Saravanan666/pypi-org huggingface dataset:
Package: hottbox
Welcome to the toolbox for tensor decompositions, statistical analysis, visualisation, feature extraction,
regression and non-linear classification of multi-dimensional data. Not sure you need this toolbox? Give it
a try onmybinder.orgwithout installation.Table of ContentsInstalling HOTTBOXRunning testsHOTTBOX tutorialsDevelopmentInstalling HOTTBOXThere are two options available:Installhottboxas it is frompypi.orgby executing:# Create virtual environment based on python 3.7pipenv--python3.7# Install hottbox from pypipipenvinstallhottboxAlternatively, you can clone the source code which you can find on ourGitHub repositoryand installhottboxin editable mode:# Clone source code and cd into itgitclonehttps://github.com/hottbox/hottbox.gitcdhottbox# Create virtual environment based on python 3.7pipenv--python3.7# Install hottbox from sourcepipenvinstall-e.This will allow you to modify the source code in the way it will suit your needs. Additionally, you will be
on top of the latest changes and will be able to start using new stable features which are located ondevelopbranch until the official release. The list
of provisional changes for the next release (and the CI status) can be also be found on develop branch
inCHANGELOGfile.NOTE:To manage working environment, we usepipenv. This tools is thought of as a successor ofpipand essentially usespipandvirtualenvunder the hood. If you haven’t made a switch yet (or don’t want to) then:Instead ofpipenv installsimply usepip installInstead ofpipenv run ...make sure that you are in correct virtual environmentRunning testshottboxis under active development, therefore, if you have chosen the second installation
option, it is advisable to run tests in order to make sure that your
current version ofhottboxis stable. First, you will need to installpytestandpytest-covpackages:pipenvinstall-e'[.tests]'To run tests, simply execute inside the main directory:# Runs pytest within a virtual environmentpipenvrunpytest-v--covhottboxHOTTBOX tutorialsPlease check outour repositorywith tutorials onhottboxapi
and theoretical background on multi-linear algebra and tensor decompositions.DevelopmentWe welcome new contributors of all experience levels. Detailed guidelines can be found onour web site.
Package: hotwatch
HotWatch is a command line utility for monitoring the status ofHotQueuequeue instances.Use it like this:$ hotwatch otherqueue myqueue thisqueue
otherqueue: 1182 items
myqueue: 0 items
thisqueue: 33181 itemsFor help, usehotwatch--help.HTTP interface and other output formats are coming soon.To install it, run:pip install -U hotwatchThe source code is available onGitHub.To get help with HotQueue or HotWatch, use theHotQueue Users mailing list.ContributingThe source is available onGitHub. To contribute to the project, fork it on GitHub and send a pull request, all contributions and suggestions are welcome.
Package: hotWater
How it worksSupply a pdb file (or just the accession code) and rank the water molecules within it or scan the surface of the whole protein for most likely water hot spots.InstallationNote: This tool relies on EDTSurf, therefore runs only on Linux.
