Saravanan666/pypi-org huggingface dataset:
Package: pyscissor
pyscissorA Python3 module for extracting data from netcdf file under a shapefile region.Installationpyscissor can be installed using the following commands$gitclonehttps://github.com/nzahasan/pyscissor.git
$cdpyscissor
$python3setup.pyinstallor using pip$pipinstallpyscissorUsing pyscissorimportfionaimportnumpyasnpfromnetCDF4importDatasetfromshapely.geometryimportshapefrompyscissorimportscissor# read shapefilesf=fiona.open('data/shape.geojson')shapely_shp=shape(sf.get(0)['geometry'])# read netcdfnf=Dataset('data/sample_2.nc','r')lats=nf.variables['lat'][:]lons=nf.variables['lon'][:]# create scissor objectpys=scissor(shapely_shp,lats,lons)weight_grid=pys.get_masked_weight()#=> returns a masked array containing weights# get weighted averageavg=np.average(var,weights=weight_grid)# if only intersection mask with shape is needed use `weight_grid.mask`A detailed use case can be found in the following jupyter notebooksexample_01.ipynbexample_02.ipynbexample_03.ipynbexample_04.ipynbUsing nc2ts_by_shp.pythis package contains anc2ts_by_shp.pyscript. A command line tool that can be used to quickly extract
reduced(min/max/average/weighted average) time-series form netcdf file with shapefile# with 3d array [data/sample_2.nc] generel case$nc2ts_by_shp.py-nc=sample_2.nc-nci='Y=lat;X=lon;T=time;V=tmin;'-s=shape_esri.zip\-sp='ADM2_EN;ADM3_EN'-r=avg-o=test2.csv# with 4d array [data/sample_1.nc]$nc2ts_by_shp.py-nc=sample_1.nc-nci='Y=lat;X=lon;T=time;V=temperature;slicer=[:,0,:,:]'-sf=shape_esri.zip\-sfp='ADM2_EN;ADM3_EN'-r=wavg-o=test1.csvOptions:-nc  = netcdf file

-nci = netcdf variable and dimension information
		available options:
		X = x dimension variable name,
		Y = y dimension variable name,
		T = time dimension variable name,
		V = variable name,
		slicer = slicing index for obtaining 3d array [optional]
				
		note: `slicer` is required if variable has more than three dimension

-sf  = shape file ( can be zipped shapefile, shapefile or geojson )

-sfp = shapefile properties
		only required when shapefile contains multiple records

-r   = reducer, default is average
		Available options: min,max,avg,wavg

-o   = output file nameCauses of Erroneous output- when shapefile and netcdf file have different projection
- shapefile dosen't fully reside within netcdf bounds
Package: pyscitt
pyscitt: Python CLI tools for SCITT CCF LedgerTools to sign claims and interact with a SCITT CCF Ledger.For more information, please find thescitt-ccf-ledgerrepository athttps://github.com/microsoft/scitt-ccf-ledger.Package sources are available athttps://github.com/microsoft/scitt-ccf-ledger/tree/main/pyscitt.
Package: pyscitxt
PyPi:https://pypi.org/project/pysci/สวัสดีจ้าาาาวิธีติดตั้งเปิด CMD / Terminalpipinstallpysciวิธีใช้งานแพ็คเพจนี้เปิด IDLE ขึ้นมาแล้วพิมพ์…frompysciimportPymy=Py('')my.a()my.b()พัฒนาโดย: **** FB: *****YouTube: ****
Package: pysclump
PySClumpA Python implementation of 'Spectral Clustering in Heterogeneous Information Networks' from AAAI, 2019.This was heavily inspired by the originalimplementationin MATLAB.Figure: A similarity matrix represented as a graph. Nodes are coloured according to their assigned cluster.ReferencesLi, Xiang and Kao, Ben and Ren, Zhaochun and Yin, Dawei. 'Spectral Clustering in Heterogeneous Information Networks'. Proceedings of the AAAI Conference on Artificial Intelligence: 4221-4228.InstallationPySClump is available on PyPI! Install with:pip install pysclumpPathSimWe provide PathSim as a similarity metric between pairs of nodes. However, PySClump works with any similarity metric! See the SClump section below.from pysclump import PathSim
import numpy as np

type_lists = {
    'A': ['Mike', 'Jim', 'Mary', 'Bob', 'Ann'],
    'C': ['SIGMOD', 'VLDB', 'ICDE', 'KDD'],
    'V': ['Pasadena', 'Guwahati', 'Bangalore']
}

incidence_matrices = { 
   'AC': np.array([[2, 1, 0, 0], [50, 20, 0, 0], [2, 0, 1, 0], [2, 1, 0, 0], [0, 0, 1, 1]]),
   'VC': np.array([[3, 1, 1, 1], [1, 0, 0, 0], [2, 1, 0, 1]])
}

