Saravanan666/pypi-org huggingface dataset:
Package: pybddisasm
The Bitdefender disassembler Python wrapperBuildBuilding and installing is easy:python3setup.pybuild
python3setup.pyinstallUsageUse it by importing the pybddisasm module:importpybddisasmret,instr=pybddisasm.nd_decode_ex(code,def_code,def_data,def_stack)Exampleimportpybddisasmcode=b"\x55\x48\x8b\x05\xb8\x13\x00\x00"offset=0whileoffset<len(code):_,instr=pybddisasm.nd_decode_ex(code[offset:],len(code[offset:]),pybddisasm.ND_CODE_64,pybddisasm.ND_DATA_64)ifinstrisNone:break_,text=pybddisasm.nd_to_text(instr,0x0)print(text)offset+=instr.LengthPipUse pip to install the package:pipinstallpybddisasm
Package: pybd-miniapp
Baidu SmartProgram Module for Python for MiniApp.Installationpip install pybd-miniappUsagefrom pybd_miniapp import get_session_key, get_userinfo, get_phone_numberMethoddef get_session_key(self, appid=None, secret=None, code=None, storage=None):

def get_userinfo(self, appid=None, secret=None, code=None, session_key=None, encryptedData=None, iv=None, storage=None):

def get_phone_number(self, appid=None, secret=None, code=None, session_key=None, encryptedData=None, iv=None, storage=None):
Package: pybd-oauth
Baidu XiongZhang Oauth Module for Python.Installationpip install pybd-oauthUsagefrom pybd_oauth import get_access_info, get_oauth_code_url, get_userinfo, get_component_access_info, get_component_oauth_code_url, get_component_userinfo, get_oauth_redirect_urlMethoddef get_oauth_code_url(self, appid=None, redirect_uri=None, scope='snsapi_base', redirect_url=None, component=False, component_appid=None):

def get_access_info(self, appid=None, secret=None, code=None, component=False, component_appid=None, component_access_token=None):

def get_userinfo(self, access_token=None, openid=None, component=False):

def get_component_oauth_code_url(self, appid=None, redirect_uri=None, scope='snsapi_base', redirect_url=None, component_appid=None):

def get_component_access_info(self, appid=None, code=None, component_appid=None, component_access_token=None):

def get_component_userinfo(self, access_token=None, openid=None):

def get_oauth_redirect_url(self, oauth_uri, scope='snsapi_base', redirect_url=None, default_url=None, direct_redirect=None, random_str=True):
Package: pybdsim
pybdsimA python package containing both utilities for preparing and analysing BDSIM input and output as well as controlling BDSIM.AuthorsL. Nevay
A. Abramov
S. Alden
S. Boogert
M. Deniaud
C. Hernalsteens
F. Metzger
W. Parker
E. Ramoisiaux
W. Shields
J. Snuverink
R. Tesse
S. WalkerSetuppip install pybdsimOr from source, from the main directory:$ make installor for development where the local copy of the repository is used and can
be reloaded with local changes:$ make developLook in the Makefile for the various pip commands (e.g. for with a venv)python
>>> import pybdsim
>>> d = pybdsim.Data.Load("output.root")
>>> eventTree = a.GetEventTree()
>>> for event in eventTree:
        print(event.Summary.nTracks)
>>> dh = pybdsim.Data.Load("analysis_histograms.root")
>>> pybdsim.Plot.Histogram1D(dh.histogramspy["Event/MergedHistograms/PlossHisto"])
Package: pybeads
BEADS: Baseline Estimation And Denoising using SparsityThis is a Python translation of an awesome baseline estimation algorithm "BEADS"originally written in MATLAB. The initial translation had been done by @hsiaocy.InstallationSimply runpip install pybeadsin your terminal.UsageParameter notation and usage are same as the original MATLAB code's. Please see "Example" tab ofthis page. If you want to know the details of the parameters, please refer to the original paper in Resources.Sample dataReal chromatograms with eight different background levels (probably including the one tested in the original paper shown in Figure 12) and additional computed white noise are available in MATLAB format athttps://jp.mathworks.com/matlabcentral/fileexchange/49974-beads-baseline-estimation-and-denoising-with-sparsity, but MathWork account is required to download the zip file. For those who don't want to create a MathWork account just for this, I converted them into CSV format and included in this Python repo (sample_data/chromatograms_and_noise.csv).Redistributed with permission by courtesy of Laurent Duval.A new parameter,convThe main functionbeadsin this package has a parameter calledconvwhich does not exist in the MATLAB code. This parameter is used for a smoothing feature for derivatives (moving average using convolution, to be correct). I noticed that the MATLAB implementation sometimes gives completely different results for regularization parameters with a slight difference, for examplelam1=0.001andlam1=0.0011. This unpredictable behavior is suppressed when derivatives are smoothed. When you face such instability, I reccomend you to setconvto 3 or 5. Default isNonewhich means "no smoothing".A tip for real dataWhen you apply BEADS to your experimetal data, probably you'll find something is wrong at the both ends of your data which does not happen to the example data. The trick in the exmaple is that the both ends are smoothly decreasing to zero. To solve the issue, all you have to do is to do the same trick to your data by extending the both ends smoothly to zero. I reccomend to use a sigmoid function with an appropriate scaling factor for x, e.g. 30 to 100 or even bigger depending on the number of points of your data. Below is an exmaple.import numpy as np

