Saravanan666/pypi-org huggingface dataset:
Package: new-ai-benchmark
AI Benchmark Alphais an open source python library for evaluating AI performance of various hardware platforms, including CPUs, GPUs and TPUs. The benchmark is relying onTensorFlowmachine learning library, and is providing a lightweight and accurate solution for assessing inference and training speed for key Deep Learning models.In total, AI Benchmark consists of42 testsand19 sectionsprovided below:MobileNet-V2[classification]Inception-V3[classification]Inception-V4[classification]Inception-ResNet-V2[classification]ResNet-V2-50[classification]ResNet-V2-152[classification]VGG-16[classification]SRCNN 9-5-5[image-to-image mapping]VGG-19[image-to-image mapping]ResNet-SRGAN[image-to-image mapping]ResNet-DPED[image-to-image mapping]U-Net[image-to-image mapping]Nvidia-SPADE[image-to-image mapping]ICNet[image segmentation]PSPNet[image segmentation]DeepLab[image segmentation]Pixel-RNN[inpainting]LSTM[sentence sentiment analysis]GNMT[text translation]For more information and results, please visit the project website:http://ai-benchmark.com/alphaInstallation InstructionsThe benchmark requires TensorFlow machine learning library to be present in your system.On systems thatdo not have Nvidia GPUs, run the following commands to install AI Benchmark:pipinstalltensorflow
pipinstallai-benchmarkIf you want to check theperformance of Nvidia graphic cards, run the following commands:pipinstalltensorflow-gpu
pipinstallai-benchmarkNote 1:If Tensorflow is already installed in your system, you can skip the first command.Note 2:For running the benchmark on Nvidia GPUs,NVIDIA CUDAandcuDNNlibraries should be installed first. Please find detailed instructionshere.Getting StartedTo run AI Benchmark, use the following code:fromai_benchmarkimportAIBenchmarkbenchmark=AIBenchmark()results=benchmark.run()Alternatively, on Linux systems you can typeai-benchmarkin the command line to start the tests.To run inference or training only, usebenchmark.run_inference()orbenchmark.run_training().Advanced settingsAIBenchmark(use_CPU=None,verbose_level=1):use_CPU={True, False, None}:   whether to run the tests on CPUs  (if tensorflow-gpu is installed)verbose_level={0, 1, 2, 3}:   run tests silently | with short summary | with information about each run | with TF logsbenchmark.run(precision="normal"):precision={"normal", "high"}:   ifhighis selected, the benchmark will execute 10 times more runs for each test.Additional Notes and RequirementsGPU with at least 2GB of RAM is required for running inference tests / 4GB of RAM for training tests.The benchmark is compatible with bothTensorFlow 1.xand2.xversions.ContactsPlease contactandrey@vision.ee.ethz.chfor any feedback or information.
Package: new-alias
NEW ALIASAboutNew Aliasis an alias generator designed to protect online identity. It generates
plausible-sounding names, usernames, and passphrases, as well as real open addresses in the
United States that are not tied to any particular individual or business (made available
through the OpenAddress project - you can read more on them here:https://openaddresses.io/).Installation and UsageThis program is available as the python package "new-alias". If python is installed on your system,
then you should be able to run "pip install new-alias" (with a dash) without any issues. After the
package is installed, the program can be run on the command line by simply typing the package name
"new_alias" (with an underscore).AttributionsThis program relies on some external data sources and libraries to work. They are as follows:Name Generation:uses open source name files that can be found here:https://gist.github.com/elifiner/cc90fdd387449158829515782936a9a4Username Generation:uses an open source word dictionary that can be found here:https://github.com/dwyl/english-words?search=1Passphrase Generation:uses an open source text file of words that can be found here:https://gist.github.com/deekayen/4148741Address Generation:uses the python library 'random-address', the documentation for which
can be found here:https://pypi.org/project/random-address/('random-address' is available through the MIT License)LicenseThis project is licensed under the MIT License - see theLICENSEfile for details.
