Saravanan666/pypi-org huggingface dataset:
Package: workon-poetry
workon-poetryBash and Python scripts to make switching and starting projects more efficient and less error-prone by automating some of the boring stuff and incorporating some opinions about best practices.DependenciespoetryvirtualenvSetup your Python environmentLaunch aterminalon Linux (orgit-bashon Windows) then:Update your pip and virtualenv packagesClone theworkon-poetryprojectCreate a virtualenv within theworkon-poetrydirActivate your new Python virtual environmentInstall this Python package in "--editable" modeAny Python version greater than3.7should work.
As of 2023 most Linux systems use Python3.9or higher:pipinstall--upgradevirtualenvpoetry
gitclonegit@gitlab.com:tangibleai/community/workon-poetrycdworkon-poetry
python-mvirtualenv--python3.9.venv
ls-halYou should see a new.venv/directory.
It will contain your python interpreter and a fewsite-packageslikepipanddistutils.Now activate your new virtual environment by sourcing.venv/bin/activate(on Linux) or.venv/scripts/activate(on Windows).# bin/activate on Linux OR `Scripts/activate` in git-bash on Windowssource.venv/bin/activate||source.venv/Scripts/activateDeveloper installOnce you have a shiny new virtual environment activated you can installworkon-poetryin--editablemode.
This way, when you edit the files and have the package change immediately.Make sure you are already within your clonedworkon-poetryproject directory.
And makes sure your virtual environment is activated.
You should see the name of your virtual environment in parentheses within your command line prompt, like(.venv) $.
Then when you installworkon-poetryit will be available for import within any other Python application in that virtual environment.pipinstall--editable.User installIf you don't want to contribute, and you just want toUSEworkon-poetrythe MathText modules, you can install it from a binary wheel on PyPi:pipinstallworkon-poetry
Package: workonsh
workonshA live synchronizer local and remote machine. Similar to lsyncdInstallRequirements:fswatchandrsync.To install from pypipip install workonshFrom git repopip install git+https://github.com/ngocbh/workonshUsageRunworkonsh --helpAn example to create a session:workonsh -n <project_name> -s <source-dir> -d <dest-dir> -e "*__pycache__" -f .gitignore -i 5
Package: workos
WorkOS Python LibraryThe WorkOS library for Python provides convenient access to the WorkOS API from applications written in Python,hosted on PyPiDocumentationSee theAPI Referencefor Python usage examples.InstallationTo install from PyPi, run the following:pip install workosTo install from source, clone the repo and run the following:python setup.py installConfigurationThe package will need to be configured with yourapi keyat a minimum andclient idif you plan on using SSO:importworkosworkos.api_key="sk_1234"workos.client_id="client_1234"SDK VersioningFor our SDKs WorkOS follows a Semantic Versioning (SemVer) process where all releases will have a version X.Y.Z (like 1.0.0) pattern wherein Z would be a bug fix (e.g., 1.0.1), Y would be a minor release (1.1.0) and X would be a major release (2.0.0). We permit any breaking changes to only be released in major versions and strongly recommend reading changelogs before making any major version upgrades.More InformationSingle Sign-On GuideDirectory Sync GuideAdmin Portal GuideMagic Link Guide
Package: work-os-ipython-magic
Work OS IPython Custom MagicIPython Custom Magic that helps define a Work OS Smart Docs.RequirementsJupyterLab >= 3.0InstallTo install the custom magics, execute:pipinstallwork_os_ipython_magicThen in your Notebook, you need to load this custom magic:importwork_os_ipython_magic%load_extwork_os_ipython_magicUninstallTo remove the extension, execute:pipuninstallwork_os_ipython_magic
Package: workoutizer
WorkoutizerWorkoutizer is a simple web application for organizing your workouts and sports activities. It is designed to work
locally on any UNIX-like system running Python.Track your activities to get an overview of your overall training, similar to platforms likestravaorgarmin connect- but without