def sigmoid(x):
    return 1 / (1 + np.exp(-x))

# y is your data

xscale_l, xscale_r = 100, 100
dx = 1
y_l = y[0]*sigmoid(1/xscale_l*np.arange(-5*xscale_l, 5*xscale_l, dx))
y_r = y[-1]*sigmoid(-1/xscale_r*np.arange(-5*xscale_r, 5*xscale_r, dx))
y_ext = np.hstack([y_l, y, y_r])
len_l, len_o, len_r = len(y_l), len(y), len(y_r)
plt.plot(range(len_l, len_l+len_o), y)
plt.plot(y_l, 'C1')
plt.plot(range(len_l+len_o, len_l+len_o+len_r), y_r, 'C1')ResourcesOriginal paper (2014)Preprint onlaurent-duval.euProject websiteOriginal MATLAB code
Package: pybeamline
Streaming process mining withpyBeamlinepyBeamlineis a Python version of Beamline. While the same set of ideas and principles of Beamline have been ported intopyBeamline, the underlying goal and technology is very different.pyBeamline is based on ReactiveX and its Python binding RxPY. RxPY is a library for composing asynchronous and event-based programs using observable sequences and pipable query operators in Python. Using pyBeamline it is possible to inject process mining operators into the computation.For a complete documentation of the library seehttps://www.beamline.cloud/pybeamline/. To install the library use:pip install pybeamlineA complete Jupyter notebook presenting all techniques available is available athttps://github.com/beamline/pybeamline/blob/master/tutorial.ipynb.
Package: pybeans
pybeansCommon toolkit for python.Python version >= 3.6Common code for myself.Features:AppTool classCombine config & config_local & config_test (if --test)Act as dict to get config by key (connected by dot), it can be overrited by ENV variablelogger helper (pre-configged email handler)Pre-configged SMTP email client@log annotation.Utility functionsemail helperload & dump json@benchmark annotationOS detector@deprecated annotationget home dirdeep mergeGet windows foldersstring alignment for Chineseget dict value by key (connected by dot)now, todayrandom_sleepGetCh classinput value for multiple platformsTODO:send_email support CC.
Package: pybeanstalk
A pure-Python client library for beanstalkd. beanstalkd is a lightweight queuing daemon
based on libevent. It is meant to be used across multiple systems, and takes
inspiration from memcache. More details on beanstalk can be found at:http://xph.us/software/beanstalkd/This client library aims to be simple and extensible. It provides both a single thread,
single connection serialized (select-based) beanstalk connection with optional, simple
thread pool implementation, and a basic Twisted client. Both can be used directly, or
be used as basis for for more sophisticated client applications. Please see the examples
directory for usage examples.To install, just run python setup.py install from this directory, or use the shortcuts
in the Makefile. For Twisted support, run install with the ‘twisted’ extra.The package home is athttps://github.com/beanstalkd/pybeanstalk, with an issue tracker
and a wiki. Bug reports and pull requests most welcome.
Package: pybeastx
py-Ultroid LibraryA stable userbot base library, based on Telethon.Installationpip install py-UltroidDocumentationUsage=> Create folders namedplugins,addons,assistantandresources.=> Add your plugins in thepluginsfolder and others accordingly.=> Create a.envfile withAPI_ID,API_HASH,SESSION,REDIS_URI&REDIS_PASSWORDas mandatory environment variables. Check.env.samplefor more details.=> Runpython -m pyUltroidto start the bot.Creating pluginsTo work everywhere@beastx_cmd(pattern="start",)asyncdef_(e):awaiteor(e,"Ultroid Started")To work only in groups@beastx_cmd(pattern="start",groups_only=True,)asyncdef_(e):awaiteor(e,"Ultroid Started")Assistant Plugins 👇@asst_cmd("start")asyncdef_(e):awaite.reply("Ultroid Started")Made with 💕 by@TeamUltroid.LicenseUltroid is licensed underGNU Affero General Public Licensev3 or later.CreditsLonamiforTelethon
Package: pybeaut
