Saravanan666/pypi-org huggingface dataset:
Package: riemapp
riemappriemapp is a fast, easy-to-use, minimal library for Python 3.7+ that aliasesmanim0.16.0+ functions for
visualising animated and intuitive complex mappings (transformations from the
real plane to the complex plane) for various shapes and real-valued functions in
two dimensions. It uses a minimum number of dependencies throughFFmpegandpangocairoon Linux.Users and learners may use riemapp to:Plot (user-defined)PointsLinesTrianglesSquaresRectanglesOther regular polygonsCirclesIrregular polygons…and so onCreate smooth, precise animations for plotted figures and map them on the
Argand plane according to user-defined complex functions.Save these animations and play them in the default video player availableStructureRight now,riemappaliases the geometries provided bymanimunderriemapp.geometry. Users can either use these alias classes or directly use
theMObjects provided bymanim.riemappprogrammatically generatesmanimanimations, and the code for this
is available underriemapp.core. All of the information added by a user is
passed into a placeholder class which inheritsmanim.Scene. This class'
object is then used to render the animation.InstallationInstall dependenciesFFmpegInstall FFmpeg through theirdownload pageor your system's package manager (apt,brew, ...) or cloneSaransh-cpp/FFmpeg.Add thebinfolder to system path.pangocairo(Linux systems)Installlibpango1.0-devif you are on a Linux system -sudo apt-get update
sudo apt install libpango1.0-devInstall riemappriemappuses modernPythonpackaging and can be installed usingpip-python -m pip install riemappUsage exampleIn[1]:importriemappasrpManimCommunityv0.16.0.post0In[2]:importnumpyasnpIn[3]:square=rp.geometry.Square(2.)In[4]:squareOut[4]:Square(side_length=2.0)(aliasformanim.Square)In[5]:cm=rp.ComplexMap(square,lambdaz:np.e**z)In[6]:cmOut[6]:ComplexMap(f=Square(side_length=2.0)(aliasformanim.Square),transformation=<lambda>)In[7]:cm.generate_animation(run_time=2.)Out[7]:Animate(f=Square(side_length=2.0)(aliasformanim.Square),transformation=<lambda>)In[8]:cm.render(preview=False)https://user-images.githubusercontent.com/74055102/193077326-2c21cb9e-eb24-473e-b69c-3376f7664ecd.mp4ContributingIf you want to contribute toriemapp(thanks!), please have a look at ourContributing Guide.
Package: rife-ncnn-vulkan-python
RIFE ncnn Vulkan PythonIntroductionrife-ncnn-vulkanis nihui's ncnn implementation of Real-Time Intermediate Flow Estimation for Video Frame Interpolation.rife-ncnn-vulkan-python wrapsrife-ncnn-vulkan projectby SWIG to make it easier to integrate rife-ncnn-vulkan with existing python projects.DownloadsLinux/Windos/Mac X86_64 binary buildreleasesare available now.BuildFirst, you have to install python, python development package (Python native development libs in Visual Studio), vulkan SDK and SWIG on your platform. And then, there are two ways to build it:Install source distribution from PyPI (Currently in developing, need to download models before build.)Use setuptools to build and install into python package directly.Use CMake directly (The old way)Install from PyPIpipinstallrife-ncnn-vulkan-pythonUse setuptoolspythonsetup.pyinstallUse CMakeLinuxgitclonehttps://github.com/ArchieMeng/rife-ncnn-vulkan-python.gitcdrife-ncnn-vulkan-python
gitsubmoduleupdate--init--recursive
cmake-Bbuildsrccdbuild
makeWindowsI used Visual Studio 2019 and msvc v142 to build this project for Windows.Install visual studio and open the project directory, and build. Job done.The only problem on Windows is that, you cannot useCMake for WindowsGUI to generate the Visual Studio solution file and build it. This will make the lib crash on loading.One way isusing Visual Studio to open the project as directory, and build it from Visual Studio.
