Saravanan666/pypi-org huggingface dataset:
Package: itango
An interactive Tango client.DescriptionITangois aPyTangoCLI based onIPython.
It is designed to be used as an IPython profile.It is available since PyTango 7.1.2 and has been moved to a separate
project since PyTango 9.2.0.RequirementsITango is compatible with python 2 and 3. It requires:PyTango>= 9.2IPython>= 1.0However, a compatiblity package is available asitango-0.0.1.
It provides compatibility for:7.2 <=PyTango< 90.10 <=IPython< 5InstallITango is available onPyPI:$ pip install itango         # latest version (tango 9)
$ pip install itango==0.0.1  # tango 8 compatibilityUsageITango can be started using theitangoscript:$ itango  # Or itango3 if using python 3or thetangoprofile:$ ipython --profile=tangoFeaturesITango works like a normal python console, but it provides a nice set of
features from IPython:proper (bash-like) command completionautomatic expansion of python variables, functions, typescommand history (with up/down arrow keys, %hist command)help system ( object? syntax, help(object))persistently store your favorite variablescolor modesFor a complete list checkout theIPython web page.It also adds set ofPyTangospecific features:automatic import of Tango objectsdevice and attribute name completionlist tango devices, classes, serverscustomized tango error messagedatabase utilitiesCheck out thedocumentationfor more informations.
Package: itanicpackagegna
vidstreamUnder construction! Not ready for use yet! Currently experimenting and planning!Developed by Florian Dedov from NeuralNine (c) 2020Examples of How To Use (Buggy Alpha Version)Creating A ServerfromvidstreamimportStreamingServerserver=StreamingServer('127.0.0.1',9999)server.start_server()# Other Code# When You Are Doneserver.stop_server()Creating A ClientfromvidstreamimportCameraClientfromvidstreamimportVideoClientfromvidstreamimportScreenShareClient# Choose Oneclient1=CameraClient('127.0.0.1',9999)client2=VideoClient('127.0.0.1',9999,'video.mp4')client3=ScreenShareClient('127.0.0.1',9999)client1.start_stream()client2.start_stream()client3.start_stream()Check out:https://www.youtube.com/c/NeuralNine
Package: itanium-demangler
Itanium DemanglerThePython Itanium Demangleris a pure Python parser for theItanium C++ ABI symbol mangling language. Note that MSVC mangling language is not supported.This demangler generates an abstract syntax tree from mangled symbols, which can be used for directly extracting type information, as opposed to having to interpret the C++ source code corresponding to the demangled symbolThere is also a built-in AST stringifier, so the demangler can be used as a replacement forc++filtor for formatting backtraces.RequirementsThe demangler runs on Python 2.7 and 3.3+ and has no dependencies.InstallationInstalling via PyPI:pip install itanium_demanglerUsing a local repository for development:git clone https://github.com/whitequark/python-itanium_demangler
cd python-itanium_demangler
python setup.py develop --userUsagefromitanium_demanglerimportparseasdemangleast=demangle("_ZN5boost6chrono24process_system_cpu_clock3nowEv")print(repr(ast))# <FuncNode func <Node qual_name (<Node name 'boost'>, <Node name 'chrono'>, <Node name 'process_system_cpu_clock'>, <Node name 'now'>)> (<Node builtin 'void'>,) None>print(ast)# boost::chrono::process_system_cpu_clock::now()Future considerationsA similar (i.e. also parsing to an AST) implementation of a demangler for the MSVC mangling language would be useful to have.License0-clause BSD
Package: itarC
project ITARJITARJ - Is This A Real Job - is a python console app that allows users to register and view fake job alerts. It also allows a user to flag a registered fake job as false with prove.Installationpip install itarC
python
import itarjUsagefor a user to add a fake job alert, the user must be logged in or create a new account if there is no existing accounts. User can view jobs by proving a keyword to search
