Saravanan666/pypi-org huggingface dataset:
Package: convtest-prl
READMEconvtestis an open source code to do the convergence test  byvasp. It supportsANYparameters.FeaturesSupportANYparameters in INCAR add KPOINTS and EOS. (Of course, all the values for the parameters should be correct).Note:The EOS keyword is conducted by changing the scale factor, as a result, the coordinate system of the atom position should be fraction, not CartesianSupport runVASPin the script, and generate the shell or qsub(pbs) scripts to submit the jobs.Installpipinstallconvtest-prlUsagePrepare the template of All VASP-needed files [INCAR, POSCAR, POTCAR, KPOINTS]Prepare the INPUT.convtest file to specify the parameters for convergence test.If run the test on HPC using PBS(now, it only support PBS now), prepare the pbs scripts.INPUT file formatSyntaxStatesExamplesPARAMSpecify the parameters for convergence test, case insensitivePARAM    ENCUTPARAMLISTThe value list of the parameters, case insensitiveThere are two ways to specify the value1. Keep in one line with the PARAMLIST key words2. Multilines(must with end mark  END_PARAMLIST)1.For cut-offPARAMLIST 200..30..500(two dots)orPARAMLIST 200 230 260 ... 5002.For KPOINTSPARAMLIST2 3 43 4 5...END_PARAMLISTVASPRUN1(Default) for run the VASP code in the script0 for generate *.sh or *.pbs script according to your templateVASPRUN 1KEEPRESULTALL(Default) : for keep all the result generated by vasp(several folders)MIN : for minimum results (Only the data file will be reserved)KEEPRESULT ALLISTEST1 means TEST mode, it doesn't run the vasp, and the energy is random0(Default) means not test mode, run the vaspTODOThe convergence of size in doping or defect system?1.How?The error caused by the size effect is most ascribed to the self-interaction?$$
E_{2N} = 2E_N
$$Property-based convergence?Supercell2.Todo listConvergence of doping systemConvergence of the defect systemAuthorMingqing Liao(廖名情)liaomq1900127@163.comPhase Research Lab(PRL) @ Penn State(PSU)FGMS Group @ Harbin Institute of Technology
Package: convtools
convtoolsconvtoolsis a specialized Python library designed for defining data
transformations dynamically using a declarative approach. It automatically
generates custom Python code for the user in the background.Installationpip install convtoolsDocumentationconvtools.readthedocs.ioGroup by examplefromconvtoolsimportconversionascinput_data=[{"a":5,"b":"foo"},{"a":10,"b":"foo"},{"a":10,"b":"bar"},{"a":10,"b":"bar"},{"a":20,"b":"bar"},]conv=(c.group_by(c.item("b")).aggregate({"b":c.item("b"),"a_first":c.ReduceFuncs.First(c.item("a")),"a_max":c.ReduceFuncs.Max(c.item("a")),}).pipe(c.aggregate({"b_values":c.ReduceFuncs.Array(c.item("b")),"mode_a_first":c.ReduceFuncs.Mode(c.item("a_first")),"median_a_max":c.ReduceFuncs.Median(c.item("a_max")),})).gen_converter())assertconv(input_data)=={'b_values':['foo','bar'],'mode_a_first':10,'median_a_max':15.0}Built-in reducers likec.ReduceFuncs.First* Sum
* SumOrNone
* Max
* MaxRow
* Min
* MinRow
* Count
* CountDistinct
* First
* Last
* Average
* Median
* Percentile
* Mode
* TopK
* Array
* ArrayDistinct
* ArraySorted

DICT REDUCERS ARE IN FACT AGGREGATIONS THEMSELVES, BECAUSE VALUES GET REDUCED.
* Dict
* DictArray
* DictSum
* DictSumOrNone
* DictMax
* DictMin
* DictCount
* DictCountDistinct
* DictFirst
* DictLast

AND LASTLY YOU CAN DEFINE YOUR OWN REDUCER BY PASSING ANY REDUCE FUNCTION
OF TWO ARGUMENTS TO ``c.reduce``.What's the point if there are tools like Pandas / Polars?convtools doesn't need to wrap data in a container to provide functionality,
it simply runs the python code it generates onany inputconvtools is lightweight (though optionalblackis highly recommended for
pretty-printing generated code out of curiosity)convtools fosters building pipelines on top of iterators, allowing for stream
processingconvtools supports nested aggregationsconvtools is a set of primitives for code generation, so it's just different.Supportwestandskif (Nikita Almakov) -Link to supportReporting a Security VulnerabilitySee thesecurity policy.