If you have a linux system, install via pip fromPyPi(recommended):$pip2install--userhotWaterIf your system lacks pip,install it first.Python versionThe tool was developed using Python 2.7.UsagePython 2.7 shell>>>fromhotWaterimport*>>>rank_waters('3m1k')CreatingmesharoundproteinsurfaceusingEDTSurf[...otheroutputmessages...]RankedwaterpositionsalongwithscoreshavebeenwrittenouttoafileFor the scan mode, you need to use a high performance server (depending on size of protein, can require up to 64GB RAM per core). You will be testing several million of points so please be aware that this will take some time. If your job dies (for e.g. due to insufficient memory resources), rerun it (using fewer threads) in the same folder. The calculation will restart from the last checkpoint.>>>scan_surface('3m1k',threads=4,threshold=0.999)The points predicted above the threshold will be written out to a PDB file (‘<input>_predicted_waters.pdb’). You can append this output with the original PDB for viewing in pymol etc. The predicted waters are chain ‘W’. If you wish to see more predictions, decrease the ‘threshold’ parameter (hint - not too drastically, a threshold of 0.99 will already yield several thousands of positive predictions and any threshold below 0.9 will yield very many false positive predictions). If you wish to remove excess waters (positively predicted water molecules that clash with one another), run:>>>cluster_predicted_waters('3m1k_predicted_waters.pdb',threshold=1.4)LicenceMITAuthorsJan Zaucha
Package: hotweb
HOTWEB WEB FRAMEWORKPython web framework for designing lucrative websites in python programming language. The goal of HOTWEB FRAMEWORK
is to allow developers to develope websites in one language, that is python because you can do anything using Python Programming languageAuthorReal Manlow (aka ManlowCharumbira)Contactsinstagram.com/realmanlowrealmanlow20@gmail.comcharumbiramanlow20@gmail.com
Package: hotweb-cli
HOTWEB WEB FRAMEWORKPython web framework for designing lucrative websites in python programming language. The goal of HOTWEB FRAMEWORK
is to allow developers to develope websites in one language, that is python because you can do anything using Python Programming languageAuthorReal Manlow (aka ManlowCharumbira)Contactsrealmanlow20@gmail.comcharumbiramanlow20@gmail.com
Package: hotword_detection
This library provides functionality for detecting a hotword in given audio file using MFCC features and Dynamic Time Warping (DTW) pattern matching algorithm.InstallationThisproject is on pypiTo install from pypi:pip install hotword_detectionFrom this repository:git clone https://github.com/sakethgsharma/HotWordDetection.git
python setup.py installUsageExample scriptsFor training a hotword, run:python bin/trainHotword.pyFor testing, run:python bin/checkHotword.pySupported featuresMel Frequency Cepstral CoefficientsChoice of selecting any suitable hot word through appropriate training paradigmSupports variable sampling frequenciesAmplitude based Voice Activity Detector(VAD) used during recordings to remove extraneous noisePersonalization using automatic DTW thresholdingMFCC FeaturesMFCC vectors are used in this module since they are the most commonly extracted features used for speech recognition systems.ParameterDescriptionalphaParameter used in pre-emphasis filtering. Should be any value between 0 and 1.NNumber of FFT points.fsSampling frequency of stored audio file.frame_durDuration of 1 speech frame.num_filtersNumber of filters used in the Mel filterbank.lower_freqLower frequency bound used for constructing filterbank.upper_freqUpper frequency bound used for constructing filterbank. Should be less than fs/2.Dynamic Time WarpingDynamic time warping (DTW) is an algorithm for measuring similarity between two temporal sequences which may vary in speed.ReferenceMFCC tutorialDTW Wiki
Package: hotxlfp
hotxlfphotxlfp intends to be a python version of the javascripthandsontable excel formula parserdifferences are acceptable to make it more pythonic or the function implementations more correct.InstallYou can install using pippip install hotxlfpUsageCreate a Parserimport hotxlfp

p = hotxlfp.Parser()Parse excel formulasp.parse('SUM(1,2,3)') # returns {'result': 6, 'error': None}It's also fine to use semi-colons as separators (they're used by excel depending on your locale)p.parse('SUM(1;2;3)') # returns {'result': 6, 'error': None}Custom functionsSay you have a function called triple:def triple(x):

    return x*3You can teach the parser to use it with set_functionp.set_function('TRIPLE', triple)

p.parse('TRIPLE(2)') # returns {'result': 6, 'error': None}VariablesYou can also set variables that you can then use in your formulasp.set_variable('foo', 33)

p.parse('foo/3') # returns {'result': 11.0, 'error': None}ContributingFork the projectInstalling DependenciesDepends on ply and python-dateutil.To install dependencies automatically using pip run:pip install -r requirements.txtTestingpython setup.py testCoveragecoverage run --source hotxlfp setup.py testUpdate SUPPORTED_FORMULAS.mdInside the project directory run:python -m "scripts.update_supported_formulas"
Package: houdini
Houdini bindings for Python (c.f.https://github.com/vmg/houdini)installationInstallation is with pip:pipinstallhoudiniYou need to have the houdini shared library available somewhere on your
dynamic linker’s search path—some instructions are provided below.usage>>>importhoudini>>>print(houdini.escape_html("3 < 5"))3 &gt; 5The API is as described in thelibrary’s
README, except all these functions
accept a unicode string and return a unicode string. If no escaping is
done, the return value will be the original string:>>>string="hello">>>houdini.escape_html(string)isstringTruegetting that shared libraryI submitteda pull requestadding the capability to produce shared libraries to Houdini’s Makefile.