Package: itasca
Python connectivity for Itasca software.This library implements a connection via sockets between Python and
the numerical modeling software from Itasca Consulting Group.
Functions are provided to read and write files in the Itasca FISH
binary format.www.itascacg.com/softwareFLAC, FLAC3D, PFC2D, PFC3D, UDEC & 3DECSeehttps://github.com/jkfurtney/itasca-pythonfor more information.
Package: itasca-stub
itasca-stubThis repository contains code to generateitasca.pyifor PFC600.Itasca provides great python interface, But it is too weak compared to PyCharm.
When writing PFC in PyCharm, the keyworditascahas no typehint.
Thus, the project is developed, and here's a preview.InstallationManualCopy theitascadirectory to your pythonsite-packagesdirectory.
Make sure to copy to your current environment.
If the internal Python of PFC is used, then you should copy to the path like:Itasca\PFC600\exe64\python36\Lib\site-packages.pippip install itasca-stubBest wishes!ContributionYou can submit issues and PRs at any time, welcome for your contribution!
Package: it-automation-martin
IT_Automation ProjectIT_Automation_Project is a Python library I wrote to complete the final project in Google's IT automation with Python class.The library provides basic system monitoring, image processing, PDF file generation,  and email generation.overviewThere are 7 modules in this project.health_checksThis module contains functions for checking if system resources are overloaded and then emailing a error message.ChangeImageFunctions for converting images in a directory into jpeg images, images can also be resized.emailsThis module contains functions for generating and sending emails. Email attachments are optional.reportsFunctions for generating pdf reports.report_emailThis module is specific to the final assignment but I will in include it here.
Generates a pdf report from Google's supplier data. The report is attached to an email message and sent.Supplier_image_uploadThis module is specific to the final assignment but I will in include it here. Makes a post request for every jpeg image in a directory. This script is used for Google's IT_automation class. The directory contains images for every fruit that will be displayed in customers website.runThis module is specific to the final assignment but I will in include it here. Functions for reading a directory and then making post request with the data. This is used for Google's IT automation class project. Reads a directory with files containing information on fruits and then makes a post request to the class website to show the data.InstallationUse the package managerpipto install it-automation-martin.pipinstallit-automation-martinUsagehealth_checksfromit_automationimporthealth_checkscpu_percent_usage_threshold=80available_disk_space_percent_threshold=20memory_threshold=500*1024*1024# 500MBemail_body='Please check your system and resolve the issue as soon as possible.'sender="test_email@gmail.com"receiver="test_email@gmail.com"health_checks.check_systems(cpu_percent_usage_threshold,available_disk_space_percent_threshold,memory_threshold,sender,receiver,email_body)changeImagefromit_automationimportchangeImageimage_directory=os.path.expanduser('~')+'/Images'output_directory=os.path.expanduser('~')+'/Images'resize_width=600resize_height=400convert_image(image_directory,resize_width,resize_height,output_directory)ContributingPull requests are welcome.LicenseMIT
Package: itaxotools-calculate-distances
Calculate DistancesCalculate distances between DNA sequences. Leverages Rust for faster computation.Originally part ofTaxI2.Installationcalculate_distances is available on PyPI. You can install it throughpip:pip install itaxotools-calculate-distancesUsageImport the distance calculation functions, each of which take two string arguments:from itaxotools import calculate_distances as calc