Package: newbar-afisha
Тулза для командной строки для быстрого просмотра афиши ньюбара. Не требует авторизации в vk.com. Не имеет красивого вывода (пока).Setuppipinstall--usernewbar-afishaExample$newbar-afisha1маяпнКИНОВОРИГИНАЛЕССУБТИТРАМИВ20-00смотримсдрузьямиПрометей2012года.Входбесплатный.c20-002маявтJAZZ-JAMSESSION90%импровизации.АтмосфераNewYork.Входбесплатный.c20-003маясрВечеринкаTheOneС22-00резидентбараDJСтасРинкош.Входбесплатный.c22-004маячтREGGAEFEVER«ReggaeFever»–вечераямайскогозвукавЕкатеринбургеДесантселекторов:ИВАНГОГОЛИНHOMERJS-ТОЛЬКОВИНИЛ-ONLYVINYL-ТОЛЬКОВИНИЛ-Входбесплатный.c22-005маяптСHOSENBYEYWAxSNOWBOXChosenByEywa-инди-роксэлементамипхкипанка-пробивныеDIY-щики,создающиесвойстиль,своитусы,свойкругИзбранных.SNOWBOX-англоязычныйдэнсовыйинди-поп-ритмично-мелодичныепрофи,которыйгоджаднозабирающиесердцасвердловчан.Началов19-00.Вход300Р.c19-005маяптMAGICSOULFULHOUSENIGHTВесенняяночьдушевныххаусритмовотрезидентаиоснователя"соулфул"вечеринок-ВадимаЧикурова,атакжедвухгостей-VamDanиLapshin!Всюночьспециальнодлявасвшестичасовоммиксе:соулфул,дипиджазихаус.Началов2300,входсвободный.c23-006маясбKICKIN' JASS ORCHESTRA IN NEW BAR Майские праздники обещают быть горячими, потому что Kickin'JassOrchestraустраиваютбольшуювечеринкуBlackSaturdayвNewBar!Погрузимсявмирдиксиленда,традиционногоиновоорлеанскогоджаза,апослеполуночивасждутзажигательныетанцыотdjNicktheKick,djSevaLesPunshikинашегоспециальногогостя-djMistafesterНачалов21-00.Вход200Р.c21-007маявсИГРОВАЯВвашемраспоряжениивсевозможныенастольныеикарточныеигры.)Входбесплатный.c18-00
Package: newbookapi
Py-Newbook API InteractionThis project is about interacting with the Newbook API. It provides methods to authenticate, test the API, manage guests, sites and bookings.Class: NewbookApiThis class is used to interact with the Newbook API.Methodsinit(self, base_url: str,username: str, password: str , region: str) -> NoneInitialize the NewbookApi class.Parameters:username (str): The username for the API.password (str): The password for the API.region (str): The region for the API.get_api_keys(self) -> dictGet the API keys.Returns:dict: The response from the API.auth_test(self, api_key: str) -> dictTest the authentication with the API.Parameters:api_key (str): The API key to test.Returns:dict: The response from the API.get_guests_lists(self) -> dictGet the guests lists.Returns:dict: The response from the API.create_new_guest(self, new_guest) -> dictCreate a new guest.Parameters:new_guest (dict): The new guest details.Returns:dict: The response from the API.update_existing_guest(self, updated_guest) -> dictUpdate an existing guest.Parameters:updated_guest (dict): The updated guest details.Returns:dict: The response from the API.get_sites_list(self) -> dictGet the sites list.Returns:dict: The response from the API.get_bookings_list(self, booking) -> dictGet the bookings list.Parameters:booking (dict): The booking details.Returns:dict: The response from the API.create_new_booking(self, new_booking) -> dictCreate a new booking.Parameters:new_booking (dict): The new booking details.Returns:dict: The response from the API.update_existing_booking(self, existing_booking) -> dictUpdate an existing booking.Parameters:existing_booking (dict): The existing booking details.Returns:dict: The response from the API.
