hallux executablehalluxmain source codes for halluxscriptscomplimentary scripts for managing the repotestsunit- and integration- tests for hallux
Package: halma-game
Halma GameInstall from pippip install halma-gameTo run simply just execute in terminal/cmd:python -m halma-gamePrerequisite: pygame library
Tested on pygame 1.9.6 (Python 3.7.6)Font: Coolvetica (https://www.dafont.com/coolvetica.font)FeatureGame configuration screen with board piece animation8x8 and 10x10 board size (8x8 currently not supported by game model)Beautiful Light Mode and Dark ModeAI vs AI or human team picker with customizable colorInformative team name, move history, and move timerLatest ChangesAdded human player supportAdded 4-Player support (Team 2 vs 2)Multiple roundsTo be developedOnline matchDebug/Strategy mode built for AI developmentMultiprocessing/Multithreading GUI element and AI computation to be parallel (continuous timer)PyPI packageScreenshotDark Mode Starting ScreenLight Mode Playing Screen
Package: halmos
HalmosHalmos is asymbolic testingtool for EVM smart contracts. A Solidity/Foundry frontend is currently offered by default, with plans to provide support for other languages, such as Vyper and Huff, in the future.You can read more in our post: "Symbolic testing with Halmos: Leveraging existing tests for formal verification."Join theHalmos Telegram Groupfor any inquiries or further discussions.Installationpip install halmosOr, if you want to try out the nightly build version:pip install git+https://github.com/a16z/halmosUsagecd /path/to/src
halmosFor more details:halmos --helpExamplesRefer to thegetting started guideand theexamplesdirectory.ContributingRefer to thecontributing guidelines.DisclaimerThese smart contracts and code are being provided as is. No guarantee, representation or warranty is being made, express or implied, as to the safety or correctness of the user interface or the smart contracts and code. They have not been audited and as such there can be no assurance they will work as intended, and users may experience delays, failures, errors, omissions or loss of transmitted information. THE SMART CONTRACTS AND CODE CONTAINED HEREIN ARE FURNISHED AS IS, WHERE IS, WITH ALL FAULTS AND WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING ANY WARRANTY OF MERCHANTABILITY, NON-INFRINGEMENT OR FITNESS FOR ANY PARTICULAR PURPOSE. Further, use of any of these smart contracts and code may be restricted or prohibited under applicable law, including securities laws, and it is therefore strongly advised for you to contact a reputable attorney in any jurisdiction where these smart contracts and code may be accessible for any questions or concerns with respect thereto. Further, no information provided in this repo should be construed as investment advice or legal advice for any particular facts or circumstances, and is not meant to replace competent counsel. a16z is not liable for any use of the foregoing, and users should proceed with caution and use at their own risk. See a16z.com/disclosures for more info.
Package: halo-app
HaloTheHaloLib is a python based library utilizingServerlesstechnology andmicroservices architectureHalo provides the following features:Flask development for AWS Lambda & Dynamodbcorrelation id across microservicesstructured json based loggingsample debug log in productionsupport for microservice transactions with the saga patternusing SSM Parameter Store over Lambda env variablesServerless Error Handling & trace id for end usersLambda timeoutmanagement forslow HTTP responsesootb support for Idempotent service invocations (md5)If you are building a Python web app running on AWS Lambda (Django or Flask), use this library to manage api transactions:sagax = load_saga("test", jsonx, schema)
            payloads = {"BookHotel": {"abc": "def"}, "BookFlight": {"abc": "def"}, "BookRental": {"abc": "def"},
                        "CancelHotel": {"abc": "def"}, "CancelFlight": {"abc": "def"}, "CancelRental": {"abc": "def"}}
            apis = {"BookHotel": self.create_api1, "BookFlight": self.create_api2, "BookRental": self.create_api3,
                    "CancelHotel": self.create_api4, "CancelFlight": self.create_api5, "CancelRental": self.create_api6}
            try:
                self.context = Util.get_lambda_context(request)
                ret = sagax.execute(self.req_context, payloads, apis)
                return {"saga": "good"}, 200
            except SagaRollBack as e:
                return {"saga": "bad"}, 500LicenseThis project is licensed under the MIT LicenseAcknowledgmentsYan Cui -https://theburningmonk.comflowpl -https://github.com/flowpl/saga_py
Package: halo-aws
HaloTheHaloLib is a python based library utilizingServerlesstechnology andmicroservices architectureHalo provides the following features:Flask development for AWS Lambda & Dynamodbcorrelation id across microservicesstructured json based loggingsample debug log in productionsupport for microservice transactions with the saga patternusing SSM Parameter Store over Lambda env variablesServerless Error Handling & trace id for end usersLambda timeoutmanagement forslow HTTP responsesootb support for Idempotent service invocations (md5)If you are building a Python web app running on AWS Lambda (Django or Flask), use this library to manage api transactions:sagax = load_saga("test", jsonx, schema)
            payloads = {"BookHotel": {"abc": "def"}, "BookFlight": {"abc": "def"}, "BookRental": {"abc": "def"},
                        "CancelHotel": {"abc": "def"}, "CancelFlight": {"abc": "def"}, "CancelRental": {"abc": "def"}}
            apis = {"BookHotel": self.create_api1, "BookFlight": self.create_api2, "BookRental": self.create_api3,
                    "CancelHotel": self.create_api4, "CancelFlight": self.create_api5, "CancelRental": self.create_api6}
            try:
                self.context = Util.get_lambda_context(request)
                ret = sagax.execute(self.req_context, payloads, apis)
                return {"saga": "good"}, 200
            except SagaRollBack as e:
                return {"saga": "bad"}, 500LicenseThis project is licensed under the MIT LicenseAcknowledgmentsYan Cui -https://theburningmonk.comflowpl -https://github.com/flowpl/saga_py