PybeautPLEASE NOTEThis module does not intend to steal the credits for the creation of this module, only for personal non-atributive proyects.IMPORTANT!Recently the Pystyle library has suffered an update that contains non-legitimate code and that can put at risk your computer and your data, that's why I have been forced, as a good action towards the community, to upload my own module renamed as "Pybeaut" to continue giving the service that Pystyle used to give with no malicious contexts.PD:If you have any recommendations or new possible implementations of the module features, let us know through an issue in the official repository of the module or by posting a request in the official Pypi portal.Copyright Present Backist-TheWisker 2022-2023
Package: pybeautifier
PyBeautifierPython beautifier tcp server based on autopep8, yapf, isort.Only suport Unix-like system and python3.3+ currently.WhyBefore this, I useatom-beautifyto format my code, but it's too slow(about 3 seconds) because every format operation will create a new python process.So I write the beautifier server in python and beautifier client in node.js, they communicate by tcp socket. It's performance is much better(about 300 ms).Install$ pip install pybeautifierBesides, you should install one or more of autopep8, yapf, isort based on your needs.Usage$ pybeautifier       # front ground process
$ pybeautifier -d    # daemon process, logging to /tmp/pybeautifier.logIt will start listening to tcp://${BEAUTIFIER_HOST}:${BEAUTIFIER_PORT}.Env variables:BEAUTIFIER_HOST - IP address or hostname (Default: 127.0.0.1)
BEAUTIFIER_PORT - Port number (Default: 36805)Start at boot via systemd(Ubuntu16 or Arch Linux):$ wget https://raw.githubusercontent.com/guyskk/pybeautifier/master/pybeautifier.service
$ cp pybeautifier.service /usr/lib/systemd/system/
$ systemctl start pybeautifier
$ systemctl enable pybeautifierProtocolRequest(JSON):{
    'data': 'text_need_format',
    'formaters': [
        {
            'name': 'formater_name',
            'config': {}  # None or dict
        },
        ... # formaters
    ]
}Response(JSON):{
    'error': 'error message',
    'data': 'formated text'
}
Package: pybeautify
BeautifierInstall this package : pip install pybeautifyOpen the python console and type : import beautifyBeautifier is a windows application for arranging the files within a folder.Everybody want their files to be arranged in an organized way within a folder.So let's see an application that does this for us.Let's have a look at the folder in which the files are not well organized 🤢.Before running the application.Now let's see the same folder when the files within the folder are properly organized (Beautified)😍.After running the application.So how to run the application 🤔.You can either clone this repository or download only the installerFor better user experience try the installer.Once after downloading the installer / cloning the repository.Run the application.Copy the path of your target folder.Paste the path in your application.Click the Beautify button and see the magic happen.In case if you need to undo the changes click the Undo Button and the changes will be reverted.Files back to their initial state.
Package: pybeauty
PyBeautyPython module for beautifully varying RGB colour sets which can be used for setting colours anywhere!
This module basically varies RGB values in various random ranges via threading.Timer() executing continously after very
small interval of time i.e. in milliseconds hence resulting in beautiful transition of colours.InstallationSimply using PyPi:pip install pybeautyUsageSimply use this code (Modify according to your needs):frompybeautyimportBeautydefon_new_color(rgb_color):r_value=rgb_color[0]g_value=rgb_color[1]b_value=rgb_color[2]#Now you can do anything with the RGB values (set as background, set as text colour, etc..).Beauty(Parameters,on_new_color)#Parameters is a dictionary for optional parameters (More about them specified below).Optional Parameters that are available are listed below in Parameters section and have to be passed as a Dictionary (keys as name of parameters listed in Parameters section and value is your desired choice according to the options available for that parameter as specified in the Parameters section) which will be the first parameter for Beauty() constructor.Parametersmode (Optional)Specifies colour set in which the colours have to vary.Parameter Value Type:str or list.Options for mode parameter"dark":Varies the colour in dark colours only (useful for dark mode projects)."light":Varies the colour in light colours only (useful for light mode projects).