# Create PathSim instance.
ps = PathSim(type_lists, incidence_matrices)

# Get the similarity between two authors (indicated by type 'A').
ps.pathsim('Mike', 'Jim', metapath='ACA')

# Get the similarity matrix M for the metapath.
ps.compute_similarity_matrix(metapath='ACVCA')SClumpOnce we have the similarity matrices (PathSim shown here), running SClump is really simple.from pysclump import SClump

# Construct similarity matrices.
similarity_matrices = {
    'ACA': pathsim.compute_similarity_matrix(metapath='ACA'),
    'ACVCA': pathsim.compute_similarity_matrix(metapath='ACVCA'),
}

# Create SClump instance.
sclump = SClump(similarity_matrices, num_clusters=2)

# Run the algorithm!
labels, learned_similarity_matrix, metapath_weights = sclump.run()If we have n nodes to be clustered into k clusters,labelsis a n-by-1 vector, with entries from 0 to (k - 1) indicating the cluster index assigned.learned_similarity_matrixis the n-by-n matrix S referenced in the paper, indicating node-to-node similarity.The clusters themselves are assigned by k++-means clustering either on the similarity matrix directly, or on the Laplacian of the learned similarity matrix.AcknowledgementsThis would not have been possible without the assistance of my CS529 teammates at IIT Guwahati:Yagyansh Bhatia (yagyanshbhatia)Dhananjay Shukla (dshukla1997)Credit for visualization is completely due to Ramyani Ghosh (ramyani-ghosh).
Package: pySCM
pySCM is a simple climate model developed in Python for producing timeseries of
annual mean global mean surface temperature from projections of greenhouse gases.
pySCM is purposely very simple using only a few couple differential equations.
This means that pySCM is very fast and is controlled using only a few parameters.DocumentationInstructions for using pySCM and a description of the equations used in pySCM are
provided in theDocumentation.Developmentgitclonegit@github.com:bodekerscientific/pyscm.gitpipinstall-e.Tests can be run locally withpython setup.py test
Package: py-scm
This is a python library supporting statechart (in scxml format) originated by David Harel.
Features like hierarchical states, parallel states, and history are ready for you to command.
You won’t find another lib as easy and flexible to use as SCM.Just take a look and run scm_tutorial.py please.
The code is listed here:fromscmimportStateMachineManagerclient_scxml="""
<scxml>
    <state id='appear'>
        <transition event='born' ontransit='say_hello' target='live'/>
    </state>
    <parallel id='live'>
            <transition event='hp_zero' target='dead'/>
            <state id='eat'>
            </state>
            <state id='move'>
            </state>
    </parallel>
    <final id='dead'/>
    </scxml>
"""classLife:def__init__(self):self.mach_=StateMachineManager.instance().getMach('the life')self.mach_.set_do_exit_state_on_destroy(True)self.mach_.register_state_slot("appear",self.onentry_appear,self.onexit_appear)self.mach_.register_state_slot("live",self.onentry_live,self.onexit_live)self.mach_.register_state_slot("eat",self.onentry_eat,self.onexit_eat)self.mach_.register_state_slot("move",self.onentry_move,self.onexit_move)self.mach_.register_state_slot("dead",self.onentry_dead,self.onexit_dead)self.mach_.register_action_slot('say_hello',self.say_hello)self.mach_.StartEngine()deftest(self):self.mach_.enqueEvent("born")#self.mach_.frame_move(0) # state change to 'live'StateMachineManager.instance().pumpMachEvents()self.mach_.enqueEvent("hp_zero")#self.mach_.frame_move(0) # state change to 'dead'StateMachineManager.instance().pumpMachEvents()defonentry_appear(self):print("come to exist")defonexit_appear(self):print("we are going to...")defonentry_live(self):print("start living")defonexit_live(self):print("no longer live")defonentry_eat(self):print("start eating")defonexit_eat(self):print("stop eating")defonentry_move(self):print("start moving")defonexit_move(self):print("stop moving")defonentry_dead(self):print("end")defonexit_dead(self):assert(0and"should not exit final state");print("no, this won't get called.")defsay_hello(self):print("\n*** Hello, World! ***\n")if__name__=='__main__':StateMachineManager.instance().set_scxml("the life",client_scxml)life=Life()life.test()StateMachineManager.instance().pumpMachEvents()The output you should seecome to exist
we are going to...

