Saravanan666/pypi-org huggingface dataset:
Package: nanohelp
nanohelpBusiness logic to abstract the raw nano node RPC logicDocumentationhttps://nanohelp.readthedocs.io/en/latest/Installationpip install nanohelpUsagefromnanohelp.secretimportSecretManagerfromnanohelp.walletimportWalletManager# Initialize a SecretManagersecret_manager=SecretManager()# Initialize a WalletManager, passing in the secret managerwallet_manager=WalletManager(secret_manager)# Define user and project detailsuser1="user1"user2="user2"project_id="my-project"# Create a new wallet for User1, this also generates and stores a new private keywallet_id_user1,account_address_user1=wallet_manager.create_wallet(user1)# Create a new wallet for User2wallet_id_user2,account_address_user2=wallet_manager.create_wallet(user2)# Transaction from User1's account to User2's accountamount=1000# amount of Nano to be senttransaction_block=wallet_manager.make_transaction(wallet_id_user1,account_address_user1,account_address_user2,amount,secret_manager.get_private_key(project_id,user1))# Print transaction blockprint(f"Transaction block:{transaction_block}")
Package: nanohttp
nanohttpA very micro HTTP framework.documentationContributionBranchingA new branching model is applied to this repository, which consists of a
master branch and release branches.Master branchThe master branch is an integration branch where bug fixes/features are
gathered for compiling and functional testing.Release branchThe release branch is where releases are maintained and hot fixes
(with names like release/v2.x.x) are added. Please ensure that all your
production-related work are tracked with the release branches.With this new model, we can push out bug fixes more quickly and achieve
simpler maintenance.
Package: nanohub-remote
NanohubtoolsA set of tools/apps to run on nanohubInstallationpip install nanohub-remoteUsageimportnanohubremoteasnrauth_data={'client_id':XXXXXXXX,'client_secret':XXXXXXXX,'grant_type':'password','username':XXXXXXXX,'password':XXXXXXXX}# to get username and password, register on nanohub.org (https://nanohub.org/register/)# to get client id and secret, create a web application (https://nanohub.org/developer/api/applications/new), use "https://127.0.0.1" as Redirect URLsession=nr.Session(auth_data)Available Nanohub PointsToolsTOOLNAME=''# valid Nanoohub tool name e.g. pntoytool=nr.Tool(auth_data)# Get Available input parametersparams=tool.getToolParameters(TOOLNAME)# Submit a simulation experimentjob_id=tool.submitTool(params)# Check Statusstatus=tool.checkStatus(job_id['job_id'])# Get Resultsresults=tool.getResults(job_id['job_id'])# Submit an wait for resultsresults=tool.submitTool(params,wait_results=True)Sim2LsTOOLNAME=''# valid Nanoohub tool name e.g. pntoys2l=nr.Sim2L(auth_data)# Get Available input parametersparams=s2l.getToolParameters(TOOLNAME)# Submit a simulation experimentjob_id=s2l.submitTool(params)# Check Statusstatus=s2l.checkStatus(job_id['job_id'])# Get Resultsresults=s2l.getResults(job_id['job_id'])# Submit an wait for resultsresults=s2l.submitTool(params,wait_results=True)
Package: nanohubtools
NanohubtoolsA set of tools/apps to run on nanohubInstallationpipinstallnanohubtoolsUsageimportnanohubtoolsasntauth_data={'client_id':XXXXXXXX,'client_secret':XXXXXXXX,'grant_type':'password','username':XXXXXXXX,'password':XXXXXXXX}# to get username and password, register on nanohub.org (https://nanohub.org/register/)# to get client id and secret, create a web application (https://nanohub.org/developer/api/applications/new), use "https://127.0.0.1" as Redirect URLtool=nt.Qdotexplorer(auth_data,parameters={'Number of States'},modal=True,mode='split-right')# modal defines if the container outputs to use FloatView or standard ipywidgets Output# mode defines the positions of new windows of Floatview is