And another way is build it from powershell just like what is written in therelease.ymlAbout RIFERIFE (Real-Time Intermediate Flow Estimation for Video Frame Interpolation)https://github.com/hzwer/arXiv2020-RIFEHuang, Zhewei and Zhang, Tianyuan and Heng, Wen and Shi, Boxin and Zhou, Shuchanghttps://rife-vfi.github.iohttps://arxiv.org/abs/2011.06294UsagesExample Programfromrife_ncnn_vulkan_pythonimportRifefromPILimportImagewithImage.open("input0.png")asimage0:withImage.open("input1.png")asimage1:rife=Rife(gpuid=0)# or RIFE(0) like upstreamimage=rife.process(image0,image1)image.save("output.png")If you encounter a crash or error, try upgrading your GPU driver:Intel:https://downloadcenter.intel.com/product/80939/Graphics-DriversAMD:https://www.amd.com/en/supportNVIDIA:https://www.nvidia.com/Download/index.aspxModelmodelupstream versionrife1.2rife-HD1.5rife-UHD1.6rife-anime1.8rife-v22.0rife-v2.32.3rife-v2.42.4rife-v3.03.0rife-v3.13.1rife-v44.0rife-v4.64.6Original RIFE Projecthttps://github.com/hzwer/arXiv2020-RIFEOther Open-Source Code Usedhttps://github.com/Tencent/ncnnfor fast neural network inference on ALL PLATFORMShttps://github.com/webmproject/libwebpfor encoding and decoding Webp images on ALL PLATFORMShttps://github.com/nothings/stbfor decoding and encoding image on Linux / MacOShttps://github.com/tronkko/direntfor listing files in directory on Windowshttps://github.com/nihui/rife-ncnn-vulkanthe original rife-ncnn-vulkan project
Package: rife-ncnn-vulkan-python-TAS
This is but a minimalist version of rife-ncnn-vulkan with updated models for my script.
it will contain the latest models + rife4.6 for speedy inference, head to releases to download the wheels.
Windows only cuz I cba to figure out why Mac and Linux won't build.Credit to the creators and maintainersInstall through pypipipinstallrife-ncnn-vulkan-python-TASIntroductionrife-ncnn-vulkanis nihui's ncnn implementation of Real-Time Intermediate Flow Estimation for Video Frame Interpolation.rife-ncnn-vulkan-python wrapsrife-ncnn-vulkan projectby SWIG to make it easier to integrate rife-ncnn-vulkan with existing python projects.Original RIFE Projecthttps://github.com/hzwer/arXiv2020-RIFEOther Open-Source Code Usedhttps://github.com/Tencent/ncnnfor fast neural network inference on ALL PLATFORMShttps://github.com/webmproject/libwebpfor encoding and decoding Webp images on ALL PLATFORMShttps://github.com/nothings/stbfor decoding and encoding image on Linux / MacOShttps://github.com/tronkko/direntfor listing files in directory on Windowshttps://github.com/nihui/rife-ncnn-vulkanthe original rife-ncnn-vulkan project
Package: riff
RiffRuff + diff = RiffRunRuff⚡, and filter out violations not caused by your branch.
Riff usesgit diffto detect code lines modified in the current branch, and filters Ruff's output accordingly.
Riff only fails when violations are detected in modified lines.RationaleRuff doesn't have a baseline feature, so Riff can come handy for enforcing Ruff rules in larger repositories quickly, without having to fix every single existing violation.UsageLocallyRunriff, followed by Riff arguments (optional, see below), and Ruff arguments (optional, see limitations).Runningriffwithout arguments will run it in the current directory.Riff expects to be run in a repository folder.As a pre-commit hookCopy this to your.pre-commit-configfile- repo: https://github.com/dorschw/riff
  hooks:
  - id: riff
    rev: v0.0.287.0To pass other arguments to Riff (and Ruff), add theargskey, e.g.args: ["--base-branch=origin/master"]Argumentsalways_fail_on: comma-separated list of Ruff error codes. When detected by Ruff, Riff will consider them as failures, even if they're not in lines modified in the current branch.print_github_annotation: boolean (defaultfalse). When set totrue, will addGitHub Annotations, making the violations more visible when reviewing code in GitHub'sModified Filestab.base_branch: string (defaultorigin/main). Change toorigin/masteror whatever your base branch is named.LimitationsWhen using Ruff's--fixfeature, Ruff will fix everything it isconfiguredto, regardless of the modified lines. Riff cannot control this behavior.Riff cannotcurrentlyrun Ruff with a--formatconfiguration. (seehere)
Package: riffaraffa
riffaraffaLa riffa e la raffa python package.Free software: MIT licenseDocumentation:https://riffaraffa.readthedocs.ioGitHub repo:https://github.com/robertopreste/riffaraffaFeaturesShow available moviesRandomly choose a movie to watchAdd a new movie to the listUsageCommands:add     Add a movie to the database.
choose  Choose a movie from the list.
show    Show available movies from the database.Installationpip install riffaraffaCreditsThis package was created withCookiecutterand thecc-pypackageproject template.History0.1.0 (2019-11-06)First release.0.2.0 (2020-04-28)Refactor to use GSheet to keep track of movies.
