Saravanan666/pypi-org huggingface dataset:
Package: pity
Pity: Peercoin made easyForked from Ofek's awesomeBit library.Pity is based on Bit, thePython's fastestBitcoin library and was designed from the beginning to feel intuitive, be
effortless to use, and have readable source code.Pity is so easy to use, in fact, you can do this:>>> from bit import Key
    >>>
    >>> my_key = Key(wif="...")
    >>> my_key.get_balance('eur')
    '12.51'
    >>> # Let's pity the fool! Umm,... Let's donate!
    >>> outputs = [
    >>>     # the Peercoin Foundation
    >>>     ('p92W3t7YkKfQEPDb7cG9jQ6iMh7cpKLvwK', 10, 'usd'),
    >>>     # Beer for willy, PeerExplorer <https://peercoinexplorer.net/charts/>
    >>>     ('PA3VZmupxdsX5TuS1PyXZPsbbhZGT2htPz', 3, 'eur')
    >>> ]
    >>>
    >>> my_key.send(outputs)
    '1da615c003bb1bd98354378fa5e95287993dab152d876fa0cc3980566ce6d7ee'FeaturesPython's fastest available implementation (100x faster than closest library)Seamless integration with existing server setupsSupports keys in cold storageFully supports 25 different currenciesFirst class support for storing data in the blockchainDeterministic signatures via RFC 6979Access to the blockchain (and testnet chain) through multiple APIs for redundancyExchange rate API, with optional cachingOptimal transaction fee API, with optional cachingCompressed public keys by defaultMultiple representations of private keys; WIF, PEM, DER, etc.Legacy P2PKH and Segwit nested-P2WPKH transactionsLegacy P2SH and Segwit nested-P2WSH transactionsIf you are intrigued, continue reading. If not, continue all the same!InstallationBit is distributed onPyPIas a universal wheel and is available on Linux/macOS
and Windows and supports Python 3.5+ and PyPy3.5-v5.7.1+.pip>= 8.1.2 is required.$ pip install pityDocumentationDocs arehosted by Github Pagesand are automatically built and published
by Travis after every successful commit to Bit'smasterbranch.Creditsofekfor the original bit codebase.backpackerfor help with the porting.Additional
Package: pitybugmaker
一、安装（python版本建议3.7以上）pipinstalldubborequests二、升级包pipinstall--upgradedubborequests三、示例获取dubbo服务详情# 导入importdubborequests# 获取dubbo服务详情data=dubborequests.search('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')获取服务下的所有方法# 导入importdubborequests# 获取dubbo服务下的所有方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService')# 获取dubbo服务指定的方法data=dubborequests.list('cn.com.xxx.sso.ehr.api.dubbo.SsoEmpInfoService','login')通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口importdubborequestsfromdubborequestsimportConfig# 先配置zookeeper中心地址Config.zookeeper_url_list=['192.168.240.15:2181','192.168.240.15:2182','192.168.240.15:2183']invoke_data={"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# 通过zookeeper获取服务的ip和端口, Telnet命令测试dubbo接口data=dubborequests.zk_invoke(*invoke_data)Telnet命令测试dubbo接口importdubborequestsinvoke_data={"ip":'xxxx',"port":7777,"service_name":"cn.com.xxxxx.sso.ehr.api.dubbo.SsoEmpInfoService","method_name":"login","data":{"account":"xxxx","password":"xxxx"}}# Telnet命令测试dubbo接口data=dubborequests.telnet_invoke(*invoke_data)
Package: pity-of-thieves
This is a technical demonstration ofBalladeer. I first wrote it for theIcehouse game jamin 2021.Balladeer helps you build parser-based Interactive Fiction for the Web.
Balladeer is a Python library.InstallationWindowsLinuxWindowsPity of Thievesis a command line program.
You use it from the Windows command interpreter.To launch a new command window:Tap the Windows key so that the Start Menu pops up.Type the wordcmd.When you see theCommand Promptapp highlighted, tap the Enter key.You should see a prompt like this (your user name will differ):Microsoft Windows [Version 10.0.18362.1139]
(c) 2019 Microsoft Corporation. All rights reserved.

C:\Users\author>PrerequisitesDownload and install Python fromhttps://www.python.org/. You need Python version 3.8 or higher.
Make sure to check the option to addpythonto your environment path.
This makes command line operation more easy.After you’ve installed Python, open a command window and typepython.
