Saravanan666/pypi-org huggingface dataset:
Package: hf-transfer
HF TransferSpeed up file transfers with the Hub.DISCLAIMERThis library is a power user tool, to go beyond~500MB/son very high bandwidth
network, where Python cannot cap out the available bandwidth.This isnotmeant to be a general usability tool.
It purposefully lacks progressbars and comes generally as-is.Please file issuesonlyif there's an issue on the underlying downloaded file.Contributingpython3-mvenv~/.venv/hf_transfersource~/.venv/hf_transfer/bin/activate
pipinstallmaturin
maturindevelophuggingface_hubIf you are working on changes withhuggingface_hubgitclonegit@github.com:huggingface/huggingface_hub.git# git clone https://github.com/huggingface/huggingface_hub.gitcdhuggingface_hub
python3-mpipinstall-e".[quality]"You can use the following test script:importos# os.environ["HF_ENDPOINT"] = "http://localhost:5564"os.environ["HF_HUB_ENABLE_HF_TRANSFER"]="1"fromhuggingface_hubimportHfApi,logginglogging.set_verbosity_debug()hf=HfApi()hf.upload_file(path_or_fileobj="/path/to/my/repo/some_file",path_in_repo="some_file",repo_id="my/repo",repo_type="model")
Package: hf-trim
hf-trimA package to reduce the size of 🤗 Hugging Face models via vocabulary trimming.The library currently supports the following models (and their pretrained versions available on theHugging Face Models hub);BART: Denoising Sequence-to-Sequence Pre-training for Natural Language GenerationmBART: Multilingual Denoising Pre-training for Neural Machine TranslationT5: Exploring the Limits of Transfer Learning with a Unified Text-to-Text TransformermT5: A Massively Multilingual Pre-trained Text-to-Text Transformer"Why would I need to trim the vocabulary on a model?"🤔To put it simply, vocabulary trimming is a way to reduce a language model's memory footprint while retaining most of its performance.Read morehere.CitationIf you use this software, please cite it as given below;@software{Srivastava_hf-trim,
author = {Srivastava, Aditya},
license = {MPL-2.0},
title = {{hf-trim}}
url = {https://github.com/IamAdiSri/hf-trim}
}InstallationYou can also run the following command to install from PyPI;$pipinstallhf-trimYou can install from source;$gitclonehttps://github.com/IamAdiSri/hf-trim
$cdhf-trim
$pipinstall.UsageSimple ExamplefromtransformersimportMT5Config,MT5Tokenizer,MT5ForConditionalGenerationfromhftrim.TokenizerTrimmerimportTokenizerTrimmerfromhftrim.ModelTrimmersimportMT5Trimmerdata=[" UN Chief Says There Is No Military Solution in Syria","Şeful ONU declară că nu există o soluţie militară în Siria"]# load pretrained config, tokenizer and modelconfig=MT5Config.from_pretrained("google/mt5-small")tokenizer=MT5Tokenizer.from_pretrained("google/mt5-small")model=MT5ForConditionalGeneration.from_pretrained("google/mt5-small")# trim tokenizertt=TokenizerTrimmer(tokenizer)tt.make_vocab(data)tt.make_tokenizer()# trim modelmt=MT5Trimmer(model,config,tt.trimmed_tokenizer)mt.make_weights(tt.trimmed_vocab_ids)mt.make_model()You can directly use the trimmed model withmt.trimmed_modeland the trimmed tokenizer withtt.trimmed_tokenizer.Saving and Loading# save withtt.trimmed_tokenizer.save_pretrained('trimT5')mt.trimmed_model.save_pretrained('trimT5')# load withconfig=MT5Config.from_pretrained("trimT5")tokenizer=MT5Tokenizer.from_pretrained("trimT5")model=MT5ForConditionalGeneration.from_pretrained("trimT5")LimitationsFast tokenizers are currently unsupported.Tensorflow and Flax models are currently unsupported.RoadmapAdd support for MarianMT models.Add support for FSMT models.IssuesFeel free to open an issue if you run into bugs, have any queries or want to request support for an architecture.ContributingContributions are welcome, especially those adding functionality for new or currently unsupported models.