[start_rgb, end_rgb]:Varies the colour from start_rgb value (can be from 0 to 255) to end_rgb value (can be from 0 to 255).Default Value:"" (i.e. varies from 0 to 255 RGB Values).start (Optional):Specefies colour in RGB format from which colours have to start varying.Input type for start parameter:list [R_Value, G_Value, B_Value] (eg. [0, 0, 0] for black).Default Value:[0, 0, 0] (for "dark", none or other mode parameter specified) and [255, 255, 255] (for "light" mode parameter specified).time (Optional):Specifies the time in milliseconds after which the colour is changed according to its range.
Useful for decreasing the time when using on slow hardware for maintaining the smoothness.Parameter Value Type:int.Default Value:40 ms (Just perfect for majority hardware types).So go ahead and enjoy the beauty of time varying RGB colour sets!
Package: pybec
PyBECPython package for extracting and manipulating Born Effective Charges from QuantumEspresso OutputInstallationThe PyBEC PackagePyBEC is available via the Python Package Index (PyPI).Inside the virtual environment for your project:pip install pybecJupyter NotebookFirst install PyBEC as discussedabove.There is an associated Jupyter Notebook that demonstrates a lot of the packages parsing and plotting
capabilities.  It can be found in the release archive for eachgithub release.
Download and extract the archive, and run the contained Jupyter Notebook.UsageAuser manualandAPI documentationare available online.CopyrightCopyright (c) 2020, Brett HendersonAcknowledgementsProject based on theComputational Molecular Science Python Cookiecutterversion 1.3.
Package: pybecker
PyBecker - controlling Becker RF Shutter with PythonThis library is based on the work ofole1986(https://github.com/ole1986/centronic-py)PyBecker requires a Becker Centronic USB Stick in order to communicate with the Shutters.
The pairing need as well to be performed before and is not yet part of the libraryThe goal of this library is to be used in Home assistant custom component to control your becker shutters.
This component is not yet publicly released.RequirementsFrom 0.0.5 pybecker uses asyncio it requires pyhton 3.7 or aboveInstallationThe easiest way to install pybecker library is usingpip:pip install pybeckerUsageThe goal of this library is to be used in your home automation component.
however after installation you can test it by runingpython -m pybecker -a <UP|DOWN|PAIR|HALT> -c <CHANNEL>
Package: pybedforms
pybedforms'pybedforms' is a Python version of 'Bedforms 4.0', a Matlab program written by David Rubin and Carissa Carter (seethis USGS publicationandthis interactive webpage). The bedform topographies are created in exactly the same way as they were in Bedforms 4.0; however, the 3D visualization is different. We useMayavito build the block diagrams; these plotting functions were simplified from the'blockdiagram' Python package. All the key classes and functions are in the'dune_topo.py' module. The'Notebook_with_examples' jupyter notebookillustrates how to build bedform models using (1) the default parameters and (2) a set of parameters predefined by Rubin & Carter. The model can be visualized as a block diagram using the "plot_3D" function:You can also extract a "core" from the model and visualize it in 3D:Requirementsmatplotlibnumpymayaviskimagescipytqdm
Package: pybedlite
pybedliteSee documentation onpybedlite.readthedocs.org.conda install -c bioconda pybedliteORconda create -n pybedlite pybedlite
conda activate pybedliteNote that while there is a version of pybedlite on pypi versions of pybedlite >=
0.0.2 cannot at present be installed via pypi because they have dependencies
that preclude publishing to pypi. For this reason installation via conda is
