Saravanan666/pypi-org huggingface dataset:
Package: py-battleship
This is a simple, but super cool Battleship game. Lets Play!!!Installation$pipinstallpy-battleshipOr, you can download the source and$gitclonegit@github.com:rhenter/battleship-python.git$cdbattleship-python$pythonsetup.pyinstallAdd sudo in the beginning if you met problem.How to UseTo play use py-battleship or python -m battlefieldDocumentationIn progressContributingPlease send pull requests, very much appreciated.Fork therepositoryon GitHub.Make a branch off of master and commit your changes to it.Install requirements.pip install-rrequirements-dev.txtInstall pre-commit.pre-commitinstallCreate a Pull Request with your contributionChangelog1.3.2Update Game Image1.3.1Bugfix: Add click lib as pinned1.3.0Improve UI,BugFix: Robbot choiceCreate Brainiac Class1.2.1BugFix: Final and current shot Statistics1.2.0BugFix: Adding ship using same coordinatesBugFix: Robbot using repeated coordinates1.1.3Add raw image to be seen on Pypi1.1.2Change ci to cicleCIUpdate Pypi1.1.1Remove debug and change travis config1.1.0Add testsAdd codecov and travis integrationUpdate ReadmeRemove blink from messages1.0.0Change game play to be MultiplayerChange game to finish when CPU or Player1 wins or use CTRL+CRefactor language to be centralCreate Custom exceptionsUse Python Click to print the board using colorsUse Python Click to improve the main function0.3.13BugFix: Exit game with CTRL+CMove exception treatment to battlefield.pyCreate more exceptionsCreate a centralized language translator0.3.12Improve UI to print statistics0.3.11Update Readme0.3.10Fix table layout0.3.9Refactor Main: Remove unnecessary codeRemove duplicated codeAdd translation0.3.8Fix: Readme Pypi0.3.7Fix: Readme Pypi0.3.6Update readme0.3.5Use vertical label in upper case0.3.4Add more status messages0.3.3Fix logical0.3.1Add locale folder to Manifest.in0.3.0Add Gettext/internationalization support0.2.0Bug FixesImprove better UIFix layoutChange to use letters instead of only numbers0.1.0 (2019-01-01)initial release
Package: pybaum
Installationpybaum is available onPyPIandAnaconda.org. Install it with$pipinstallpybaum#or$condainstall-cconda-forgepybaumAboutpybaum provides tools to work with pytrees which is a concept borrowed fromJAX.What is a pytree?In pybaum, we use the term pytree to refer to a tree-like structure built out of
container-like Python objects. Classes are considered container-like if they are in the
pytree registry, which by default includes lists, tuples, and dicts. That is:Any object whose type is not in the pytree container registry is considered a leaf
pytree.Any object whose type is in the pytree container registry, and which contains
pytrees, is considered a pytree.For each entry in the pytree container registry, a container-like type is registered
with a pair of functions that specify how to convert an instance of the container type
to a (children, metadata) pair and how to convert such a pair back to an instance of the
container type. Using these functions, pybaum can canonicalize any tree of registered
container objects into tuples.Example pytrees:[1,"a",object()]# 3 leaves(1,(2,3),())# 3 leaves[1,{"k1":2,"k2":(3,4)},5]# 5 leavespybaum can be extended to consider other container types as pytrees.
Package: pybayesbandit
# pybayesbanditBayesian bandits in Python3.## Quickstart```text$ pip install pybayesbandit```## Usage```text$ pybayesbandit --helpusage: pybayesbandit [-h] [-p PARAMS [PARAMS ...]] [-d MAXDEPTH] [-t TRIALS][-C C] [-e EPISODES] [-hr HORIZON] [--plot] [-v]{random,ucb,thompson,vi,uct,rollout,aotree} {bernoulli}{total,simple}Bayesian bandits in Python3.positional arguments:{random,ucb,thompson,vi,uct,rollout,aotree}learner type{bernoulli}           bandit type{total,simple}        game settingoptional arguments:-h, --help            show this help message and exit-p PARAMS [PARAMS ...], --params PARAMS [PARAMS ...]bandit parameters-d MAXDEPTH, --maxdepth MAXDEPTHmaximum number of timesteps in the tree lookahead(default=10)-t TRIALS, --trials TRIALSnumber of trials in Monte-Carlo sampling (default=30)-C C                  UCT exploration constant (default=2.0)-e EPISODES, --episodes EPISODESnumber of simulation episodes (default=200)-hr HORIZON, --horizon HORIZONnumber of timesteps in each episode (default=100)--plot                plot cumulative regret-v, --verbose         verbose mode```## Examples```text$ pybayesbandit ucb bernoulli total -p 0.5 0.8 0.3 -e 100 -hr 50 -vRunning pybayesbandit ...>> learner  = ucb>> bandit   = bernoulli([0.5, 0.8, 0.3])>> episodes = 100>> horizon  = 50Done in 0.257 sec.Results:>> Reward =  32.3900 ± 3.4173>> Regret =   7.6530 ± 1.7081``````text$ pybayesbandit thompson bernoulli total -p 0.5 0.8 0.3 -e 100 -hr 50 -vRunning pybayesbandit ...>> learner  = thompson>> bandit   = bernoulli([0.5, 0.8, 0.3])>> episodes = 100>> horizon  = 50Done in 0.297 sec.Results:>> Reward =  35.2200 ± 3.8822>> Regret =   4.4560 ± 2.6086``````text$ pybayesbandit uct bernoulli total -p 0.5 0.8 0.3 -e 100 -hr 50 --trials 15 --maxdepth 5 -vRunning pybayesbandit ...