Package: newcat
newcatprint (cat) only new lines in files (after previous run of newcat). This is useful to parse recent log records.Installpipx install newcatExample$echoThisisline1>/tmp/test.log# works like normal /bin/cat now$newcat/tmp/test.logThisisline1# only new lines are printed$echoThisisline2>>/tmp/test.log
$newcat/tmp/test.logThisisline2# no new lines => nothing on stderr$newcat/tmp/test.log# despite file is having two lines$cat/tmp/test.logThisisline1Thisisline2How does this magic work?newcat stores some info about file (including position in file) instate file. Default state file is/tmp/.newcat.state, but can be overriden withNEWCAT_STATEenvironment variable or-s/--stateoption. Normally, newcat prints file content starting from this position (which was saved before), thus lines which were already printed before, will not be printed on new newcat run.Sometime file content it rewritten (e.g. afterecho New content > /tmp/test.log). To detect this situation newcat checks two things:file inode changedfile size is less then old printed positionif any of these conditions are met, file considered as rewritten and newcat prints it from the beginning.
Note: this is not absolutely reliable, and there is a chance that sometimes newcat will not detect when file is overwritten.
Package: new-celery-config
Celeryis a distributed task queue library for Python. It accepts some of its configuration via environment variables–but some configuration needs to be specified as Python code.new-celery-configis a Python package that lets you set any top-level Celery key using an environment variable containing YAML.InstallationThe latest stable can be installed via pip:python3 -m pip install new-celery-configUsage(Usage) as a moduleTo set configuration values, you must set an environment variables for each top-level key (as documented in the Celery documentation).Each environment variable is prefixed withNEW_CELERY_, followed by the config key name in lowercase. The value for each environment variable must be valid YAML (or JSON–remember that JSON is a subset of YAML).You must also set the environment variableCELERY_CONFIG_MODULEtonew_celery_config.as_moduleto enable Celery to read all of the other environment variables that you have set.For example, setting these environment variables in the shell looks like:exportCELERY_CONFIG_MODULE=new_celery_config.as_moduleexportNEW_CELERY_broker_url='transport://userid:password@hostname:port/virtual_host'exportNEW_CELERY_broker_transport_options='{"visibility_timeout": 36000}'And in your Python code, initialize the Celery object as follows:app=Celery()If you want to change the name of theCELERY_CONFIG_MODULE, you can use theconfig_from_envvarfunction. For example:exportARBITRARY_CELERY_CONFIG_MODULE=new_celery_config.as_moduleapp.config_from_envvar("ARBITRARY_CELERY_CONFIG_MODULE")You can test that the configuration works by examining theapp.confobject:print(app.conf.broker_transport_options)# prints out {'visibility_timeout': 36000}Usage (as an object)Celery also accepts configuration in the form of a Python object. If you prefer this way, you can give Celery anew_celery_config.Configobject. For example:fromceleryimportCeleryimportnew_celery_configapp=Celery()app.config_from_object(new_celery_config.Config())Contributing changes tonew-celery-configIf you want to make changes tonew-celery-config, you can clone this repository. You can runmakein the root directory to show commands relevant to development.For example:make fmtautomatically formats Python code.make lintruns pylint and mypy to catch errors.make testruns unit tests.