uploading all your sensitive health data to some 3rd party cloud.FeaturesAutomatic import of Garmin.fitfiles and.gpxfilesAutomatic naming of activities based on daytime, sport and geo locationRender your activity gps data on different OSM mapsPlot your activity specific data e.g. heart rate, pace, temperature, cadence and altitudeIntegrate laps into both plots and mapsConnected plots and map via mouse hoveringFind sections with highest speed and max altitude gain usingsportgemsand
highlight on mapAdd untracked activities manually via the GUIExport activities as.gpxfilesAdd as many different sports as you wantStatusWorkoutizer is still in a somewhat experimental phase. Things might change a lot from one version to another. However,
I'm happy to receive bug reports and feedback.Getting StartedInstall workoutizer using pippip install workoutizerInitialize workoutizer to provide some demo data and run it:wkz init --demo
wkz runSee the help description of the CLI withwkz --helpand subcommands, e.g.:wkz manage --help.In case you want to run workoutizer on a Raspberry Pi in your local network, follow theRaspberry Pi setup instructions.GalleryDashboardSport PageActivity Page 1/2Activity Page 2/2ChangelogSeeChangelog.ContributingContributions are welcome - check out theContribution Guidelines.ThanksLibraries and other tools used by Workoutizer:leaflet-uibyRarutodjango-colorfieldbyFabio Caccamopython-fitparsebydtcooperleaflet-color-markersbypointhiFont Awesome IconsPaper-Dashboard ProbyCreative Tim
Package: workpathapi
workpathapiThis package allows you to interact with theWorkpathAPI.PrerequisitesThere is only one mandatory Python package that needs to be installed to useworkpathi. e.requests. One can install it with the following command.pip install requestsIf you want the API to return a pandas DataFrame you additionally need to install pandas.pip install pandasInstallationIf all prerequisites are met the installation is as simple as executing the commandpip install workpathUsageTo get data from the Workpath API you only need three steps.1. Import moduleImport the module, for example like this.from workpathapi import WorkpathAPI2. Instanciate WorkpathAPICreate an instance of the WorkpathAPI.api = WorkpathAPI(company='dataatelier', api_token='YOUR_WORKPATH_TOKEN')You need to pass two arguments. Your company and the API token.
Note: If your API token is set as an environment variable asWORKPATH_API_TOKEN = "YOUR_WORKPATH_TOKEN"then you don't have to pass the argumentapi_token.3. Get goals from the APIIf you want to get all goals, simply executegoals = api.get_goals()The output corresponds to the output of API endpointgoals, describedhereIf you want the result as a pandas DataFrame you can pass the argumentoutput_format='DataFrame'If you want information about a specific goal, one can executegoal = api.get_goal(goal_id=1001)See APIdocumentationfor further information.
Package: workq
In programming, there are some problems with recursive algorithms.
One of them is the stack: each recursion adds a new frame to the
stack.  This can be mitigated using tail recursion, but tail recursion
isn’t always possible.  A second problem is loops: consider loading a
series of files which contain an “include” instruction, where one of
the files contains an “include” for itself or for another file which
contains an “include” for it.One good solution for these problems is to recast the recursive
algorithm as an iterative one.  AWorkQueueis a tool for doing
exactly this; it is an iterator for work items, where work items may
be added to the queue during iteration.  AWorkQueuealso has
support for tracking items that have been added to the queue before,
eliminating the loop problem by simply ignoring duplicates.Basic UsageThe basic usage of aWorkQueueis very simple–one simply
initializes it with a sequence of work items, then iterates over the
items, adding new items as necessary:wq = workq.WorkQueue([item])
for item in wq:
    # Do work

    # Add one item to the queue
    wq.add(new_item)

    # Alternatively, add a sequence of items to the queue
    wq.extend(new_items)Each item added to the queue is tracked, and attempts to add an item
that has already been added will simply be ignored.  This can be
disabled by passingunique=Falseto theWorkQueueconstructor.