Package: hfttools
Copyright (c) 2016 Colin SwaneyPermission is hereby granted, free of charge, to any person obtaining a copyof this software and associated documentation files (the "Software"), to dealin the Software without restriction, including without limitation the rightsto use, copy, modify, merge, publish, distribute, sublicense, and/or sellcopies of the Software, and to permit persons to whom the Software isfurnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in allcopies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS ORIMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THEAUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHERLIABILITY, 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 THESOFTWARE.Description: # hfttoolsA Python toolkit for high-frequency trade research.Website: [https://cswaney.github.io/hfttools/](https://cswaney.github.io/hfttools/)## What?HFT Tools is a Python toolkit for financial researchers. "But I don't use Python!" No worries--all will be explained (keep reading).## Why?The goal of this project is to provide a common, open-source tool for market microstucture research using NASDAQ HistoricalView-ITCH data. Don't pay for data!## Sure. But what does is actually do?HFT Tools creates scalable, research-ready databases from NASDAQ HistoricalView-ITCH data files. These data files are provided "as is" in a compressed, binary format that is not particularlyl useful. HFT Tools decodes these files and creates tables containing the time series of messages as well as the time series of reconstructed order books.## Installation![alt text](https://img.shields.io/pypi/v/hfttools.svg "pypi")If you're a Python user, simply install using the Python package manager:```pip install hfttools```## Basic UsageTo create a new HDF5 database from an ITCH data file `itch_010113`:```pythonimport hfttools as hfthft.unpack(fin='itch_010113.bin',ver=4.1,date='2013-01-01',fout='itch.hdf5'nlevels=10,names=['GOOG', 'AAPL'],method='hdf5')```This will create a file `itch.hdf5` containing message and order book data for Google and Apple. To read the order book data back into your Python session, use `hft.read`:```pythonhft.read(db='itch.hdf5',date='2013-01-01',names='GOOG')```For more information, see our tutorial at the projects [webpage](https://www.google.com).## TipsCreate massive datasets quickly by running multiple jobs. All databases generated by HFT Tools support simultaneous read/write.Platform: UNKNOWNClassifier: Development Status :: 3 - AlphaClassifier: Programming Language :: Python :: 3.5
Package: hfurl
HFURL - Human-friendly URLThis is a tiny python library that provides parsing for human-firendly.
Completely disregarding RFC it correctly parses url with no schema
(eg.example.comis equivalent tohttps://example.com/).Useful when reading input URL from user, who as we al know, often omit schema.Usagefromhfurlimportparse_urlurl=parse_url("example.com:443/about")asserturl.host=="example.com"
Package: hg19genome
hg19genomeA package to work with hg19 genomic intervals.InstallIf you dont already have numpy and scipy installed, it is best to downloadAnaconda, a python distribution that has them included.https://continuum.io/downloadsDependencies can be installed by:pip install -r requirements.txtPyPI install, presuming you have all its requirements installed:pip install hg19genome(not yet!!)Usagefromhg19genomeimportHg19Genomegenome=Hg19Genome()genome.n_CpGsgenome.n_basesgenome.tss()genome.tss(upstream=1000,downstream=1000)
Package: hg38genome
hg38genomeA package to work with hg38 genomic intervals.InstallIf you dont already have numpy and scipy installed, it is best to downloadAnaconda, a python distribution that has them included.https://continuum.io/downloadsDependencies can be installed by:pip install -r requirements.txtPyPI install, presuming you have all its requirements installed:pip install hg38genome(not yet!!)Usage# ailist version: 0.1.7fromhg38genomeimportHg38Genomegenome=Hg38Genome()genome.n_CpGsgenome.n_basesgenome.tss()genome.tss(upstream=1000,downstream=1000)
Package: hgallpaths
A mercurial extension to allow pushing and pulling from all paths specified in
the configuration.InstallationAdd hgallpaths extension to your ~/.hgrc:[extensions]
hgallpaths = /path/to/hgallpaths.pyThe list of all paths is available from thepathscommand:$ hg pathsAlternatively you can install hgallpaths withpip:$ pip install hgallpathsor withsetuptools:$ python setup.py installWith either of those methods you don’t need to specify the path to hgallpaths
in your hgrc configuration:[extensions]
hgallpaths =ConfigurationYou can exclude certain paths in the configuration. For example to always
exclude the pathfooandbar, as well as excludebazwhen pushing
you add this to your ~/.hgrc (or repo hgrc):[hgallpaths]
exclude = foo bar
exclude_push = bazUsageThe two commands supported at the moment arepushallandpullall. For
example to push to all paths run:$ hg pushall
Package: hgana
HGAna: Analysis Tool for Host-Guest BindingDocumentationOnline documentation is available atajax23.github.io/HGAna.The docs include an example for analyzingbinding affinityfor cyclodextrin simulations and anAPI reference.DependenciesHGAna supports Python 3.5+.Installation requiresnumpy,pandasandseaborn.InstallationYou may instead want to use the development version from GitHub:pip install git+https://github.com/ajax23/HGAna.git#egg=hgana

pip install git+https://github.com/ajax23/HGAna.git@develop#egg=hganaOr download the repository and install in the top directory via:pip install .TestingTo test HGAna, run the test in the test directory.DevelopmentHGAna development takes place on Github:www.github.com/Ajax23/HGAnaPlease submit any reproducible bugs you encounter to theissue tracker.How to Cite HGAnaWhen citing HGAna please use the currentZenodo DOIcorresponding to the used HGAna version. (Current DOI is listed in the badges.)
