Saravanan666/pypi-org huggingface dataset:
Package: puppetry
Remote objects, like puppet.For a small project I need to communicate between two process. In one process I
have a class which create an object. The other process should access the
functions and variables of this object. The process play with the object like an
puppetry.Installpip install puppetryBasic usageExample class:class HelloWorld(object):

    def __init__(self, name=''):
        self.name = name

    def hello(self, name=None):
        if name: return 'Hello ' + name
        return 'Hello ' + self.nameServer:from puppetry import RemoteServer

server = RemoteServer((HOST, PORT), obj=HelloWorld('world'))
server.start()Client:from puppetry import RemoteClient

client = RemoteClient((HOST, PORT))
print(client.hello())

client.name = 'puppetry'
print(client.hello())See more examples in the example folder.DevelopmentClone repo:git clone https://github.com/axju/puppetry.gitCreate virtual environment and update dev-tools:python3 -m venv venv
source venv/bin/activate
pip install --upgrade wheel pip setuptools twine toxInstall local:pip install -e .Publish the packages:python setup.py sdist bdist_wheel
twine upload dist/*Run some tests:tox
python setup.py test
Package: puppettable
PuppettablePupppettable is a highly-scalable remote-hosted data storage for big datasets of small samples (under 1 MB).
It makes it easy to handle data transparently by using a Python's data structures API interface. It allows to useMicrosoft Azure Table Storageas the backend for the data.How to installIt is available in the official PIP repository:pipinstallpuppettableBasic usageYou need to create a Storage account in Microsoft Azure.Puppettablerequires aconnection_stringto connect to the Azure Table Storage service.>>>frompuppettableimportAzureTableService>>>tables=AzureTableService(connection_string)>>>tablesAzure5Tables:["dataset1","dataset2","dataset3",...,"mnist"]Once the objecttablesis instantiated, it can be used as a dictionary to create or retrieve tables from the service.
The tables are lazy-created as soon as an element is appended. They offer the same behaviour as a Python array:>>>tables>>>table=tables["newDataset"]>>>table.insert("foo")>>>table.insert("bar")>>>table.append_many(["foo2","bar2"])>>>print("The length of the table is:",len(table))Thelengthofthetableis4>>>print("The size of the table (in Bytes) is:",table.size())Thesizeofthetable(inBytes)is:14Every table keeps track of its internal statistics. The length and the size are computed dynamically, and the size is an estimation.>>>table=tables["dataset4"]>>>tableTable:'dataset4';Partition:'default';Length:10565;Size:67.599,49KBManaging data inside a table follows the same API as a Python array:>>>table=tables["newDataset"]>>>table[0]foo>>>table[0:2]['foo','bar']>>>table[-1]bar2>>>table[-2:]['foo2','bar2']>>>table[:]['foo','bar','foo2','bar2']>>>table[::2]['foo','foo2']>>>table[0]="new_foo">>>table[2:4]=["new_foo2","new_bar2"]>>>table[:]['new_foo','bar','new_foo2','new_bar2']Following the Azure distribution concepts, every table might have different partition keys for better distribution of the data. A partition key acts as an isolated group inside a table:>>>tablesAzure5Tables:["dataset1","dataset2","dataset3",...,"mnist"]>>>table=tables["dataset4"]>>>tableTable:'dataset4';Partition:'default';Length:10565;Size:67.599,49KB>>>table.set_partition("test")>>>tableTable:'dataset4';Partition:'test';Length:0;Size:0,0KB>>>table.set_partition()>>>tableTable:'dataset4';Partition:'default';Length:10565;Size:67.599,49KBThe deletion of elements/tables follows the same principle as the dictionaries and arrays in Python. Note though that the length of the table might stay intact as it is computed based on the maximum index detected in the data.
This might lead to incoherent statistics due to having all the previous elements removed but having an element in a high position in the table.
The size and the length can only be recalculated after eliminating the latest elements in the table.Supported typesPuppettable supports natively the following types:Numpy arraysPandas DataFrames / SeriesDictionariesArrays / TuplesStrings / Integers / Floats
Package: pupquiz
Pup Quizpip install pupquiz && py -m pupquizPup Quizfacilitates vocabulary acquisition by employingspaced repetitionprinciples, quizzing words in a systematic order where words in a critical state are quizzed the most often, followed by a bucket of new words and then buckets of words of descending criticality. Seedemo video.At the moment this tool is meant to be used together withBoost Note. Present your word-definition list in a note followingly.word 1
~ definition for word 1
word 2
~ definition for word 2
...You can override this behavior in%APPDATA%\pupquiz\config-user.json(refer to%APPDATA%\pupquiz\config-default.json).