*** Hello, World! ***

start living
start eating
start moving
stop eating
stop moving
no longer live
endSimplyyou load the scxml from external file or from a string defined in your code.you connect theseonentry_onexit_, etc. slotsyou start the engine, call the framemove in main loop.Done.It’s that easy!Read the tutorials at:(English)http://zen747.blogspot.tw/2017/07/a-scm-framework-tutorial-statechart.html(Traditional Chinese)http://zen747.blogspot.tw/2017/07/scm-framework.html
Package: pyscm-ml
pySCMA fast implementation of the Set Covering Machine algorithm using a dynamic programming algorithm to select the rules of greatest utility.Marchand, M., & Taylor, J. S. (2003). The set covering machine. Journal of Machine Learning Research, 3, 723–746.Installationpip install pyscm-mlorpython setup.py installRunning testspython setup.py testContributorsAlexandre Drouin(package maintainer)Francis BrochuGaël Letarte St-PierreMazid OsseniPier-Luc PlanteThibaud Godon
Package: pyscnn
scnn: Scalable Convex Neural NetworksA library for global optimization of shallow neural networks.
API documentation atReadTheDocs.RequirementsPython 3.8 or newer. Development dependencies are listed indev_requirements.txt.SetupInstall usingpip:python -m pip install pyscnnOr, clone the repository and manually install:git clone https://github.com/pilancilab/scnn.git
python -m pip install scnnContributionsComing soon!CitationPlease cite our paper if you use this package.@article{DBLP:journals/corr/abs-2202-01331,
  author    = {Aaron Mishkin and
               Arda Sahiner and
               Mert Pilanci},
  title     = {Fast Convex Optimization for Two-Layer ReLU Networks: Equivalent Model
               Classes and Cone Decompositions},
  journal   = {CoRR},
  volume    = {abs/2202.01331},
  year      = {2022},
  url       = {https://arxiv.org/abs/2202.01331},
}Looking for the code to replicate our experiments?
Seescnn_experiments.
Package: pyscope
This is the repository forpyscope,
a pure-Python package for robotic scheduling, operation, and control of small
optical telescopes.pyscopeis anopen-sourceproject that provides a set of tools to rapidly and easily
control astronomical instrumentation. It is designed to be modular and extensible,
allowing users to easily add support for new devices and observatories.pyscopeis built on top of theASCOMstandard, but also provides support for
non-ASCOM devices. Users may also access their devices through third-party applications
such asMaxIm DL.Observatories who usepyscopecan take
advantage of thetelrunmodule, which provides a simple interface for fully-robotic observatory control.pyscopeis aiming to become anastropy-affiliated package.FeaturesControl observatory hardware with PythonSupport forASCOMand non-ASCOM devicesObservatoryconvenience methods likerun_autofocusandrecentertelrunmodule
for fully-robotic operation of an observatoryBasic data reduction tools likeavg_fitsandccd_calibSimple analysis scripts likecalc_zmagPowered byAstropy,Astropy-affiliatedpackages, andASCOMInstallationpyscope is available on PyPI and can be installed with pip:pipinstallpyscopepyscope will be available on conda-forge soon.Development InstallationWe recommend using a virtual environment for development. You may create a new
virtual environment with pip:python-mvenvpyscope-devsourcepyscope-dev/bin/activateOr with conda:condacreate-npyscope-devpython=3.10.12condaactivatepyscope-devTo install pyscope for development, clone the repository and install with pip:gitclonehttps://github.com/WWGolay/pyscopecdpyscopepipinstall-e".[dev]"UsageTBDDocumentationAll supporting documentation can be found atreadthedocs.CitingIf you use this package in your research, please cite it using the following:ContributingPlease see thedeveloper documentation.LicenseThis project is licensed under theGNU AGPLv3 License.IssuesPlease post any issues you findhere.
