Saravanan666/pypi-org huggingface dataset:
Package: decat
Decatthisisawesome-->['this','is','awesome']Decatis a Python package capable of de-concatenating strings that do not have
white-spaces in them, or in other words, it allows the user to infer spaces
programmatically. This is a simple utility that comes in handy with various modern
Natural Language Processing(NLP) tasks such as cleaning, exploration or even manipulation
of text.Zipf's Lawis
at the
core of this
project, the aim is to provide an easy interface for programmers to extract meaningful
information out of deformed pieces of texts.Get StartedInstall It>>pipinstalldecatPlay With It>>decat-isomeweirdtext>>['some','weird','text']or>>python-mdecat-ijustanotherstring>>['just','another','string']Use It In Your ProjectsSample Codefromdecatimportdecatweird_text='“AnyfoolcanwritecodethatacomputercanunderstandGoodprogrammerswritecodethathumanscanunderstand.”–MartinFowler'weird_text_simplified=decat(weird_text)print(weird_text_simplified)Console['any', 'fool', 'can', 'write', 'code', 'that', 'a', 'computer', 'can',
'understand', 'good', 'programmers', 'write', 'code', 'that', 'humans', 'can',
'understand', 'martin', 'fowler']Features🪶 A light weight package, built around the features available in standard library📚 An ever-expanding vocabulary, knows more than 300K English words🪃 Simplistic design, allows for easy expansion to new languages and custom vocabulary setsDependencies⭕️None🎉Limitations❗ Requires Python >= 3.6❗ ️All input will be treated as lower-case>>ATitleCaseString-->['a','title','case','string']❗️ Punctuation marks, numbers and special characters will be stripped from the input and
will not be preserved in the output>>dummy.email1234@gmail.com-->['dummy','email','gmail','com']LicenseMIT
Package: decavision
The AI team at Décathlon Canada developed a library to help with the training of image
classification models. It is specially made to exploit the free TPUs that are offered
in Google colab notebooks. You can find the full documentationhereVersion 1.4.2Update dependencies and testing functionsVersion 1.4.1Fix hyperparameter optimization for multilabelVersion 1.4.0Added multilabel classificationVersion 1.3.0Use suggested image sizes
Add EfficientNetV2 modelsVersion 1.2.1Change to Tensorflow 2.5Version 1.2.0Add semi-supervised learning featuresVersion 1.1.3Link to public repositoryVersion 1.1.2Change name of packageVersion 1.1.1Fix typo in split_trainVersion 1.1.0Remove google scrapingVersion 1.0.0Original release
Package: decawave-1001-rjg
decawave-1001-rjgIntroductionThis is a device driver enable a Raspberry Pi to use the Decawave 1001 UWB positioning module.The Decawave is a low cost UWB positioning module. A group of at least 4 modules forms a mesh network that can locate a fifth, mobile module with an accuracy of around +-0.2 meters. For more information and datasheets seeDecawave's website.The DWM1001 is available as a development board about the size of a credit card.Driver FeaturesConnects over SPISupports hardware interrupts for data readyOptionally enables high priority thread schedulingLimitationsRequires python 3.7ExamplesExamples are available onGithub.
Package: decay
decaydecay is anopen source,
MIT licensed library which groups code for managing changes in values
based on a predefined rule over time.Installpip install decayYou can also download/clone the source, in which case you have to:git clone https://github.com/pyl1b/decay.git
python setup.py installTo contribute a patch clone the repo, create a new branch, install in
develop mode:python setup.py develop
Package: decaychain
decaychainThis package decays single or multiple radionuclides and computes the daughter radionuclides and their concentrations at a user defined time.Currently this package has only been tested on Python 3.6 running on Linux OS.Installation$pipinstalldecaychainSyntax for UseExample>>> import decaychain.BatemanMulti as decay>>> decay.bateman_multi({"U-238":1e7, "235U":1e7}, 3e9, "yr"){'U-235': 0.3735948863819144, 'Th-231': 0.3735948863834592, 'Pa-231': 0.37361227209089354, 'Ac-227': 0.3736122836452778, 'Th-227': 0.3684561382285081, 'Ra-223': 0.37361198361845205, 'Rn-219': 0.37361198361845205, 'Po-215': 0.3736122836886527, 'Pb-211': 0.3736122836886891, 'Bi-211': 0.37361228368869126, 'Tl-207': 0.37258111378571535, 'Po-211': 