x = "ACGT"
y = "AN-A"

calc.seq_distances_p(x, y)  # 0.5
calc.seq_distances_p_gaps(x, y)  # 0.66
calc.seq_distances_jukes_cantor(x, y)  # 0.82
calc.seq_distances_kimura2p(x, y)  # infUnit testsOnly basic tests included. More extensive unit testing is currently done as part ofTaxI2.
Package: itaxotools-convphase
ConvPhaseA convenient phase program.The purpose of this program is to combinePHASEandSeqPHASEinto a single python package, while making some crucial configuration options available.Unfortunately, internal communication betweenPHASEandSeqPHASEis done through Fasta files. However, an iterative protocol was implemented to parse and write common Python datatypes. It is also possible to work with TSV and Fasta variants (MolD, HapView) by leveragingTaxi2.This is a computational backend. For the GUI application, please visitConvPhaseGui.InstallationConvPhase is available on PyPI. You can install it throughpip:pip install itaxotools-convphaseExecutablesDownload and run the standalone executables without installing Python fromthe latest ConvPhaseGui release page.No executables are currently provided for the command-line tool.UsageThe package comes with a command-line tool:convphase examples/simple.fas ambiguous.fas
convphase examples/simple.tsv phased.tsv -p 0.4 -q 0.4The program will replicate the input file format for the output file.Allele identifiers are appended to the individual identifiers.The following options fromPHASEare available:phase threshold (-p)allele threshold (-q)number of iterations (-n)thinning interval (-t)burn-in (-b)For some examples on how to use the Python API, please have look at thescriptsfolder.DependenciesBuilding from source requires:C++ compiler (GCC,msvc)haxe&hxcppPHASEandSeqPHASEare included as git submodules.Taxi2is included as a setuptools dependency.CitationsStephens, M., Smith, N., and Donnelly, P. (2001). A new statistical method for haplotype reconstruction from population data. American Journal of Human Genetics, 68, 978--989.Stephens, M., and Donnelly, P. (2003). A comparison of Bayesian methods for haplotype reconstruction from population genotype data. American Journal of Human Genetics, 73:1162-1169.Flot, J.F. (2010) seqphase: a web tool for interconverting phase input/output files and fasta sequence alignments. Mol. Ecol. Resour., 10, 162–166.
Package: itaxotools-convphase-gui
ConvPhaseGuiReconstruct haplotypes from sequence data. Input and output can be in TSV or FASTA format.This is a Qt GUI forConvPhase, a convenient phase program that combinesPHASEandSeqPHASE.ExecutablesDownload and run the standalone executables without installing Python.InstallationConvPhaseGui is available on PyPI. You can install it throughpip:pip install itaxotools-taxi-gui
convphase-guiUsageFor information on how to use the program, please refer to the 1st section of theHapsolutely manual.PackagingIt is recommended to use PyInstaller from within a virtual environment:pip install ".[dev]" -f packages.html
pyinstaller scripts/convphase.specCitationsConvPhaseGuiwas developed in the framework of theiTaxoToolsproject:Vences M. et al. (2021): iTaxoTools 0.1: Kickstarting a specimen-based software toolkit for taxonomists. - Megataxa 6: 77-92.Sequences are phased usingPHASEandSeqPHASE:Stephens, M., Smith, N., and Donnelly, P. (2001). A new statistical method for haplotype reconstruction from population data. American Journal of Human Genetics, 68, 978--989.Stephens, M., and Donnelly, P. (2003). A comparison of Bayesian methods for haplotype reconstruction from population genotype data. American Journal of Human Genetics, 73:1162-1169.Flot, J.F. (2010) seqphase: a web tool for interconverting phase input/output files and fasta sequence alignments. Mol. Ecol. Resour., 10, 162–166.
Package: itaxotools-fitchi
FitchiHaplotype genealogies based on Fitch distances.This is a Python package forFitchi. For more information on the original, seehere.Click for a comprehensive output exampleInstallationFitchi is available on PyPI. You can install it throughpip:pip install itaxotools-fitchiUsageThe original command-line tool is included as part of the installation. It produces HTML files from Nexus files, as demonstrated with theexample input and output files. For information about the available options, you may refer to theoriginal documentation.Note that you will needalldependencies in order to run Fitchi this way:fitchi examples/example.nex examples/example.html -m 3 -p pop1 pop2
start examples/example.html  # browse results on WindowsYou may also invoke Fitchi from Python usingcompute_fitchi_tree(). This returns a tree in the form ofHaploNodeobjects, which can be used for downstream analysis or visualization. Only scipy is required in this case.See thescriptsfolder for some usage examples.DependenciesFitchi requiresscipy.
Extra statistics requirebiopython.
Visualization requirespygraphviz.To install pygraphviz, please followtheseinstructions from the pygraphviz documentation.
For example, to install pygraphviz on Windows, first installGraphvizto the default location, then execute the following command in PowerShell:pip install pygraphviz --config-setting build_ext^="^--include-dir=C:\Program Files\Graphviz\include" --config-setting build_ext^="^--library-dir=C:\Program Files\Graphviz\lib"CitationMatschiner M (2015) Fitchi: Haplotype genealogy graphs based on the Fitch algorithm. Bioinformatics, 32:1250-252.
Package: itaxotools-haplodemo
HaplodemoA graphical backend module to visualize, edit and export haplotype networks.This isnota standalone application. For an implementation that visualizes sequence files, visitHapsolutely.ExamplesLay out the initial graph using a modified spring algorithm:Interact with the graph before saving the results:Supports haploweb visualization:InstallationHaplodemo is available on PyPI. You can install it throughpip:pip install itaxotools-haplodemoExecutablesStandalone executables are included for demonstrating the library capabilities.It isnotpossible to open custom haplotype networks with the demo program.UsageLaunch the demo application to get an overview of the features:haplodemoTo get started on instantiating the scene, view and controls, look atwindow.py.For some examples of data visualization, look atdemos.py.The network can be given in tree or graph format using theHaploTreeNodeandHaploGraphtypes. Alternatively, populate the scene manually with nodes and edges.
Package: itaxotools-haplostats
HaplostatsFind unique haplotypes, fields for recombination and subset sharing.InstallationHaplostats is available on PyPI. You can install it throughpip:pip install itaxotools-haplostatsUsageIn Python, import and instantiateHaploStats:from itaxotools.haplostats import HaploStats
stats = HaploStats()Add your data one entry at a time. Each entry is represented by its subset tag, plus a list of associated sequences. These are usually different alleles of the same specimen:# Two specimens of different species, with two alleles each.
# There are three haplotypes in total. There is a single field
# for recombination (FFR), as the specimens are connected through
# a common sequence: 'ACT'.