Package: hgapi
hgapi is a pure-Python API to Mercurial, that uses the command-line
interface instead of the internal Mercurial API. The rationale for
this is twofold: the internal API is unstable, and it is GPL.hgapi works for any version of Mercurial, including  < 1.9, and will
instantly reflect any changes to the repository. It also has a really
permissive license (do whatever you want, don’t blame me).For example of code that uses this API, take a look athttps://bitbucket.org/haard/autohookwhich now uses hgapi
exclusively.
Package: hg-autohooks
Mercurial Autohooks Extension=============================This project is an extension for Mercurial that enables Mercurial hooks tobe included inside a source repository such that they are automaticallydetected and utilised merely by being present.It is important to realise that using this extension means that youare giving permission to run code as your user to anyone who can commit tothe repositories you are using. For this reason, the extension will onlybe activated for respositories with a default upstream that you haveconfigured as 'trusted'.Installation------------pip install hg-autohooksAdd the following to your Mercurial configuration:[extensions]hgautohooks=[autohooks]trusted="ssh://hg@hg/"The `trusted` configuration is a list of repository upstream addressprefixes are trusted. The extension will only be active for repositorieswhose default upstream starts with one of the strings in this list.Automatic hooks---------------To use the automatic hooks, create a top-level directory inside yourrepository named either `hg-autohooks` or `.hg-autohooks` and thenadd hook files inside it. The file names should be prefixed with thehook name and have a suffix of `.sh` or `.py` for shell or Pythonextensions respectively. Pre- and post- hooks should be named'pre_hookname.ext' or 'post_hookname.ext' respectively.Example-------To require that your Python module can be successfully importedbefore allowing it to be committed, create a file named`hg-autohooks/pre_commit.import.py` containing:```python"""Mercurial pre-commit hook to try importing the project."""# pylint: disable=invalid-name,unused-argumentimport subprocessdef pre_commit(ui, repo, **kwargs):"""Try importing the project and see if anything bad happens."""imp = subprocess.Popen(("bin/python", "-c", "import foo"),cwd=repo.root, stdout=subprocess.PIPE, stderr=subprocess.PIPE)stdout, stderr = imp.communicate()if imp.returncode or stdout or stderr:if stdout:ui.write(stdout)if stderr:ui.write(stderr)return Truereturn False```
Package: hg-autoshelve
AutoShelve is a Mercurial extension that shelves modified files
before applying changes to the repository then unshelve them.Why would I use it ?I not sure that there is a valid reason for using it. But it’s a
pragmatic solution for durty use cases. Autoshelve will avoid you
wasting time until you meet and find a good solution.Note:Shelve operations may be very long for certain repositories. In
this cases you may want to disable or enable autoshelve in the
configuration file of the repository.InstallationInstall hg-autoshelve usingpip:pip install hg-autoshelveThen enable the extension in yourmercurial configuration file:[extensions]
hgext3rd.autoshelve=
Package: hgcanttype
Corrects simple typing errors in commands usingDamerau-Levenshtein distance.Ever typedhg dfif,hg dofforhg banrch? This fixes that.Some examples of how it helps:$ hg dfif
Correcting 'dfif' to 'diff'

$ hg brnch
Correcting 'brnch' to 'branch'Installation & SetupInstalling hg-canttype is simple:$ pip install hgcanttypeSetup is easy too, just add hgcanttype to your hgrc:[extensions]
hgcanttype=You can configure the distance to consider a command “close enough” like so:[canttype]
distance = 5The default is 1. Take note that setting the distance too high is a bad idea:$ hg dfif
Correcting 'dfif' to 'help'You can also configure the plugin to provide suggestions rather than
automatically correcting the command, just like git:$ hg dfif
hg: unknown command 'dfif'

Did you mean this?
    diffThis is easy to configure:[canttype]
suggest = trueNote that it will automatically do this if it finds more than one command, even
if you have suggestions turned off:$ hg cu
hg: unknown command 'cu'

Did you mean this?