Package: riffdog
riffdogRiffdog Terraform / Reality scanner - finding 'things' in the Real World which
Terraform didn't put there.This project works by firstly loading your terraform state files -notyour
terraform files, and building a memory object that represents what terraformthinksit has deployed. The second step is then to access your environment
and actually look whatisthere, and it builds another memory object.Then it compares the two, and looks for:Things that TF put there, but arn't thereThings that are there, that TF doesn't know aboutFor this to work, youmustinstall a resouce pack, for instanceriffdog_awsCommand line vs LibraryRiffdog is both a command line tool and a python library. The command line tool
basically creates a config object and calls the scan method.To install (for example with the AWS resources)$ pip install riffdog[aws]To run:$ riffdog -b bucketname_containing_statesFor full command line reference, please see the docs #FIXME - link to docs!Light vs Full Scan modeAWS and Terraform are very complex: for instance, a EC2 instance is a computer,
a collection of network cards, volumes, etc. In 'light' mode, we do a high level
scan to see if all the main components are there - in 'full' mode, it inspects
all elements (as far as RiffDog is aware of, see below) - i.e. checks that all
network cards, volumes, etc are mounted as intended.IgnoresIts important to realise that not all infrastructure is deployed via TF - for
instance auto scaling, or service discovery systems may be interacting with your
infrastructure, and this is OK, but you don't want RiffDog raising alerts on
those.Caveats:This is pretty muchalwaysa work under development, as AWS adds more features
modules etc. The system is designed to be modular, but we're only able to keep
up with modules that we use - so if you use a feature of AWS that we don't scan
please feel free to add a module. If you need help, please contact us or file
a ticket.TestingAutomated testing of this system is quite difficult. Ultimatly these are here to make sure that changes to internal data structures do not break other functions (e.g. some data objects such as network interfaces are used by multiple features: both EC2 instances and Lambdas). The real test is whether it works against the current Terraform and AWS API's, not a snapshot from previous years.Tests go into the tests folder,Tox is used to make sure compatibility with various versions of python & libraries
Package: riffusion-api
Riffusion Reverse APIThe Riffusion API provides a convenient way to generate music with lyrics using Riffusion.InstallationTo use this package, you'll need to install it and its dependencies. You can do this with pip:pipinstallriffusionUsageHere's a basic example of how to use this package to generate a song:fromriffusion.riffimportsing# Define your lyrics and stylelyrics="Hey guys, how's it going"style="Pop"# Generate audio and visual variationssing(lyrics,style)DependenciesThis package relies on several external libraries:requests: for making HTTP requests to the Riffusion API.json: for working with JSON data.base64: for decoding base64-encoded data.os: for file and directory operations.moviepy: for video and audio editing.
Make sure to install these dependencies along with the package.Please note, this is not an official package or API
Package: rifmator_engine
This is a small module for Python that allows you to find the rhyme to established Russian word.Working with module1) Search rhyme the wordSearch rhymes is the method of find_rhyme class Rifmator. To search, simply call this method an instance of the class Rifmator, and pass as a parameter remueve word. If the rhyme is not found will return None, otherwise return a list of rhymes.P. S:If the rhyme is not found poprobute to indicate the emphasis in the word upper case the stressed vowel, because the word is not found in the dictionary and it was not possible to calculate the stress machine.2) Adding words to the dictionaryIf you need to add a new word to the dictionary, use the add_word method in class Rifmator. In the entered word must include the indication of stress of the upper register of the stressed vowel. After calling the function it will return True or False depending on success or failure adding to the dictionary, respectively.3) Save a dynamic dictionary in a fileAll actions happen with a dictionary in memory, then there is work with a dynamic dictionary. If you want something to change in the dictionary had acted upon the next startup use the method save_dicts class Rifmator.5) configuration ModuleAll module settings are in the file config.py. The following changes are available:rhymes_dict - Path to head points rhyming dictionaryling_dict - Path to file-linguistic dictionaryuse_wiki - whether to Use linguistical studies in the analysis of the word Wiktionary (requires Internet connection)learning - Auto-learning of words for the introductionThe full version of the documentation read:https://github.com/alxmamaev/Rifmator_Engine