enabledtool.loadExperiment('IDSESSION')IfanexperimentwascreatedbeforesAvailable Nanohub ToolsBravaisViewerSimplified, supported byCrystal Viewer Toolnt.CrystalViewerConstructor(auth_data,modal=False)CrystalViewerSimplified, supported byCrystal Viewer Toolnt.CrystalViewerConstructor(auth_data,modal=False)CrystalLab, supported byCrystal Viewer Toolnt.CrystalLab(auth_data)CrystalViewerMaterial, supported byCrystal Viewer Toolnt.CrystalViewerMaterial(auth_data,modal=False)CrystalViewerBravais, supported byCrystal Viewer Toolnt.CrystalViewerBravais(auth_data,modal=False)CrystalViewerConstructor, supported byCrystal Viewer Toolnt.CrystalViewerConstructor(auth_data,modal=False)SimpleQuantumDot, supported byQuantum Dot Labnt.SimpleQuantumDot(auth_data,modal=False)StackedQuantumDot, supported byQuantum Dot Labnt.StackedQuantumDot(auth_data,modal=False)PNToy, supported by [PN Junction Lab] (https://nanohub.org/resources/pntoy)nt.PNToy(auth_data,modal=False)Driftdiffusionlab, supported by [Drift-Diffusion Lab] (https://nanohub.org/resources/semi)nt.Driftdiffusionlab(auth_data,modal=False)DFTExplorer, supported by [DFT calculations with Quantum ESPRESSO] (https://nanohub.org/resources/dftqe)nt.DFTExplorer(auth_data,modal=False)
Package: nanohub-uidl
Nanohub - UIDLUIDL StatsLatest ReleasePyPI DownloadsA set of tools to create Javascript apps to consume nanohub WSInstallationpip install nanohub-uidlUsagefromnanohubuidl.teleportimportTeleportProject,TeleportElementfromnanohubuidl.materialimportMaterialContentfromnanohubuidl.authimportAUTHProject=TeleportProject("My App")Component=Project.rootComponent.addStateVariable("myvariable",{"type":"boolean","defaultValue":True})STATE_LOADER_STATUS="loader_status"STATE_LOADER_OPEN="loader_open"STATE_ERROR_STATUS="error_status"STATE_ERROR_OPEN="error_open"Login,CLogin=Auth.Login(Project,Component,client_id="MYAPPID",client_secret="MYAPPSECRET",url="https://nanohub.org/api/developer/oauth/token",open_state=STATE_LOGIN_OPEN)Login.content.events["onError"]=[{"type":"stateChange","modifies":STATE_ERROR_OPEN,"newState":True},{"type":"stateChange","modifies":STATE_ERROR_STATUS,"newState":'$e'},]Login.content.events["onAuth"]=[{"type":"stateChange","modifies":STATE_ERROR_OPEN,"newState":False},{"type":"stateChange","modifies":STATE_LOADER_OPEN,"newState":False},]Grid=t.TeleportElement(MaterialContent(elementType="Grid"))Button=MaterialBuilder.Button(title="Reset Setting",variant="text",onClickButton=[{"type":"stateChange","modifies":"parameters","newState":resetSettings}])Grid.addContent(Button)Component.addNode(Grid)Project.buildReact("Myapp.html");
Package: nanoid
Nano IDA tiny, secure, URL-friendly, unique string ID generator for Python.Safe. It uses cryptographically strong random APIs and tests distribution of symbols;Compact. It uses a larger alphabet than UUID (A-Za-z0-9_-). So ID size was reduced from 36 to 21 symbols.UsageInstall Nano ID using pip:pip install nanoidNormalThe main module uses URL-friendly symbols (A-Za-z0-9_-) and returns an ID with 21 characters (to have a collision probability similar to UUID v4).fromnanoidimportgenerategenerate()# => NDzkGoTCdRcaRyt7GOepgSymbols-,.()are not encoded in the URL. If used at the end of a link they could be identified as a punctuation symbol.If you want to reduce ID length (and increase collisions probability), you can pass the length as an argument.fromnanoidimportgenerategenerate(size=10)# => "IRFa-VaY2b"Don’t forget to check the safety of your ID length in IDcollision probability calculator.Custom Alphabet or LengthIf you want to change the ID's alphabet or length you can use the internal generate module.fromnanoidimportgenerategenerate('1234567890abcdef',10)# => "4f9zd13a42"Non-secure API is also available:fromnanoidimportnon_secure_generatenon_secure_generate('1234567890abcdef',10)ToolsID size calculatorto choice smaller ID size depends on your case.