>> learner  = uct(trials=15, maxdepth=5, C=2.0)>> bandit   = bernoulli([0.5, 0.8, 0.3])>> episodes = 100>> horizon  = 50Done in 7.066 sec.Results:>> Reward =  36.2800 ± 5.4828>> Regret =   3.4360 ± 4.5856```## LicenseCopyright (c) 2018 Thiago Pereira Bueno All Rights Reserved.pybayesbandit is free software: you can redistribute it and/or modify itunder the terms of the GNU Lesser General Public License as published bythe Free Software Foundation, either version 3 of the License, or (atyour option) any later version.pybayesbandit is distributed in the hope that it will be useful, butWITHOUT ANY WARRANTY; without even the implied warranty ofMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU LesserGeneral Public License for more details.You should have received a copy of the GNU Lesser General Public Licensealong with pybayesbandit. If not, see http://www.gnu.org/licenses/.
Package: pybb
Pybb is a django forum application. For now PyBB is unstable.
If some feture exists in rev.A then it could be dropped in rev.B.ContactsSend all questions tolorien@lorien.nameDocumentationBasic info:http://packages.python.org/pybb/Installation/DownloadMost recent version is on bitbucket. Package on pypi.python.org
is updated from time to time.PyBB DemoQuick way to test pybb is to installpybb-demoproject.
It is preconfigured django project which you can setup and run in five minuetes.TemplatesPyBB is shipped with default templates which you can use as basis for
development your own templates. PyBB is not shipped with any stylesheets,
you can find some CSS inpybb-demoproject.TestsTo run tests you need django-webtest and lxml packages to be installed
Package: pybbfmr
pybbfmr is a python package to load, process and model
2D (field-frequency) broadband ferromagnetic resonance (bbfmr) measurements.UsageThe basic concept is to load the measurement data stored in the
binary NI-TDMS file format using one of the Measurement classes.
(The base Measurement class can also be fed directly with 2D
data.) Several processing operations are included that can be
applied to the data by using Measurement().add_operation().
The data can be plotted (using matplotlib) by using
Measurement().plot().Several lmfit models for fitting the data to bbFMR models
such as the Polder susceptibility and various damping and
dispersion models.Finally, a graphical user interface to visualize and process
the 2D data using guidata and guiqwt is included.See the data [1] of [2] for a usage example and for a detailed
description of the physics behind the modeling and the
“derivative divide” processing method in particular.RequirementsThe following packages are required. (The versions in brackets are the tested
versions. Other versions will probably work just as well):Python (3.5.2)lmfit (0.9.5)matplotlib (1.5.3)npTDMS (0.8.2)numpy (1.11.2)scipy (0.18.1)guiqwt (3.0.3)guidata (1.7.6)pyqt (>4)ContributePlease use the issue tracker to report problems and suggest changes
and new features. Get in touch if you want to know more about the
package.ContributorsHannes Maier-FlaigLukas LiensbergerStefan WeichselbaumerReferencesMaier-Flaig, “Analysis of broadband FMR in the frequency domain - dataset and reference implemenation of derivative divide,” (2017), [https://osf.io/u27sf/…](https://osf.io/u27sf/?view_only=bc9d8bd783324875960eab1e0286e77a)Hannes Maier-Flaig, Sebastian T. B. Goennenwein, Ryo Ohshima, Masashi Shiraishi, Rudolf Gross, Hans Huebl: “Analysis of broadband ferromagnetic resonance in the frequency domain”, 2017; [arXiv:1705.05694](http://arxiv.org/abs/1705.05694).
Package: pybbm
PyBBM - Django forum solutionPyBBM is a full-featured django forum solution with these features:AvatarsCustom profiles and support of Custom User Model (since django 1.5)Post editingPre-moderationCustom sanitizationAnonymous postingSubscriptionsPolls…All features is based on:+94% tests covered codeTwitter bootstrap compatible default themeReady to use example projectThe main point in development of pybb is to build it so it could beeasilyintegrated to existing django based site. This mean that pybb does not provide features like user registration, password restoring.  It does not provide authentication page. (But example project provides ;))PyBBM includes ready to useexample/test project with instructionsi18n supportPYBB support English, Russian, Slovak, Ukrainian, Brazilian Portuguese, Polish, Hebrew, French, Chinese, Japanese,
German, Spanish, Italian, Swedish translations now. Feel free to contribute translation for another language or to correct existing.
You should enable django.middleware.locale.LocaleMiddleware to activate
django locale autodetecting.More linksSupport Forum and DEMO:http://pybbm.org/PyPi:http://pypi.python.org/pypi/pybbm/Sourcecode:https://github.com/hovel/pybbm/Documentation:http://pybbm.readthedocs.org/en/latest/Page on djangopackages.com:http://www.djangopackages.com/packages/p/pybbm/
Package: pybbmini
Package for Bitblock-Miniexampletests 폴더 내부의 파일을
python3 test_led.py  로 실행