required.Requires python 3.8+(for python < 3.8, please use pybedlite <= 0.0.3)Getting Setup for Development WorkPoetryis used to manage the python development environment.A simple way to create an environment with the desired version of python and poetry is to useconda.  E.g.:condacreate-npybedlitepython=3.8poetry
condaactivatepybedlite
poetryinstallIf the methods listed above do not work try the following:mambacreate-npybedlite-cconda-forge"python=3.9.16""poetry=1.6.1"mambaactivatepybedlite
poetryinstallIf, duringpoetry installon Mac OS X errors are encountered running gcc/clang to buildpybedtoolsor other packages with native code, try setting the following and re-runningpoetry install:exportCFLAGS="-stdlib=libc++"Checking the BuildRun all checks with:./ci/check.sh
Package: pybedrock
pybedrockA python library for analysis and modification of world data in Minecraft Bedrock.Installation$ pip install pybedrockSupported versionspybedrock supports Windoes, MacOS and Linux on various CPU architectures.Windows AMD64MacOS x86_64MacOS arm64MacOS universal2Linux x86_64Linux i686Linux aarch64Linux ppc64leLinux s390xCPython 3.6✅✅N/AN/A✅✅✅✅✅CPython 3.7✅✅N/AN/A✅✅✅✅✅CPython 3.8✅✅✅✅✅✅✅✅✅CPython 3.9✅✅✅✅✅✅✅✅✅CPython 3.10✅✅✅✅✅✅✅✅✅CPython 3.11✅✅✅✅✅✅✅✅✅PyPy 3.7 v7.3N/AN/AN/AN/A✅✅✅N/AN/APyPy 3.8 v7.3N/AN/AN/AN/A✅✅✅N/AN/APyPy 3.9 v7.3N/AN/AN/AN/A✅✅✅N/AN/AUsageThe document is under development.Please see demostration codes as follows:DemonstrationsMake a custom spawner (Google Colaboratory)Webapp to edit world datahttps://mcbe-edit-web.vercel.app/Change logContributing to the projectcoming soon!LicenseThis package is distributed under theMIT license.CreditThis package makes use of following repositories with modifications.mcberepairbyreedacartwrightMIT LicenseCopyright (c) 2018-2019 Reed A. Cartwrightreed@cartwrig.htleveldb-mcpebyMojangBSD-3-Clause licenseCopyright (c) 2011 The LevelDB Authors. All rights reserved.
Package: pybedtools
OverviewTheBEDTools suite of programsis widely
used for genomic interval manipulation or “genome algebra”.pybedtoolswraps
and extends BEDTools and offers feature-level manipulations from within
Python.See full online documentation, including installation instructions, athttp://daler.github.io/pybedtools/.Whypybedtools?Here is an example to get the names of genes that are <5 kb away from
intergenic SNPs:frompybedtoolsimportBedToolsnps=BedTool('snps.bed.gz')# [1]genes=BedTool('hg19.gff')# [1]intergenic_snps=snps.subtract(genes)# [2]nearby=genes.closest(intergenic_snps,d=True,stream=True)# [2, 3]forgeneinnearby:# [4]ifint(gene[-1])<5000:# [4]printgene.name# [4]Useful features shown here include:[1]support for all BEDTools-supported formats (here gzipped BED and GFF)[2]wrapping of all BEDTools programs and arguments (here,subtractandclosestand passing
the-dflag toclosest);[3]streaming results (like Unix pipes, here specified bystream=True)[4]iterating over results while accessing feature data by index or by attribute
access (here[-1]and.name).In contrast, here is the same analysis using shell scripting.  Note that this
requires knowledge in Perl, bash, and awk.  The run time is identical to thepybedtoolsversion above:snps=snps.bed.gzgenes=hg19.gffintergenic_snps=/tmp/intergenic_snpssnp_fields=`zcat$snps|awk'(NR == 2){print NF; exit;}'`gene_fields=9distance_field=$(($gene_fields+$snp_fields+1))intersectBed-a$snps-b$genes-v>$intergenic_snpsclosestBed-a$genes-b$intergenic_snps-d\|awk'($'$distance_field' < 5000){print $9;}'\|perl-ne'm/[ID|Name|gene_id]=(.*?);/; print "$1\n"'rm$intergenic_snpsSee theShell script comparisonin the docs
for more details on this comparison, or keep reading the full documentation athttp://daler.github.io/pybedtools.
Package: pybee
pybeepybee 提供一些辅助函数，方便使用 Python 来写系统维护/部署脚本, 使用 Bash 写维护/部署脚本实在不爽；例如提供 sed、awk 工具对应的功能函数，但 pybee 目标不是编写一个 python 版的 sed/awk 工具编译安装依赖工具python 3.4+poetry执行下面命令安装依赖包poetry install编译poetry buildpybee 模块pybee 模块封装了或者增加常见系统维护需要的函数pybee.path 增强 os.path 模块的一些函数pybee.compress 封装 zip/tar.gz 压缩函数pybee.sed 提供 sed 工具类似功能的函数pybee.ask 封装在 termia 常见交互操作的函数pybee.importutil 提供把一个 py 文件当作模块 import 的函数还有其他模块，这里就不一一列出pybee.action 模块在 pybee 模块的基础上把常见的操作封装成 action，下面就是一个列子import pybee