If the work items are not hashable, or must be kept unique based on
some property of the item (e.g., an instance attribute), then pass akeycallable to theWorkQueueconstructor; this callable will
be called with one argument–the work item–and must return the key
corresponding to that item.Work CountsThe length of aWorkQueueobject is the number of work items still
in the queue.  AWorkQueuealso keeps track of the total number of
work items that have been added to it; this count can be accessed
through thecountproperty.  Finally, the number of items that
have been worked can be accessed through theworkedproperty.  As
an example:>>> wq = workq.WorkQueue(['a', 'b'])
>>> next(wq)
'a'
>>> wq.add('c')
>>> len(wq)
2
>>> wq.count
3
>>> wq.worked
1Work Item UniquenessAWorkQueueobject uses a Pythonsetto track the items that
have previously been added, to prevent duplications.  This isn’t
required for every application, and some applications may have a large
number of work items, or even a never-ending stream of them.  To
accommodate this, theuniquekeyword argument may be passed to theWorkQueueconstructor with a value ofFalse; this will disable
using thesetand keep memory usage under control.Another problem with usingsetis that some work items may not be
hashable, or the objects may be distinct when the work that they
represent is not.  To accommodate this, use thekeykeyword
argument to theWorkQueueconstructor; this identifies a callable,
similar to thekeyparameters ofsort()andsorted(),
which is passed the work item and returns a key to use with theset.  This can also be used to keep memory usage under control, by
allowing thesetto store, say, a short string, rather than a
large object.
Package: work-queue
The Cooperative Computing Tools (cctools) is a software
package for enabling large scale distributed computing
on clusters, clouds, and grids.  It is used primarily for
attacking large scale problems in science and engineering.You can read more about this software at:http://ccl.cse.nd.edu/softwareThe software is developed by members of the Cooperative
Computing Lab at the University of Notre Dame, led by
Prof. Douglas Thain.  The file CREDITS lists the many
people that have contributed to the software over the years.For complete instructions on how to build, install, and use
the software, see here:http://ccl.cse.nd.edu/software/manualsIf you are impatient, the following commands will build
and install the software in your home directory:./configure --prefix ${HOME}/cctools
make clean
make install
export PATH=${PATH}:${HOME}/cctools/bin
chirp_statusThis software package is
Copyright (c) 2003-2004 Douglas Thain
Copyright (c) 2005-2019 The University of Notre Dame
This software is distributed under the GNU General Public License.
See the file COPYING for details.This product includes software developed by and/or derived
from the Globus Project (http://www.globus.org/)
to which the U.S. Government retains certain rights.This product includes code derived from the RSA Data
Security, Inc. MD5 Message-Digest Algorithm.This product includes public domain code for the
SHA1 algorithm written by Peter Gutmann, David Ireland,
and A. M. Kutchman.This product includes the source code for the MT19937-64
Mersenne Twister pseudorandom number generator, written by
Makoto Matsumoto and Takuji Nishimura.
Package: workreport
OverviewworkreportThis project was generated withcookiecutterusingjacebrowning/template-python.SetupRequirementsPython 3.9+InstallationInstall it directly into an activated virtual environment:$ pip install workreportor add it to yourPoetryproject:$ poetry add workreportUsageAfter installation, the package can imported:$ python
>>> import workreport
>>> workreport.__version__
Package: work-report-tool
Work Report ToolTool generating HTML reports based on results fetched from Hubstaff API v1Free software: MIT licenseDocumentation:https://work-report-tool.readthedocs.io.FeaturesTODOCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2021-02-27)First release on PyPI.
Package: worksforme
Works For MeA very basic soundboard to build an atmospheric background sound, for example
for role playing games.InstallationJust use PyPi:pip install worksformeI strongly recommend to usemetaindexwith
theaudiopackage together withworksforme:pip install metaindex[audio]If you'd rather not, at least installmutagen, otherwise even less metadata
will be available in the web interface.UsageYou point the soundboard to your audio libraries or library and it starts a
primitive web server atlocalhost:8050:worksforme ~/Music ~/that/other/music/libraryThat's it. Open your browser atlocalhost:8050and start playing around.LicenseMIT.