Package: puprelease
PupreleasePublishing a new version of your Python package has never been easier:Installation$ pip install pupreleaseThis will get you theUsageIn the root directory of the package you want to release a new version of
(where yoursetup.pyfile is located):$ pupThen follow along with the program.Git tags for versioningWe recommend using git tags as the single-source-of-truth for package
versions.To do this, add the following lines to yoursetup.py, replacing theversion=...argument of thesetup()call:setup(...setup_requires=["setuptools_scm"],use_scm_version={"version_scheme":"post-release","local_scheme":"dirty-tag",},# Example configuration.# See the docs [*] for other options.)[*]setuptools_scmdocumentation.Then callpup, which will take care of the rest, for each new release.Also, check-outsemantic versioning.
Package: pup-tools
# pup-toolsA collection of Python tools, available via `python3 -m pup.TOOL [...]`or `pup.TOOL`, which provide built using only the Python standard library.## Usage### httpFetch a document over HTTP.```$ pup.http get https://da.gd/uaPython-urllib/3.6$```### xpathRun XPath queries on a document provided via stdin, and print theresults.```$ pup.http get 'http://rss.accuweather.com/rss/liveweather_rss.asp?locCode=02451' | pup.xpath ./channel/title ./channel/item/titleWaltham, MA - AccuWeather.com ForecastCurrently: Intermittent Clouds: 93F$```## ContributingBug reports and pull requests are welcome on GitHub at https://github.com/duckinator/pup-tools. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the [Contributor Covenant](http://contributor-covenant.org) code of conduct.## LicenseThe program is available as open source under the terms of the [MIT License](http://opensource.org/licenses/MIT).## Code of ConductEveryone interacting in the pup-tools project’s codebases, issue trackers, chat rooms and mailing lists is expected to follow the [code of conduct](https://github.com/duckinator/pup-tools/blob/master/CODE_OF_CONDUCT.md).
Package: pupu-sqlalchemy-clickhouse
ClickHouse dialect for SQLAlchemy.InstallationThe package is installable through PIP:pip install sqlalchemy-clickhouseUsageThe DSN format is similar to that of regular Postgres:>>> import sqlalchemy as sa
>>> sa.create_engine('clickhouse://username:password@hostname:port/database')
Engine('clickhouse://username:password@hostname:port/database')For SSL add ssl parameter to URL:>>> import sqlalchemy as sa
>>> sa.create_engine('clickhouse://username:password@hostname:port/database?ssl=True')
Engine('clickhouse://username:password@hostname:port/database')It implements a dialect, so there’s no user-facing API.TestingThe dialect can be registered on runtime if you don’t want to install it as:from sqlalchemy.dialects import registry
registry.register("clickhouse", "base", "dialect")
Package: puput
Puput is a powerful and simple Django app to manage a blog. It uses the awesomeWagtail CMSas content management system.Puput is the catalan name forHoopoewhich is indeed a beautiful bird.Visit thedocumentationfor an in-depth look at Puput.FeaturesBuilt with Wagtail CMS and DjangoInspired in Wordpress and ZinniaSimple & responsive HTML template by defaultSEO friendly urlsSupport for Disqus commentsEntries by author, tags, categories, archives and search termLast & popular entriesConfigurable sidebar widgetsRSS feedsRelated entriesExtensible entry modelConfigurable default template colorSocial share of blog entries (Facebook, Twitter and LinkedIn)Markdown fields (https://github.com/torchbox/wagtail-markdown)Examples of blog sites made with PuputOpen Study RoomAPSLNautic AdvisorTrespamsBody TherapyAstroIP/DESetupThe setup process is explainedhere.Related repositorieswordpress-to-puput: Import your Wordpress blog data into Puput.blogger-to-puput: Import your Blogger blog data into Puput.zinnia-to-puput:  Import your Zinnia blog data into Puput.docker-puput:  Docker image for Puput blog.puput-demo: An example of blog Django app using Puput.divio-wagtail-puput: A Divio Cloud addon to install the Wagtail Puput weblog.