stats.add('mysteriosa', ['ACT', 'ACC'])
stats.add('enigmatica', ['ACT', 'ATT'])After adding all entries, you are ready to analyze the dataset:haplotypes = stats.get_haplotypes()
fors = stats.get_fields_for_recombination()

common_haplotypes = stats.get_haplotypes_shared_between_subsets()
common_fors = stats.get_fields_for_recombination_shared_between_subsets()For a more detailed look at the available methods, please have a look at theexample script.
Package: itaxotools-hapsolutely
HapsolutelyReconstruct haplotypes and produce genealogy graphs from population data.Phase sequences: Reconstruct haplotypes from sequence dataHaplotype visualization: Generate haplotype networks, genealogies and haplowebsHaplotype statistics: Detect fields for recombination and subset overlapHapsolutely is a comprehensive program that integratesConvPhase,haplodemo,popart_networksandhaplostats.Input files can be in TSV, FASTA or SPART/XML format.ExecutablesDownload and run the standalone executables without installing Python.InstallationHapsolutely is available on PyPI. You can install it throughpip:pip install itaxotools-hapsolutely
hapsolutelyUsagePlease refer to theHapsolutely manualfor information on how to use the program.CitationsHapsolutelywas developed in the framework of theiTaxoToolsproject:Vences M. et al. (2021): iTaxoTools 0.1: Kickstarting a specimen-based software toolkit for taxonomists. - Megataxa 6: 77-92.Sequences are phased usingPHASEandSeqPHASE:Stephens, M., Smith, N., and Donnelly, P. (2001). A new statistical method for haplotype reconstruction from population data. American Journal of Human Genetics, 68, 978--989.Stephens, M., and Donnelly, P. (2003). A comparison of Bayesian methods for haplotype reconstruction from population genotype data. American Journal of Human Genetics, 73:1162-1169.Flot, J.F. (2010) seqphase: a web tool for interconverting phase input/output files and fasta sequence alignments. Mol. Ecol. Resour., 10, 162–166.Networks are generated using either ofFitchiorpopart_networks:Matschiner M (2015) Fitchi: Haplotype genealogy graphs based on the Fitch algorithm. Bioinformatics, 32:1250-252.Leigh, JW, Bryant D (2015). PopART: Full-feature software for haplotype network construction. Methods Ecol Evol 6(9):1110-1116.Bandelt H, Forster P, Röhl A (1999). Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16(1):37-48.Clement M, Snell Q, Walke P, Posada D, Crandall, K (2002). TCS: estimating gene genealogies. Proc 16th Int Parallel Distrib Process Symp 2:184.Doyle, J. J. (1995) The irrelevance of allele tree topologies for species delimitation, and a non-topological alternative. Syst. Bot., 20, 574-588.BioPythonis used to create ML/NJ trees if needed.networkxis used for laying out the initial graph.Cock, P.J. et al., 2009. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics, 25(11), pp.1422-1423.Hagberg, A., Swart, P. & S Chult, D., 2008. Exploring network structure, dynamics, and function using NetworkX.
Package: itaxotools-pygblocks
PyGblocksPure Python implementation for the algorithm behind Gblocks.DifferencesCan define which characters are considered as gapsAny character that is not defined as a gap is considered for conservationCan define how many gaps are allowed per position (number or percentage)Positions that only contain gaps are not pre-emptively removedConservation threshold may be set below 50%No support for similarity matricesInstallationPyGblocks is available on PyPI. You can install it throughpip:pip install itaxotools-pygblocksUsageFirst create a mask from your sequences, then apply that mask to each sequence:from itaxotools.pygblocks import compute_mask, trim_sequences

sequences = [
    "--TTTNNTACTTTTTTT-ATT",
    "--TTTNTTACGTTTTTG-ATT",
    "--TTTNTTAGTTTTTTC-ATT",
]

mask = compute_mask(sequences)
trimmed_sequences = trim_sequences(sequences, mask)You may customize the trimming parameters and enable logging
when creating the mask:from itaxotools.pygblocks import Options, compute_mask

options = Options(
    IS=2,    # Minimum Number Of Sequences For A Conserved Position
    FS=3,    # Minimum Number Of Sequences For A Flank Position
    CP=2,    # Maximum Number Of Contiguous Nonconserved Positions
    BL1=3,   # Minimum Length Of A Block, 1st iteration
    BL2=3,   # Minimum Length Of A Block, 2nd iteration
    GT=2,    # Maximum Number of Allowed Gaps For Any Position
    GC="-",  # Definition of Gap Characters
)

mask = compute_mask(sequences, options, log=True)You may optionally set IS, FS and GT as a percentage of the number of sequences
by setting IS, FS and GT values to zero, then modifying the percentage
defaults if desired:options = Options(
    IS=0, FS=0, CP=2, BL1=3, BL2=3, GT=0, GC="-",

    IS_percent = 0.50
    FS_percent = 0.85
    GT_percent = 0.00
)

mask = compute_mask(sequences, options, log=True)You may find the above examples, plus some examples on how to use PyGblocks
with BioPython alignments, in thescriptsfolder.CitationsCastresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis.
Mol Biol Evol. 2000 Apr;17(4):540-52. doi: 10.1093/oxfordjournals.molbev.a026334. PMID: 10742046.
Package: itaxotools-spart-parser
SpartParserParse, edit and write data in the SPART and SPART-XML file formats.Includes a GUI for converting between the two formats.InstallationPyInstaller is available on PyPI. You can install it throughpip:pip install itaxotools-spart-parserUsageMost of the functionality is included in the Spart class. Use the class methods
to open, edit and write data in the Spart file format.from itaxotools.spart_parser import Spart
spart = Spart.fromXML("examples/spart.xml")