Package: workspace-cli
WorkspaceWorkspacestreamlines management and adoption of mono-repositories, by providing a wrapper around multi-repo tooling.It was initially implemented to manage Python projects, but can be extended to interpret other types of projects.DocumentationHomeInstallationConfigurationBasic usageTemplatesPluginsFAQDevelopmentInstall dependencies:pyenvshell3.8.6# Or other version >= 3.8pre-commitinstall# Configure commit hookspoetryinstall-Epoetry-Epipenv-Ecookiecutter# Install Python dependenciesRun tests:poetryruninvverifyTodosExperiment with non-Python workspacesMore detailed plugin documentationExample workspacesTest output on shells with limited color supportLabelling projectsProject aliasesLicenseThis project is distributed under the MIT license.
Package: workspace_manager
workspace_manager - Package description goes here--------------------------------------Installation------------Use::> sudo pip install workspace_manageror::> sudo easy install workspace_manageror::> git clone git://github.com/arinker/workspace_manager-py.git> cd workspace_manager-py> sudo make installUsage-----Development Status------------------Community---------Authors-------* Arno Rinker <arinker@byteyard.de>Copyright---------workspace_manager is Copyright (c) 2014, Arno Rinkerworkspace_manager is licensed under the New BSD License. See the LICENSE file.
Package: workstation-cli
Workstation🕮 DocumentationFor detailed documentation (todo), please seeherepipinstallworkstation--user🪛 DevelopFirst install workstationpyenvinstall-s3.8.12
pyenvlocal3.8.12
poetrylock
nox-spre-commit--install
nox-spre-commit--install--hook-typecommit-msgReleasegitswitch--createreleasemain
nox-srelease----patch
gitpushoriginrelease
Package: work-stream
work-stream简介这是一个用于应对运维工作的模块，能够将提前设定好的运维任务流水线式执行，并且支持流程化编排。特性支持流程状态管理。每个流程/块支持接收上一流程/块的返回值。支持分支流程，需要自己设定判断表达式。支持流程编排。版本python3.6+安装pip3 install work-stream文档详见:https://work-stream.readthedocs.io/zh/latest/?badge=latest
Package: workstream-dbt-core
workstream-dbt-coreA CLI and Python library for integrating dbt-core and Workstream.Installationpipinstallworkstream-dbt-coreUsageInstalling this package installs a CLI app. You can learn about its commands and options using:workstream--helpReporting a dbt InvocationReport a dbt-core invocation to Workstream by posting artifacts from dbt'stargetdirectory
to the Workstream API. The CLI defaults to searching for a directory namedtargetin the
current working directory, but this is configurable with the--target-pathor-toption.workstreamreport-t/path/to/dbt/target--client-idabc123--client-secretxyz987Exit CodesBy default,workstream reportwill always exit with a 0 code, even if it encounters critical errors, so that it doesn't interrupt later steps in your pipeline. If you would likeworkstream reportto exit with a nonzero code on error, you can run it with the--exit-nonzerooption:workstream report --exit-nonzeroEnvironment VariablesAll CLI options can also be set using environment variables. Vars start with the prefixWORKSTREAM_DBT_and then share their name with their associated option. The following command is equivalent to the previous one:WORKSTREAM_DBT_TARGET_PATH="/path/to/dbt/target"WORKSTREAM_DBT_CLIENT_ID="abc123"WORKSTREAM_DBT_CLIENT_SECRET="xyz987"workstreamreportContributingThis project is built withPoetry. After cloning, install with:poetryinstallThen spawn a subshell with a virtual environment activated:poetryshellTesting and LintingThis project uses pytest and ruff. Withpoetry shellactivated, run tests with:pytestFormat and lint with:ruffformat