Package: pupy
PUPY ~ Pretty Useful PythonThis package (pupy) is full of Pretty Useful Python.These thingsInstallin'Installing is EZPZ...pip install pupyWant more???Pupy has a few optional dependenies for reading and writing files which can be installed with the following command:pip install pupy[io]Or you can pick and choose...If you plan on using Jason you can installujsonpip install ujsonorrapidjsonfor a speed boostpip install python-rapidjsonand if pupy can't find either it'll fall back on the python-stdlib json thing.But wait theres more! Pupy has several optional dependencies for savings and loads which you can install with...pip install ruamel.yaml  # If ya mel in your spare time
pip install msgpack  # If you wanna pack messages
pip install toml  # toml (aka 'that other markup language'(?))
pip install aiofiles  # if you wanna do async stuffTestimonials'Ahead of the curve.' -Haley who goes to Harvard'huh?' -Tim Apple'If I were stranded on a dessert island and had to pick between having a copy pupy or a thing of water I would pick the water, but if I didn't have to pick it wouldn't hurt to have.' -Ryan of the fro with his fro'I don't use python.' -KirstenKirsten Chief Evernote Officer'I can't say google wouldn't not go down if it weren't for pupy.' -Ben W from the g-suite'A literary masterpiece on par with my second greatest work finite jest.' -Bananas Foster Wallace'Best place for python savings and loads in the tri-content area.' -Genghis Khan
Package: pupyl
pupyl - A Python Image Search LibraryTable of contents🧿 pupyl what?🎉 Getting started📦 Installation🚸 Usage🐚 Command line interface📌 Dependencies📝 Documentation🖊️ Citation🧿 pupyl what?Thepupylproject (pronouncedpyoo·piel) is a pythonic library to perform image search tasks (even over animated GIFs). It's intended to make easy reading, indexing, retrieving and maintaining a complete reverse image search engine. You can use it in your own data pipelines, web projects and wherever you find fit!🎉 Getting started📦 InstallationInstallingpupylon your environment is pretty easy:# pypipipinstallpupylor# anacondacondainstall-cpolicratuspupylFor installation troubleshooting, visittroubleshooting.🚸 UsageYou can callpupyl's objects directly from your application code. For this example, a sample database will be indexed and after that, the following image will be used as a query image (credits:@dlanor_s):pupylalso supports usinganimated gifsas query images and can store and retrieve it too.frompupyl.searchimportPupylImageSearchfrompupyl.webimportinterfaceSEARCH=PupylImageSearch()SEARCH.index('https://github.com/policratus/pupyl''/raw/main/samples/images.tar.xz')# Using, for instance, a remote image. Local images have pretty faster results.QUERY_IMAGE='https://images.unsplash.com/photo-1520763185298-1b434c919102?w=224&q=70'[*SEARCH.search(QUERY_IMAGE)]Disclaimer: the example above createspupylassets on your temporary directory. To define a non-volatile database, you should definedata_dirparameter.This will return:# Here's the simplest possible result>[486,12,203,176]With more information and returning image metadata from the results:# The results with image metadata[*SEARCH.search(QUERY_IMAGE,return_metadata=True)]Now an excerpt of the (possible) return is:[{"id":486,"internal_path":"/tmp/pupyl/0/486.gif","original_access_time":"2021-12-03T13:23:47","original_file_name":"icegif-5690.gif","original_file_size":"261K","original_path":"/tmp/tmp3gdxlwr6"},{"id":12,"internal_path":"/tmp/pupyl/0/12.gif","original_access_time":"2021-12-03T13:23:46","original_file_name":"roses.gif","original_file_size":"1597K","original_path":"/tmp/tmp3gdxlwr6"},...]To interact visually, use the web interface:# Opening the web interfaceinterface.serve()A glimpse of the web interface, visualizing the results shown above:Alternatively, you can interact withpupylvia command line. The same example above in CLI
terms:🐚 Command line interface# Indexing imagespupyl--data_dir/path/to/your/data/dirindex/path/to/images/# Opening web interfacepupyl--data_dir/path/to/your/data/dirserve# Searching using command line interfacepupyl--data_dir/path/to/your/data/dirsearch/path/to/query/image.ext💡 Typepupyl --helpto discover all the CLI's capabilities.📌 DependenciesSee all dependencies here:dependencies.📝 DocumentationSee a getting started guide and the API reference onhttps://pupyl.readthedocs.io/.🖊️ CitationIf you usepupylin your publications or projects, please cite:@misc{pupyl,author={Nelson Forte de Souza Junior},title={pupyl - A Python Image Search Library},howpublished={\url{https://github.com/policratus/pupyl}},year={2021}}
Package: pupynere
Pupynere is a Python module for reading and writing NetCDF files,
using the same API as Scientific.IO.NetCDF and pynetcdf. It depends only
on Numpy, so you don’t need to have the NetCDF library installed.Changelog:1.0.15Added fix for empty attributes.1.0.14Added support for Unicode attributes.1.0.13Fixed bug when reading character variables without mmap.1.0.12Fixed bug.1.0.11Fixed bug.1.0.10Fixed bug when packing integer attributes in 64-bit systems.1.0.9Should work with Python 2.3.