nanoid-dictionary with popular alphabets to use with nanoid/generate;nanoid-dictionarywith popular alphabets to use.Other Programming LanguagesC#Clojure and ClojureScriptCrystalDartGoElixirHaskellJavaJavaScriptNimPHPRubyRustSwiftChangelogv2.0.0Replace ~ to - in default alphabetAdd non-secure fast generatorReduce default characters from 22 to 21v0.3.0Fix array out of bound error.CreditsAndrey Sitnik forNano ID;Dair Aidarkhanovfor main contribution to v2.0, and adding test cases.Aleksandr Zhuravlev forID collision probability.
Package: nanoid-dictionary
Alphabets and string functions designed to be used withNano ID.Installationpipinstallnanoid-dictionaryUsageAvailable alphabets and functions:alphabet_stdhuman_alphabetlookalikeslowercasenumbersprevent_misreadings(unsafe_chars, alphabet)uppercaseprevent_misreadings(unsafe_chars, alphabet)accepts a string and removes all the characters that look similar by default. The function is also case-insensitive.fromnanoid_dictionaryimport*alphabet_std# => _-0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZhuman_alphabet# => _-23456789abcdefghijkmnpqrstuvwxyzABCDEFGHIJKMNPQRSTUVWXYZlookalikes# => 1l0olowercase# => abcdefghijklmnopqrstuvwxyznumbers# => 0123456789prevent_misreadings(lookalikes,'a1l0o')# => auppercase# => ABCDEFGHIJKLMNOPQRSTUVWXYZThanks toAndrey Sitnik forNano ID.Aleksandr Zhuravlev for incredibleNano ID calculator.
Package: nanoinject
NanoinjectNanoinject is a terrifically small and simple dependency injection container
for Python 3.6+. Its' key features:Easy enough to use in five minutes.Configurable in code or config files.Pretty feature complete.Installationpip install nanoinjectUse guideDependency injection is a way to achieveInversion of Control.Use in codeclassA:value=42classB:def__init__(self,a):self.a=ac=Container()c.add('a',lambdac:A())c.add('b',lambdac:B(c.get('a')))assert42==c.get('b').a.valueUsing configurationIt starts with declaring your services in YAML format:values:scalar_value:42services:a:class:Amodule:example.adependencies:-value:scalar_valueb:class:Bmodule:example.bdependencies:-aAnd then letting the config object configure the container based on that YAML file:importosfromnanoinjectimportContainer,ConfigclassA:def__init__(self,value):self.value=valueclassB:def__init__(self,a):self.a=ac=Container()config=Config.from_yaml_file(os.path.dirname(__file__)+'/services.yaml')config.config(c)assert42==c.get('b').a.value
Package: nanoinsight
NanoINSightNanoINSight is a repeat annotation tool for insertions called byNanoVar.Installation:Option 1: Using Pippip install nanoinsightOption 2: Cloning from GitHub repositorygit clone https://github.com/benoukraflab/nanoinsight.git
cd nanoinsight
pip install .Installation of dependencies1.MAFFTOption 1: Condaconda install -c bioconda mafftOption 2:Please visithereto download the "without_extensions" source package
and visitherefor instructions to install.Please note that MAFFT source package with extnesions is not needed as it supports RNA structural alignments.Path of executable binary is needed. You can get it by typing "which mafft" in the terminal window.2.RepeatMaskerOption 1: Condaconda install -c bioconda repeatmaskerOption 2:Please visitherefor instructions to install.Run:Option 1: Run with NanoVar command by adding the "--annotate_ins [species]" parameternanovar [Options] --annotate_ins human sample.fq/sample.bam ref.fa working_dirFor more details: seeNanoVar wikiOption 2: Run via the command-linenanoinsight [-h] [-v] [-q] [-t int] [-i path] [-u path] [-m path] [-r path] 