Package: newchain-account
newchain-accountSign NewChain transactions and messages with local private keysQuickstartpipinstallnewchain-accountDeveloper SetupDeveloper setupIf you would like to hack on newchain-account, please check out theEthereum Development Tactical Manualfor information on how we do:TestingPull RequestsCode StyleDocumentationDevelopment Environment SetupYou can set up your dev environment with:gitclonegit@github.com:newtonproject/newchain-lib-account-py.gitcdnewchain-lib-account-py
virtualenv-ppython3venv
.venv/bin/activate
pipinstall-e".[dev]"To run the integration test cases, you need to install node and the custom cli tool as follows:apt-getinstall-ynodejs# As sudo./tests/integration/ethers-cli/setup_node_v12.sh# As sudocdtests/integration/ethers-cli
npminstall-g.# As sudoTesting SetupDuring development, you might like to have tests run on every file save.Show flake8 errors on file change:# Test flake8when-changed-v-s-r-1newchain_account/tests/-c"clear; flake8 newchain_account tests && echo 'flake8 success' || echo 'error'"Run multi-process tests in one command, but without color:# in the project root:pytest--numprocesses=4--looponfail--maxfail=1# the same thing, succinctly:pytest-n4-f--maxfail=1Run in one thread, with color and desktop notifications:cdvenv
ptw--onfail"notify-send -t 5000 'Test failure ⚠⚠⚠⚠⚠' 'python 3 test on newchain-account failed'"../tests../newchain_accountRelease setupFor Debian-like systems:apt install pandocTo release a new version:makereleasebump=$$VERSION_PART_TO_BUMP$$How to bumpversionThe version format for this repo is{major}.{minor}.{patch}for stable, and{major}.{minor}.{patch}-{stage}.{devnum}for unstable (stagecan be alpha or beta).To issue the next version in line, specify which part to bump,
likemake release bump=minorormake release bump=devnum. This is typically done from the
master branch, except when releasing a beta (in which case the beta is released from master,
and the previous stable branch is released from said branch).If you are in a beta version,make release bump=stagewill switch to a stable.To issue an unstable version when the current version is stable, specify the
new version explicitly, likemake release bump="--new-version 4.0.0-alpha.1 devnum"
Package: newcli
# newcliUtility to create a new Python CLI.## Quickstart```bashpipenv install newclinewcli init```## Install```bash# Command(s)pipenv install newclipip3 install --user newcli```## Commands### `init````bash# Commandnewcli init````newci` will then prompt you for basic information about your project!The output creates this folder structure:```bash{{project}}/├── LICENSE├── MANIFEST.in├── Pipfile├── README.md├── setup.py├── tox.ini└── {{project}}├── __init__.py├── __version__.py├── cli.py└── core.py```## Template CLI Project### Testing CLI`cd` into the directory and install to your current virtualenv```bash# Commandpipenv isntall -e .```Now run the new tool!```{{project}}Usage: {{project}} [OPTIONS] COMMAND [ARGS]...{{project}}Options:--help  Show this message and exit.```Now you can begin adding new functions!### VersioningThe project will be date versioned with as today's `YEAR.MONTH.DAY.SUBVERSION`. This handles most project updates great, and required the user to update the subversion manually in `__version__.py`.### Publish to PyPy-   Creating a new repository on [PyPi](https://pypi.org/) is quick and easy. Quickly build and upload a new project or update an existing one with:```bash# Commandpython setup.py upload```## TODO-   100% unit tests and run on TravisCI-   populate GitHub information from .gitconfig-   init a new GitHub repository-   add .travis.yml configuration-   add template tox configuration-   add template test files and folder structure-   add template README.md-   ability to create, register, and share new templates
Package: newcode-utils
New Code UtilsBasic components for the development of NewCode_RequirementsInstall pip currentQuick start1.Add"newcode_utils"toyourINSTALLED_APPSsettinglikethis::INSTALLED_APPS=[...'newcode_utils',]ComponentsAdminAuditAdminAuditStackedInlineAuditTabularInlineModelsAuditHelpersUtilsFile departments of columbiaUtils permission restDeploy pypi versionsinstall requirementspipinstall-Utwinewheelsetuptoolsupdate repositorypython3.7setup.pysdistbdist_wheel
twinecheckdist/*
twineupload--repositorypypidist/newcode-utils-0.1.1*
Package: newconan
newconancreates default project structure that is convenient for developing in IDEs like Clion and Visual Studio.Requirementscmake>= 3.14Installation$pipinstallnewconanCreate Project$newconanTestExe# create exe project$newconanTestSharedLibrary-shared# create shared library project$newconanTestStaticLibrary-static# create static library projectProject StructureTestSharedLibrary
├── .git
├── .travis
│   ├── install.sh
│   └── run.sh
├── assets
│   └── public
│       └── TestSharedLibrary
├── cmake
│   ├── conan.cmake
