Saravanan666/pypi-org huggingface dataset:
Package: thcrdt
THCRDTOverviewTangledHub library that handles Conflict-free Replicated Data types.Licencingthcrdt is licensed under the BSD license. Check theLICENSEfor details.InstallationpipinstallthcrdtTestingdocker-composebuildthcrdt-test;docker-composerun--rmthcrdt-testBuildingdocker-composebuildthcrdt-builning;docker-composerun--rmthcrdt-builningPublishdocker-composebuildthcrdt-publish;docker-composerun--rmthcrdt-publishCRDT supported in this libraryCRDT_Dictdoc:dict=crdt.from_({'cards':[{'x':0,'y':10,'z':20}]}).unwrap()CRDT_Listdoc:dict=crdt.from_({'cards':[[1,2,3]]}).unwrap()CRDT_Counterdoc:dict=crdt.from_({'cards':[Counter(1)]}).unwrap()increment(int)Increase counter valuedoc['cards'][0].increment(2)decrement(int)Decrease counter valuedoc['cards'][0].decrement(1)APIthcrdt api is using thethresultlibrary, so all api functions are returning result wrapped inOkorErrobject.Therefore, in order to reach into the result object, you should use.unwrap()as in examples.crdt=CRDT()crdt.from_(self, o: Any)Creates a new CRDT object and populates it with the contents of the passed objectExample:Create document with initial statedoc_s0:dict=crdt.from_({'cards':[{'x':0}]}).unwrap()crdt.clone(self, Any)Creates a new copy of the CRDT instanceExample:doc_clone=crdt.clone(doc_s0)crdt.change(self, doc: Any, fn: Callable)Modify an CRDT object, returning an updated copyExample:# CLIENT A# changes on client Adefdoc_ca(doc:dict):doc['cards'][0]['x']=5doc['cards'][0]['y']=10doc['cards'][0]['z']=20# The doc_a0 object is treated as immutable, you must never change it directly, create doc_a0 clone using crdt.clone().# In order to update doc_a0 you should use crdt.change() instead.doc_a1:dict=crdt.change(crdt.clone(doc_s0).unwrap(),doc_ca).unwrap()crdt.merge(self, a: Any, b: Any)Example:Merges the two CRDT instances# CLIENT B# Create initial document on client Bdoc_b0:dict=crdt.from_({'cards':[{}]}).unwrap()# Now merge this two documentsdoc_b1:dict=crdt.merge(doc_b0,doc_a1).unwrap()# changes on client Bdefdoc_cb(doc:dict):doc['cards'][0]['x']=-5doc['cards'][0]['y']=-10doc['cards'][0]['z']=-20doc_b2:dict=crdt.change(crdt.clone(doc_s0).unwrap(),doc_cb).unwrap()# Now merge the changes from client B back into client A. You can also# do the merge the other way round, and you'll get the same result.final_doc:dict=crdt.merge(doc_b2,doc_a1).unwrap()crdt.get_changes(self, root: Any, doc: Any)Returns a list of all the changes that were made in the documentExample:# Create document with initial statedoc1s:dict=crdt.from_({'cards':[{}]}).unwrap()# CLIENT A# changes on client Adefdoc_ca(doc:dict):doc['cards'][0]['x']=5doc['cards'][0]['y']=10doc['cards'][0]['z']=20# In order to update doc1s you should use crdt.change().doc_a1:dict=crdt.change(crdt.clone(doc1s).unwrap(),doc_ca).unwrap()# Get changes made on client A. These changes are encoded as byte arrays (Uint8Array)doc_a1_changes:list=crdt.get_changes(doc1s,doc_a1).unwrap()crdt.apply_changesApplies the list of changes to the given document, and returns a new document with those changes appliedExample:# CLIENT B# Now apply changes on client Bdoc_b1,patch=crdt.apply_changes(doc1s,doc_a1_changes).unwrap()
Package: thctools
技术指标这是一个基于事件驱动设计模式的技术指标算法，可用股市预测行情趋势。目前已实现MACD,KDJ,MA,RSI等重要指标。为了便捷的使用，简单封装成该接口，以便需要的人使用。环境要求：pyhonpandasdoctesttushare调用方式1：数据源要求：数据结构：pandas.Dataframe参数：
['date', 'open', 'high', 'low', 'close']示例：dateopenhighlowclose02019110633.8034.1533.3333.4612019110533.9534.1333.4533.8122019110433.6934.4533.4833.8532019110133.3633.6433.1133.5042019103133.7234.2033.3733.4252019103034.3434.3433.5233.7862019102935.2535.2534.3334.3472019102835.3035.5034.4435.3582019102534.0834.1133.5934.0092019102433.9334.1433.3533.84调用代码：fromthctoolsimportTechnicalthc_obj=Technical(df)thc_obj.mathc_obj.macdthc_obj.kdj测试案例：fromthctoolsimportTechnicalts.set_token('24c7a5d5b40cd5db779cbc888ba4516d4be3384c0cf897caeaf2415b')pro=ts.pro_api()df=pro.query('daily',ts_code='603019.SH')df=df.rename(columns={'trade_date':'date'})[['date','open','high','low','close']]print(df.head(10))tech_obj=Technical(df)print(tech_obj.ma.head(10))print(tech_obj.macd.head(10))print(tech_obj.kdj.head(10))结果：ma:MA10MA20MA5MA60date00.0000.00.0000.02014110610.0000.00.0000.02014110720.0000.00.0000.02014111030.0000.00.0000.02014111140.0000.09.3020.02014111250.0000.010.2320.02014111360.0000.011.2560.02014111470.0000.012.3820.02014111780.0000.013.6220.020141118912.1440.014.9860.020141119macdDEADIFEMA12EMA26MACDdate00.0000.0007.6207.6200.0002014110610.0120.0617.7377.6760.0982014110720.0450.1747.9657.7910.2582014111030.1030.3358.3007.9650.4642014111140.1900.5378.7388.2010.6942014111250.3080.7809.2828.5020.9442014111360.4581.0599.9318.8721.2022014111470.6411.37210.6879.3151.4622014111780.8571.72211.5579.8351.7302014111891.1072.10612.54410.4381.99820141119kdjDJKRSVdate00.0000.0000.0000.02014110610.0000.0000.0000.02014110720.0000.0000.0000.02014111030.0000.0000.0000.02014111140.0000.0000.0000.02014111250.0000.0000.0000.02014111360.0000.0000.0000.02014111470.0000.0000.0000.020141117855.55688.88966.667100.020141118962.963107.40877.778100.020141119
Package: th-django-analytics
Quick startAdd “analytics” to your INSTALLED_APPS setting like this:INSTALLED_APPS = [
    ...
    'analytics',
]Include the polls URLconf in your project urls.py like this:path("analytics/", include("analytics.urls")),Runpython manage.py migrateto create the analytics models.Runpython manage.py collectstaticsto collect the statics files.Dashboard Data Processingpython manage.py data_processing
Package: thdl
THDLTHDL is a bunch of tools (hidden under single program) for easing the work with VHDL language.
It is (and will always be) based solely on the text processing, no semantic analysis.
Such approach draws clear line what might be included and what will never be supported.
'T' in the 'THDL' stands for 'Text'.
However, donotread THDL as "Text Hardware Description Language" and donottreat it as such.DocumentationCheck thewiki.SPDX-License-Identifier: GPL-3.0-or-laterhttps://spdx.org/licenses/GPL-3.0-or-later.htmlCopyright (c) 2021 Michał Kruszewski
Package: thea
Thea"Titaness of (...) the shining light of the clear blue sky"fromWikipediaretrieved 1 November 2018.Thea is used to control the environment of model (train) layouts based
on real-world data and simulation models. Current development is focused
around lighting ðŸŒ„ but we plan to expand the functionalities to include
sound ðŸ”‰ and actuator control.ðŸŒ± OriginThis project was started in order to control lighting of model-train
layouts in more interesting ways. Most solutions only offer manual
and rule based control resulting in very predictive behavior. Thea
breaks with this by controlling the model environment based on real-word
data and simulation models that introduce an element of randomness.âœ… PrinciplesScience based environment simulation;Simple to start but complex if you want to;Modern user interface;Support for common hardware;âœ¨ FeaturesCurrently Thea is in early development so the list of available features