            [-s species] [VCF] [working_directory]

Example:
        nanoinsight -t 4 -s human sample.nanovar.pass.vcf ./work_dirRequired parameters:ParameterDescription-sSpecify species for repeatmasker (e.g. human)[VCF]Path to VCF input file[working_directory]Path to working directoryAdditional Parameters:ParameterDescription-hShow help message-vShow version-qhide verbose-tNumber of threads to be used [1]-iPath to ins_seq.fa file (NanoVar output)-uPath to sv_support_reads.tsv file (NanoVar output)-mPath to mafft executable file-rPath to RepeatMasker executable fileOutput:OutputDescription.ins.con.fastafasta file of consensus sequences of insertions found in the VCF input filerm_outputoutput directory ofRepeatMaskerCitation:If you use NanoINSight, please cite:Authors:Asmaa Samy-AsmaaSamyMohamedMahmoud.Tham Cheng Yong-cytham.Touati Benoukraf-benoukraflab.
Package: nano-keras
nano-kerasOverviewnano-kerasis a deep learning library written in Python usingNumPy. It's designed to handle the creation and training process of most neural network types, allowing you for quick and easy prototyping and deployment.The project is heavily inspired byKeras, the most popular deep learning API in the world, as I'm trying to implement my library in simmilar style and functionality to KerasKey Features- Simplicity: Built using Python and NumPy, making it easy to read and understand each part- Educational: Intended as a learning tool to understand neural network components at a lower level- Customization: Allows for tinkering and understanding the core mechanics of neural network operationsWhat you can find in nano-kerasLayers: Dense, Dropout, Reshaping layers, Convolutional layers, Pooling layers and Recurrental LayersOptimizers: SGD, Adam, Adadelta, Adagrad, RMSProp, NAdam and much moreActivation functions: Sigmoid, Tanh, ReLU, ELU, LeakyReLU, SoftmaxLoss functions: MAE, MSE, BCE, CCE, Hinge, HuberCallbacks: EarlyStopping, LearningRateScheduler, CSVLoggerAnd much more, you can find all the implemented items inhereInstalationnano-kerasis available onPyPIso in order to download it open a terminal and paste:pipinstallnano-kerasYou now should have succesfully installed nano-keras so to use it in your python file you only need to import it like this:importnano_kerasIf you have an issue message me on github or send me an emailDocumentationDocumentation is under development and should be finished in the next few daysYou can access ithereLicenseThis project is licensed under the MIT License - see the LICENSE file for detailsSpecial thanksI'd like to thank my teacher,Mateusz Kozlowski, who inspired me to start working on this project and kept me motivated to finish thisEveryone who showed support for me in real life and on LinkedInWithout you this project would've never come to life
Package: nanolab
##NanoLabNanoLab is an easy-to-use testing tool designed to run test cases against a local network of nano-nodes. It utilizesNanoMock, a highly customizable tool for creating dockerized nano networks, to facilitate quick and efficient testing of various configurations. Simply provide a config file for the test case and watch NanoLab streamline your testing process.