Accepts file objects instead of only filenames.1.0.8Allow writing version 2 files (Large Files).1.0.7Removed reads from asserts to allow PYTHONOPTIMIZE.1.0.6Allows zero-length record variables.1.0.5Added the option to open files without using mmap, since mmap can’t
handle huge files on Windows.1.0.4Fixed packing of dimensions when writing a file. The order was being
read from a dictionary (essentially unordered), instead of from the list
with the proper order.1.0.3Fixed bug so that it can write scalar variables.1.0.2Fixed broken 1.0.1,var.shapewas returning the current number
of records in the first dimension, breaking the detection of record
variables.1.0.1Changed the code to read the variable shape from the underlying
data object.1.0.0Initial stable release. Handles record arrays properly (using a single
mmap for all record variables) and writes files.
Package: puq
Version:2.6Authors:Martin HuntWeb site:https://github.com/c-PRIMED/puqDocumentation:http://c-primed.github.io/puq/Copyright:This document has been placed in the public domain.License:MIT License.PurposePUQ is a framework for building response surfaces and performing Uncertainty
Quantification (UQ) and sensitivity analysis. It was created with the goal of
making an easy to use framework that could be easily integrated and extended.FeaturesImplemented as a Python library but can be used from the command line
with a minimum of Python knowledge.Collects all results into a single HDF5 file.Implements Monte Carlo and Latin Hypercube sampling.For better scalability, includes a Smolyak sparse grid method.Builds response surfaces from sample points.Includes GUIs to visualize and compare PDFs and response surfaces.Can use PyMC to perform Bayesian calibration on input parameters.DependenciesPUQ is tested to work under Python 2.7+.PUQ requires the following Python modules:numpy >= 1.6scipy >= 0.8matplotlib >= 1.1sympy >= 0.7.1h5py >= 1.3jsonpickleposterpytestpymcInstallThis package uses distutils, which is the default way of installing
python modules. To install in your home directory, use:python setup.py install --userTo install for all users on Unix/Linux or Mac:python setup.py build
sudo python setup.py installHistoryPUQ is based upon work supported by the Department of Energy [National Nuclear Security Administration]
under Award Number DE-FC52-08NA28617.