Package: rift-framework
RiftA magicalPython3->TONportalRift is a full-stack development framework forTON (The Open Network)that makes it easy for developers to use Python to develop, test, and deploy smart contracts on the TON network. With Rift, you can leverage the simplicity and versatility of Python to build and interact with TON, without having to learn the complexities of FunC or Fift. For examples of how Rift simplifies these processes, visitRift's website.FeaturesDevelop smart contracts using Python syntax and OOP featuresInteract with the TON network to query data and deploy contractsTest smart contracts with an easy-to-use testing frameworkStandalone framework that only requiresPython 3.10Can be used at any stage of the project, from development to testing to deploymentQuick StartInstallPython 3.10+Installriftpipinstallrift-framework# or from sourcegitclonehttps://github.com/sky-ring/riftcdrift
pipinstall-e.Initialize your project:riftinit<project-name>Develop your contracts in<project>/contracts/Write your tests in<project>/tests/Place your deploy scripts in<project>/deployers/Useriftto build, test, or deploy:# in project folder# builds TARGETriftbuildTARGET# tests TARGETrifttestTARGET# deploys TARGETriftdeployTARGETFor more information, visit the documentation website atdocs.skyring.io/rift.GuidesStep-by-step guide on how to useRiftto develop on TON:Coming Soon!Step-by-step guide on integratingRiftinto existingFunCprojects:Coming Soon!Standard Contracts ImplementationJetton Implementation (jettons)NFT ImplementationDEX ImplementationRoadmapMilestone 1: Python Framework for Contract DevelopmentSemi One-to-One Mapping of Functions and Expressions (Base Compiler, Python -> FunC)First Higher Layer over the Base Mappings to Simplify Type Calls (leveraging OOP Capabilities)Second Higher Layer over the Base, Simplifying Contract Development towards Maximizing Code Reusability and Simplicity (leveraging Meta Programming Capabilities)Providing Standard Smart Contracts Implementation with RiftMilestone 2: Deploying, Testing, Interaction CapabilitiesSimple Interaction Interface with TON BlockchainSimple Deploying Options of Developed ContractsTesting Framework for the Contracts Developed with RiftMilestone 3: What's Next?Stay Tuned! We have extra plans that we will share soon with the community to further developRift.Support the ProjectIfRifthas been a lifesaver for you, giving it a star on GitHub is the ultimate high five!You can also show your love by contributing toRiftthrough code, ideas, or even a kind word.Feeling extra generous? TreatRiftto a coffee by donating to this TON address:EQAIhZCDT7-pvweWh6c_76X7Dnv6Qlzt7-l1NNP8upZ_AreuFinally, spreading the word aboutRiftis a big boost for the project and helps us reach more people.ContributingIf you're interested in contributing to Rift, please seeCONTRIBUTING.mdfor the necessary specifications and procedures.SupportersSpecial thanks to theTON Societyfor their support and grant, without which the project would not be feasible.
Package: rift-tonlib
PyTONLibThis is standalone Python library based onlibtonlibjson, the functionality is similar to theton-http-apiwith the following restrictions:a client can connect to only one LiteServer;a client is asyncronious;no requests cache.InstallationFrom PyPiCurrently, the library works for Windows, Mac and Linux only on Intel CPUs:(Windows) Install OpenSSL v1.1.1 for Win64 fromhere.Install Python 3 package:pip3 install pytonlib.DockerIn this repo Compose file is provided to deploy the example of service withpytonlib:docker-compose-fdocker-compose.jupyter.yamlbuild