0.0010311699029807882, 'Fr-223': 0.0051561454435370985, 'At-219': 3.000702007281776e-07, 'Bi-215': 3.0007020072818374e-07}This decays both U-238 and U-235 at a concentration of 1e7 Bq for 3e9 years.Syntax>>> decay.bateman_multi({dictionaryinput}, time, "time units")dicitonaryinput= dictionary with key nuclide as string and values as nuclide concentration_time= a number (float or integer)time units= string e.g. ("years", "yr", "minutes", "m", "hours", "hr" etc)The output is a dictionary in the same format at the inputThe Pint module(https://pint.readthedocs.io/en/0.12/)  is used to handle time units so a variety of time units can be used.The nuclide input is tolerant of a variety of radionuclide formats i.e. U-235, U-238, 235U etcHow it worksradioactivedecay uses decay data from ICRP Publication 107 (2008) combined with a Bateman Decay solution to calculate the final concentrations of nuclideshttps://journals.sagepub.com/doi/pdf/10.1177/ANIB_38_3LimitationsThe following processes are not modelled by radioactivedecay:ingrowth of progeny from spontaneous fission decaysneutronics, so no modelling of induced radioactivity or fissionDatadecaychain
Article:https://www.icrp.org/publication.asp?id=ICRP%20Publication%20107Supplementary Data (ZIP file):https://journals.sagepub.com/doi/suppl/10.1177/ANIB_38_3File used: ./ICRP-07.NDX (column names as per ./UserGuide.pdf - table on page 4)ThanksWith particular thanks to @bjodah for use of the batemaneq module (https://github.com/bjodah/batemaneq) and Alex Malins for leading the way (https://github.com/alexmalins/radioactivedecay)
Package: decbinconverter
M1-2022-gitIntroductionThis repository is a fork from the previous repository.
The bugs in the converter have been fixed and now we want to publish our work as a publicly available python package.Getting startedYou should be working fromyour own repositorythat is a fork of M1-2022-git-workflow.
In order to run this project, you will have to follow these steps.Clone this projectmove into the project foldercdM1-2022-git-workflowSet up a virtual environmentCreate the virtual environmentpython-mvenvmyvenvActivate venv.venv/bin/activateInstall pytestpipinstall-UpytestExecute main scriptpythonmain.pyInstructionsMerge feature branch into devNow that the converter has no more bugs, we want to merge our branch feature into the dev branch.
We will do a pull request (on your own repo). On GitHub, go to the "Pull requests tab" and click "New pull request".
Selectbaseandcompare. Remember : we want to mergedecimal-binary-converterintodev.
Then,Create the pull request. Add some description of the work you have done and publish the Pull Request.Note: We could have just mergedecimal-binary-converterintodevfrom the command line. However, when working on a real project, you probably won't have the rights to do so. Remember : dev is a public branch. So all the work going down there should be carefully reviewed and tested.Publish your workWe now have an awesome binary/decimal two ways converter ! It's time to publish it so the rest of the world can enjoy it !
We will publish it on PyPI (Python Package Index) which is a public repository of softwares for Python.First, you have to create an account onPypi.orgThen, in your repository, you will find a.github directoryInside this directory, you will find .yml files that defines workflows (using GitHub actions)Open the yml files and take time to understand them. Do not hesitate to ask the teacher about themHands on !We want to create a workflow that will, on publish, test our code and if tests succeed, then publish our package on PyPIIn GitHub, click on theActionstab, then click onnew workflowChoose among the suggestions the template that best suits your use-case and clickConfigureYou may find some useful informations in thePython documentationWhen creating a release on GitHub, do not forget to create a tag corresponding to that releasePull requestOnce the workflow is setup and tested (you have published your package using it) you can open a pull request to theoriginal repository
Package: decbot
DECbotA Discord bot that uses DECtalk text-to-speech (think Stephen Hawking or
Moonbase Alpha).DECbotuseswineand the original DECtalksay.exeto synthesize text from text chat into a voice channel. The bot offers a set of
commands allowing users to control how and whereDECbotsynthesizes speech.
