Saravanan666/pypi-org huggingface dataset:
Package: numismatic
Numismatic - Coin Collecting for Digital Assets===============================================|Join the chat at https://gitter.im/numismatic-chat/Lobby| |PyPIlicence| |PyPI version| |Python versions| |PyPI format|Install-------::pip install numismaticRun---Run the ``coin`` script from anywhere and explore from there::coincoin listcoin infocoin info -a BTC,ETH,XMR,ZECcoin pricescoin prices -a BTC,ETH,XMR,ZECcoin subscribe -a BTC,ETH,XMR,ZEC collect runcoin subscribe -e bitfinex -e gdax collect -t Trade runContribute----------::git clone https://github.com/snth/numismatic.gitcd numismaticpip install -e .# Add awesome new features and submit Pull Requests.. |Join the chat at https://gitter.im/numismatic-chat/Lobby| image:: https://badges.gitter.im/numismatic-chat/Lobby.svg:target: https://gitter.im/numismatic-chat/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge.. |PyPI licence| image:: https://img.shields.io/pypi/l/numismatic.svg:target:.. |PyPI version| image:: https://img.shields.io/pypi/v/numismatic.svg:target:.. |Python versions| image:: https://img.shields.io/pypi/pyversions/numismatic.svg:target:.. |PyPI format| image:: https://img.shields.io/pypi/format/numismatic.svg:target:
Package: numix
Numix
!PyPI version !Build Status !Coverage StatusNumix is a Python package that generates random numbers of various types and distributions. You can use Numix to create random integers, floats, decimals, fractions, complex numbers, and more. Numix also supports generating random numbers from common probability distributions, such as uniform, normal, binomial, Poisson, etc.Numix is useful for applications that require randomness, such as simulations, cryptography, games, testing, and data analysis. Numix is easy to use, flexible, and fast.Installation
You can install Numix from PyPI using pip:pip install NumixAlternatively, you can clone this repository and install from source:git clonehttps://github.com/abelzk/numix.gitcd Numix
python setup.py installUsage
To use Numix, simply import the Numix module and call the appropriate function for the type of random number you want. For example:Pythonimport NumixGenerate a random integer between 1 and 10n = Numix.randint(1, 10)
print(n)Generate a random float between 0 and 1x = Numix.random()
print(x)Generate a random decimal with 2 digits after the decimal pointd = Numix.decimal(2)
print(d)Generate a random fraction with denominator 5f = Numix.fraction(5)
print(f)Generate a random complex number with real and imaginary parts between -1 and 1c = Numix.complex()
print(c)Generate a random number from a normal distribution with mean 0 and standard deviation 1z = Numix.normal()
print(z)
AI-generated code. Review and use carefully. More info on FAQ.
For more details and examples, please refer to the documentation.License
Numix is licensed under the MIT License. See the LICENSE file for more information.Contributing
Numix is an open source project and welcomes contributions from anyone. If you have any suggestions, bug reports, or feature requests, please open an issue on GitHub. If you want to contribute code, please fork the repository and submit a pull request. See the CONTRIBUTING file for more guidelines.
Package: numjuggler
numjugglerTool to rename cells, surfaces, materials and universes in MCNP input files. Seehttps://numjuggler.readthedocs.ioCurrent status-- shows status of the tests defined intravis_testsfolder.-- available from PyPI.-- documentationInformation in the help message, returned bynumjuggler -h modeis
outdated. Therefore, the best way to see all current modes is to search forargs.mode ==string inmain.py, and read comments in the correspondent
sections of code.Documentationhttps://numjuggler.readthedocs.ioshould be considered as the main source of information.There is also a github reponumjuggler.docscontaining presentations and reports related to numjuggler.InstallThe numjuggler package is available at PyPI:https://pypi.org/project/numjuggler/. The preffered
way to install it using pip:>pip install numjugglerAlternatively, one can clone from github and install in so-called development mode:>git clone git@github.com:travleev/numjuggler.git
>cd numjuggler
>pip install -e .