You should see something like this:C:\Users\author>python
Python 3.8.2 (tags/v3.8.2:7b3ab59, Feb 25 2020, 22:45:29) [MSC v.1916 32 bit (Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>>Typequit()and press Return.Virtual EnvironmentFirst make a fresh Python virtual environment:python -m venv C:\Users\author\balladeer-appUpdate the package manager within it:C:\Users\author\balladeer-app\Scripts\pip install -U pip wheelInstall dependencies:C:\Users\author\balladeer-app\Scripts\pip install aiohttpInstall (or update) Balladeer:C:\Users\author\balladeer-app\Scripts\pip install -U balladeerDownloadDownload therepository as a zip file.
Unzip it to a local directory.cdtopity_of_thieves.RunYou can run the demo in two modes.Launch a local web server to play in a browser (http://localhost:8080):C:\Users\author\balladeer-app\Scripts\python -m pot.serverOr text-only in the terminal:C:\Users\author\balladeer-app\Scripts\python -m pot.storyLinuxThe Linux command line is generally more easy to work with than the Windows command prompt.
If you’re finding the Windows command prompt tricky, you can installGit Bashwhich behaves in a
Linux-like way.I encourage you to move to a Linux operating system when you are able.
You can try one out at little cost on aRaspberry Pior similar device.Here are the install instructions for Linux. You need Python version 3.8 or higher.Virtual EnvironmentFirst make a fresh Python virtual environment:python3 -m venv ~/balladeer-appUpdate the package manager within it:~/balladeer-app/bin/pip install -U pip wheelInstall dependencies:~/balladeer-app/bin/pip install aiohttpInstall (or update) Balladeer:~/balladeer-app/bin/pip install -U balladeerDownloadDownload therepository as a zip file.
Unzip it to a local directory.cdtopity_of_thieves.RunYou can run the demo in two modes.Launch a local web server to play the web app (http://localhost:8080):~/balladeer-app/bin/python -m pot.serverOr text-only in the terminal:~/balladeer-app/bin/python -m pot.storyThe freedom to copyYou are free to use this project as a teaching example, or as the basis of your own work.
Please read the licence and make sure youunderstand the Affero GPL.
Package: piudb
Unlike a database, this one doesn’t store records, but store objects directly .
Home-page:https://github.com/Peiiii/piudbAuthor: Wang Pei
Author-email:1535376447@qq.comLicense: UNKNOWN
Description: UNKNOWN
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Package: piuma
Piuma is an no-headache ultra-lightweight local document database written
purely in python. Piuma is designed without just theabsoulute bareessentials in mind. In the core version of Piuma there is no query language or
any advanced search/modify functions. In its current version Piuma only stores
data in memory, I plan to add local storage subpackage hopefully in the near
future. This database should not be taken too seriously and should really only
be used for small projects and testing.Quick LinksGithub:https://github.com/emit07/piumaDocumentation:https://piuma.readthedocs.io/Why youshoulduse Piuma?Light and Small:Piuma’s core is written with one very small file and canbe sub millisecond fast because of its memory storageEasy to Use:Piuma runs out of the box and is easy to use and learn.Piuma also requires no dependencies or external servers.Experimenting:If you are trying something new and you need a fastdatabase that just works while testing then Piuma is a good choice.No Dependencies:Piuma is written with no external dependecies.Why youshould notuse Piuma?Big Database:Piuma was not designed to be used as a big database; Piumaonly runsonlyin memory (for now) so the limit of how big it could be
comes much quicker than other databaseACID Guarantees:Because of Piumas small nature it does not have room forACIDGuaranteesQuery Language:Piuma does not have a query language (though I currentlyworking on a query submodule)Storage:While Piuma supports interchangeable storage, it only has memorystorage built inWhy is it called Piuma?Piuma is the Italian word for feather and (from what I feel) the word feather
can convay lightness.
Package: piupdue
piupduePython package that enables a compiled Ardunio Sketch to be uploaded to
an Arduino Due from a RaspberryPI (connected by USB).Based on theArduino BOSSA C++ source
code.Install using: $ pip install pyupdueSketch file must be saved locally on PI and be of type “.cpp.bin”.Run from cmd lineusage: piupdue.py [-h] -f SKETCHFILE [-p PORT] [-l LOGFILE]optional arguments: -h, –help show this help message and exit -f
SKETCHFILE, –file SKETCHFILE Sketch file to upload. Including path.
(/path/File.cpp.bin) -p PORT, –port PORT Port Due is connected on.