The bot can also take multiple commands at once, allowing multiple sounds and
voices to be played back at the same time.RequirementsPython 3wineA copy of the DECtalk executable and support. This includessay.exe,dectalk.dll, and the dictionary,dtalk_us.dic.CommandsDECbotcan synthesize text into different voice channels depending on the
command:!dec talk <text>plays the text back in the current voice channel.!dec tell <@mention> <text>plays the text back in the voice channel of the
user mentioned.The presence ofDECbotcan also be controlled (to minimize annoyance):!dec quietstops the currently playing text immediately.!dec leaveforces the bot to leave its current voice channel.Both TTS commands run using the "Perfect Paul" voice with phonemes enabled (so
the bot can "sing"). Additional options can be specified as they would in a
normalsay.execommand: with brackets and a colon ([:command]). For example,DECbotcan talk as "Frail Frank" by starting the text with[:nf].Installation$pipinstalldecbotThe bot can also be run from source as a module. In the top level directory:$python-mdecbotRunningA new Discord bot must be set up before the application can be run:Create a new Discord application in thedeveloper portal.Fill in the general information, and note theClient IDon this page.Set up your bot in the "Bot" tab. Note theTokenon this page.Next, to start the application:Create aDECbotconfiguration file. At minimum, this must have the bottoken, and the path to the DECtalk executable,tts.bin.Get an invite link (theclientfield must be specified in the config):$decbot--inviteHave the Discord server administrator add the bot. Note that it must be
granted the ability to read and send text messages, and be able to view,
join, and talk in voice channels.Start the bot. The application looks for a configuration file in the same
directory called.decbot. Specify a different path as follows:$decbot--config/path/to/my/configTo stop the bot, the application can be stopped from the command line, or
the owner can issue!dec quitin the Discord server chat.
Package: decc
decc: Cooperative Co-evolutionary Differential EvolutionCooperative Co-evolutionary Differential Evolution algorithms in Python with NumPy.This repository provides simple implementations for some CC-based DE algorithms. All the implementations are from scratch using NumPy, they might slightly differ from the original papers.Quick StartThedecclibrary works with two entities:Problemrepresents a minimization problem (objective function, dimensionality and bounds).The objective function must receives a matrix as input (each row represents a solution) and produce a matrix as output (each row is the objective value for the respective solution).Optimizerrepresents a DE algorithm for solving a minimization problem.Maximization of a real functiongis equivalent to minimize-g.In order to use an optimizer, you must first define a problem. Currently, there are two optimizer available: (i)DECC(also known as CCDE), with the variantsDECC-OandDECC-H; and (ii)DECC-G. A basic example is found below:importnumpyasnpfromdeccimportProblemfromdecc.optimizers.deccimportDECCOptimizerfromdecc.optimizers.decc_gimportDECCGOptimizerdefobjective(x:np.ndarray)->np.ndarray:# The Sphere function is a common#   benchmark for optimizersreturnnp.sum(x**2,axis=-1)# First, we must define the problemproblem=Problem(objective,dims=100,lower_bound=-100.0,upper_bound=100.0)# Then, we can instantiate the optimizersF=0.5CR=0.8seed=42max_fn=int(1e5)pop_size=50decc_h=DECCOptimizer(problem,seed,pop_size,grouping='halve',F=F,CR=CR,max_fn=max_fn)decc_o=DECCOptimizer(problem,seed,pop_size,grouping='dims',F=F,CR=CR,max_fn=max_fn)decc_g=DECCGOptimizer(problem,seed,pop_size,n_subproblems=max(1,problem.dims//4),sansde_evaluations=max_fn//3,de_evaluations=max_fn//5,F=F,CR=CR,max_fn=max_fn)# Lastly, we can optimize the objective and#   retrieve the results.foroptimizerin[decc_o,decc_h,decc_g]:result=optimizer.optimize()print(f'{optimizer}:{result["best_fitness"]}')# DECC-O: 1.638248431845568e-05# DECC-H: 0.0006988301174715161# DECC-G: 1.5340782547163752e-10RoadmapAdd support forDECC-DG;Add support forDECC-gDG;Improve documentation;Add unit tests;Add validation benchmark functions from the original papers;
Package: deceit
deceitintroductionboilerplate requests code for creating simple api clients.  includes
a standard requests retry adapter for retrying errors 429, 502, 503, and 504,
and a base api exceptions class that can be used for api-specific error
handling.  includes hooks that can be used to add request and response
logging to a database if needed for debugging / traceability.named after a group of lapwings.  pax avium.usagefromdeceit.api_clientimportApiClientfromdeceit.exceptionsimportApiExceptionclassAirflowException(ApiException):passclassAirflowApiClient(ApiClient):def__init__(self,*args,default_timeout=None,**kwargs):super().__init__(*args,base_url='http://localhost:8080/api/v1',default_timeout=default_timeout,exception_class=AirflowException,**kwargs)self.session.auth=('username','password')defconnections(self):returnself.get('connections')anchoring off of base urlif you provide abase_urlto the constructor ofApiClient, all
calls to theApiClient.sendfunction will be anchored to thebase_url.
In theAirflowApiClientexample above, thegetto theconnectionsendpoint will useposixpath.jointo construct the full url, e.g.,http://localhost:8080/api/v1/connections.  It is important to note
that deceit usesposixpath.joinnoturllib.parse.urljoin.So make sure not to prefix anchored routes with/.presend and postsendThedeceit-fulApiClientincludes hooks for doingpresendandpostsendactions.  If you subclassApiClientand overridepresend,
you can perform actions such as logging therequests.PreparedRequestor adding an hmac signature.  If you subclassApiClientand overridepostsendyou can add additional post-request, pre-exception handling,
such as logging the request / response cycle.presendtakes
one parameter, therequests.PreparedRequest, whilepostsendtakes
two parameters, therequests.PreparedRequestand therequests.models.Response.timeoutYou can set the default timeout to use with requests by including
thedefault_timeoutparameter to theApiClientconstructor.contributingprerequisitespython3.9 or python3.10docker-composeinternet connectiongetting startedstandard avian setup usingmakecd/path/to/deceit
makesetup
maketest
Package: decent
Decentis a data validation library for Python 2 & 3. There are many like it, but this one is mine.Read thedocumentationfor more details.Quick examplefromdecentimport*schema=Schema({'name':All(Strip(),NotEmpty()),'age':Range(min=0,max=200),})try:output=schema(input)...exceptInvalidase:print('\n'.join(e.messages))...ThanksThis library takes inspiration fromVoluptuousandGood, but doesn’t implement many of their more magical features. You may be interested in them if you find yourself wanting more.LinksDocumentationon Read the DocsDecent onPyPILicenseMIT, see theLICENSEfile.
Package: decentralise
decentraliseMake (some) Stan programs non-centered automatically.Inspired by readingthis paper.InstallationRequires python 3.6+.
Install withpip:pipinstalldecentraliseExampleThis package provides a command line tool:decentralise, which is used as follows:decentralise<input-file><output-destination>It will take any normally distributed parameters that have variances that are themselves parameters, and reparameterise them to make them non-centered.
For example, the canonical eight schools code is:data {
  int<lower=0> J; // number of schools
  vector[J] y; // estimated treatment effects
  vector<lower=0>[J] sigma; // s.e. of effect estimates
}
parameters {
  real mu;
  real<lower=0> tau;
  vector[J] theta;
}
model {
  theta ~ normal(mu, tau);
  y ~ normal(theta, sigma);
}Oncedecentraliseis applied, this program becomesdata {
  int<lower=0> J; // number of schools
  vector[J] y; // estimated treatment effects
  vector<lower=0>[J] sigma; // s.e. of effect estimates
}
parameters {
  real mu;
  real<lower=0> tau;
  vector[J] theta_std;
}
transformed parameters {
  vector[J] theta = mu + theta_std * tau;
}
model {
  theta_std ~ normal(0, 1);
  y ~ normal(theta, sigma);
}I wrote this tool for fun, and have not thoroughly tested it.
For example, it will fail for any parameters whose sampling statements are not vectorised.
e.g.:x ~ normal(mu, tau);will work, butfor i in (1:n) {
    x[i] ~ normal(mu, tau);
}will not.
There are probably a ton of other cases where it will break that I have not anticipated, as well!
Package: decentralized-p2p
CS50P peer to peer networkA simple system to handle networking through python sockets, in a p2p styleInstallationDownload PyPI librarypipinstalldecentralized-p2pImport the peer class in your main filefrompeerimportPeerUsage/ExamplesDeclare a peer object with:my_peer=Peer()To create a new network, use the Peer.create_network method.
You will need to specify your username, password, ip and eventual signature and encryption keysmy_peer.create_network("Username","Password","192.168.1.2","None","None")In another file, call the sign up method to connect to the newly created network:my_peer_2.signup("SecondUsername","SecondPassword","192.168.1.2")Now you can send and receive messages respectivly with the .send() and .read() methods.FeaturesAsyncronous message send and receiveTotally decentralized system, allows for wide horizontal expansionAsymmetrix signature implemented through ecdsaAsymmetric encryption implemented using fernetRunning TestsTo run tests, run the following commandpytesttest_project.pyAuthors@NeekoKun@NeekoKun02
Package: decentralizedroutines
DecentralizedRoutinesDecentralized routines orquestration through Kinesis working poolcreate virtual environmententer command: pip -m venv venvactivate virtual environnment (venv\Scripts\activate.bat)Create .env file in root folder Ie:LOG_LEVEL=[DEBUG]GIT_USER=[GIT_USER]GIT_TOKEN=[GIT_TOKEN]GIT_ACRONYM=[GIT_ACRONYM]GIT_SERVER=[GIT_SERVER]SOURCE_FOLDER=[SOURCE_FOLDER]
Package: decentra-network
Decentra NetworkDevelop or use applications in your independent, decentralized application network.Explore the website »..........IntroducingDecentra Network is anopen source blockchainthat combinesspeed,securityanddecentralization. Decentra Network has very high speeds, scalability, asymptotic security and complete decentralization.