is a bit short. However we have a lot planned:Accelerated model timeDay and night cycle ðŸŒ“Hardware control over MQTTHousehold lightingWeather patterns ðŸŒ€Traffic ðŸš—Opening-hours ðŸ•“Graphical user interfaceMoon and stars ðŸŒ›âœ¨DCC train control ðŸš‚Weather sounds ðŸ”‰ðŸ¤” Getting startedCurrently there is not much use in this project as an end user. However
if you would like to contribute head over to thecontributingsection
of our documentation. We are happy to receive pull-requests.ðŸ“š DocumentationAll our documentation including on how to get started can be foundhere.ðŸ“ƒ LicenseThea is created by Mike van Sighem and licensed under LGPL version 3.
Refer to thelicensefor more details.ðŸ’› ContributingWe are happy to see contributors on the project. Head over to thecontributingsection
of our documentation and submit your first pull-requests.
Package: theabbie
TheAbbieAbout MeMy OctocatMy BlogTasks10 Ways to contact meDonateabout MeHello World, I am Abhishek ChaudharyA pseudo-introvert, a web developer, and a Makerhttps://theabbie.github.ioResumehttps://orcid.org/0000-0003-1526-9128Abhishek ChaudharyQuick InfoNameAbhishek ChaudharyBorn11 January, 2002EducationB.E.Alma materFr C Rodrigues institute of technologyNationalityIndianOccupationWeb DeveloperSkillsHTML, CSS, JavaScript, Node.js, SEOOther NameTheAbbieTitleCEO of TheAbbieKnown ForTheAbbiemy octocatmy bloghttps://theabbie.github.io/blogtasksBornGot a jobMarriedHave childrenDie10 ways to contact meMailInstagram DMTelegramWhatsappLinkedinTwitterSnapchatICQFacebookCalldonate
Package: thealot
TheAlot is a modular IRC bot framework for Python3.InstallpipinstallthealotConfigure{"server":"irc.quakenet.org","port":6667,"channel":"#TheAlot","nickname":"TestAlot","prefix":"!","database":"sqlite:///alot.db","reconnection_interval":10,"plugins":[]}Runpython-mthealot.thealotorfromthealotimportTheAlotbot=TheAlot()if__name__=="__main__":bot.start()
Package: thealtening
An unofficial python package made forhttps://thealtening.com/The API supports basic and premium plans ONLYclass thealtening.API()parameters:apikey - REQUIRED - thealtening's API key needed to generate/favorite/private accounts (found here:https://panel.thealtening.com/#account)password="password" - Optional - the password given to the account's login (12345-12345@alt.com:Password)verify=True - Optional - Verifies the account's API key by requesting the license fromhttps://api.thealtening.com/v1/license, prints the error if one is givenfile=None - Optional - The file your accounts generated (using API.generate()) will be stored inlicense()Requests the license affiliated with the API key (defined above)Returns the account info or an error (if one is given)generate()Generates an account using thealtening's APIReturns the account generatedparameters:repeat=1 - Optional - How many accounts will be generated (if more than one, it returns a list)login=False - Optional - Logs you into the account to get the UUID and the full usernameinfo=False - Optional - Requests more info from thealtening's APIfile=None - Optional - The file your accounts will be stored in (if none, will keep the file same as the one defined in thealtening.API()favorite()"favorites" the last account generated in the programReturns nothing or an error (if one is given)parameter:atoken=None - Optional - "Favorites" that account instead of the last one generatedprivate()"privates" the last account generated in the programReturns nothing or an error (if one is given)parameter:atoken=None - Optional - "Privates" that account instead of the last one generatedalt_login()logs you into an account and returns the response fromhttps://authserver.thealtening.com/authenticateparameter:atoken=None - Optional - Logs you into that account instead of the last one generatedset_API()Sets your api to the one providedparametersapikey - REQUIRED - thealtening's API key needed to generate/favorite/private accounts (found here:https://panel.thealtening.com/#account)verify=True - Optional - Verifies the account's API key by requesting the license fromhttps://api.thealtening.com/v1/license, prints the error if one is givenstatus()Returns the status ofhttps://authserver.thealtening.com/andhttps://sessionserver.thealtening.com/I am not affiliated with thealtening in any way.l
Package: theano-hf
Theano-hf-py3This is a Python 3 verson ofboulanni/theano-hf.Installpipinstall--upgradetheano-hfUsageimporttheano_hfOriginal DescriptionI wrapped my Hessian-free code in a generic class, usable as a black-box to train your models if you can provide the cost function as a Theano expression.It includes all the details in Martens (ICML 2010) and Martens & Sutskever (ICML 2011) crucial to make it work:Tikhonov damping with the Levenberg-Marquardt heuristics,Gauss-Newton matrix products (you specify an Theano expressionsto section your computational graph in 2),Proper handling of batches and mini-batches (an example SequenceDataset class is provided for variable-length input)Conjugate gradient (CG) with information sharing, backtracking, preconditioning and terminations conditions.Structural damping for RNNs.It relies heavily on the Rop. In practice, I could make it work without hassle for a feed-forward network, an RNN with different objectives, NADE (Larochelle) and a more complex model (RNN-NADE) that ties two scans together, so it seems reasonably flexible.
Only the gradients and Gauss-Newton matrix products (95% of the computation) are in Theano, CG and the training logic is in python. It runs on GPU, but for the models I tried, it was a bit slower.
Hessian-free is slow, you need CG batch sizes of 1000+ (don't skimp on this), but you can get really better results than SGD from it with almost zero tweaking.There is an option to save and recover a checkpoint of training and do early stopping.I included an RNN example that can memorize an input for 100 time steps (example_RNN). Launch it on 4 cores, come back in 8 hours, and you should have at least one nice solution with 0 error on the validation set.
In comparison, SGD can solve this problem about 0.0% of the time.It is available here:https://github.com/boulanni/theano-hfIf you use this software for academic research, please cite the following paper:[1] N. Boulanger-Lewandowski, Y. Bengio and P. Vincent, "Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription", Proc. ICML 29, 2012.Author: Nicolas Boulanger-Lewandowski
University of Montreal, 2012
Package: theape
TheAll-Purpose Experimenteris a plugin-based system meant to create a unified front-end for different device-related testing.InstallationIf you have the repository you can install it by using thesetup.pyfile.pythonsetup.pyinstallAlternately you can pull it from Pypi.pipinstalltheapeIf you are installing it system-wide you will probably have to prefix this and other install commands withsudo.DocumentationThe APE has some online help.ape-hAPE (the all-purpose-evaluator)

Usage: ape -h | -v
       ape [--debug|--silent] [--pudb|--pdb] <command> [<argument>...]
       ape [--debug|--silent] [--trace|--callgraph] <command> [<argument>...]

Help Options:

    -h, --help     Display this help message and quit.
    -v, --version  Display the version number and quit.

Logging Options:

    --debug   Set logging level to DEBUG.
    --silent  Set logging level to ERROR.

Debugging Options:

    --pudb       Enable the `pudb` debugger (if installed)
    --pdb        Enable the `pdb` (python's default) debugger
    --trace      Enable code-tracing
    --callgraph  Create a call-graph of for the code

Positional Arguments:

    <command>      The name of a sub-command (see below)
    <argument>...  One or more options or arguments for the sub-command

Available Sub-Commands:

    run    Run a plugin
    fetch  Fetch a sample configuration-file
    help   Display more help
    list   List known plugins
    check  Check a configuration

To get help for a sub-command pass `-h` as the argument. e.g.:

    ape run -hInstalling Testing DependenciesThe APE is currently being tested usingbehaveso if you want to run the tests, you’ll need that,pyhamcrestandmock. All three are on pypi so if you have pip installed you can install them from the web (if installing system wide run as root).pipinstallbehavepipinstallpyhamcrestpipinstallmock
Package: theark
Install Instructions
: pip install thearkThe Ark is a library of commonly used tools for automating a website. These tools include:Email Client
: Quick way of sending test results to an email address or a list of email addressesField Handlers
: Takes in different field types for form automation and handles them appropriatelyInput Generator
: Creates a random user to input in a form.Picard Client
: Posts to a created Picard schema.Rhino Client
: Post test results to the Rhino front-end.S3 Client
: Sending files to and getting files from S3.Screen Capture
: Getting a full page, single viewport or scrolling screenshot of a webpage.Selenium Helpers
: A Selenium wrapper that simplifies basic Selenium commands and raises improved exceptionsThe packages in the requirements.txt will need to be installed to get the most out of The Ark.> Written with [StackEdit](https://stackedit.io/).
Package: theatre
TheatreIn the face of ambiguity, refuse the temptation to guess.Finally, the music/video player API you've been waiting for!This modulehadto be built because other music player APIs in python weren't multi-tasking,
easy to use, fast and lightweight (at the same time).(It's a wrapper over MPV's json ipc interface.)This module can be used from multiple Processes/Threads (even across machines) thanks to ZProc.🐍🏕️
Package: theatre-cli
Overviewtheatre-cli is a powerful command-line tool written in Python that transforms your terminal into a personal movie theater. With theatre-cli, you can effortlessly watch your favorite movies stored locally on your device. It provides a seamless and immersive movie-watching experience right from the command line.FeaturesWatch movies conveniently using a text-based interface.Supports popular media players likempvandVLC.Easy-to-use setup and configuration.Compatible with Python 3.10 and higher.InstallationPrerequisitesBefore you can enjoy theatre-cli, ensure you have the following dependencies installed:Python 3.10 (or higher)mpvVLCInstallation StepsClone the repository:gitclonehttps://github.com/virajsazzala/theatre-cli.gitcdtheatre-cliCreate a virtual environment:python-mvenvvenvsourcevenv/bin/activateInstall requirements:pipinstall-rrequirements.txtInstall the package in editable mode:pipinstall-e.UsageLaunch theatre-cli by running the command provided above.Follow the on-screen instructions to set up your movie directory.Enjoy your movies with a cinematic experience right from your terminal.ContributionsContributions to theatre-cli are welcome! Whether you want to add features, fix bugs, or improve documentation, feel free to fork the repository and submit a pull request.
Package: theatro-cfg-loader
Cfg-LoaderCfg-Loader is a library that allows to easily load configuration settings.
It usesmarshmallowto deserialize input data into a target format configuration data.Main featuresinput data validation and automatic processing usingmarshmallowsubstitution of environment variables in input data (followingdocker compose variable substitution syntax)configuration loading from .yaml fileRequirementsPython>=3.6A simple example>>>fromcfg_loaderimportConfigSchema,BaseConfigLoader>>>frommarshmallowimportfields# Declare your configuration schema>>>classMyConfigSchema(ConfigSchema):...setting1=fields.Str()...setting2=fields.Int(required=True)...setting3=fields.Float(missing=13.2)# Declare mapping to substitute environment variable>>>substitution_mapping={'FILE_PATH':'file'}# Initialize config loader>>>my_config_loader=BaseConfigLoader(MyConfigSchema,substitution_mapping=substitution_mapping)# Load configuration>>>config=my_config_loader.load({'setting1':'/home/folder/${FILE_PATH?:file path required}','setting2':'4'})>>>config=={'setting1':'/home/folder/file','setting2':4,'setting3':13.2}True# Invalid input data>>>my_config_loader.load({'setting1':'/home/folder/${FILE_PATH?:file path required}','setting3':13.4})Traceback(mostrecentcalllast):...cfg_loader.exceptions.ValidationError:{'setting2':['Missing data for required field.']}>>>my_config_loader.load({'setting2':12,'setting3':'string'})Traceback(mostrecentcalllast):...cfg_loader.exceptions.ValidationError:{'setting3':['Not a valid number.']}# Variable substitution invalid>>>my_config_loader.load({'setting2':'${UNSET_VARIABLE?Variable "UNSET_VARIABLE" required}'})Traceback(mostrecentcalllast):...cfg_loader.exceptions.UnsetRequiredSubstitution:Variable"UNSET_VARIABLE"requiredDocumentationFull documentation is available athttps://cfg-loader.readthedocs.io/en/stable/.
Package: thebe
Thebe (WIP)Thebe is a python command line app. Its purpose is to let you run your code in cells like Jupyter but while using any editor. It does this by watching the cells for changes, and running them if it sees one.So far it only is tested to run on Mac and UbuntuIt probably has a metric dump truck full of bugsAnd it only works with matplotlib graphsInstallationDependencies:Install pandoc:on Mac via brew:brew install pandocfor linux seepandoc.orgInstall ipykernel:python3 -m pip install ipykernel
python3 -m ipykernel install --userInstall thebeRun:pip install thebeHow to useRun:thebe (File you want to run) (Port you want to display on)To utilize cells encapsulate your code blocks in:$$$$.
e.g.:$$$$
from random import random
import numpy as np
import matplotlib.pyplot as plt
print(random())
$$$$
plt.plot(np.sin(np.arange(10)))
print(random())
$$$$
print(random())
$$$$In your browser of choice go tolocalhost:(Port number)to look at your standard outputs, errors, and plots.This program is still pretty early on so there's likely a lot of bugs.
Package: thebear
BearThe decluttering deduplicator.A bear as a spirit animal is strong and confident, it's a guide to take
leadership in your life without fear, provides courage and a stable foundation
to face challenges. The bear spirit helps to dedicate time and energy to
introspective practices.Same as the bear spirit, this application provides you with confidence to take
leadership in your digital life, find all the mess you've been collecting for
a while and gives you a stable foundation to face the challenge of removing
duplicated data on your machine.Once you start removing duplicates, soon you realize how much free space you've
gained and looking through the various files from the high-level point of view
will slightly poke you to set the order to the files, to categorize them and
eventually make your machine a clean space.Feel free to open a pull request with your improvements for the project, open
an issue in case of bug or a feature request and come and talk about the
project in theMatrix communityInstallationCurrently there is a Python module installation available, and some
platform-specific releases. Check the assets in the GitHubreleases.BinariesThe Windows build is made specifically for Windows 10, so it might not work
without Universal CRT present on the system. The GNU/Linux build is created
on Debian trusty and anything older than that most likely won't work. Use
Python installation instead.The "extension".linuxand.macosis just a workaround for GitHub assets
since it does not allow the same name for multiple assets.Feel free to rename it tobearand put it somewhere on yourecho $PATH(echo %PATH%for Windows) or call it in-place. Don't forget to make it
executable first if on GNU/Linux or MacOS withchmod +x bear.Python packageRequirementsPython 3.7+ (3.6 should work too)You can install a stable version with:pip install https://github.com/KeyWeeUsr/Bear/zipball/stable
pip install thebearFor the cutting-edge available changes usemasterbranch:pip install https://github.com/KeyWeeUsr/Bear/zipball/masterUsageThere is a list of basic use-cases:remove all duplicates and keep the newest (modified date) files:bear --duplicates folder1 folder2 ... --keep-newestremove all duplicates and keep the oldest (modified date) files:bear --duplicates folder1 folder2 ... --keep-oldestfind all duplicate files within specific foldersbear --duplicates folder1 folder2 ...hash all files in specific foldersbear --hash folder1 folder2 ...traverse folders for filesbear --traverse folder1 folder2 ...hash specific files:bear --files file1 file2 ...There are other, advanced options you can list withbear --helpto speed up
the lookup, to control the output and more.