###Features:Run test cases against a local network of nano-nodesLeverages NanoMock for dockerized nano network creationSimple configuration with JSONCompatible with Python 3.8+ and Docker###How to install:pip install nanolab###How to use:CommandDescriptionnanolab listList all available testcasesnanolab run -t {testcase}execute a testcase###How to use with options:Commandflag-t --test-caseUse one of the available testcases (nanolab list)Can be a/path/to/config.jsonon your disk--gh-user --gh-repo --gh-pathDefault :gr0vity-dev nanolab-configs defaultUsed innanolab listto show available testcasesUsed innanolab runto download the selected testcase-i --imageList of docker images used per testrun
Package: nanolayer
Nanolayer CLInanolayerhelps keep container layers as small as possible.It does so by automatically deleting any installation leftovers (such as apt-get update lists, ppas, etc)Installationpipx install nanolayerGH Release installation:Usage:nanolayerinstallgh-releasecli/clighExampleFROMpython:3.10RUNapt-get-yupdate&&apt-getinstall-yhtoplayer size:22MBFROMpython:3.10RUNcurl-sfLhttps://github.com/devcontainers-contrib/nanolayer/releases/download/v0.4.0/nanolayer-x86_64-unknown-linux-gnu.tgz|tarfxvz--C/&&\chmod755/tmp/nanolayer&&ls/tmp&&\/nanolayerinstallapt-gethtop&&\rm/nanolayerLayer size:1.6MB
Package: nanoleaf
A Python module for the coolest lights with the worst software support.This module aims to do more than just act as a wrapper for API calls. It
provides several convenience functions to perform more complicated and
robust actions than are possible in some of the other Aurora wrappers
I’ve seen. For instance, being able to switch to a random new effect, or
toggle the on/off state with a single command.Support The ProjectThis is a pet project, and I’m doing it because I need API support just
as badly as you do. But, if it really does make your life better, I’d
appreciate a cup of coffee.BTC: 1Gr31rgb6UXEdXwbwQGUsadcd7AnY7okXT
LTC: Lajqnm28UipLbzJqvyy4tRQFf39xQy6B48InstallIt’s super easy - just use pip to get the latest version.pip install nanoleaf --upgradeSetupThere are two pieces of information you’ll need to control your Aurora:
The IP address and an auth token.Finding IP AddressFor most people, the IP address that the Aurora uses to communicate is
the one assigned by your router, but this might not necessarily be true
depending on your network setup. Either way, you can get this by using
the setup class. After about 90 seconds, this will return a list of the
IP address of every Aurora found on the network.fromnanoleafimportsetupipAddressList=setup.find_auroras()Generate Auth TokenTo generate an auth token, you must first press and hold the power
button on the Aurora for about 5-7 seconds, until the white LED flashes
briefly. Then, call the Setup class like so:fromnanoleafimportsetuptoken=setup.generate_auth_token("192.168.1.129")Be sure to store this auth token somewhere for future use. If you lose
this token, you’ll have to generate another. Personally, I just keep it
in the scripts I’ve written that call this library.ExamplesTurn on and set to an effectfromnanoleafimportAuroramy_aurora=Aurora("169.254.123.123","5EvbR2FjfmYfAkEtOkEnolnZbe6qOB")my_aurora.on=Truemy_aurora.effect="Violets Are Blue"Set multiple Auroras to the same random effectleft_side=Aurora("192.168.1.56","5EvbR2FjfmYfAkEtOkEnolnZbe6qOB")right_side=Aurora("192.168.1.78","fAkeR2FjfmYfAkEtOkEnolnZtOkEn")left_side.effect=right_side.effect_random()Add a new effectPresently, you must create your own raw dict that exactly matches the
structure found on theAPI
documentation.