The main features of Decentra Network are:Less than 3-5 Seconds block timeLow size (~20mb per 1m user)10k+ transactions per secondLow Transaction FeeCustom and low cost Token, NTF etc. Creation system (Scheduled Feature)Usability even on mobile devicesEnvironmentally FriendlyAsymptotic security against Sybil attacks (51 Attack)Completely decentralized structureOfficial community officers supported in-chainIn-chain developer incentivesBuilt-in application structureCustom wallet system*Some features will be adjusted in stable release.The software is written inPEP8format andonlyneeds dependent libraries for GUI panel. Decentra Network software, designed with a focus on thecommunity on the Github platform, In addition,Stability,FunctionalandUnittests of all systems are ready and automated. It also has various structures forautomatic setup of test environments. It is fully compatible withGit code management systemandAgile mindset.The Decentra-Network has 4 control areas:GUIThe GUI was made withkivyand some auxiliary libraries to becross platform. It was intended to be useful with aminimalistdesign.The GUI, which has a useful structure, is ready foradditionsandchanges.The GUI has a total of 4 pages.CLI MenuThe CLI Menu panel is designed to be useful.CLI ArgumentsThe CLI Arguments panel is designed to make some adjustments quickly and in multiple ways.WEB APIIt has been developed to make web api control easier and to provide control by other languages and other systems.DocumentsOur documents are available in thedocsfolder andthiswebsite.ContributeDecentra Network is a completely community driven project, you can contribute in any way if you follow theguidelinesandterms.Analysis && StatisticsRecent Activity/ Recent activityTop Contributors/ Top contributorsStructure/ StructureGithub Statistics...SponsorsFounder : Onur Atakan ULUSOY
Package: decentriq-dcr-compiler
Decentriq DCR Compiler (DDC)PublishWhenever you change something in the data model exposted by DDC, run the
following command:# generates schema json files
cargo build

# if run for the first time
poetry install

# generates typing files in python source dir
poetry run poe codegen-schemaCommit the schema files s.t. they will be included when the package
is published through CI.Commits need to be tagged with e.g.decentriq_dcr_compiler-v0.1.0for the CI pipeline to build the artifact.Debug modeGo into your venv (such as for example the poetry environment of the python
tests)cdinto this directorymaturin developMaturin will now install the package into your env and the tests will use
the latest version
Package: decentriq-platform
Decentriq - Python SDKThe Decentriq Python SDK exposes theDecentriq platform's functionality via easy-to-use programming constructs and, as such, allows
users to interact with the platform in a programmatic way.Releases of this library are hosted onhttps://pypi.org/project/decentriq-platform/and can be installed via the Python package managerpip.Please refer to theofficial documentationfor tutorials on how to install and use the
Decentriq Python SDK, as well as for detailed API documentation.DevelopmentKnown IssuesPoetry cannot find recently released packageIf you release a newdecentriq_dcr_compilerpackage and want to runpoetry lock --no-updateto update the lock file, then you might need topoetry cache clear --all .first in order to have poetry be able to pick
up the recently released version.
Package: decent-tools
Command-line tools for programming and reconfiguring wireless sensor nodes from Decentlab GmbH.DescriptionDevelopment of command-line tools to managedecentnode. Currently, the following tools are completed:dnbsl- msp430 bsl programmerdntc65i- tc65i managerdnmotes- list decentnodesDeveloped on MacOSX 10.10 and tested on Debian GNU/Linux (jessie).InstallationBefore installing withpip, please make sure that you remove any previous (either installed manually or withapt-get)decent-toolspackage.Thepython-msp430-toolsdependency is not correctly packaged forpypi; therefore it can be installed using this command from the trunk:sudo apt-get install bzr # needed for the following
sudo pip install bzr+lp:python-msp430-tools/trunk/@python-msp430-tools-0.7#egg=python_msp430_tools-0.7Finally, the decent-tools can be installed as follows:sudo pip install decent-toolsThat’s all folks.