pip3로 설치해야함...콘트롤 모드#-*-coding:utf-8-*-
from pybbmini import *

# 연결 
board = BBBoard('COM18', 57600)

# ------------------------------------------
# DISPLAY
# ------------------------------------------
board.display.show(Symbol.NUM_5)

board.display.show(Symbol.CHAR_H)

symbol = '11011:11011:11011:11011:11111'
board.display.symbol(symbol)

symbol = Symbol("01010:"
                "01010:"
                "01010:"
                "11111:"
                "11111")
board.display.show(symbol)

board.display.color(Color.RED)
delay(1000)

board.display.color(Color.GREEN)
delay(1000)

board.display.color(Color.BLUE)
delay(1000)

board.display.clear()

# ------------------------------------------
# BUTTON
# ------------------------------------------
print(board.buttonA.isPressed())
print(board.buttonB.isPressed())
print(board.buttonAB.isPressed())

# ------------------------------------------
# BUZZER
# ------------------------------------------
board.buzzer.melody()
board.buzzer.tone(Note.C4, 2000)

tune = ["C4:4", "D4:4", "E4:4", "C4:4", "C4:4", "D4:4", "E4:4", "C4:4", "E4:4", "F4:4", "G4:8", "E4:4", "F4:4", "G4:8"]
board.buzzer.play(tune)

# ------------------------------------------
# TOUCH
# ------------------------------------------
board.touch0.isTouched()
board.touch1.isTouched()
board.touch2.isTouched()

# ------------------------------------------
# DigitalWrite
# ------------------------------------------
board.digitalWrite(Pin.P3, 1)
board.digitalWrite(Pin.P3, 0)

# ------------------------------------------
# DigitalRead
# ------------------------------------------
val = board.digitalRead(Pin.P0, PinMode.INPUT_PULLUP)
print(val)