Package: numkit
numkitis a small collection of numerical helper functions and
classes (“numerical first aid kit”) that have been useful forGromacsWrapperand related projects.Originally,numkitwas part ofGromacsWrapperbut was split off
into its own small package in version 0.7.0 of GromacsWrapper.Getting numkitInstall withpipfrom PyPi withpip install numkitor withcondafrom theconda-forgechannelconda install -c conda-forge numkitThe source code is available under the BSD 3-clause license (see file
LICENSE) from GitHub in the repositoryhttps://github.com/Becksteinlab/numkitgit clone https://github.com/Becksteinlab/numkitPython 2/3Python 2.7 is still supported. Python 3 support for releases 3.7 - 3.11
is tested.ContributingContributions are very welcome in all forms, especially through issue
reports and pull requests.
Package: numkl
# NUMKL[![version](https://img.shields.io/pypi/v/numkl.svg)](https://pypi.org/project/numkl/)
[![conda](https://anaconda.org/refraction-ray/numkl/badges/version.svg)](https://anaconda.org/refraction-ray/numkl)This package works as the python wrapper to directly call some MKL routines while keep the same interface with numpy.## InstallUsepip install numklOrconda install -c refraction-ray numklYou should make sure Intel MKL library and Intel compilers are installed and configured for relevant enviroment variables. Especially, environment variableMKLROOTis necessary for pip installation. And properLD_LIBRARY_PATHis necessary in runtime.Currently, you also need cython preinstalled in your python enviroment for pip installation.Note this package is in its very early age, no guarantee on successful installation and usage. And this package only supports linux.## Example`python import numpy as np from numkl import eig a =np.array([[0.,1.0],[1.0,0.]])e,v = eig.eighx(a) `## WhyThis package is not reinventing wheels like numpy, instead, it provide features that current numpy doesn’t provide.For the symmetric or Hermitian matrix eigenproblem, numpy has already provided the interfacenumpy.linalg.eighandnumpy.linalg.eigvalsh. By correctly configuring and linking, these two functions also can directly calling MKL routines. So why bother?There are at least two aspects why numpy eigenproblem interface is not good enough:The 32 bit int overflow and unable to calculate eigenproblem for large matrix. See [this issue](https://github.com/numpy/numpy/issues/13956). Note currently this issue cannot be solve by simply hacking the compiling parameters, instead one need to change the source code of numpy.The memory waste due to keeping the input matrix. See [this issue](https://github.com/numpy/numpy/issues/14024). Actually, it costs two times of the space in numpy for getting all eigenvalues than directly using lapack routine.In a word, this package is designed for “push-to-the-limit” style computations, where you can compute the eigenproblem for matrix dimension larger than 32766. And the interface is seamlessly integrated with numpy.
Package: numla
Numla PackageFast numpy LAbeled aRRaY for financial time series data. Simply load, slice, cache, and analyze. Accelerators: C, Numba, Vectorization.pip3 install numlafrom numla import larryorimport numla as laohlcv = np.array([[1, 2, 3, 4, 5], [6, 7, 8, 9, 10]])label = [['open', 'high', 'low', 'close', 'volume'], ['2022-01-17 00:00:00', '2022-01-18 00:00:00']]dk = larry(ohlcv, label, dtype=float)ordk = larry(dataframe)
Package: numlet
NumletNumlet es una pequeña librería basada en Python capaz de convertir más de dos duocentillones de números diferentes a letras.Instrucciones de instalaciónPero antes,Asegurate de tener la última versión de pip instalada.Nota que la primera alternativa se lleva a cabo desde un archivo normal de Python y la