Methods of making this much easier are planned for future updates.effect_data={"command":"add","animName":"My Random Animation","animType":"random","colorType":"HSB","animData":None,"palette":[{"hue":0,"saturation":100,"brightness":100},{"hue":120,"saturation":100,"brightness":100},{"hue":240,"saturation":100,"brightness":100}],"brightnessRange":{"minValue":25,"maxValue":100},"transTime":{"minValue":25,"maxValue":100},"delayTime":{"minValue":25,"maxValue":100},"loop":True}my_aurora.effect_add_raw(effect_data)Delete an effectmy_aurora.effect_delete("My Random Animation")
Package: nanolib
nanolib[![image](https://img.shields.io/pypi/v/nanolib.svg)](https://pypi.org/project/nanolib/)
[![codecov](https://codecov.io/gh/Matoking/nanolib/branch/master/graph/badge.svg)](https://codecov.io/gh/Matoking/nanolib)
[![Build Status](https://travis-ci.com/Matoking/nanolib.png?branch=master)](https://travis-ci.com/Matoking/nanolib)
[![image](https://readthedocs.org/projects/nanolib/badge/?version=latest)](https://nanolib.readthedocs.io/en/latest/?badge=latest)A set of tools for handling functions related to the NANO cryptocurrency protocol.FeaturesSolve and verify proof-of-workCreate and deserialize legacy and universal blocksAccount generation from seed using the same algorithm as the original NANO wallet and NanoVaultFunctions for converting between different NANO denominationsHigh performance cryptographic operations using C extensions (signing and verifying blocks, and generating block proof-of-work)
* Proof-of-work generation supports SSE2, SSSE3, SSE4.1, AVX and NEON instruction sets for improved performance. The best supported implementation is selected at runtime with a fallback implementation with universal compatibility.Backed by automated testsCompatible with Python 3.6 and upLicensed under the very permissiveCreative Commons ZerolicenseInstallationYou can install the library using pip:` pip install nanolib `nanolib requires a working build environment for the C extensions. For example, on Debian-based distros you can install the required Python header files and a C compiler using the following command:` apt installbuild-essentialpython3-dev`DocumentationAn online copy of the documentation can be found at [Read the Docs](https://nanolib.readthedocs.io/en/latest/).You can also build the documentation yourself by runningpython setup.py build_sphinx.CommandsThesetup.pyscript comes with a few additional commands besides installation:build_sphinx* Build the documentation inbuild/sphinx/html.test* Run tests using pytestspeed* Run a benchmark testing the performance of various cryptographic operations used in the library.Donationsxrb_33psgb1exxuftgjthbz4tsgzm5qmyzawrfzptpmp3nwzousbypqf6bcmrk69
Package: nanolife
Simple pygame implementation of Conway’s Game of Life.ScreenshotInstallationInstall with pip:pip install nanolifeInstall from source:python setup.py installRunningRun via launch script installed with pip package:nanolifeRun as a Python module:python -m nanolifeUsing inside of codeTo import the class in to your own code:from nanolife.LifeGame import LifeGame
LifeGame().run()ControlsThere are a couple keybinds available:q - Quits - Start/stop (toggle pause)r - Randomize the gridLinkshttps://github.com/DevDungeon/NanoLifePyhttps://pypi.org/project/nanolife/ContactNanoDano <nanodano@devdungeon.com>
Package: nanoLLM
nanoLLMnanoLLM is a Python package that provides a flexible and efficient implementation to create LLM bots over extensible dataset.InstallationYou can install nanoLLM directly from PyPI using pip:pipinstallnanoLLMAlternatively, you can clone the repository and install from source:gitclonehttps://github.com/jamesliu/nanoLLM.gitcdnanoLLM
pipinstall.UsageDocumentationFull documentation is availablehere.ContributingWe welcome contributions to nanoLLM! If you're interested in contributing, please see ourcontribution guidelinesandcode of conduct.LicensenanoLLM is licensed under the Apache License 2.0. See theLICENSEfile for more details.SupportFor support, questions, or feature requests, please open an issue on ourGitHub repositoryor contact the maintainers.ChangelogSee thereleasespage for a detailed changelog of each version.