Leave blank for auto selection. -l LOGFILE, –log LOGFILE Save output to
log file. # Use in Python ProgramUse the Upload function found in piupdue.py, Ex:import piupduepiupdue.Upload(‘/usr/update/FastSketch.cpp.bin’, ‘/dev/ttyACM1’,
‘/var/log/piupdue.log’)Some backgroundThe Arduino Due is a microcontroller board based on the Atmel SAM3X8E
ARM Cortex-M3 CPU. It is the first Arduino board based on a 32-bit ARM
core microcontroller instead of the more common AVR. The different mcu
means the performance is better but also means the booting process is
different from the AVR, Ardunio has designed the board such that
flashing firmware is easier than what the stock SAM3X has offered,this
linkexplains the booting process and the tricks that Arduiro implemented.The “avrdude” program is used to upload code to the AVR based Arduinos
and there are quite a few examples of how to do this from the
RaspberryPI. BOSSAC is used by Arduino to upload code to the ARM, it’s
the command line variation ofBOSSAwhich is a
simple and open source flash programming utility for Atmel’s SAM family
of flash-based ARM microcontrollers designed to replace Atmel’s SAM-BA
software.I required the ability to upload new code from a RaspberryPI to a Due. I
couldn’t find any info on getting BOSSAC to run on the PI so I have
written this package in Python to replicate the fucntionality.
Package: piva
PIVA - Python Interactive Viewer for ArpesPIVA is a GUI-application for data visualisation from Angle-Resolved
Photoemission Spectroscopy (ARPES) experiments.PIVA is intended to support ARPES experimenters by providing a python tool
for fast inspection of acquired data.
It has been developed by beamline scientists for that exact purpose and
contains functionality for preliminary analysis that is often required during
an ARPES experiement.Please refer to thedocumentationfor more.
Package: pive
![pive Logo](/artwork/pive_logo_optimized_100x100.png)Python Interactive Visualization Environment=====python-ive[ˈpaiθən-ˈaivi](alternative titles: *p-ive* or preferably **pive**)current version: 0.3.3What is pive?Pive is a template based visualization tool utilizing D3.js to create interactive visualizations on the fly. It is aimedat users who want to enhance their web applications with dynamic D3.js visualizations without diving deep into thecoding of D3.js.Install pive:Clone this repository:```git clone https://github.com/daboth/pive.git```and install manually:```python setup.py install```or install with pip:```pip install pive```You may need to add ```sudo``` before executing each command.Now write a simple script to render a chart:```python#!/usr/bin/env pythonimport pive.environment as environmentimport pive.inputmanager as inputmanager# Assuming you have a testdata.json file with some datapoints# in the same directory. Try to create JSON-Objekts as Key/Value# pairs or use a JSON formatted String Object. CSV is also# supported.input_path = 'samples/numerical.json'############################## Basic usage of pive ############################### 1)Set up the environment by creating the input manager and# passing it to an environment. Optionally, you can omit# an output path. Default is 'output/'.manager = inputmanager.InputManager(mergedata=False)env = environment.Environment(inputmanager=manager)# 2) Load your dataset into the environment to get a# list of supported visualizations.supported = env.load(input_path)# 3) Check if your desired chart is in the list and choose# it as your visualization object. Alternatively you can# print out the list of the supported charts and choose directly# from it. The accessors, e.g. CHART_LINE, are environment# constants and represent the charts included in pive.if environment.CHART_LINE in supported:chart = env.choose(CHART_LINE)#You can now edit the charts properties.chart.set_width(900)chart.set_height(500)# 4.1) Let the environment render the chart.# The visualizuation files will be generated# in the output path defined in the environment.env.render(chart)# 4.2) Optionally you can receive the# javascript code and its dataset as json.code = env.render_code(chart)```
Package: pivimage
PivimageNote, that the project is still under development!PIVimageis a small library assisting with reading PIV images. It provides specific utilities to handle PIV images and
to perform certain operations on them, which are useful in the pre-processing stage of PIV analysis.Available operations are ...rotating imagesinterfacing with double frame images in one or two filesplottingMore features will be added in the future.InstallationpipinstallpivimageExamplesTestsTests can be found in the foldertests/. They can be run withpytest:pytestGet a coverage report withpytest--cov--cov-reporthtml
Package: pivotalclient
pivotalclientA lightweight Pivotal Tracker REST API client written in Python.LICENSEMIT LicenseCopyright (c) 2016 CloudBolt SoftwarePermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: pivotal-django-zendesk
Django Zendeskdjango_zendesk provides single-sign on functionality between a
django.contrib.auth based site and Zendesk. Other authentication
systems are compatible as long as they implement the@login_requireddecorator.   This differs from the other
implementations in that it exposes out company, external_id, tags, etc.Note:This fork provides for changes specifically for Pivotal Energy SolutionsSETUPdjango_zendesk needs two settings.py variables to be implemented:ZENDESK_URL: The URL of your support page, will either be on
zendesk.com or your own domain (via a CNAME record)ZENDESK_TOKEN: The authentication token token you receive from
Zendesk when setting up remote authenticationThe only other code setup required is pointing a URL at thedjango_zendesk.views.authorizemethod, it will look something like:(r'zendesk/$', 'django_zendesk.views.authorize')Zendesk itself needs a bit of setup, including the URL we just set up
above and a log-out URL which already should be implemented somewhere
in your site.Zendesk's documentation for remote authentication ishere:If you're running the tests, make sure to set theTEST_DATABASE_CHARSETsetting so that test databases are created to be utf8 compatible.CREDIT:Initial idea byJon Galeswith improvements
byAlexander Ljungberg.See initial idea/blog post [here][intial_idea] andhereBuild Process:Update the__version_info__inside of the application. Commit and push.Tag the release with the version.git tag <version> -m "Release"; git push --tagsBuild the releaserm -rf dist build *egg-info; python setup.py sdist bdist_wheelUpload the datatwine upload dist/*
Package: pivotaltracker
OverviewThis module provides a simple Pythonic interface to the PivotalTracker API.
It also provides both a simple commandline interface to Pivotal.QuickstartThis is the primary API for using Pivotal.  First, you need an API token from Pivotal.
You can generate one in your profile settings: <https://www.pivotaltracker.com/profile>.Next, you simply create a client:import pivotaltracker
client = pivotaltracker.Client(token="YOUR API TOKEN")Now you can execute any of the API methods on that client.  All method calls will return Python dictionaries.
You can find detailed documentation in the docstrings for now, until I get the API docs created.
Here’s a quick rundown in the meantime:get_project(project_id)get_all_projects()get_story(project_id, story_id)get_stories(project_id, query=None, limit=None, offset=None)get_iterations(project_id, limit=None, offset=None)get_done_iterations(project_id, limit=None, offset=None)get_current_iterations(project_id, limit=None, offset=None)get_backlog_iterations(project_id, limit=None, offset=None)add_story(project_id, name, description, story_type, requested_by=None, estimate=None, current_state=None, labels=None)update_story(project_id, story_id, name=None, description=None, requested_by=None, story_type=None, estimate=None, current_state=None, labels=None)delete_story(project_id, story_id)add_comment(project_id, story_id, text, author=None)deliver_all_finished_stories(project_id)Source CodeYou can contribute to the source code on GitHub: <http://github.com/mjpizz/pivotaltracker>Release Notes0.0.3added feature submission to the tool0.0.2added bug submission to the tool0.0.1original Client API object, very basic commandline tool (only submits chores)AdvancedCommandline ToolSimply runpt helpon the commandline to see options.  The first time you run the tool,
it will walk you through creating your API key and setting up your configuration.More documentation to come, later.
Package: pivot-based-NMT
Title         : Teacher-Student FrameWork for Zero-Shot Machine Translation
Author        : xxlucas
Logo          : True[TITLE]IntroductionTS-FrameWork is machine translation framework which is based on OpenNMT-py.The main idea about how to implement is coming fromA Teacher-Student Framework for
Zero-Resource Neural Machine TranslationHere is the paper :[arXiv:1705.00753]And if you don’t know what zero-shot mean, please do a Google search and you will find the answer.UsageIf you want to translate some resource-poor languages into the target language, usually such a parallel corpus is difficult to build.So there is a commonly used method called pivot-based method to solve this situation.
It means that if the source-to-target parallel corpus are not available but we can find the source-to-pivot language pairs and the pivot-to-target language pairs,and build a NMT model to solve the problem.
In this way, our problem becomes very easy to solve: train two NMT models for the source-pivot and the pivot-target language pairs, respectively.
Both of them also bring two new problems.The result is that the training time is too long,and error propagation that is,the training error from the former model will be the input of the latter one.Therefore,if we train a model once that all the issue will be vanished.Assume that the source-to-pivot and pivot-to-target languages are all available.**Step 0. preprocess the raw data **mkdirdatacddatamkdirteachermkdirstudentpython../preprocess.py--train_srcpath_to_pivot--train_tgtpath_to_target\--save_datadata/teacherpython../preprocess.py--train_srcpath_to_source--train_tgtpath_to_pivot\--save_datadata/student**Step 1. train teacher model on pivot-to-target **#theGNMTstyleteachermodelpythontrain.py-datadata/teacher-save_model./model\-layers8-rnn_size1024-rnn_typeGRU\-encoder_typebrnn-decoder_typernn\-train_steps200000-max_generator_batches2-dropout0.1\-batch_size128-batch_typesents-normalizationsents-accum_count2\-optimadam-adam_beta20.998-decay_methodnoam-warmup_steps8000-learning_rate1e-3\-max_grad_norm5-param_init0-param_init_glorot\-valid_steps10000-save_checkpoint_steps10000\-world_size1-gpu_ranks0**Step 2. train student model on source-to-pivot **#thetransformerstudentmodelpythontrain.py-datadata/student/-save_modelstudent\-layers6-rnn_size512-word_vec_size512-transformer_ff2048-heads8\-encoder_typetransformer-decoder_typetransformer-position_encoding\-train_steps100000-max_generator_batches2-dropout0.1\-batch_size4096-batch_typetokens-normalizationtokens-accum_count2\-optimadam-adam_beta20.998-decay_methodnoam-warmup_steps8000-learning_rate2\-label_smoothing0.1-save_checkpoint_steps10000\-world_size1-gpu_ranks0--teacher_model_pathmodel_step_200000.ptYou can evaluate the model with OpenNMT-py's api.
Package: pivottablejs
Drag’n’drop Pivot Tables and Charts forJupyter/IPython Notebook,
care ofPivotTable.jsInstallationpip install pivottablejsUsageimportpandasaspddf=pd.read_csv("some_input.csv")frompivottablejsimportpivot_uipivot_ui(df)Advanced UsageInclude anyoption to PivotTable.js’s pivotUI() functionas a keyword argument.pivot_ui(df,rows=['row_name'],cols=['col_name'])Independently control the output file path and the URL used to access it from Jupyter, in case the default relative-URL behaviour is incompatible with Jupyter’s settings.pivot_ui(df,outfile_path="/x/y.html",url="http://localhost/a/b/x.html")
Package: pivpnpy
DescriptionA thin python wrapper for pivpnInstallation###From pypipip3installpivpnpy###From this git repo:# Ensure you have setuptools >= 21.3python3-mpipinstall--upgradepip

gitclonehttps://github.com/m00ninite/pivpnpy.gitcdpivpnpy
python3-mpipinstall-e.Usagefrompivpnpyimportpivpn# Create a userpivpn.create_profile(user="Hello_World",ttl=1080)# List usersprofiles=pivpn.list_profiles()print(profiles[0]['status'])# Prints "Valid"# Delete a userpivpn.delete_profile(user="Hello_World")
Package: pivpy
PIVPyPython based post-processing PIV data analysisMerging the three packages:https://github.com/tomerast/Vecpyhttps://github.com/alexlib/pivpy/tree/xarrayhttps://github.com/ronshnapp/vecpyHow do I get set up?Usepip:pip install pivpyWhat packages are required and which are optionallvreaderby Lavision if you use vc7 filesnetcdf4if you want to store NetCDF4 files by xarraypyarrowif you want to store parquet filesnumpy,scipy,matplotlib,xarrayare must and installed with thepivpyHow to get started?Look into thegetting started Jupyter notebookand additional notebooks:NotebooksHow to test?From a command line just use:pip install pytest
pytestDocumentation on Github:PIVPy on ReadTheDocsHow to help?Read the ToDo file and pick one item to program. Use Fork-Develop-Pull Request model to
contributeHow to write tutorials and add those to the documentationUsing great tutorialhttp://sphinx-ipynb.readthedocs.org/en/latest/howto.htmlwe now can
prepare IPython notebooks (see in /docs/source) and convert those to .rst files, thenpython setup.py sphinx-build
sphinx-build -b html docs/source/ docs/build/htmlgeneratesdocs/build/htmldirectory with the documentation
Package: pivtestdata
PIV Test DataThis repository provides test data which is freely available on the internet, so all credit goes to the original
authors!!! Available datasets can be found under these links:PIV Challenge 2001ILA Vortex PAIRILA Boundary Layer PAIRIntended use of this package is to have a convenient interface to PIV sample data to test PIV algorithms.Note, that the data is not stored in this repo but it assists in downloading it from the respective websites on demand.
Once downloaded, the repo helps you to retrieve the file names quickly from a local user folder.InstallationYou can install this package via:pipinstallpivtestdataor the latest dev version directly from the git repo:pipinstallgit+https://github.com/matthiasprobst/piv-test-data.git@mainUsageMinimal example (for more see thenotebook):ToDoThere is more potential sample data here to be added in the future:Japanese standard images