Saravanan666/pypi-org huggingface dataset:
Package: numtools
numtoolsnumeric-gmbH toolboxPackagescsyslib: basic coordinates transformationsintzip: convert sequence of integers into human-friendly string (and vice-versa)serializer: mix in handling serialization to msgpack and json.vgextended: extension ofvgbuilt on top ofvgandnumpyRequirementsRequirements are specified inrequirements.txt(pip install-rrequirements.txt):numpy>=1.17.3vg>=1.6.1msgpack>=0.6.1msgpack-numpyDev RequirementsFor Contributing, generating documentation and/or tests, requirements are
described inrequirements_dev.txt.History0.6.0 (2019-12-16)Serialize smoothly numpy data. Add msgpack-numpy as dependency0.5.0 (2019-11-20)add option to keep integer keys in JSON format.0.4.0 (2019-11-19)First release on PyPI.
Package: num-to-rus
num_to_rusНебольшая библиотека, позволяющая переводить числа в слова на русском
языкеУстановкаЧтобы установить библиотеку, нужно выполнить следующую команду:pip install num_to_rusИспользованиеДля того, чтобы использовать библиотеку, нужно импортироватьConverterизnum_to_rus, создать его экземпляр и вызвать
у него методconvert, которому передать число, которое нужно конвертироватьfromnum_to_rusimportConverterconv=Converter()print(conv.convert(512))# 'пятьсот двенадцать'ТестированиеЧтобы запустить тесты, нужно выполнить следующую команду:python -m unittestЛицензияПроект находится под лицензиейGPL-3.0
Package: num-to-str-repr
NUM_TO_STR_REPRSimple package that converts numbers (int and float)
to the Russian and Ukrainian string representation.The supported number in range [-googol, googol].InstallationUse the package managerpipto install num-to-str-repr.pipinstallnum-to-str-reprExampleBy default the language is Russian.fromnum_to_str_repr.number_converterimportNumberConverterconverter=NumberConverter()# Int numberconverter.convert(789_567_361_890_000_321)"семьсот восемьдесят девять квадриллионов пятьсот шестьдесят семь триллионов триста шестьдесят один миллиард восемьсот девяносто миллионов триста двадцать один"# Float numberconverter.convert(534.321)"пятьсот тридцать четыре целых триста двадцать одна тысячная"fromnum_to_str_repr.number_converterimportNumberConverterconverter=NumberConverter("UA")# Int numberconverter.convert(789_567_361_890_000_321)"сімсот вісімдесят дев'ять квадрильйонів п'ятсот шістдесят сім трильйонів триста шістдесят один мільярд вісімсот дев'яносто мільйонів триста двадцять один"# Float numberconverter.convert(132.41)"сто тридцять дві цілих сорок одна сота"Run testspython3-munittesttests.num_to_str_reprLicenseMIT
Package: numtostr-rus
Simple python number-to-russian-string converter.Current version works only for ints.Requires python version 3.6.2 or higher.Examples:>>>importnumtostr_rus>>>>>>numtostr_rus.convert(0)'ноль'>>>numtostr_rus.convert(-508)'минус пятьсот восемь'>>>numtostr_rus.convert(600)'шестьсот'>>>numtostr_rus.convert(...42*10**606+73*10**177...)'сорок два центиллиона центиллионов семьдесят три септендециллиона квадрагинтиллионов'
Package: numutil
Strings to Numbers:>>> from numutil import str2num, num2str
>>> str2num('1.3 million')
1300000
>>> str2num('three and a half')
Fraction(7, 2)
>>> str2num('123,456.789')
123456.789Numbers to Strings:>>> num2str(1234567, style='newspaper')
'1.23 million'
>>> num2str(1234567, style='words')
'one million, two hundred thirty four thousand, five hundred sixty seven'numutil might be useful for people mining data from text, or for people running web apps that need to parse numbers from user-entered strings, or render numbers in a user-friendly format.
Package: numutils.n2w
A python package to convert a number to words.Usagefrom numutils import n2w

n = n2w(1023)
n.words()will outputone thousand and twenty threeFree software: MIT licenseFeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-12-18)First release on PyPI.0.1.3 (2021-01-17)Fix installer dependecies
Package: numword-georgia
Numword GeorgiaNumword GeorgiaUsageInstallationLicenseUsageConverts numbers to wordsfromnumword_georgiaimporttranslatefornumberin[5909,9999,7000,7707,91]:print(f"Number{number}is '{translate(number)}'")Number 5909 is 'ხუთი ათას ცხრაას ცხრაი'
Number 9999 is 'ცხრაი ათას ცხრაას ოთხმოცდაცხრამეტი'
Number 7000 is 'შვიდი ათასი'
Number 7707 is 'შვიდი ათას შვიდას შვიდი'
Number 91 is 'ოთხმოცდათერთმეტი'Installationpip install numword-georgiaLicensenumword-georgiais distributed under the terms of theMITlicense.
Package: numworkshop
Numworks-workshop.pyThis project is a python wrapper for the numworksworkshop.How to install ?Just install the pypipackageWith pip :pip install numworkshopOr with poetry :poetry add numworkshopHow to use ?fromnumWorkshopimportScript,Workshopworkshop=Workshop("email","password")toaster=Script(name="name",description="description",content="print('hello-world')",public=True)workshop.create_script(toaster)toaster.content="print('nsi.xyz')"# Since we use the script name to get acess and edit your script, your should use the name parameter# of the edit_script method, this will update the script at the end of the process and not break script# Other parameter are updated throught Script object...workshop.edit_script(toaster,name="namev2")workshop.delete_script(toaster)script=workshop.get_script("https://workshop.numworks.com/python/thierry-barry/annuite_constante")# This return a script object.print(script)If you find a bug or want a new feature you can open an issue.Adding feature ?First clone the project :git clone https://github.com/LeGmask/numWorkshop.gitInstall project withpoetry:poetry installThen you're ready to go !
Package: numx
NumX - Import NumbersJust Import Numbers.>>fromnumximportp25# The 25th prime>>print(p25)97This library allows importing useful numbers, as the Nth prime, prime lists, random numbers, fibonacci, e, pi, ...The library isthoroughly tested, and usessympyas its computational mind.How to Downloadpip install numxSupported Number TypespN- the Nth prime.plN- list of the first N primes.PN- count the primes upto N.PLN- list of primes upto N.nN- the number N.rN- random integer in range [0, N].piN- pi to N decimal places (as numx.__Float).eN- e to N decimal places (as numx.__Float).tN- Euler's totient function of N.faN- N! (N factorial).fiN- fibonacci(N), starting from fi0 == 0.Moreover, for big numbers you can use:2e7to denote2 * 10**72p7to denote2 ** 7_as a dot, so:6_25p_5is6.25 ** 0.5An import can fail only when importing a variable written in a bad format (e.g. numx.n7e will fail).When it fails, numx will raise the numx.__NumXError exception, which inherits from ValueError.numx.__Float is sympy.Float, which supports the str() and float() functions.How to TestThe library is thoroughly tested. If you want to run the test, just run:>> git clone https://github.com/tomhea/numx.git
>> pytest numx
Package: nuna-sql-tools
This package contains Python modules for helping developers
produce and maintain data analysis projects. In particular:dataschema: a library for defining data schemas using Python
dataclasses, that that can be easily converted between protobuffers,
Scala case classes, sql (ClickHouse) create table statements,
Parquet Arrow schemas and so on, from a central Python based
representation. Includes facilities to generate sample date and
compare schemas for validations.sql_analyze: a library for analyzing SQL statements. In particular
the raw SQL statments are parsed and converted to a Python based
data structure. From here, they can be converted to a data graph,
visualized, and information about the lineage of tables and columns
can be infered. Support for now SparkSql and ClickHouse dialects
for parsing.To try out the SQL Analyze Viewer, which uses thesql_analyzelibrary
to visualize SQL statements, you can runsql_analyze-viewerafter
installing.For more details please check theGitHub project.
Package: nunchaku
Nunchaku: Optimally partitioning data into piece-wise segmentsnunchakuis a statistically rigorous, Bayesian algorithm to infer the optimal partitioning of a data set into contiguous piece-wise segments.Who might find this useful?Scientists and engineers who wish to detect change points within a dataset, at which the dependency of one variable on the other change.For example, ify's underlying function is a piece-wise linear function ofx,nunchakuwill find the points at which the gradient and the intercept change.What does it do?Given a dataset with two variables (e.g. a 1D time series), it infers the piece-wise function that best approximates the dataset. The function can be a piece-wise constant function, a piece-wise linear function, or a piece-wise function described by linear combinations of arbitrary basis functions (e.g. polynomials, sines).For piece-wise linear functions, it provides statistics for each segment, from which users select the segment(s) of most interest, for example, the one with the largest gradient or the one with the largest $R^2$.For details about how it works, please refer to ourpaper, freely available onBioinformatics.InstallationTo install via PyPI, type in Terminal (for Linux/Mac OS users) or Anaconda Prompt (for Windows users withAnacondainstalled):> pip install nunchakuFor developers, create a virtual environment, install poetry and then installnunchakuwith Poetry:> git clone https://git.ecdf.ed.ac.uk/s1856140/nunchaku.git
> cd nunchaku 
> poetry install --with devQuick startDataxis a list or a 1D Numpy array, sorted ascendingly; the datayis a list or a 1D Numpy array, or a 2D Numpy array with each row being one replicate of the measurement.
Below is a script to analyse the built-in example data.>>> from nunchaku import Nunchaku, get_example_data
>>> x, y = get_example_data()
>>> # load data and set the prior of the gradient
>>> nc = Nunchaku(x, y, prior=[-5, 5]) 
>>> # compare models with 1, 2, 3 and 4 linear segments
>>> numseg, evidences = nc.get_number(num_range=(1, 4))
>>> # get the mean and standard deviation of the boundary points
>>> bds, bds_std = nc.get_iboundaries(numseg)
>>> # get the information of all segments
>>> info_df = nc.get_info(bds)
>>> # plot the data and the segments
>>> nc.plot(info_df)
>>> # get the underlying piece-wise function (for piece-wise linear functions only)
>>> y_prediction = nc.predict(info_df)More detailed examples are provided ina Jupyter Notebook in our repository.DocumentationDetailed documentation is available onReadthedocs.Development historyv0.15.0: supports detection of piece-wise functions described by a linear combination of arbitrary basis; supports Python 3.11.v0.14.0: supports detection of linear segments.Similar packagesTheNOTpackage written in R.Thebeastpackage written in R.CitationIf you find this useful, please cite our paper:Huo, Y., Li, H., Wang, X., Du, X., & Swain, P. S. (2023). Nunchaku: Optimally partitioning data into piece-wise linear segments.Bioinformatics.https://doi.org/10.1093/bioinformatics/btad688
Package: nunet
NU-Net: a self-supervised smart filter for enhancing blobs in bioimagesWhile supervised deep neural networks have become the dominant method for image analysis
tasks in bioimages, truly versatile methods are not available yet because of the
diversity of modalities and conditions and the cost of retraining. In practice,
day-to-day biological image analysis still largely relies on ad hoc workflows often
using classical linear filters. We propose NU-Net, a convolutional neural network filter
selectively enhancing cells and nuclei, as a drop-in replacement of chains of classical
linear filters in bioimage analysis pipelines. Using a style transfer architecture, a
novel perceptual loss implicitly learns a soft separation of background and foreground.
We used self-supervised training using 25 datasets covering diverse modalities of
nuclear and cellular images. We show its ability to selectively improve contrast, remove
background and enhance objects across a wide range of datasets and workflow while
keeping image content. The pre-trained models are light and practical, and published as
free and open-source software for the community. NU-Net is also available as a plugin
for Napari.InstallationUse PyPI (Python Package Index)pipinstallnunetor clone this repo and install it locallygitclonehttps://github.com/LaboratoryOpticsBiosciences/nunet.gitcdnunet
pipinstall-e.UsageThe repo provides two scripts: one to test and the other to train a NU-Net.For common steps to test and train NU-Nets,Go to release pagehttps://github.com/LaboratoryOpticsBiosciences/nunet/releasesDownload an archive callednunet_models.tarand unzip it in the root directory of
the repo. It should unzipconfig/folder andmodels_filter_slider/folder.To test pre-trained NU-Nets,Execute./scripts/test_nunet.pyfollowing its instruction on the top of
the script.Get help message by invoking the scriptpython scripts/test_nunet.py --help.To train the pre-trained NU-NetsExecute./scripts/train_nunet.pyfolowing its instruction.Note that the provided NU-Net models on the releases page are not reproducible until
we later release private datasets, namely ones prefixed withLOB_. Find more details
in the paper.CitationThis work was accepted by BIC (Bio-Image Computing) workshop at ICCV2023. The paper will
become available soon.