Package: convtt
convttConvolutional Neural Netoworks Training Toolsexample of DenseNet trainingThe example is included in thebinfolder in the package with the file name ofconvtt_train_densenet.py.Here is a code snippet of creating a trainer and train the network given the model and the dataset.# convtt_train_densenet.pyfromconvtt.modelsimportdensenetfromconvtt.train.trainerimport*# initialise traineroptimiser=build_optimiser(model=model,name='ScheduledSGD',milestones=[10,20],lr=0.1)driver=build_driver(model=model,training_epoch=30,batch_size=128,training_data=dataset.train['images'],training_label=dataset.train['labels'],validation_data=None,validation_label=None,test_data=dataset.test['images'],test_label=dataset.test['labels'],optimiser=optimiser)trainer=build_trainer(optimiser=optimiser,driver=driver)test_acc=trainer.eval()print(test_acc)
Package: convunits
# Python Unit-Converter library (py version ofconvunits)This library serves as the Python equivalent of the originalconvunitslibrary written in TypeScript.## InstallationUse the Python package manager (i.e. pip) to install convunits.`bash pip install convunits `## UsageIn general, you can convert from one unit of the same quantity to another.`python >>> from convunits import Convert >>> Convert(10,'km').to('miles')6.2137121212121205 `Also works with arrays (lists, and such to some extent):`python >>> from convunits import Convert >>>Convert([1,2, 3],'m').to('ft')array([3.28084,6.56168, 9.84252]) `## Contributing### Adding new unitsTo add new units to convunits, add or update one of the JSON definitions in thedefinitions. Once the definitions is updated, regenerate all the Python unit definitions by running thejson_to_py.pyscript intoolsdirectory:`bash python tools/json_to_py.py `And check that the new units have been included inpy/convunits/unit_definitions/*files and also inpy/convunits/definitionsfile (if it’s a new quantity).
Package: convx
Convx | A conversion tool for binary, hex, decimal.This tool is created for a school lesson regarding Information Representation and conversion between binary, decimal and hex.Further, this tool has the additional functionality of:Adding and subtracting binary.Converting between decimal and binary using two's compliment.Converting between decimal and BCD.InstallationTo install Convx you can usepip install.pipinstallconvxUsageSimply import Conx usingimport. The functions available are listed below.# Decimal to BinarydecimalToBinary(x:int)# Binary to DecimalbinaryToDecimal(x:str)# Decimal to HexdecimalToHex(x:str)# Binary to HexbinaryToHex(x:str)# Decimal to BCDdecimalToBCD(x:int)# BCD to DecimalbcdToDecimal(x:str)# Adding BinaryaddBinary(x:str,y:str)# Subtracting BinarysubBinary(x:str,y:str)# Binary to Denary using two's complimenttwoBinaryToDenary(x:str)# Denary to Binary using two's complimenttwoDenaryToBinary(x:int)An example usage of Convx for a cli is given below :fromconvximport*try:ifstr(sys.argv[1])=="dtb":binary=decimalToBinary(int(sys.argv[2]))result=f"[*]{int(sys.argv[2])}to binary ={binary}"print(result)elifstr(sys.argv[1])=="btd":decimal=binaryToDecimal(str(sys.argv[2]))result=f"[*]{str(sys.argv[2])}to decimal ={decimal}"print(result)elifstr(sys.argv[1])=="dth":hex=decimalToHex(str(sys.argv[2]))result=f"[*]{str(sys.argv[2])}to hex ={hex}"print(result)elifstr(sys.argv[1])=="bth":hex=binaryToHex(str(sys.argv[2]))result=f"[*]{str(sys.argv[2])}to hex ={hex}"print(result)elifstr(sys.argv[1])=="dtbcd":bcd=decimalToBCD(str(sys.argv[2]))result=f"[*]{str(sys.argv[2])}to BCD ={bcd}"print(result)elifstr(sys.argv[1])=="bcdtd":decimal=bcdToDecimal(str(sys.argv[2]))result=f"[*]{str(sys.argv[2])}to BCD ={decimal}"print(result)elifstr(sys.argv[1])=="add":binary=addBinary(str(sys.argv[2]),str(sys.argv[3]))result=f"[x]{str(sys.argv[2])}+{str(sys.argv[3])}={binary}"print(result)elifstr(sys.argv[1])=="sub":binary=subBinary(str(sys.argv[2]),str(sys.argv[3]))result=f"[x]{str(sys.argv[2])}-{str(sys.argv[3])}={binary}"print(result)elifstr(sys.argv[1])=="2btd":decimal=twoBinaryToDenary(str(sys.argv[2]))result=f"[*]{str(sys.argv[2])}to decimal ={decimal}"print(result)elifstr(sys.argv[1])=="2dtb":binary=twoDenaryToBinary(int(sys.argv[2]))result=f"[*]{str(sys.argv[2])}to binary ={binary}"print(result)elifstr(sys.argv[1])=="help":print(help())exceptIndexError:print("[*] No arguments inputed. Exiting.")Update Log0.1.3Fixed a bug with the banner.0.1.2Added usage in README.Updated example cli code.0.1.1Added decimal to BCD and BCD to decimal.Added pytest for decimal to BCD and BCD to decimal.Added 'help' text at banner information.
Package: conway
Conway is a dead-simple implementation of Conway’s Game Of Life using myBlessings terminal library. It detects your terminal size and color depth
and blits a lovely cellular automaton for your ogling pleasure.FeaturesSimple implementationPretty colorsFew caloriesNudges itself out of repetitive patternsRather than having a zillion features, Conway focuses on clarity of
implementation. It’s fun to hack on. Try implementing differentwrapparameters fornext_board!Getting it runningpip install conway
conway.pyYou should see life explode before your eyes. When you’re done, hit control-C,
and it’ll clean up nicely after itself.KudosRipped off a really elegant implementation of the algorithm from Jack Diedrich
(and ruined it).Version History1.1Use “fullscreen mode” so we don’t leave a big white screen behind
afterward.1.0Initial release
Package: conway-life
Python interface for Game of LifePython wrapper for C implementation of Conway's Game of Life algorithm.This only provides low-level utilities. It is intended to be used as a dependency for higher-level
pure Python packages; as of this update, they are:life-web-uiWeb UI for Conway Game of LifeInstallationUse PyPi packageconway-lifepython3-mpipinstall--upgradeconway-lifeDesign notesNone of the methods allocate any Python objects; output objects must be created by caller.
This both simplifies memory management and makes it possible to avoid unneeded
garbage collection for large objects.APIrun(width, height, n_threads, n_iters, pos_start, pos_end, calllback)width:      Width of the board;integerheight:     Height of the board;integern_threads:  Number of worker threads (not yet supported);integern_iters:    Number of iterations to run;integerpos_start:  Initial position; booleanlistof sizewidthxheightpos_end:    (Output) Final position; booleanlistof sizewidthxheight. Must be pre-allocated.callback:   Iteration calllback, orNone(see below)return value: number of actually executed iterations
(never more thann_iters, but could be less, see below)callback(n_iter, count, bhash, pos_ptr, fin)n_iter:     current iteration (see below);integercount:      count of cells;integerbhash:      hash of current position;integerpos_ptr:    internal memory pointer to the current position;integer.
Methodread_ptrcan be used to extract the positionfin:        1 if this is final iteration, 0 if notreturn value:Noneorinteger; value 1 will trigger iterations to stop immediately.Notescallback(if defined) is calledbeforefirst iteration, and then
againafterevery iterations, including the last (where fin=1). Therefore,normallycallback method is called1 + n_iterstimes.However this method also detects loops and if your sequence deteriorates
to a loop, it will cut it short;finwould still be set to 1 on the last
iteration only regardless. Hash values used in loop detection is passed
to the callback.read_ptr(width, height, pos_ptr, position)width:      Width of the board;integerheight:     Height of the board;integerpos_ptr:    Internal memory pointer returned in a callback (see methodrun);integerposition:   (Output) Intermediary position; booleanlistof sizewidthxheight.
Must be pre-allocated.return value: 1 on success
Package: conway-polynomials
Python interface to Frank Lübeck’s Conway polynomial databaseIntroductionFrank Lübeck maintains a list of pre-computed Conway polynomial
coefficients at,https://www.math.rwth-aachen.de/~Frank.Luebeck/data/ConwayPol/index.htmlThese are used in several computer algebra systems such as GAP and
SageMath to provide quick access to those Conway polynomials. The aim
of this package is to make them available through a generic python
interface. The package consists of a single module containing a single
function that returns a dict of dicts,conway_polynomials.database().
The dictionary’s format is{p: {n: coefficients}}, whereprepresents your prime andnyour degree. The tuple of coefficients
is returned in ascending order; that is, the first coefficient (at
index zero) is for the constant (degree zero) term.This package is an evolution of the SageMathconway_polynomialspackage hosted at,http://files.sagemath.org/spkg/upstream/conway_polynomials/and is maintained by the same team of developers. We have kept the
versioning scheme consistent to reflect that.ExamplesRetrieve the coefficients of the Conway polynomial for prime p=2 and
degree n=5:>>> import conway_polynomials
>>> cpdb = conway_polynomials.database()
>>> cpdb[2][5]
(1, 0, 1, 0, 0, 1)The result is cached, so subsequent computations should be fast even
if you call the function again:>>> conway_polynomials.database() is conway_polynomials.database()
TrueHowever, the result is also mutable, so if you need to modify it for
some reason then you should create a copy; otherwise your changes will
affect future calls:>>> cpdb = conway_polynomials.database()
>>> cpdb[5][5]
(3, 4, 0, 0, 0, 1)
>>> cpdb[5][5] = (8, 6, 7, 5, 3, 0, 9)
>>> conway_polynomials.database()[5][5]
(8, 6, 7, 5, 3, 0, 9)TestingA few doctests within the module (and this README) ensure that
everything is working. You can run them from the repository or from a
release tarball using:PYTHONPATH=src python -m doctest \
  README.rst \
  src/conway_polynomials/__init__.pyOr, if you have pytest installed, with simply:pytest
Package: conway-pygame
Conway's game of lifeThis is an implementation of the Conway's game of life using pygame.The Universe is circular : left border touch the right one, top border touch the bottom one.Many games are implemented, the rules come fromhttps://en.wikipedia.org/wiki/Conway%27s_Game_of_Life.I've only implemented "simple" games, using the 8 cells around the current cell.Available Gamesconway classicHighLifeDay&NightImmigration(With colors !)QuadLife(more colors !)Life without death (Flakes)34 Life B34/S34SeedsDiamoeba B35678/S56782x2 B36/S125Morley B368/S245Anneal B4678/S35678InstallationUsing pip$cd/path/to/the/projects
$mkdirConway&&cdConway
python3-mvenv./venvsource./venv/bin/activate
pipinstallconway-pygameWhen installed with pip, you can use theconway_pygamecommand to play a game.Installation with git$gitclonehttps://gitlab.com/frague59/conway.git
$cdconway
$python3-mvenv./venv
$.venv/bin/activate
$pipinstall-r./requirements.txtUsageWith GIT install$python3-mconway_pygame--help
pygame2.1.2(SDL2.0.16,Python3.9.12)Hellofromthepygamecommunity.https://www.pygame.org/contribute.html
Usage:python-mconway_pygame[OPTIONS][[conway|highlife|dayandnight|immigration|quadlife|replicator|flakes|34life|diamoeba|seeds|2x2|morley|anneal]]Conway'sgameoflifeusing`pygame<https://www.pygame.org/>`_.