Until/unless that’s merged, you’ll need to usemy
forkto build those
libraries. It should be simple:gitclone'https://github.com/zacharyvoase/houdini.git'cdhoudinimakeThen, forLinux:sudocplibhoudini.so/usr/local/libsudoldconfig# Refresh the dynamic linker cache.and onOS X(you may not want to usesudohere,/usr/local/is normally user-writable):cplibhoudini.dylib/usr/local/libunlicenseN.B.: this doesn’t apply to Houdini itself, but all the code written
by me is released as follows:This is free and unencumbered software released into the public domain.Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any means.In jurisdictions that recognize copyright laws, the author or authors of
this software dedicate any and all copyright interest in the software to
the public domain. We make this dedication for the benefit of the public
at large and to the detriment of our heirs and successors. We intend
this dedication to be an overt act of relinquishment in perpetuity of
all present and future rights to this software under copyright law.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 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.For more information, please refer tohttp://unlicense.org/
Package: houdini-package-runner
Thehoudini_package_runnerproject aims to provide an extensible API and set of tools for analyzing and acting upon
files in a Houdini package.The current tools are all geared towards Python compatibility and styling.Supported file types include:Python files and packagesPython code/context sections inside Houdini XML type filesMenus (MainMenu*.xml, ParmMenu.xml, etc)Python panelsShelf toolsDigital Assets (binary or expanded asset folders)Python code sections (PythonModule, OnCreated, etc)Python code inside DialogScript definitionCallbacksDefault parameter expressionsMenu scriptsIncluded shelf toolsCurrently, the runner tools only functionoutsideof Houdini on disk files.The following read-only tool runners are provided:pylint - Performpylintanalysis on Python codeflake8 - Performflake8analysis on Python codeThe following tool runner which can modify files are provided:black - Performblackformatting on Python codeisort - Useisortto sort Python importsmodernize - Usepython-modernizefor support Python 2 to 3 conversion.NOTES:In order for the above runner tools to work you'll need to have them installed and available via commandlineOperations on binary digital asset files (.otl, .hda) requires that Houdini's providedhotlcommand be available to run.
Package: hou-flask
oss-authBasic authentication and authorization applicationDocumentationYou will need to install the package dependencies first,
see the Installation section for details.To build and open the documentation simply run:bin/build-docsInstallationIf you need to install pyenv/virtualenvwrapper you can run thebin/setup-osxcommand
Please note that this will modify your bash profileAssuming you have virtualenv wrapper installedmkvirtualenvoss-authworkonoss-authpipinstall-rrequirements_dev.txtpipinstall-e.DockerIf you want to use docker for this projectDownload and installDocker for MacIn the root of this repo:docker-composebuilddocker-composeupVerify the application is running with:curlhttp://localhost:5000/statusPyCharmTo integrate PyCharm with your virtual environmentinstall according to the standard installation instructionsIn your project settings (shortcut:cmd+,) navigate toProject->Project InterpreterSelect the gear icon in the upper right cornerSelectAdd LocalSelect$HOME/.envs/oss-auth/bin/python3.5and clickOKClickApplyand thenOKFeaturesTODOCreditsThis package was created withCookiecutterand thetimmartin19/oss-template@flaskproject template.History0.0.1 (2018-06-27)First release on PyPI.
Package: hou-flask-psycopg2
# Highly Opinionated Utils: Flask-Psycopg2Provides the ability to integrate Flask directly with psycopg2
No need for a filthy ORM## Installation`bash pip installhou-flask-pscyopg2`Sometimes on macs psycopg2 is a little pain in the ass.  You’ll see
errors like`bash >>> ld: library not found for-lssl>>> clang: error: linker command failed with exit code 1 (use-vto see invocation) >>> error: command 'clang' failed with exit status 1 `To fix these try any of the followingxcode-select –installbrew install opensslLDFLAGS=”-L/usr/local/opt/openssl/lib” CPPFLAGS=”-I/usr/local/opt/openssl/include” pip install hou-flask-pscyopg2History0.0.1 (2018-06-27)First release on PyPI.