# ------------------------------------------
# AnalogWrite
# ------------------------------------------
board.analogWrite(Pin.P3, 0)

# ------------------------------------------
# AnalogRead
# ------------------------------------------
val = board.analogRead(Pin.P4)
print(val)


# ------------------------------------------
# Servo
# ------------------------------------------ 
servo = Servo()
servo.attach(board, Pin.P3)
servo.move(100)

# ------------------------------------------
# Ultrasonic 미실장
# ------------------------------------------ 
us = Ultrasonic()
us.attach(board, Pin.P3, Pin.P0)
print(us.distance())


# ------------------------------------------
# Board Close
# ------------------------------------------
 board.close()
Package: pybbm-private-messages
=====PYBBM Private Messages=====This is a plugin to add private messaging to the django forum solution `pybb`Prerequisites:1. `Django>=1.8`2. `pybbm>=0.17`Quick Start1. `pip install pybbm-private-messages`2. Add `private_messages` to your `INSTALLED_APPS` in `settings.py` BEFORE `pybb` (it overrides some templates)3. Add `django_select2` to your `INSTALLED_APPS`4. Run `manage.py migrate private_messages`5. Add the urls to your project `urls.py` file, e.g.:```urlpatterns = [...url(r'^forum/', include('pybb.urls', namespace='pybb')),url(r'^forum/', include('private_messages.urls', namespace='private_messages')),]```6. Add `'private_messages.context_processors.unread_messages'` to your template context processors in settings.7. Adding a `{% block private_messages %}{% endblock %}` to your `PYBB_TEMPLATE` will place a link to the inbox with the text: "Inbox" and a bootstrap badge adjacent to it with the number of unread messages, if there are any. For just the number of unread messages, use `{% block unread_msgs %}{% endblock %}`.
Package: pybbm-tbw
PyBBM - modified version of pybb (developed by lorien and dropped in mid 2010).Documentation aviable on ReadTheDocsPyBBM includes ready to useexample/test project with instructionsThe main point in development of pybb is to build it so it could beeasilyintegrated to existing django based site. This mean:pybb does not provide features like user registration, password restoring.
It does not provide authentication page. You should use your favorite
application for such things. You can try well known django-registrationhttp://code.google.com/p/django-registration/.
Package: pybcj
In data compression, BCJ, short for Branch-Call-Jump, refers to a technique that improves the compression of
machine code of executable binaries by replacing relative branch addresses with absolute ones.
This allows a LZMA compressor to identify duplicate targets and archive higher compression rate.BCJ is used in 7-zip compression utility as default filter for executable binaries.pybcj is a python bindings with BCJ implementation by C language.
The C codes are derived from p7zip, portable 7-zip implementation.
pybcj support Intel/Amd x86/x86_64, Arm/Arm64, ArmThumb, Sparc, PPC, and IA64.Development statusA development status is considered asBetastate.InstallationAs usual, you can install pybcj using python standard pip command.pip install pybcjAlternatively, one can also use conda:conda install -c conda-forge pybcjWARNINGWhen use it on MSYS2/Mingw64 environment, please set environment variableSETUPTOOLS_USE_DISTUTILS=stdlibto install.LicenseSPDX-License-Identifier: LGPL-2.1-or-laterSPDX-URL:https://spdx.org/licenses/LGPL-2.1-or-later.htmlCopyright (C) 2020-2022 Hiroshi MiuraCopyright (C) 1999-2010 Igor Pavlov
Package: pybcoin