Options:-w,--widthINTEGERWidthofthegrid.-h,--heightINTEGERHeightofthegrid.-n,--initialINTEGERNumberoflivingcellsatstart.-d,--debugDEBUGmode-Slowdownthegameandwriteroundstostdout.--versionShowtheversionandexit.--helpShowthismessageandexit.With pip install$conway_pygame--help
Package: conwech
ConWechConWech is a Python package for spellingreallylarge numbers in english using a couple functions and some cleverly built tuples. For more information on the large number names and period naming conventions used by this module see the wikipedia pagehere.Read more about the package contents and structurehere.Command-line InterfaceConWech also comes with an excruciatingly simple CLI. Run the help command after installing with pip for more insight.$ pip install conwech
$ conwech --helpDeveloper's NoteThis is really just a personal project I started for fun. When I first heard aboutthisinteresting property of the number four whilst mindlessly falling down the youtube rabbit hole, I was inspired to break from my nominal comatose daze and write something that could demonstrate such behavior with some simple guess-and-check fun in the terminal. However, for said fun and futility to ensue, one must first be able to spell whatever number one desires, and while there seem to be some pretty neat solutions out there already (numspellfor example), I was far too lazy to read through them. I'd also wager they have limitations which would have left me unsatisfied. Besides, in my inevitable dive through wikipedia, I had become rather infatuated with large number names and the process of generating them algorithmically.So here we are, both wasting our time spelling numbers so we can count letters and then spell more numbers... Eventually I wanted to try writing a "bonafide" python package, so that happened. Then I wanted to practice usingclickfor CLI instead ofargparse. I may never go back... EDIT: I went back... As clean as click is, I didn't enjoy typing--just to spell negative numbers. Anyway, I digress. If you find any use for what's here, then that's awesome. Happy to help! However, I don't plan on maintaining this package in a traditional fashion (I have a bad habit of constantly renaming things), so... use at your own risk.Godspeed,Kc4T
Package: conx
The On-Ramp to Deep LearningBuilt in Python 3 on Keras 2.Read the documentation atconx.readthedocs.ioAsk questions on the mailing list:conx-usersImplements Deep Learning neural network algorithms using a simple
interface with easy visualizations and useful analytics. Built on top of
Keras, which can use eitherTensorFlow,Theano, orCNTK.A network can be specified to the constructor by providing sizes. For
example, Network(“XOR”, 2, 5, 1) specifies a network named “XOR” with a
2-node input layer, 5-unit hidden layer, and a 1-unit output layer.
However, any complex network can be constructed using thenet.connect()method.Computing XOR via a target function:importconxascxdataset=[[[0,0],[0]],[[0,1],[1]],[[1,0],[1]],[[1,1],[0]]]net=cx.Network("XOR",2,5,1,activation="sigmoid")net.dataset.load(dataset)net.compile(error='mean_squared_error',optimizer="sgd",lr=0.3,momentum=0.9)net.train(2000,report_rate=10,accuracy=1.0)net.test(show=True)Creates dynamic, rendered visualizations like this:ExamplesSeeconx-notebooksand thedocumentationfor
additional examples.InstallationSeeHow To Run
Conxto see options on running virtual machines, in the cloud, and personalinstallation.
Package: coocop
COOCOP - Copyout and CopyPaiting implementationThis is an implementation of the Copyout and CopyPairing image augmentation techniques. The paper about this can be found here:Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairingInstallationInstall or update with pip:pip install coocop -UInstall development version:pip install git+https://github.com/t-systems-on-site-services-gmbh/coocop.git -UCitation / BibTeXThis is how you can cite this work with LaTeX / BibTeX:@article{Copyout,
title = "{Improved Image Augmentation for Convolutional Neural Networks by Copyout and CopyPairing}",
author = {Philip May},
journal = {arXiv.org},
year = "2019",
archivePrefix = {arXiv},
eprint = {arXiv:1909.00390 [cs.CV]},
url = {https://arxiv.org/abs/1909.00390},
}
Package: coodeer
Library and CLI Tool for creating minimalistic, local debian packages repository.
Debian packages are expected to reside in an S3 bucket.
Thedpkg-scanpackagesis required to be locally installed.CLI UsagePrerequisitesSet up environment variables: AWS Credentials and default bucket name.#copyexamplefiles#envrc(https://direnv.net/)cp .envrc.example .envrc#..addAWScredentialsifneeded,adjustbucket..direnv allowUpload debian packagescoodeer upload example-dependencies_1.23_all.deb
coodeer upload example_1.23.0_all.deb
coodeer upload example_1.23.1_all.debPublish (default) specificationcoodeer publish repository-specification.example.yamlCreate repositoriescoodeer create /tmp/my-repositories
Package: cooka
CookaDoc|简体中文Cooka is a lightweight and visualization toolkit to manage datasets and design model learning experiments through web UI.