│   ├── symlink.cmake
│   └── symlink.py
├── src
│   ├── main.cpp
│   └── main.h
├── test
│   └── test.cpp
├── .clang-format
├── .gitignore
├── .gitlab-ci.yml
├── .travis.yml
├── appveyor.yml
├── build.py
├── CMakeLists.txt
├── CMakeSettings.json
├── conanfile.py
└── README.mdnewconanwill automatically create the git repository which is.gitfolder.assetsfolder will contains resource files which will be symlink to${CMAKE_CURRENT_BINARY_DIR}/bin/assets. In this way, your binary can use the relative path./assetsto access the resource files.cmakefolder contains somecmake macrosto symlink folder and setupconan.srcfolder contains the main source code for your project.testfolder contains all the testcppfiles..clang-formatis the default format thatclang-formatwill use..gitignoreignores everything except exisiting folders and files. You can edit this file to add other folders to git..gitlab-ci.ymlis the default ci configuration forgitlab..travis.ymland folder.travisis the default ci configuration fortravis.appveyor.ymlis the default ci configuration forappveyor.build.pywill be used bygitlab-cito build and upload this project asconan recipefor others to use your library.CMakeLists.txtwill define a target for your project and link all the necessary libraries against it.CMakeLists.txtalso scanstestfolder and create corresponding a test target for eachcppfile.CMakeSettings.jsonis used byVisual Studio. This file will makeVisual Studioput thebuildfolder relative to your project rather than some hashed folder which you can't find easily.conanfile.pydefines the library dependencies.conanwill download and compile all the required libraries and copy*.dll/*.dylibto${CMAKE_CURRENT_BINARY_DIR}/binfolder. At the same time, dependent library resource files will also be copied.README.mdshows how to build this project usingcmakeandconan.Add dependencyYou can add library dependencies to your project by modifying therequiresattribute ofconanfile.py:classProjectNameConan(ConanFile):name="ProjectName"version="1.0.0"settings="os","compiler","build_type","arch"requires=(# Add dependencies here."library1/1.0.0@conan/stable","library2/2.0.0@conan/testing",...)And then refreshcmake,conanwill download and compile all the listed dependencies.
Package: new-contributor-wizard
New Contributor WizardDescriptionNew Contributor Wizard is a GUI application build to help new contributors get started with Open Source. It was an idea to bring together all the Tools and Tutorials necessary for a person to learn and start contributing to Open Source. The application contains different courseware sections like Communication, Version Control System etc. and within each section, there are respective Tools and Tutorials.A Tool is an up and running service right inside the application which can perform tasks to help the user understand the concepts. For example, encrypting a message using the primary key, decrypting the encrypted message using the private key, and so on, these tools can help the user better understand the concepts of encryption.A tutorial is comprised of lessons which contain text, images, questions and code snippets. It is a comprehensive guide for a particular concept. For example, Encryption 101, How to use git?, What is a mailing list? and so on.In addition to providing the Tools and Tutorials, this application is build to be progressive. One can easily contribute new Tutorials by just creating a JSON file, the process of which is documented in the project repository itself. Similarly, a documentation for contributing Tools is present as well.Project RepositoryProject repository can be found onDebian Salsa.Project ManagementProject management i.e. issue/bug tracker is present onRedminehosted on Debian.Prerequisites To Build ApplicationGNU/Linux OS (Tested on Debian 9)Python (Tested on Python => 3.5)Kivy (Tested on ==1.10.1)How To InstallMake sure you have all thedependencies of Kivyinstalled. Then run:$ pip install new-contributor-wizardHow To Run$ new-contributor-wizardDocumentationDeveloper DocumentationThese documentations help developers who are willing to build this application from source. Checkout docs fromhere.Contributor DocumentationThese documentations contains guildelines for the contributors get started with best practices to help out in contributing to this project. Checkout docs fromhere.Contribute To TutorialsContributing Tutorials is as simple as creating a JSON file, NO CODING REQUIRED! You can create a JSON file in order to contribute to Tutorials of any module of your choice. VisitContribute To Tutorialsto know how.Contribute To ToolsIn order to contribute tools for any module of this application visitContribute To Toolsdocumentation.ChangelogsChangelogs for this project is based onSemVeror Semantic Versioning. Checkout Changelogs fromhere.ContributorsCheckoutCONTRIBUTORSto know more about the awesome people behind this project.