    ci
    cp
    coLicenseAs this is a derived work of the Mercurial project, the license is GPLv2+ as
per theMercurial Licensepage.Change History1.0.8 (4th April 2014)Fix indexing error when not using suggestions1.0.7 (4th April 2014)Don’t recommend the same command multiple times1.0.6 (24th March 2014)I hate Restructured Text1.0.5 (24th March 2014)Provide suggestions if multiple matches were found.Provide suggests all the time if [canttype]/suggest = true.1.0.4 (12th March 2014)Handle no command being passed in. Thank you, Andrew Taumoefolau!1.0.3 (11th March 2014)Removed pointless print statement1.0.2 (10th March 2014)Fix more typos…1.0.1 (10th March 2014)Fix typos. The irony.1.0.0 (10th March 2014)Initial release
Package: hgchat
Hugging Chat PythonInstallationAs libraryFrom PypipipinstallhgchatFrom Codebergpipinstall--index-urlhttps://codeberg.org/api/packages/Bavarder/pypi/simple/hgchatAs an interactive promptgitclonehttps://codeberg.org/Bavarder/hgchat.git# or https://github.com/Bavarder/hgchat.gitcdhgchatUsageAs libraryfromhgchatimportHGChathgchat=HGChat()r=hgchat.ask(user_input)foriinr:char=i["token"]["text"]ifchar=="
":print("\n",end="")else:print(char,end="")As an interactive promptpythonchat.py
Package: hg-commit-sanity
hg-commit-sanity: Mercurial Commit Sanity=========================================.. image:: https://api.travis-ci.org/paylogic/hg-commit-sanity.png:target: https://travis-ci.org/paylogic/hg-commit-sanity.. image:: https://pypip.in/v/hg-commit-sanity/badge.png:target: https://crate.io/packages/hg-commit-sanity/.. image:: https://coveralls.io/repos/paylogic/hg-commit-sanity/badge.png?branch=master:target: https://coveralls.io/r/paylogic/hg-commit-sanity``hg-commit-sanity`` is a Mercurial extension that allows to easily create precommit hooks to do sanity checks on commits.Kudos to `Matthew Schinckel <http://schinckel.net/2013/04/07/hg-commit---prevent-stupidity>`_Installation------------.. sourcecode ::pip install hg-commit-sanityConfiguration-------------An example of your .hgrc:.. code-block:: cfg[extensions]hg_commit_sanity =[hg_commit_sanity].py =^[^#]*import pdb; pdb.set_trace\(\).js =^[^(//)]*console\.[a-zA-Z]+\(.*\)This will Abort the commit in case it will find import pdb; pdb.set_trace() in *.py files and console. in *.js filesContact-------If you have questions, bug reports, suggestions, etc. please create an issue on the `GitHub project page <http://github.com/paylogic/hg-commit-sanity>`_.License-------This software is licensed under the `MIT license <http://en.wikipedia.org/wiki/MIT_License>`_See LICENSE.txt© 2013 Paylogic International.CHANGELOG=========0.0.1------ initial version
Package: hg-credentials
This is an extension for Mercurial 5.6 or later, allowing you to store
HTTP passwords securely. The extension itself does not offer any
commands, you simply enable it, and get an extra prompt:$ hg pull
pulling from https://example.com/private/repo
http authorization required for https://example.com/private/repo
realm: Mercurial
user: me
password: <SECRET>
would you like to save this password? (Y/n)  y
searching for changes
no changes foundThat would result an a new item named in your key chain or key ring:Mercurial (me@example.com)Once a password is saved, there’s nothing more to do. You’ll get a new
prompt, should the password suddenly stop working. To manage or delete
your passwords, use theKeychain Servicesapplication included with
macOS, GNOME Keyring or something similar included in your desktop
environment.RequirementsPython 3.6 or later.Mercurial 5.6 or later.SecretStorageon
platforms other than macOS.Windows is not supported, yet.Installation and usageInstall the extension and its dependencies with Pip:$ pip install .Then, add the following lines to your~/.hgrc:[extensions]
credentials =To avoid entering passwords for each and every repository, useauth.schemes:[auth]
example.prefix = example.com
example.username = meThis will cause all repositories onhttps://example.comto resolve
to the same Keychain item. Seehg help config.authfor details.AlternativesThe most obvious alternative to this extension is theMercurial
Keyringextension. It
supports older versions of Mercurial and more backends, but saves
passwords in a less readable fashion.Future plansConsider whether it makes sense to implement a completely customurllib2password manager, so passwords aren’t stored in memory
any longer than strictly necessary.AcknowledgementsThanks you to Octobus and Heptapod for hosting this project, and for
making Mercurial development fun again!