Package: pyscopus
PyScopus is a Python wrapper for Scopus API:http://dev.elsevier.com/index.html** Updates on 10/09/2018Add a new function to retrieve/search serial title metadata** Updates on 09/29/2018Add a workaround for filtering author publication** Updates on 02/06/2018Solved author search affiliation problem** Updates on 01/05/2018Add full text link and author list when searching for articles** Updates on 12/29/2017Improve: Fix bugs on start index when searching. Improve citation retrieval code.Fix bugs on print/starting index** Updates on 12/28/2017Improve: Compatible with Python 3.6 and fixed bugs on imports** Updates on 09/07/2017Improve: An authorized API key is used for debugging.Website updated.** Updates on 02/13/2017Added ‘search()’; (originally added in Dec. 2016)** Updates on 10/04/2016Added ‘retrieve_abstract()’Removed ‘search_abstract()’Improved: 1) Allow users to save xml files for both abstract and author retrieval xml files; 2) Display unicodes when searching, instead of ignoring and force them into ascii encoding.** Updates on 09/14/2016Add function for searching publications in a venueThis can help users retrieve publication information from a specific venue within a specific year range.** Updates on 04/07/2016Add Citation Overview API!!This can help retrieve annual citation counts over a specified year range.
Please note that this requires special authorization.
Package: pyscord-storage
pyscord-storageFree unlimited file hosting using Discord serverAPIUpload From URLUpload From FileUsageimportpyscord_storageresult=pyscord_storage.upload_from_file("path/to/your.file")print(result)importpyscord_storageresult=pyscord_storage.upload_from_url("waifu.jpg','https://github.com/animemoeus/pyscord-storage/raw/master/tests/temp/takagi.png")print(result)AboutServer StatusMax upload size limit is 8MB.Click here for detail.media.discordapp.net & cdn.discordapp.com.Click here for detail.proxy_url.Click here for detail.How long my Discord file link will work?Click here for detail.Increase Upload LimitI don't know if this will work, but I think if the server gets a boost, we can increase the upload limit up to 50 MB or 100MB.https://support.discord.com/hc/en-us/articles/360028038352-Server-Boosting-FAQ-Discord Serverhttps://discord.gg/kZuWeKzgkqExample Implementationhttps://api.animemoe.us/waifu/https://waifu.animemoe.us/
Package: pyscores2
![](https://vignette.wikia.nocookie.net/horrormovies/images/8/8a/Psycho.jpg/revision/latest/top-crop/width/360/height/450?cb=20150415212637)
# pyscores2
Python API to ship strip theory code Scores2
[This notebook](https://github.com/martinlarsalbert/pyscores2/blob/master/docs/notebooks/01_run_scores2.ipynb) shows how this works.
Package: pyscos2000
pyscos2000Parsing and checking SCOS-2000 databases with native python.You can find thedocumentation
here.InstallationTo installpyscos2000you will have to clone the repository and install
it like this:git clone https://gitlab.irf.se/irf/pyscos2000.git
pip install ./pyscos2000In case you want to actually modify this library be sure to clone the
repository through ssh and install it in a way that’ll allow you to build
the documentation, too:git clone git@gitlab.irf.se:irf/pyscos2000.git
pip install -e ./pyscos2000[docs]UsageTo load a SCOS-2000 database from the.datfiles in yourASCIIdirectory, run this:import pyscos2000

scos = pyscos2000.SCOS('./ASCII')The various tables will then be available as (for example)scos.plf.Each table has the rows available as therowsproperty, e.g.scos.plf.rows.LicenseMIT
Package: pyscovery
pyscovery is a Python plugin loader that will search for classes based from alist of modules and optionally use the file system to recurse into packages.This is different from pkg_resources and friends since it doesn't require youto add every module that might have packages, it will discover it for you.I wrote this because none of the existing solutions fit my need of being ableto logically group similar plugins in the filesystem.Say you have the following structure in your project:module/__init__.pyplugin.pyplugins/__init__.pyplugin1/__init__.pyplugin2/__init__.pyplugin3.pyWith pyscovery, the following code will find plugins 1, 2, and 3 for you:import pyscoveryfrom plugin import Pluginpyscovery.add_module('plugins')for plugin in pyscovery.find(Plugin, True, False):print pluginRecursion in the filesystem is off by default, since that's the way people areused to.  If there is enough demand, I will make it the default.If you want to create instances of all the classes found instead of justgetting the class it self, you can use the following:for plugin in pyscovery.find(Plugin, True, True):print plugin
Package: pyscpapi
pyscpapiInstallingYou can get the library directly from PyPI:python3 -m pip install pyscpapiIf you are using Windows, then the following should be used instead:py -3 -m pip install pyscpapiHOW TO USERead official API:https://api.scpslgame.com/Simple Code:importasynciofromPyscp_Api.apiimportAPIasyncdefstart():ip=awaitAPI.ip()serverinfo=awaitAPI.serverinfo(id_=YOUR_ID,key=YOUR_KEY,list_="true",players="true")lobbylist=awaitAPI.lobbylist(key=YOUR_KEY,minimal="Test")return(ip,serverinfo,lobbylist)ip,serverinfo,lobbylist=asyncio.run(start())print(f"IP:{ip}")print(f"Server Info:{serverinfo}")print(f"Lobby List:{lobbylist}")Donatehttps://money.yandex.ru/to/410015858804944/0
Package: pyscpi
pyscpiA Python library for communicating with SCPI devices and a helper library for communicating with the Keysight'sSmart Bench Essentialseducational equipment. The library communicates using multiple backends including PyVisa, USBTMC and socket communication. The library also provides helper functions for reading oscilloscope waveforms and plotting them.Using PyVisa and Keysight's IOLibraryyou need to install Keysight's IOLibrary and PyVisa.Using alternative methods including usb and ethernetYou can use USBTMC, a standard for communicating with instruments using USB using generic drivers. This method works both in Windows and WSL2. Alternatively, you can use the standard TCP/IP sockets to communicate with the instrument. However, you need to connect the instrument on the same network as your computer, either using a direct ethernet cable or a switch/router. If you are not using a router, then you may need to set the instrument's IP address manually or use a DHCP server for dynamic IP allocation. Further information can be found in thehere.Getting StartedInstallingYou can install the library using pip:python-mpipinstall--upgradepyscpiconnecting to the instrument using PyVisaimportpyvisaasvisarm=visa.ResourceManager()inst=rm.open_resource('<resource address>')print(inst.query('*IDN?'))connecting to the instrument using USBTMCfrompyscpiimportusbtmcinst=usbtmc.Instrument(<VendorID>,<ProductID>)print(inst.query("*IDN?"))connecting to the instrument using socket (driverless)frompyscpiimportscpiinst=scpi.Instrument('<IP address>',5025)print(inst.query('*IDN?'))Reading oscilloscope waveformfrompyscpi.keysightimportoscimportnumpyasnpt,y1=osc.readSingleChannel(inst,1)Plotting oscilloscope waveform# %matplotlib ipymplimportmatplotlib.pyplotaspltplt.plot(t,y1)plt.show()closing the connectioninst.close()AcknowledgmentsThanks toKeysight Educationfor providing the Smart Bench Essentials educational equipment.USBTMCis used for communicating with the instruments using USB.
Package: py-scProportionTest
Single Cell Proportion Test in Pythonis designed to analyze the difference between the proportion of cells in clusters between two scRNA-seq samples. A permutation test is used to calculate a p-value for each cluster, and a confidence interval for the magnitude difference is returned via bootstrapping. Results can be visualized using a point range plot. View thetutorialto get started. If you are working with an Seurat object, you may consider theimplementation in R.InstallationCurrent release:pipinstallpy-scProportionTestDevelopment version:pipinstallgit+https://github.com/SamuelAMiller1/py-scProportionTest.gitCitingMiller SA, Policastro RA, Sriramkumar S, Lai T, Huntington TD, Ladaika CA, Kim D, Hao C, Zentner GE, O’Hagan HM. LSD1 and Aberrant DNA Methylation Mediate Persistence of Enteroendocrine Progenitors That Support BRAF-Mutant Colorectal Cancer. Cancer Res. 2021 Jul 15;81(14):3791-3805. doi: 10.1158/0008-5472.CAN-20-3562. Epub 2021 May 25. PMID: 34035083; PMCID: PMC8513805.
Package: pyscrabbler
PyScrabblerA Python package for retrieving a list of valid words and their values in Scrabble™ given a set of letters [seven to fifteen].DescriptionMethodsgetScrabbleWords(letters)Parameter:String; provided letters.Returns:2D-List; words and their base values.Exceptions:Error: Letter count must be between seven and fifteen.: occurs when providedStringis less than seven characters OR longer than fifteen characters.Error: No argument provided.: occurs when not provided with an argument.Example Use In Code:storedWords=getScrabbleWords('JUHSINE')forwordinstoredWords:print(word)Example Use In Terminal:python-mpyscrabblera,r,t,w,t,x,y,zExample Output:['EH', 5]
['EHS', 6]
['EISH', 7]
['EN', 2]
['ENS', 3]
['ES', 2]
['HE', 5]
['HEN', 6]
['HENS', 7]
...InstallationWith Python installed, run the following in a command prompt:python-mpipinstallpyscrabblerLegalThis project was developed for educational purposes. I do not own, nor claim to own, anything involving Scrabble™. Scrabble™ is a trademark owned by Hasbro Inc. and all rights are reserved to its respective owner.
Package: pyscramblesgenerator
pyscramblesgenerator.generate_scramble("cube type", N)
"cube type" can be "2x2x2" up to "7x7x7", plus pyraminx, skewb and megaminx
N can be anything that is integer/ Example: 28So it should look like this: pyscramblesgenerator.generate_scramble("3x3x3", 28)