ac = pybee.action.ActionContext([
  ('SCRIPT_DIR', pybee.path.get_script_path(__file__)),
  ('DIST_DIR', '$CURRENT_DIR/dist'),
  ('OUT_PUT_DIR', '$DIST_DIR/test-demo-portable'),
])

ac.prepare_dir(
  [
      '$DIST_DIR', '$OUT_PUT_DIR',
      '$OUT_PUT_DIR/portable',
  ]
)

ac.check_bin([
  ('gradle','please install gradle', 'GRADLE_BIN'),
])

ac.exec_cmd(
  [
      '$GRADLE_BIN', 'packDist', '-x', 'test'
  ]
)

ac.unzip(
  '$DIST_DIR/test-demo/test-demo.jar',
  '$OUT_PUT_DIR'
)


def ignore_config_files(src, names):
  return ['project.groovy', ]

ac.copy(
  [
      ('$CURRENT_DIR/config', '$OUT_PUT_DIR', {
          'ignore': ignore_config_files
      }),
      ('$CURRENT_DIR/public', '$OUT_PUT_DIR'),
  ]
)

ac.copy(
  [
      ('run.ps1', '$OUT_PUT_DIR'),
      ('run.sh', '$OUT_PUT_DIR'),
      ('portable.groovy', '$OUT_PUT_DIR/config'),
  ],
  work_dir='$SCRIPT_DIR/portable'
)

ac.zip(
  '$OUT_PUT_DIR',
  '$DIST_DIR/test-demo-portable-{datetime}.zip',
  env_name='DIST_FILE'
)


def print_success(context):
  print('')
  zip_file = context.get_env('DIST_FILE')
  print('pack successfully, dist file is %s' % zip_file)


ac.execute(succ_func=print_success)
Package: py-bee-config
#Beebeeis an all-in-one python framework for simplifying micro service program development.ComponentsConfig- Manage configuration for yml, yaml & jsonRPC- Lightweight and high performaceSerializableProtoBufjsonhttp to be continuedService Discovery - Automatic registration and name resolution with service discoveryetcd3consulLoad Balancing - Smart client side load balancing of services built on discoveryRandomBalancerRoundRobbinBalancerWeb- Web server with a variety of advanced features, to be continuedDatabasePsd - A lightweight, fluent SQL data access and ORM libraryMongoDB - A useful wrapper formongoRedis - A useful wrapper forredis,redis-py-clusterUtility- Some useful utility packages..debugi18nguidconstmapobjectpool