spartitions = spart.getSpartitions()
print(spartitions)
subsets = spart.getSpartitionSubsets(spartitions[0])
print(subsets)
individuals = spart.getSubsetIndividuals(spartitions[0], subsets[0])
print(individuals)

spart.addIndividual("new_specimen")
spart.addSubsetIndividual(spartitions[0], subsets[0], "new_specimen")
spart.addSubsetIndividual(spartitions[1], subsets[1], "new_specimen")
spart.toMatricial("converted_copy.spart")For more details, refer to theSpart class definition,
as well as thescriptsandexamplesfolders.Demo GUIA graphical interface is included for converting between SPART and SPART-XML.Install with the optional GUI dependencies:pip install itaxotools-spart-parser[gui]
SpartParserGuiOr download and run the Windows executable from thelatest release.
Package: itaxotools-taxi2
TaxI2Calculate genetic differences between DNA sequences,This is a computational backend. For the GUI application, please visitTaxIGui.InstallationTaxI2 is available on PyPI. You can install it throughpip:pip install itaxotools-taxi2ExecutablesExplore the most recent executables by visitingthe latest TaxIGui release page.For users seeking the legacy application (v2.0.0), you may find ithere.Python APIA new API is exposed with the latest backend. Seescripts/*.pyfor some examples.
Package: itaxotools-taxi-gui
TaxIGuiCalculation and analysis of pairwise sequence distances:Versus All: Calculate genetic distances among individuals and speciesVersus Reference: Find the best matches in a reference sequence databaseDecontaminate: Filter mismatches by comparing against two reference sequence databasesDereplicate: Remove sequences very similar to others from a datasetThis is a Qt GUI forTaxI2.ExecutablesDownload and run the standalone executables without installing Python.InstallationTaxIGui is available on PyPI. You can install it throughpip:pip install itaxotools-taxi-guiThen launch the GUI and follow the instructions on the screen:taxi-gui
Package: itay-bardugo-cronmig
python-cron-migrationpython-cron-migration is a CLI package that was built for helping you manage your cronjobs by revisions files system.
It contains two main components:a CLI revision system, which can generate/upgrade/downgrade revision files by simple commands.a lightweight crontab high-level package which integrates with thecrontablibrary on your OScommandsentry pointcommandexampledescriptioncronmiginitcronmig initinitializes a new environmentcronming-revisionmakecronmig-revision make[filename]generates a new revision file .[filename]should be a short description of your revision filecronming-revisionupgradecronmig-revision upgradeupgrades all non-upgraded files by invoking theupgrademethod within your revision filecronming-revisiondowngradecronmig-revision downgrade[steps]downgrades revisions files[steps]times.[steps]is the number of downgrading (from the most upgraded file)InstallationYou can install the package via composer:composerrequirespatie/package-skeleton-laravelYou can publish and run the migrations with:phpartisanvendor:publish--provider="Spatie\Skeleton\SkeletonServiceProvider"--tag="migrations"phpartisanmigrateYou can publish the config file with:phpartisanvendor:publish--provider="Spatie\Skeleton\SkeletonServiceProvider"--tag="config"This is the contents of the published config file:return [];Usage$skeleton = new Spatie\Skeleton();echo $skeleton->echoPhrase('Hello, Spatie!');TestingcomposertestChangelogPlease seeCHANGELOGfor more information on what has changed recently.ContributingPlease seeCONTRIBUTINGfor details.SecurityIf you discover any security related issues, please emailfreek@spatie.beinstead of using the issue tracker.Credits:author_nameAll ContributorsLicenseThe MIT License (MIT). Please seeLicense Filefor more information.