Package: nupass
NuPassReadable, typable password generator script. Because your users can't deal withpwmake.NuPass provides thenupasspackage and a command-line script for generating temporary
passwords that your users can read and type. Passwords are provided by thegen_pass()function and are in the following format:{number}{Capitalized_word}{special_character}{Capitalized_word}{number}For example,4Toffee@Buttercream7.InstallationOS X & Linux:pipinstallnupassWindows:python-mpipinstallnupassUsage exampleGenerate a single password:$nupassGenerate five passwords:$nupass5Development setupUsing NuPass in your projects:importnupasstemp_pass=nupass.gen_pass()# returns a string containing your passwordIf you want to change the length of the words used in the password, you can set the parameters ofgen_pass().importnupasstemp_pass=nupass.gen_pass(min_w_len=4,max_w_len=10)# functionally the same as nupass.genpass(4, 10)Release History1.0.0ADD: Include README as long description on PyPI.CHANGE: Use native setuptools method for script installation.0.2.1ADD: Word length now set by function parameters.CHANGE: Fixed an issue where the wordlist wasn't being closed.CHANGE: Fixed an issue with invalid command-line arguments.0.2.0CHANGE: Converted to packageADD: Script added to path when installed viasetup.py0.1.0The first proper releaseMetaSean Callaway –@smcallaway–seancallaway@gmail.comDistributed under the GNU GPL v2 license. SeeLICENSEfor more information.https://github.com/NuPass/NuPassContributingFork it (https://github.com/NuPass/NuPass/fork)Create your feature branch (git checkout -b feature/fooBar)Commit your changes (git commit -am 'Add some fooBar')Push to the branch (git push origin feature/fooBar)Create a new Pull Request
Package: nuphy2
Examples:Run 40MeV/A of 40Ar through mylar/bin_nuphy2 sri -i ar40 -m mylar -e 1600 -t 3umRun the same beam through 12cm of isobutane at 950 mbar 20deg C./bin_nuphy2 sri -i ar40 -m hisobutane -e 1600 -t 120mm -p 95000 -k 293Same through the layer of mylar+isobutane./bin_nuphy2 sri -i ar40 -m hisobutane -e 1600 -t 120mm -p 95000 -k 293Similar, two mylar windows:./bin_nuphy2 sri -i ar40  -m mylar,hisobutane,mylar -e 1600 -t 3um,120mm,3um -p 95000 -k 293Some databaseshttp://nucleardata.nuclear.lu.se/toi/nuclide.asp?iZA=260059https://www.nndc.bnl.gov/nudat2/indx_dec.jspProject: nuphy2Module: react|            | In    | FireWrks   | Fully |        | In     |                          |                    |
| module     | Place | ParamCheck | Func  | Pytest | BinDir | description1             | description2       |
|------------+-------+------------+-------+--------+--------+--------------------------+--------------------|
| prj_utils  | y     | NO         | NEVER | NO     | NO     | Color,Fail,Print,GetFile |                    |
| isotope    | y     | y          | ~     | y      | y      | gives isotope data       | used by kinematics |
| kinematics | y     | y          | y     | y      | y      | kinematic calc           |                    |
| rolfs      | y     | y          | y     | y      |        |                          |                    |
| srim       | y     |            |       |        |        |                          |                    |
| xsections  |       |            |       |        |        |                          |                    |
| yields     |       |            |       |        |        |                          |                    |
| radcap     |       |            |       |        |        |                          |                    |
| tendl      |       |            |       |        |        |                          |                    |
|------------+-------+------------+-------+--------+--------+--------------------------+--------------------|
| fispact    |       |            |       |        |        | from nuphy1              |                    |
| sr         |       |            |       |        |        | nuphy1                   |                    |
| spectra    |       |            |       |        |        | nuphy1                   |                    |
./srim.py -i h1 -m al -e 24.4 -t 3mm -n 300 -w a.h5
Package: nupic
Numenta Platform for Intelligent Computing: a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources.For more information, seehttp://numenta.orgor the NuPIC wiki athttps://github.com/numenta/nupic/wiki.
Package: nupic_studio
NuPIC Studio is a virtual studio that allows developers to create, debug, and visualize HTM networks from NuPIC library. Some of its advantages:
* Users can open, save, or change their “HTM projects” or of other developers. A typical project contains data to be trained, neural network configuration, statistics, etc, which can be shared to be analysed or integrated with other projects.
* Users can create their own encoders and sensors to feed the HTM network.
* Any changes in the nupic source can be immediatedly viewed. This helps users that wish test improvements like hierarchy, attention, and motor integration.
For more information, see numenta.org or the NuPIC wiki (https://github.com/nupic-community/nupic.studio/wiki).
Package: nup-poder-judiciario
Numeração Única do Poder Judiciário - nup_poder_judiciarioEste package oferece funcionalidades relacionadas à numeração única de processos do Poder Judiciário, que segue a estrutura NNNNNNN-DD.AAAA.J.TR.OOOO, instituida pelo Conselho Nacional de Justiça.Resolução nº 65 de 16/12/2008
Disponível em:http://www.cnj.jus.br/atos-normativos?documento=119Projeto de referência em TypeScript:https://github.com/edipojuan/numero-unico-processo/blob/master/src/numero-unico-processo.util.tsUso:
``
from nup_poder_judiciario import NumeroUnicoProcessonumero_processo = NumeroUnicoProcesso('1024981-09.2022.4.01.3600')
``Atributos:
'ano' - ano do processo
'numero' - retorna só a parte NNNNNNN
'orgao' - retorna só a parte OOOO
'segmento' - retorna só a parte J
'soNumeros' - retorna só os dígitos
'tribunal' - retorna só a parte TR
'dv' - dígito verificador do processoFuncionalidades:
'calcular' - calcular a fórmula inicial
'calcularDigitoVerificador' - calcular dígito verificador
'dicionariza' - transforma em dicionário
'formatado' - retorna o número formatado
'validar' - verificar se é um número de processo válido
Package: nuqql
nuqqlnuqql is a command line instant messenger inspired bycentericqandcenterimwritten in Python and using ncurses.nuqql uses so-called backends for connecting to chat networks. Currently, nuqql
supports the following backends:nuqql-slixmppd: nuqql-slixmppd
uses slixmpp and allows nuqql to connect to XMPP chat networks.nuqql-matrixd-nio:
nuqql-matrixd-nio uses matrix-nio and allows nuqql to connect to Matrix chat
networks.nuqql-matrixd: nuqql-matrixd uses
the Matrix Python SDK and allows nuqql to connect to Matrix chat networks.
Note: the Matrix Python SDK project strongly recommends using matrix-nio, so
prefer using nuqql-matrixd-nio.nuqql-mattermostd:
nuqql-mattermostd uses the Mattermost Golang Driver and allows nuqql to
connect to Mattermost serverspurpled: purpled uses libpurple and
allows nuqql to connect to multiple chat networks. Note: purpled is less
tested than other backends, so you might want to prefer other backends.Quick StartYou can install nuqql, for example, with pip for your user only with the
following command:$pipinstall--usernuqqlThe basic nuqql setup consist of installing one or more backends and adding
your instant messaging accounts to them. Seesetupfor more
information about how to setup nuqql.RunAfter the installation, you can run nuqql with thenuqqlcommand:$nuqqlOverviewThe layout of nuqql is as follows:+--------------+----------------+
|              |                |
|              |                |
|              |                |
|              |   Log Window   |
|              |                |
| List Window  |                |
|              |                |
|              +----------------+
|              |                |
|              |  Input Window  |
|              |                |
+--------------+----------------+List Window: shows the Conversation ListLog Window: shows the Log of the current ConversationInput Window: shows the user's input of the current ConversationThe Conversation List shows your buddies and special conversations for your
backend commands and nuqql commands. Buddies are shown with their status (on,
afk, off) and their name, e.g.,[on] buddy@jabber.org. Group chats and
invites to group chats are shown with[grp]and[grp_invite]as a special
status. The nuqql and backend command conversations are shown as{nuqql}and
with{backend}in front of their name, e.g.,{backend} slixmppd.ControlsBasic controls of nuqql are:Navigate the Conversation List with the arrow keysUPandDOWNPressENTERon a conversation to open itPresshon a conversation to open it and switch to its chat logIn a conversation:Enter your message/commandSend message/command withCTRL-xSwitch to chat log window withCTRL-oorF9Search chat log with/Leave conversation with theESCkeyExit nuqql with theqkey when you are in no conversationSeecontrolsfor more information about nuqql's controls.DevelopmentMost of the development happens in thedevelbranch. When a new version of
nuqql is released, thedevelcode is merged into themasterbranch. So,
if you want to try the latest code, check out thedevelbranch, otherwise
just usemaster.ChangesSeechangelogfor changes in each version.