Package: hound
HoundA FireCloud database extensionPurposeThis repository contains the source code for the Hound database extension system.
This system aims to provide a low-latency system for logging changes to a FireCloud
workspace.This allows for attribute provenance to be reconstructed by querying the database
history, and for external tools to log changes as well.UsageUsers with hound-enabled software automatically generate logs as they continue
to do their workHound can recreate attribute value histories from logs to produce provenanceFormatHound logs data in a bucket folder. Entries are organized based on the list below.snowflakerefers to an auto-generated ID from Hound's snowflake implementation.
Snowflakes are almost guaranteed to be unique (see below)hound/: Root folder for hound data in bucket(samples|pairs|participants|sets)/: Folder for entity-metadata change logs(entity-id)/: Folder for entity data(attribute)/: Folder for attribute data on each entity(snowflake): Serial numbered files containingupdate objectsworkspace/: Folder for workspace-level metadata(attribute)/: Folder for attribute data on the workspace(snowflake): Serial numbered files containingupdate objectslogs/: Folder for event-logs(job|upload|meta|other)/: Folder for specific event entries(snowflake): Files containinglog entriesSnowflake specEncode 22-byte snowflake into 44 byte (hex encoded) object name64-bit (8 byte) unix timestamp (8 byte floating-point number)64-bit (8 byte) machine id (based on nodename) Only 6 bytes used16-bit (2 byte) random client id (generated during init of Snowflake object)16-bit (2 byte) sequence identifier (starts at 0 per client, increments from there)8-bit (1 byte) Zero field (reserved)8-bit (1 byte) checksum field (sum of remaining fields)UniquenessSnowflakes are structured to almost guarantee uniqueness. If two clients from the
same machine (or from machines with identical MAC addresses) create a snowflake
atexactlythe same time (within their system clocks' precisions)ANDthe
clients have generated the same number of snowflakes so far (clients have the same
sequence id), there is a 1/65536 chance that the snowflakes will collide (based on
client id).
Package: hourbike-cli
A CLI for Hourbike schemes across the UK.AboutThis command line application allows you to find information about the bicycle stations closest to your current location.Currently supported cities and towns are: Lincoln (hirebike), Liverpool (CityBike), Reading (ReadyBike), Sheffield (Sheffield ByCycle) and Southport (Southport Cycle Hire)Installation$ pip install hourbike-cliUsageFor help use the -h option.$ hourbike -hTo get the nearest bike stations to a loction, type:$ hourbike liverpool "liverpool cathedral"
Package: hourglass
hourglassis a minimalist scheduler forrq.hourglassprovides a date-sorted queue class,Schedule, that
stores jobs that are to be run at some point in the future, and a
daemon script,hourglass, that delegates those jobs to the regular
queues processed byrqworkerprocesses.UsageRun thehourglassdaemon script included with the package. Example
usage:import times
from datetime import timedelta
from rq import use_connection
from hourglass import Schedule

def test_job(n):
    return n

use_connection()

s = Schedule()

# schedule a job to be run 3 minutes from now
eta = times.now() + timedelta(0, 180)
job = s.enqueue(eta, test_job, 5)hourglassmanaged jobs include an additional property,eta,
which is the time passed as the first argument toSchedule.enqueueandSchedule.enqueue_job.  They also include another property,queuefor specifying which queue to dispatch the job to whenetahas elapsed.TheSchedulequeue andhourglassdaemon use UTC times under the
hood, so eta’s passed to the scheduler should be in UTC as well.Changelog0.2Compatibility updates for rq-0.3.00.1.2MadeSchedule.enqueue_jobandSchedule.compactatomic.0.1.1Fixes for Python packaging.0.1Initial release.