PyBcoin - A forcasting tool to analyze Bitcoin trend.PyBcoin is a Bitcoin trend forecasting tool which predicts the next days momentum of Bitcoin price based on historical data of Bitcoin, user sentiments on twitter and reddit alongside various commodity prices. The User interface for this forecasting tool is a Dash app.The link to the app is:pybcoinPython Version 3.4 or LaterThis Package is developed on Linux using Python 3.4 / 3.5 / 3.6 (the Anaconda distribution).EnvironmentAfter installing Anaconda, you should create a conda environment using:conda create --name pybcoin python=3Now you can switch to the new environment (on Linux):source activate pybcoinRequired PackagesThe App require several Python packages to be installed. The packages are listed in requirements.txtTo install the required Python packages and dependencies you first have to activate the conda-environment as described above, and then you run the following command in a terminal:pip install -r requirements.txtDash AppOnce done installing requisite packages, Run the the following command:python pybcoin/starter.pyThis will open a Intercative Dash app.Using PipThe package can also be installed from pypi using:pip install pybcoin
Package: py-bcrypt
py-bcrypt is an implementation the OpenBSD Blowfish password hashing
algorithm, as described in “A Future-Adaptable Password Scheme” by
Niels Provos and David Mazieres and related bcrypt-based key derivation
function implemented in OpenBSD libutil.This system hashes passwords using a version of Bruce Schneier’s
Blowfish block cipher with modifications designed to raise the cost
of off-line password cracking. The computation cost of the algorithm
is parametised, so it can be increased as computers get faster.Two interfaces are supported: a classic password hashing interface and
a key derivation function (KDF) intended for generating cryptographic
keys.
Package: py-bcrypt-w32
py-bcrypt-w32 is just a small mod to py-bcrypt to build on Microsoft Windows,
below is the original py-bcrypt description:py-bcrypt is an implementation the OpenBSD Blowfish password hashing
algorithm, as described in “A Future-Adaptable Password Scheme” by
Niels Provos and David Mazieres.This system hashes passwords using a version of Bruce Schneier’s
Blowfish block cipher with modifications designed to raise the cost
of off-line password cracking. The computation cost of the algorithm
is parametised, so it can be increased as computers get faster.
Package: pyBCS-bioturing
pyBCSThis is a python library to create a BioTuring Compressed Study (bcs) file from an AnnData (scanpy) object.bcsfiles can be imported directly intoBBrowser, a software for single-cell data.Visit ourgithubfor more detail.InstallationpipinstallpyBCS-bioturingExamplesCreate a bcs file from common formatsScanpyfrompyBCSimportscanpy2bcsscanpy2bcs.format_data("/mnt/example/data.h5ad","/mnt/example/data.bcs",input_format="h5ad",graph_based="louvain")If your data has antibody-derived tags (ADT), you can put ADT expression data in theobsas cell metadata with a distinguishable suffix. For example, ADT expression ofCD45will beCD45_TotalSeqC. In such cases, you can declarecite_seq_suffixwhen usingformat_data():scanpy2bcs.format_data("/mnt/example/data.h5ad","/mnt/example/data.bcs",input_format="h5ad",graph_based="louvain",cite_seq_suffix="_TotalSeqC")SPRINGfrompyBCSimportscanpy2bcsscanpy2bcs.format_data("/mnt/example/spring_study","/mnt/example/data.bcs",input_format="spring",graph_based="louvain")LoomfrompyBCSimportscanpy2bcsscanpy2bcs.format_data("/mnt/example/data.loom","/mnt/example/data.bcs",input_format="loom",barcode_name="CellID",feature_name="Gene",dimred_keys={"tsne":["tsne1","tsne2"]})AbloomfrompyBCSimportscanpy2bcsscanpy2bcs.format_data("/mnt/example/data.loom","/mnt/example/data.bcs",input_format="abloom",barcode_name="observation_id",feature_name="accession_id",graph_based="cluster")Create a folder from OME-TIFF files (Nanostring DSP)In this example, we useOMEclass frompyBCSto load information from OME-TIFF format. AnOMEobject requires 2 arguments: (1) an excel that hasSegmentPropertiesandTargetCountMatrix, (2) a folder that has all the OME-TIFF files for that excel file. After loading data, you can use.write()to create a folder that has all the neccessary components for BBrowser.frompyBCSimportOMEome=OME('path/to/excel_file.xlsx','path/to/tif/folder')ome.write('path/to/output_folder')
Package: pyBCV