segunda desde un Jupyter Notebook.Primera alternativa.Esta alternativa se ha probado desde PyCharm.Abre el script donde quieres importar Numlet.Ve a la terminal del IDE y ejecuta:>  pip install git+https://github.com/roylanmartinez/Numlet.gitSi trabajas desde otro IDE y no sabes como instalar un package haz clíckaquíListo. Ve a la secciónUtilización.Segunda alternativaEsta alternativa se ha probado desde Jupyter Notebook.Abre el script donde quieras importar Numlet.En la primera celda ejecuta:In []: ! pip install git+https://github.com/roylanmartinez/Numlet.gitListo. Ve a la secciónUtilización.UtilizaciónAhora en tu script simplemente la importas.fromnltimportnumletasnlEjemplo 1:n=1resultado=nl.Numero(n).a_letrasprint(resultado)UnoEjemplo 2:n=-1000.123resultado=nl.Numero(n).a_letras.lower()print(resultado)menos mil con ciento veintitrés milésimasEjemplo 3:Recuerda poner los números décimales muy pequeños en comillas, más informaciónaquín='0.0000000000000000001'resultado=nl.Numero(n).a_letras.upper()print(resultado)CERO CON UNA DIEZTRILLONÉSIMAEjemplo 4:n=-1*abs(1+1000+1.12)resultado=nl.Numero(n).a_letrasprint(resultado)Menos Mil Dos Con Doce CentésimasContribuciónLas pull requests son bienvenidas, así como comentarios acerca de mejoras o bugs.LicenciaMIT¡Espero que les guste!Repositorio:https://github.com/roylanmartinez/Numlet
Package: numlookupapi
NumlookAPI Python ClientCurrencyAPI Python Client is the official Python Wrapper around the CurrencyAPIAPI.InstallationInstall from pip:pipinstallnumlookupapiInstall from code:pipinstallgit+https://github.com/everapihq/numlookupapi-python.gitUsageAll numlookupapi API requests are made using theClientclass. This class must be initialized with your API access key string.Where is my API access key?In your Python application, importnumlookupapiand pass authentication information to initialize it:importnumlookupapiclient=numlookupapi.Client('API_KEY')Retrieve Statusprint(client.status())Retrieve Currencieshttps://numlookupapi.com/docs/validateresult=client.validate('+14158586273')# result = client.validate('14158586273', country_code='US')print(result)Contact usAny feedback? Please feel free tocontact our team.
Package: numlpa
What does it mean?The name "NumLPA" comes from the contraction of "Numerical Line Profile Analysis".What is the use of it?NumLPA is a Python package developed for research in materials science.Is it hard to use?Just type one of the available commands in a terminal and look at the generated files.BackgroundThe physical properties of a solid material are strongly impacted by the nature and quantity of structural defects it contains.
It is therefore important to have reliable tools to characterize deviations from a perfect crystal.
Line Profile Analysis (LPA) is one of the methods used for the study of microstructures from the analysis of X-ray diffraction patterns.FeaturesNumLPA Has been developed to meet the need to analyze the accuracy of LPA models.
The main features of the package are presented bellow:draw: Generate samples of dislocations by random drawing from different probability distribution models.diffract: Simulate X-ray diffraction on crystals containing the previously generated dislocations and compute the Fourier transform of the diffracted intensity.merge: Average the Fourier transform coefficients or the strain energy evaluations from multiple samples drawn from a same distribution.fit: Fit LPA models on the simulated diffraction profiles to obtain their predictions and compare them to the real parameters of the distribution.evaluate: Compute the strain energy density and the outer cut-off radius for a sample of dislocations.analyze: Perform a spatial statistical analysis and calculate the strain energy contained in a sample of dislocations.export: Export figures illustrating the previously generated data according to different representations.InstallationYou can find how to install the package in theinstallation sectionof the documentation.UsageYou can find how to use the package in theexamples sectionof the documentation.CreditsDunstan BechtAsdin AoufiAndrás BorbélyLicenseThis program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.You should have received a copy of the GNU General Public License along with this program. If not, seehttps://www.gnu.org/licenses/.
Package: numm
# nummFor programmers familiar with python or matlab who are interested in
toying with the sounds and images around them; for artists, designers,
and composers seeking a deeper understanding of the numerical systems
that underlie modern media production.numm is a minimalist media library that translates popular sound,
image, and video formats to and from numpy arrays. By coercing inputs
into common modes (eg. sample rate, bit depth), combining and mutating
these numpy arrays is greatly simplified.The general strategy for these functions is to make any assumptions
necessary such that a single array of numbers provides sufficient
information with which to reconstruct a media file, without any
additional metadata. For example, width and height are contained in
the dimensions of an array, so they may be different image to image,
but framerate, samplerate, &c is not inherent to the data, so it
should be made uniform unless explicitly specified.In the transition from an image to an array, the primary
considerations are resolution (wxh) and mode (RGB, RGBA, 8bit, 16bit,
&c). We choose not to provide any special API for resampling an
Image–this can be done with numpy if desired–and always return 8bit
RGB buffers.image2np(path)
np2image(np, path)In the case of audio, we choose to force all input to 44100Hz stereo.sound2np(path)
np2sound(np, path)Video is an array of wxhx3 arrays 30frames per second. Square pixels
are assumed.video2np(path)
np2video(np, path)Note that in particular in the case of video, these numpy buffers will
require a considerable amount of memory; preprocess accordingly (eg in
ffmpeg). We should also raise a NotEnoughMemory exception when RAM
will not hold our buffer.The live interface is provided by numpy.run.run(), a function with
just a few input-output controls, communicated through function
passing.## RequirementsPyGstPILRecommended:OpenCV## LicenceCopyright (C) 2011, Dafydd Harries <daf@numm.org>
Copyright (C) 2011, Robert Ochshorn <rmo@numm.org>This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or (at
your option) any later version.This program is distributed in the hope that it will be useful, but
WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
General Public License for more details.You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
Package: nummer-games
The Number GameThis Python module allows you to guess random numbers within your selected
number of attempts. It also allows you to guess Prime numbers within your
selected number of attempts.InstructionsEnter your terminalInstall the module:pip install nummer-gamesEnter your python interactive shell:pythonImport required functions:from nummer_games import Classify, PrimeIterate through attempts by guessing random numbers:Classify(n).guess_number()Iterate through attempts by guessing prime numbers:Prime(n).guess_prime_number()Note:n represents the number of attemptsIllustrationYou can look into the screenshots or commands below to follow through the
process of guessing random numbers and prime numbers in three attempts.pythonfrom nummer_games import Classify, PrimeClassify(3).guess_number()pythonfrom nummer_games import Classify, PrimePrime(3).guess_prime_number()Have fun. Please Feel free to contact me if you encounter any issue.
Package: nummu
nummu (南無)An animated image maker.NOTE: this project in WIP and thus interface might change a lot. Be cautious when using in production.ImageScriptexamples/helloworld.pyexamples/line.pyexamples/rect.pyBubble SortHeap SortInsertion SortMerge SortQuick SortSelection Sortexamples/sort.pyexamples/image.pyexamples/text.pyInstall$ pip install nummuUsageNummu is simply a framework so you might want to implement a class having these methods:update(delta),draw(palette). None of them are absolutely required.class HelloWorld:

    def __init__(self):
        # Do initial work here
        self.position = 0

    def update(self, delta):
        # Do some calculation before draw each frame.
        # The delta is in millisecond unit.
        #
        # Don't forget to raise StopIteration somewhere!
        #
        self.position += delta
        if self.position >= 100:
            raise StopIteration

    def draw(self, pallete):
        # Pallete is simply a numpy.zeros instance.
        # Overwrite any pixels as you want.
        #
        pallete[:, self.position, :] = 255Basic usage:# import nummu
from nummu import Nummu

# set file size
nm = Nummu(100, 100)

# add drawer defined previously
nm.add(HelloWorld())

# export to gif
nm.export('helloworld.gif', delay=5)Check the examples in project repo, and hopefully it might help you!Develop$ poetry develop
$ poetry run python examples/helloworld.pyTestCurrently nummu support running on 3.6, 3.7$ pyenv install 3.6.5
$ pyenv install 3.7.0b2
$ pyenv local 3.6.5 3.7.0b2
$ export PATH=$(pyenv root)/shims:$PATH
$ tox
py36 runtests: commands[0] | poetry develop
py36 runtests: commands[0] | poetry run pytest
py37 runtests: commands[0] | poetry develop
py37 runtests: commands[0] | poetry run pytest
  py36: commands succeeded
  py37: commands succeeded
  congratulations :)CreditThanks Pillow, numpy, numpngw and array2gif! Nummu stands on the shoulder of these giants!
Package: numops
Github Actions to update package on pypiThis repo is a reference code to automatically push the latest package release to pypi on creating a github release tags.Table of ContentAdd required files for pypiUpdate PYPI CredentialsCreate package releaseStep 1: Add required filesPypi requires following files to build a packagesetup.pysetup.cfgREADME.mdCreate a new file.github\workflows\publish-to-pypi.ymland copy paste below content.name:Upload Python Packageon:release:types:[created]jobs:deploy:runs-on:ubuntu-20.04steps:-uses:actions/checkout@v2-uses:actions/setup-python@v2-name:Install dependenciesrun:|python -m pip install --upgrade pippip install setuptools wheel twine-name:Build and publishenv:TWINE_USERNAME:${{ secrets.PYPI_USERNAME }}TWINE_PASSWORD:${{ secrets.PYPI_PASSWORD }}run:|python setup.py sdist bdist_wheeltwine upload dist/*Step 2: Update PYPI CredentialsNext add pypi credentials in github secrets with following Keys under settings -> secrets.PYPI_USERNAMEPYPI_PASSWORDStep 3: Create package releaseAfter files are inplace and pypi credentials has been updated in github repo secrets, next step is to create a release tag in the repo, which will trigger github actions to run workflow defined in.github\workflows\publish-to-pypi.yml, leading to deployment of package in pypi.Below GIF covers all the key steps involvedCreate a release tag:
On creation of release tag, github action will automatically start building distribution files and push them to pypiCheck Actions: Check whether workflow actions has initiated or not.Validate package updation in pypi:  To validate whether package has been pushed to pypi or not. Visit pypi website and search for the package nameInstall updated package: Run below pip command to install package.pip install packagename==version
Package: numpatt-sequence
number-patternsUnder construction!
Not ready for use yet. Currently experimenting and planning.
Developed by Dilith Achalan (c) 2022SummaryThis project is created to identify the number patterns on a given number sequence which will get the difference in sequence and general term or general ratio.How to import the moduleYou can importnumpattmodule which is insidenumpatternsproject folder. You may use below code snippet to importconvert_str_floatfuntion.fromnumpatterns.numpattimportconvert_str_floatBelow functions are available to use.Funtionsconvert_str_floatcheck_listget_common_termget_common_ratiocommon_differencemulti_differenceclassify_patternExamples of how to useconvert_str_float - funtionThis funtion take two parametersstring number list,seperatorand return the output as a list with floating values.# get user input to enter a number sequencenum_list=input("Enter the number sequence: ")nth=int(input("Enter the nth in sequence: "))# calling the 'convert_str_float' function to get a list with string values to floatn_list=convert_str_float(num_list,sep=",")print(n_list)check_list - funtionThis funtion will takestring number listand check if the list has at least two items to operate sequencen_list=[2,4,6,8]# calling the 'check_list' function to validate if list has at least two itemsifcheck_list(n_list):print("This list has at least two items ")
Package: numphy
Numphy provides simple access to physics objects (particles, Lorentz vectors, points, etc.) backed byNumPyarraysand/orTensorFlowtensors.Note: This project is currently under development.First stepsInstallation and DependenciesInstall viapip:pipinstallnumphyNumPy is the only dependency.DevelopmentSource hosted atGitHubReport issues, questions, feature requests onGitHub IssuesContributing and TestingIf you like to contribute, we are happy to receive pull requests. Just make sure to add a new test case and run them via:python-munittesttestsAuthorsMarcel R.Benjamin F.LicenseThe MIT License (MIT)Copyright (c) 2018 Marcel R.Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.