Package: hours
⏳ HoursA minimalistic work time logger for the command line.InstallationpipinstallhoursUsageLet's add a client first and set the hourly rate:hoursclientsadd-nBigCorporate--rate100--currency€
hoursclientslistThen log your work for today:hourslog-cBigCorporate-h8.0-p"ML pipeline"-t"fixing bugs"Get a report for the current month (or any other period):hoursreportCreate a timesheet to Excel file:hoursexportFor more information, see thedocumentation.
Package: householdenv
Household-envThis is a gym environment that represents a robot agent in a household environment for RL purposes.Table of ContentsHow to run itObservation spaceAction spaceTasksHow to run itTo run an example of the environment first install it and then run the dummy file.#!/bin/bashpipinstall-eHousehold-envpython3dummy.pyObservation spaceThe robot has a vision grid of 7x7. The vision grid inputs will return values that represent the content of that cell.The tasks encoding is binary instead of label encoding (0: task1, 1: task2...) because there is no ordering for the
tasks, but the alg. might think there is.Note: We could do the same for the vision grid, but then the observation space would increase a lot (48*3=147 for
for only 7 representable objects )NumObservationMinMax0x_coord_robot0191y_coord_robot0192task_encoding01......6task_encoding0171st action0882nd action0893rd action08104th action08(vision not yet)11vision_grid01....0158vision_grid01Objects will return the following values when within range of the 7x7 vision grid.NumObject0Nothing1wall2TV3couch4bed5fridge6dishwasher7personAction spaceOnly one action can be taken at each time step. The Num of the action to be taken is passed as the argument to thestepfunction.NumActionMinMax0move_up011move_down012move_left013move_right014(A) extend_arm015(B) retract_arm016(C) grasp017(D) drop018(E) push01TasksThe tasks encoding is binary instead of label encoding (0: task1, 1: task2...) because there is no ordering for the
tasks, but the alg. might think there is. We currently use 5 units so up to 31 tasks.NumActionBinary encoded0No tasks000001Turn on TV000012Bring user a drink000103Make beds00011
Package: house-hunter
House HunterHouse Hunter contains methods to search popular housing websitesFree software: MIT licenseDocumentation:https://house-hunter.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2018-12-02)First release on PyPI.
Package: housekeeper
HousekeeperStore, tag, fetch, and archive files with ease 🗃Housekeeperis a tool that aims to provide:a backend for storing versioned bundles of filesdifferent interfaces (Python, CLI, REST) for fetching files based on tagsa way to backup and retrieve bundles from long-term storageTodore-implement the archive/encryption interface [@ingkebil]handle clean up of expired bundles [@robinandeer]expand the CLI withgetcommand etc. [@robinandeer]InstallationHousekeeper written in Python 3.6+ and is available on thePython Package Index(PyPI).pipinstallhousekeeperIf you would like to install the latest development version:gitclonehttps://github.com/Clinical-Genomics/housekeepercdhousekeeper
pipinstall--editable.ContributingHousekeeper is using github flow branching model as described in ourdevelopment manual.DocumentationCommand line interfaceConfig fileHousekeeper supports a very simple YAML config. The following options are supported:---database:mysql+pymysql://userName:passWord@domain.com/databaseroot:/path/to/root/dirTherootoption is used to store files within the Housekeeper context.Command:initSetup (or reset) the database. It will simply setup all the tables in the database. You can reset an existing database by using the--resetoption.housekeeper--database"sqlite:///hk.sqlite3"init
Success!Newtables:bundle,file,file_tag_link,tag,versionCommand:includeInclude (hard-link) all files of an existing bundle version into Housekeeper and therootpath.housekeepermyBundleThis will only work if the bundle only has a single version which can be "imported". If you want to import a specific version of a bundle you can use the--versionoption.Command:delete filesDelete files that are not on disk anymore like his:housekeeper delete files --tag fastq --notondiskRemove all bam files before a certain date:housekeeper delete files --tag bam --before 2017-06-15Remove fastq files from a flowcell:housekeeper delete files --tag fastq --tag H0HKKALXXIt'll always ask for confirmation, unless you add --yes:housekeeper delete files --bundle sillyfish --yesIf you do not provide a --tag or --bundle, essentially deleting everything, the function will not let you do that.