It usingDeepTablesandHyperGBMas experiment engine to complete feature engineering, neural architecture search and hyperparameter tuning automatically.Features overviewThrough the web UI provided by cooka you can:Add and analyze datasetsDesign experimentView experiment process and resultUsing modelsExport experiment to jupyter notebookScreen shots：The machine learning algorithms supported are ：XGBoostLightGBMCatboostThe neural networks supported are：WideDeepDeepFMxDeepFMAutoIntDCNFGCNNFiBiNetPNNAFM...The search algorithms supported are：EvolutionMCTS(Monte Carlo Tree Search)...The supported feature engineering provided byscikit-learnandfeaturetoolsare：ScalerStandardScalerMinMaxScalerRobustScalerMaxAbsScalerNormalizerEncoderLabelEncoderOneHotEncoderOrdinalEncoderDiscretizerKBinsDiscretizerBinarizerDimension ReductionPCAFeature derivationfeaturetoolsMissing value fillingSimpleImputerIt can also extend the search space to support more feature engineering methods and modeling algorithms.InstallationUsing pipThe python version should be >= 3.6, for CentOS , install the system package:pipinstall--upgradepip
pipinstallcookaStart the web server：cookaserverThen openhttp://<your_ip:8000>with your browser to use cooka.By default, the cooka configuration file is at~/.config/cooka/cooka.py,  to generate a template:mkdir-p~/.config/cooka/
cookagenerate-config>~/.config/cooka/cooka.pyUsing DockerLaunch a Cooka docker container:dockerrun-ti-p8888:8888-p8000:8000-p9001:9001-eCOOKA_NOTEBOOK_PORTAL=http://<your_ip>:8888datacanvas/cooka:latestOpenhttp://<your_ip:8000>with your browser to visit cooka.DataCanvasCooka is an open source project created byDataCanvas.
Package: cookapps-datacenter
CookApps Data Center SDKInstallation$ pip3 install --upgrade cookapps-datacenterExamplesfrom cookapps_datacenter import DataCenter
from cookapps_datacenter.config import *

""" Athena Query Test """
if __name__ == "__main__":
    ## Athena Config - cookapps_datacenter.config.AthenaConfig
    athena_config = AthenaConfig(
        s3_bucket       = '{S3_BUCKET}',
        s3_output_uri   = '{ATHENA_RESULT_S3_URI}',
        region          = '{ATHENA_REGION}',
        tmp_local_path  = '/path/to/dir'
    )

    ## SDK
    dc = DataCenter(
        aws_profile_name='{AWS_CREDENTIAL_PROFILE}',
        athena_config=athena_config
    )
    df = dc.athena.run_query('SELECT * FROM "users"', 'test_db')
    print(df)
Package: cookbase
CookbaseA platform to validate, store and manage cooking recipes based on the JSON Cookbase Format.Cookbase proposes and implements a data model striving for anas-complete-as-possibledata structure applied to cooking data. A new suite of data formats (the [Cookbase Recipe Standard Format]) and a consistent data model structure with its database architecture and recipe data analysis tools are included in the Cookbase project.Please check out thedocumentationfor detailed information about the project and the available API.InstallCookbase can be installed through the PyPI repository using the following command:pip3 install cookbaseContributingWe are in pre-release development phase, so feel free to come up with any feature that you think should be added to our project.
Package: cookbook
IntroductionThis python package implements some recipes from the python cookbook. Some of the recipes are copied
verbatim from the pythoncookbookand some are modified versions of those at the cookbook. Others I
(John Reid) have written from scratch.LicenseAll novel parts of this software are released under the BSD. See the accompanying file python/cookbook/LICENSE.
Please also refer to original code for their licensing terms.PrerequisitesI have tested this software on python 2.6 and 2.7.InstallationThe standard python package install method should work:python setup.py build
python setup.py install