Package: new-dale-chall-readability
The new Dale-Chall readability formulaI wrote this by ordering a copy ofReadability Revisited: The new Dale-Chall readability formula. I used the book to code the library from scratch.Installation:$pipinstallnew-dale-chall-readabilityLet's try it out:$ipythonIn[1]:fromnew_dale_chall_readabilityimportcloze_score,reading_levelIn[2]:text=(...:'Latin for "friend of the court." It is advice formally offered '...:'to the court in a brief filed by an entity interested in, but not '...:'a party to, the case.'...:)In[3]:reading_level(text)Out[3]:'7-8'In[4]:cloze_score(text)Out[4]:36.91What's a "cloze score" and "reading level"?Clozeis a deletion test invented by Taylor (1953). The36.91score, above, means that roughly that 37% of the words could be deleted and the passage could still be understood. So, a
higher cloze score is more readable. They "range from 58 and above for the easiest passages to 10-15 and below for the most difficult" (Chall & Dale, p. 75).Reading levelis the grade level of the material, in years of education. The scale is from1to16+.Seethe integration test filefor text samples from the book, along with their scores.Why yet another Dale-Chall readability library?It's 2022 and there are probably a half-dozen implementations on PyPI.
So why create another one?The existing libraries have issues that made me wonder if the results were accurate. For example:From my reading, I saw thatreading levelsare a set of
ten "increasingly broad bands" (p. 75).
And they have labels like3and7-8.
The existing readability libraries treat these as floating point numbers.
But now I believe that an enumeration — or specifically,
aLiteral— captures the formula better:Literal["1", "2", "3", "4", "5-6", "7-8", "9-10", "11-12", "13-15", "16+"]I also couldn't find a good description of this "new" Dale-Chall formula, and how the
existing libraries implement it.The readability scores are important for my international dictionary app:
It shows definitions sorted with the most readable first, to increase comprehension.The entry for amicus curiaeis a good example.
But I was getting odd results on some pages.Use Test-Driven Development to squash bugs and prevent regressions.Turn examples from the book into test cases.Write with modern Python. I'm no expert, so I'm learning as I go along. E.g.,It passesPyright strict-mode type-checking.It uses recent type enhancements likeLiteral.Present a very easy API to use in any app or library.No need to instantiate an object and learn its API.Just import the needed function and call it.The result is a library that provides, I think, more accurate readability scores.ReferencesChall, J., & Dale, E. (1995).Readability revisited: The new Dale-Chall readability formula.
Brookline Books.Taylor, W. (1953).Cloze procedure: a new tool for measuring readability.Journalism Quarterly, 33, 42-46.
Package: new-dash-opsramp-analytics-utils
OpsRamp Analytics UtilitiesThis is the SDK for writing OpsRamp analytics apps. It is based ondash, and it has a number of utility functions.It containsanalysis wrapper project.It is published onPypiHow to publish on PypiAfter make updates on SDK, modify the version insetup.py.python setup.py sdist bdist_wheel
python -m twine upload dist/*

Note: if above command not works, then use below command
python -m twine upload --skip-existing dist/*To upgrade the sdk for your apppip install --no-cache-dir --upgrade opsramp-analytics-utils