docker-compose-fdocker-compose.jupyter.yamlup-dJupyter Notebook will be available on port 3100 (http://localhost:3100).ExamplesWe recommend to use IPython or Jupyter Notebook for prototyping because they allow to runasynccode. An example of runningasynccode from script could be found in the end of this section.Connecting to the first LiteServer in mainnet config:importrequestsimportasynciofrompathlibimportPathfrompytonlibimportTonlibClient# downloading mainnet configton_config=requests.get('https://ton.org/global.config.json').json()# create keystore directory for tonlibkeystore_dir='/tmp/ton_keystore'Path(keystore_dir).mkdir(parents=True,exist_ok=True)# init TonlibClientclient=TonlibClient(ls_index=0,# choose LiteServer index to connectconfig=ton_config,keystore=keystore_dir)# init tonlibjsonawaitclient.init()Reading blocks info:masterchain_info=awaitclient.get_masterchain_info()block_header=awaitclient.get_block_header(**masterchain_info['last'])shards=awaitclient.get_shards(master_seqno=masterchain_info['last']['seqno'])Reading Block Transactions for masterchain block:masterchain_info=awaitclient.get_masterchain_info()txs=awaitclient.get_block_transactions(**masterchain_info['last'],count=10)Running async code from script:importrequestsimportasynciofrompathlibimportPathfrompytonlibimportTonlibClientasyncdefmain():loop=asyncio.get_running_loop()ton_config=requests.get('https://ton.org/global.config.json').json()# create keystore directory for tonlibkeystore_dir='/tmp/ton_keystore'Path(keystore_dir).mkdir(parents=True,exist_ok=True)# init TonlibClientclient=TonlibClient(ls_index=0,# choose LiteServer index to connectconfig=ton_config,keystore=keystore_dir,loop=loop)# init tonlibjsonawaitclient.init()# reading masterchain infomasterchain_info=awaitclient.get_masterchain_info()# closing sessionawaitclient.close()if__name__=='__main__':asyncio.run(main())Running testsTo run tests inasynciomode use the following command:PYTHONPATH=./pytest--asyncio-mode=stricttests/
Package: rigatoni
RigatoniPython Server Library for NOODLES ProtocolDescriptionThis server library implements the NOODLES messaging protocol and provides objects for maintaining a scene in state.
The server uses a websocket connection to send CBOR encoded messages. To customize its implementation, the library
provides convenient interface methods to assist the user in writing their own methods for the server. The user can
also add custom delegates to add additional functionality to any of the standard components.DocumentationFor more information, check outthe documentation.InstallationInstallation is as simple as:pipinstallrigatoniFor optional dependencies and support for meshes and geometry object creation, you can installpipinstallrigatoni[geometry]Simple ExampleimportrigatoniasrigclassCustomTable(rig.Table):extra_info=Nonedefhandle_clear(self):print("Clearing table")defbasic_method(server,context):print("Hello World!")starting_state=[rig.StartingComponent(rig.Method,{"name":"basic_method","arg_doc":[]},basic_method),]delegates={rig.Table:CustomTable}withrig.Server(50000,starting_state)asserver:# do stuffpassHungry for more NOODLES?For more information and other related repositories check outthis collection
Package: rigcollector
Rigcollector is the Python client forRigsMonitoringa a web application that allows yous to monitor your mining rigs, bytracking system metrics(CPU, MEM, Disks, Network, Processes…) andmining-related metrics(GPU temperature, Hashrate, BTC Balace…).Rigcollector is bundled with the following collectors:System Metrics (CPU, MEM, load, disks, network)ATI GPU temperature for linux, and GPU-Z for WindowsProcesses InfoInfos from MtGox, Slush’s mining pool…You can easily create and use your own collector.InstallationYou can install rigcollector viaeasy_installorpip.$ pip install rigcollectorUsageBasic usage, “rigcollector -h” or “bakcollector collect -h” to show the help.You can get your rig API key in yourrig settingson RigsMonitoring.$ rigcollector collect --api-key your_rig_api_keyIf everything is ok, you can run the process in the background:$ rigcollector collect --api-key your_rig_api_key --detach 1By default, the AtiGpuCollector is disabled, to enable it…ConfigurationHere is a basicrigcollector.ymlconfig file, see below for more informations on cu
stoms collectors.Rigcollector check for a configuration file namedrigcollector.ymlbut you can set a different config file with-coption:$ rigcollector collect --api-key your_rig_api_key -c yourconfigfile.ymlProcessesCollector:
  processes:
    - bitcoind

CustomCollector:
  custom:
    - rigcollector.custom.SlushsPoolCollector
    - rigcollector.custom.MtGoxCollector

SlushsPoolCollector:
  token: YOUR_TOKEN

MtGoxCollector:
  auth_key: YOUR_AUTH_KEY
  auth_secret: YOUR_SECRET_KEYYou can desactivate any Collector with theis_activedirective.ProcessesCollector:
  is_active: 0Custom CollecorRigcollector is bundled with few customs collectors, please create a pull request if you create one.SlushsPoolCollector, gather information fromSlush Mining Pool API.MtGoxCollector, get your BTC balacnce from your MtGox accountMtGox.Create your own CollectorYou can take a look at DummyCollector in rigcollector.custom.dummy, it contains everything to get you started.License (MIT)Copyright (c) 2013 Thomas SileoPermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.