Package: hgd
IntroductionThe Head Gesture Detection (HGD) library provides a pre-trained model and
a simple inference API for detecting head gestures in short videos.
Under the hood, it uses GoogleMediaPipefor collecting the landmark features.InstallationTested for Python 3.8, 3.9, and 3.10.The best way to install HGD with its dependencies is from PyPI:python3-mpipinstall--upgradehgdAlternatively, to obtain the latest version from this repository:gitclonegit@github.com:bhky/head-gesture-detection.gitcdhead-gesture-detection
python3-mpipinstall.UsageAn easy way to try this library and the pre-trained model is to
make a short video with your head gesture.WebcamThe code snippet below will perform the following:Search for the pre-trained weights file from$HOME/.hgd/weights,
if not exists, the file will be downloaded from this repository.Start webcam.Collect the needed number of frames (default60) for the model.End webcam automatically (or you can pressqto end earlier).Make prediction of your head gesture and print the result to STDOUT.fromhgd.inferenceimportpredict_videoresult=predict_video()print(result)Video fileAlternatively, you could provide a pre-recorded video file:fromhgd.inferenceimportpredict_videoresult=predict_video("your_head_gesture_video.mp4",from_beginning=False,motion_threshold=0.5,# Optionally tune the thresholds.gesture_threshold=0.9)# The `from_beginning` flag controls whether the needed frames will be obtained# from the beginning or toward the end of the video.# Thresholds can be adjusted as needed, see explanation below.Result formatThe result is returned as a Python dictionary.{
  'gesture': 'turning',
  'probabilities': {
    'has_motion': 1.0,
    'gestures': {
      'nodding': 0.009188028052449226,
      'turning': 0.9908120036125183
    }
  }
}Head gesturesThe followinggesturetypes are available:nodding- Repeatedly tilt your head upward and downward.turning- Repeatedly turn your head leftward and rightward.stationary- Not tilting or turning your head; translation motion is still treated as stationary.undefined- Unrecognised gesture or no landmarks detected (usually means no face is shown).To determine the finalgesture:Ifhas_motionprobability is smaller thanmotion_threshold(default0.5),gestureisstationary. Other probabilities are irrelevant.Otherwise, we will look for the largest probability fromgestures:If it is smaller thangesture_threshold(default0.9),gestureisundefined,else, the corresponding gesture label is selected (e.g.,nodding).If no landmarks are detected in the video,gestureisundefined.
Theprobabilitiesdictionary is empty.
Package: hgdb-rtl
HGDB RTLThis is an experimental tool to generate symbol table from SystemVerilog designs.
It usesslangas a frontend to parse any SystemVerilog files.How to installTO install, simply run the following commandspip install hgdb-rtlhgdb-rtlwill show up in your path.LimitationsSince SystemVerilog is a complex language, there are several limitation in the current implementation.
Notice that none of them are systematic - given enough engineering effort, they can be overcome.No SSA transformation foralways_comblogic. This means that if you reassign the same variable
in the samealways_combblock, the intermediate result will not show in during debugging.Local variables declared in the procedural will not be detected.
Package: hgdistver
Warningthis module is superseeded by setuptools_scmThis module is a simple drop-in to support setup.py
in mercurial and git based projects.Alternatively it can be a setup time requirement.It extracts the last Tag as well as the distance to it in commits
from the scm, and uses these to calculate a version numberBy default, it will increment the last component of the Version by one
and append .dev{distance}
in case the last component is .dev, the version will be unchangedTis requires always using all components in tags (i.e. 2.0.0 instead of 2.0)
to avoid misstakenly releasing higher version
(i.e. 2.1.devX instead of 2.0.1.devX)It uses 4 strategies to archive its task:try to directly ask hg for the tag/distancetry to infer it from the.hg_archival.txtfiletry to read the exact version the cache file if it existstry to read the exact version from the ‘PKG-INFO’ file
as generated bysetup.py sdists(this is a nasty abuse)The most simple usage is:from setuptools import setup
from hgdistver import get_version
setup(
    ...,
    version=get_version(),
    ...,
)get_versiontakes the optional argumentcachefile,
which causes it to store the version info in a python script instead
of abusing PKG-INFO from a sdist.The setup requirement usage is:from setuptools import setup
setup(
    ...,
    get_version_from_hg=True,
    setup_requires=['hgdistver'],
    ...,
)The requirement uses the setup argument cache_hg_version_to instead of cachefile.