ruff.--fixor if you have make, lint and test with:make
Package: workstreams
workstreamsA Workstreams Python Client LibraryFor an overview of the Workstream API,click here.RequirementsPython >= 3.6Requests >= 2.19.0Getting startedpip install workstreamsworkstreamsis very simple to use -- take a look at the below example:fromworkstreamsimportWorkstreamsClientworkstreams=WorkstreamsClient('your token')workstreams.tasks.create(team_id='T3T7BFHGV',channel_id='C3T7D66J1',ws_user_id='U3T716H3N',data={'title':'test task','labels':['init-labelid123'],'checklist':[{'text':'never gonna give you up','checked':False}],'dueDate':'2018-03-07T11:46:17Z','assignee':'U3T716H3N'})Note:ws_user_idmust always be provided for app tokens.Tasks Resource (workstreams.tasks)Available methods:create(team_id, channel_id, data, ws_user_id=None)- Create a taskupdate(task_id, data, ws_user_id=None)- Update a taskfetch(task_id, ws_user_id=None)- Fetch a single taskfetch_user_tasks(team_id, user_id, ws_user_id=None)- Fetch tasks for a single userfetch_tasks_for_users(team_id, user_ids, ws_user_id=None)- Fetch tasks for multiple usersExample:fetch_tasks_for_users(team_id='T3T7BFHGV', user_ids=['U123456', 'U123457', 'U123458'], ws_user_id=None)fetch_tasks_for_channels(team_id, channel_ids)- Fetch all tasks for multiple channelsExample:fetch_tasks_for_channels(team_id='T3T7BFHGV', channel_ids=['C3T7D66J1', 'C3T7D66J2'], ws_user_id=None)fetch_changed_tasks_for_channels(team_id, channel_ids, timestamp, ws_user_id=None)- Fetch all tasks for multiple channels which changed since given timestampfetch_archived_tasks_for_channels(team_id, channel_ids, ws_user_id=None)- Fetch all archived tasks for multiple channelsarchive_tasks(task_ids, ws_user_id=None)- Archive multiple tasksrestore_tasks(task_ids, ws_user_id=None)- Restore multiple tasksfetch_all_tasks_by_label(team_id, label_id, ws_user_id=None)- Fetch all tasks by labelTasks Resource (workstreams.labels)Available methods:create(team_id, data, ws_user_id=None)- Create a new labelupdate(label_id, data, ws_user_id=None)- Update a labeldelete(label_id, ws_user_id=None)- Delete a labelfetch(label_id, ws_user_id=None)- Fetch a single labelfetch_team_labels(team_id, ws_user_id=None)- Fetch all labels for a given teamGoals Resource (workstreams.goals)Available methods:create(team_id, data, ws_user_id=None)- Create a new goalupdate(team_id, goal_id, data, ws_user_id=None)- Update a goalarchive(team_id, goal_id, ws_user_id=None)- Archive a goalfetch_all(team_id, ws_user_id=None)- Fetch all goals visible to the token ownerContributionsTBDBug ReportsTBD
Package: workthing
OfficialEventbriteSDK for PythonFree software: Apache 2 licenseDocumentation:https://eventbrite.readthedocs.org.UsageThe Eventbrite Python SDK makes it trivial to interact with the Eventbrite API:>>>fromeventbriteimportEventbrite>>>eventbrite=Eventbrite('my-oauth-token')>>>user=eventbrite.get_user()# Not passing an argument returns yourself>>>user['id']1234567890>>>user['name']DanielRoyGreenfeldYou can also specify API endpoints manually:>>>user=eventbrite.get('/users/me')>>>user['id']1234567890>>>user['name']DanielRoyGreenfeldUsage with FrameworksWhen using Flask, you can convert incoming webhook requests into Eventbrite
API objects using thewebhook_to_object()method:@app.route('/webhook',methods=['POST'])defwebhook():# Use the API client to convert from a webhook to an API objectapi_object=eventbrite.webhook_to_object(request)# Process the API objectifapi_object.type=='User':do_user_process(api_object)ifapi_object.type=='Event':do_event_process(api_object)return""TODOSAbstract the HTTP calls so they can work with all of the below:requestsGoogle’s HTTP clientTornadoCalling different HTTP libraries:Eventbrite(OAUTH_TOKEN, "requests")
Eventbrite(OAUTH_TOKEN, "google")
Eventbrite(OAUTH_TOKEN, "tornado")History3.0.0-alpha{%d} (2014-12-04)Alpha series for initial developmentInception
Package: worktime
NAMEworktime - Generate daily log web pagesSYNOPSISworktime [OPTION]…DESCRIPTIONCreates a web page with a table on the left side showing the hours of
the day, a table on the right showing the tasks of the day, and a space
in the bottom right for notes.By default only today’s log is created.Logs are printed to standard output.Web site: <http://github.com/l0b0/worktime>-s,--start=DATEFirst date to print. Default today.-e,--end=DATELast date to print. Default today.-d, –days=NAME…Create log files for only the given weekdays.-w,--weekdaysEquivalent to “–days=Monday,Tuesday,Wednesday,Thursday,Friday”.-W,--weekendsEquivalent to “–days=Saturday,Sunday”.-h,--helpPrint this documentation and exit.EXAMPLESworktime –start=2011-01 –end=2011-01 > jan.xhtmlCreate a log file jan.xhtml for January 2011.worktime –start=2010-12 –end=2011-02 –weekendsOutput a log file for each Saturday and Sunday from 2010-12-01
through 2011-02-28.worktime –weekdays –start=2012 –end=2012 > ~/project-X.xhtmlCreate a log file ~/project-X.xhtml for each week day of 2012.
Package: worktimecalc
Work Time CalculatorSmall tool to calculate the exact business time between two datetimes.I wasn't happy with the existing tools for their performance, while others only counted the business days. This was built with the goal of being as efficient as possible, easy to use and flexible.FeaturesFast! Calculations done in constant timeMultiple ways to define working hoursSpecific schedule for each day of the weekCan consider holidaysInstallpip install worktimecalcQuick exampleJust create a calculator and call it to get the difference:fromworktimecalc.calcimportWorkTimeCalculatorcalc=WorkTimeCalculator(9,18,'mon tue thu fri sat')delta=calc("2050-02-10T10:30:00","2050-03-10T18:15:00")print(delta.seconds)# 675000.0print(delta.as_dhms)# {'days': 7, 'hours': 19, 'minutes': 30, 'seconds': 0}print(delta.as_hms)# {'hours': 187, 'minutes': 30, 'seconds': 0}HolidaysPass it a list ofdatetime.dateobjects:holidays=[(2023,1,1),(2023,5,1),(2023,11,1),(2023,12,25)]holidays=[datetime.date(*d)fordinCHILE_HOLIDAYS]calc=WorkTimeCalculator(10,18,holidays=holidays)Constructor examplescalc=WorkTimeCalculator(8,15)calc=WorkTimeCalculator(8,15,'1100100')calc=WorkTimeCalculator(8,15,'sat tue thu mon sun')calc=WorkTimeCalculator("08:30","18:30")calc=WorkTimeCalculator(9,"17:45")calc=WorkTimeCalculator(datetime.time(8,30),datetime.time(18,30))calc=WorkTimeCalculator(detail=[(8,16),(8,16),(8,16),(8,16),(8,10),None,None])calc=WorkTimeCalculator(detail=[(8,"16:30"),("17:15",20),None,None,None,None,None])When in doubt simply check the descriptions for each argument.To doOvernight shifts (spanning two days)Small performance improvements (minmaxing)Allow passing holidays as list of tuples
Package: worktimething
Simple task time tracker:alias wtt='python3 -m worktimething'
wtt b 141
wtt b 142
wtt e 142
wtt b 143
wtt  # shows a summary
141 :   4h 49m
142 :   2h 55m
143 : * 1h 20m
--------------------
TOTAL :   9h 5m
wtt a 141 5h3m  # Add time manually
wtt s 141 2h30m  # Subtract time manuallyThen get summaries in Jira work log format so that you don’t have to worry about those any longer.