Package: purdue-af-grafana-iframe
purdue_af_grafana_iframeAdds a button to the launcher, which opens an iframe with a Grafana panel.Compatible withjupyterlab-theme-toggle extension.The extension is configured in~/.jupyter/lab/user-settings/purdue-af-grafana-iframe/plugin.jupyterlab-settings. Here is an example ofplugin.jupyterlab-settingscontents:{# url of a Grafana panel; to find the correct url,# click top-right of Grafana panel, then Share -> Embed"url":"https://<url>","label":"Monitoring","caption":"Open grafana dashboard","rank":0}RequirementsJupyterLab >= 4.0.0jupyterlab_iframe == 0.5.0InstallTo install the extension, execute:pipinstallpurdue_af_grafana_iframeUninstallTo remove the extension, execute:pipuninstallpurdue_af_grafana_iframeContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the purdue_af_grafana_iframe directory# Install package in development modepipinstall-e"."# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseDevelopment uninstallpipuninstallpurdue_af_grafana_iframeIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink namedpurdue-af-grafana-iframewithin that folder.Packaging the extensionSeeRELEASE
Package: purdue-af-shutdown-button
purdue_af_shutdown_buttonAdds a shutdown button to JupyterLab top-bar.To enable the button, the file.jupyter/lab/user-settings/@jupyterlab/application-extension/top-bar.jupyterlab-settingsshould contain the following:{"toolbar":[{"name":"shutdown","command":"jupyterlab-topbar:shutdown","disabled":false,"rank":100}]}RequirementsJupyterLab >= 4.0.0InstallTo install the extension, execute:pipinstallpurdue_af_shutdown_buttonUninstallTo remove the extension, execute:pipuninstallpurdue_af_shutdown_buttonContributingDevelopment installNote: You will need NodeJS to build the extension package.Thejlpmcommand is JupyterLab's pinned version ofyarnthat is installed with JupyterLab. You may useyarnornpmin lieu ofjlpmbelow.# Clone the repo to your local environment# Change directory to the purdue_af_shutdown_button directory# Install package in development modepipinstall-e"."# Link your development version of the extension with JupyterLabjupyterlabextensiondevelop.--overwrite# Rebuild extension Typescript source after making changesjlpmbuildYou can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.# Watch the source directory in one terminal, automatically rebuilding when neededjlpmwatch# Run JupyterLab in another terminaljupyterlabWith the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).By default, thejlpm buildcommand generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:jupyterlabbuild--minimize=FalseDevelopment uninstallpipuninstallpurdue_af_shutdown_buttonIn development mode, you will also need to remove the symlink created byjupyter labextension developcommand. To find its location, you can runjupyter labextension listto figure out where thelabextensionsfolder is located. Then you can remove the symlink namedpurdue-af-shutdown-buttonwithin that folder.Packaging the extensionSeeRELEASE
Package: purdy
During talks or screencasts I don’t want to be typing code, it is too error
prone and too likely to mess up my speaking flow.Purdyis both a set of
programs and a library to display colourized code in a series of animations.Thepurdycommand takes one of a Python program, a Python REPL console file
or a Bash console file. Source code is presented to the screen as if typing.
For console files, the typing pauses at a prompt, waiting for interaction.
Prompts are:>>>or...for Python REPL$for Bash consoleIf the program is paused at a prompt, pressing therightarrow will
continue. Typing animation can be skipped over by pressing the letter “s”
instead. Animation can be undone by pressing theleftarrow. More info on
keys can be found in the help dialog, viewed by pressing “?”.Example Usage:$purdycode-snippet.pyThe result looks like this:Once the code has been displayed, further key presses are ignored. At any time
you can press “q” to quit.Purdy ProgramsThe following programs come with thepurdylibrary:purdy– Animated display that looks like a program is being typed to the
screen.pat– “purdy cat”, prints ANSI colourized source.prat– “purdy RTF cat”, prints colourized source in RTF document format.
Particularly useful for copying to a clipboard and pasting full colourized
source into a document. On OS Xprat <filename> | pbcopywill put the
output directly to the clipboard.subpurdy– Full set of commands to control Purdy. Sub-commands dictate
behaviour. Does a variety of code presentation. Includes ANSI, RTF, HTML
output as well as the typewriter animations.More information can be found in the Command Line Program Documentation.Purdy TUI ControlsThe following keys help you to control the TUI purdy programs:?– Help screen<RIGHT>– next animation step<LEFT>– previous animation steps– go to the next step, skipping any animationFor custom made code using the purdy library, the following controls will also
work:S– go to the next section, skipping any animation.<TAB>– focus next window area in a multi Screen display<SHIFT><TAB>– focus previous window area in a multi Screen displayAdditionally thes,S, and<LEFT>commands all support skipping
multiple steps by specifying a number first. For example the sequence12swould skip past the next 12 steps.Purdy LibraryThepurdyscript is fairly simple. You can create more complex animations
by writing programs using the purdy library. Custom programs can have split
screens, highlighting lines, slide transitions and more.  More information can
be found in the Library Documentation.Installation$pipinstallpurdySupportsPurdy has been tested with Python 3.7 through 3.11. Terminal control is done
with theUrwidlibrary. Parsing and tokenization is
done throughPygments. Both libraries are
execellent and I’m grateful they’re publically available.Docs & SourceDocs:http://purdy.readthedocs.io/en/latest/Source:https://github.com/cltrudeau/purdy