pyBCVpyBCV es una librería de Python que simplifica la obtención de los precios de los tipos de cambio y las tasas informativas del sistema bancario proporcionados por el Banco Central de Venezuela (BCV) convirtiéndolos en un formato fácilmente utilizable en Python.InstalaciónPara instalar esta librería, puedes utilizar el siguiente comando:pipinstallpyBCVUsoLa librería pyBCV proporciona dos clases,CurrencyyBank, para obtener tasas de cambio e informativas de bancos del Banco Central de Venezuela.La claseCurrencyobtiene tasas de cambio para varias monedas y las devuelve en formato de diccionario. También proporciona métodos para obtener una tasa de cambio específica o la hora de la última actualización.frompyBCVimportCurrencycurrency=Currency()all_rates=currency.get_rate()# obtener todas las tasas de cambio de monedausd_rate=currency.get_rate(currency_code='USD',prettify=False)# obtener la tasa de cambio del dólar estadounidense sin símbolo de monedalast_update=currency.get_rate(currency_code='Fecha')# obtener la hora de la última actualizaciónLa clase Bank obtiene tasas informativas proporcionadas por varios bancos en Venezuela y las devuelve en formato de lista de diccionarios. Proporciona métodos para obtener información sobre un banco específico o todos los bancos disponibles.frompyBCVimportBankbcv=Bank("01-01-2023","31-12-2023")# Inicializar la clase Bank con fechas de inicio y finalbank_info=bcv.get_by_bank()# Obtener todas las tasas de cambio informativas de los bancos disponibles# Obtener la tasa de cambio informativa del Banco Nacional de Créditobnc_info=bcv.get_by_bank(bank_code='Banco Nacional de Crédito')ColaboradoresFrancisco GrimanJesús Alfredo Reyes VargasPropósito de pyBCVEsta librería está diseñada específicamente para recopilar y convertir estos datos en un formato fácilmente utilizable en Python, lo que permite a los desarrolladores acceder a ellos y utilizarlos en sus aplicaciones con facilidad. Con pyBCV, los usuarios pueden obtener información actualizada sobre las tasas de cambio y las tasas informativas de los bancos de manera rápida y sencilla, haciendo que el proceso de obtener estos datos sea más eficiente y conveniente.
Package: pybd
A Python API to access the Bazean Postgres databaseExample UsageA simple Python script that gets the production data from 10 wells from the state of Texas operated by XOM:frompybdimportPyBDdb=PyBD(user='bazean_postgres_username',password='bazean_postgres_password')db.set_fetch_size(10)latitude,longitude,apis=db.get_well_locations_by_ticker_and_state('XOM','TX')oil_production=[]foriinrange(10):dates,oil,gas,water=db.get_production_from_api(apis[i])oil_production+=[oil]
Package: pybda
A commandline tool for analysis of big biological data sets for distributed HPC clusters.AboutPyBDA is a Python library and command line tool for big data analytics and machine learning scaling to tera byte sized data sets.In order to make PyBDA scale to big data sets, we useApache Spark’s DataFrame API which, if developed against, automatically distributes
data to the nodes of a high-performance cluster and does the computation of expensive machine learning tasks in parallel.
For scheduling, PyBDA usesSnakemaketo automatically execute pipelines of jobs. In particular, PyBDA will first build a DAG of methods/jobs
you want to execute in succession (e.g. dimensionality reduction into clustering) and then compute every method by traversing the DAG.
In the case of a successful computation of a job, PyBDA will write results and plots, and create statistics. If one of the jobs fails PyBDA will report where and which method failed
(owing to Snakemake’s scheduling) such that the same pipeline can effortlessly be continued from where it failed the last time.DocumentationCheck out the documentationhere.
The documentation will walk you thoughthe installation process,setting up Apache Spark,usingpybda.AuthorSimon Dirmeiersimon.dirmeier at bsse.ethz.ch.
Package: pybd-base
Baidu XiongZhang Base Class for Python.Installationpip install pybd-baseUsageIn [1]: from pybd-base import BaseBaidu

In [7]: class XXX(BaseBaidu):
   ...:     pass
   ...:

In [3]: xxx = XXX()

In [4]: xxx.OPENAPI
Out[4]: 'https://openapi.baidu.com'

In [6]: xxx._requests
Out[6]: <bound method XXX._requests of <__main__.XXX object at 0x7f9248260d10>>

In [7]: