Saravanan666/pypi-org huggingface dataset:
Package: pypcapkit
For any technical and/or maintenance information,
please kindly refer to theOfficial Documentation.The PyPCAPKit project is an open source Python program focus on network packet
parsing and analysis, which works as a comprehensivePCAPfile extraction,
construction and analysis library.The whole project supportsPython 3.6or later.AboutPyPCAPKit is a comprehensive Python-native network packet analysis library,
withDictDumperas its formatted output dumper.Unlike popular PCAP file extractors, such asScapy,DPKT,PyShark,
and etc,pcapkitis designed to be much more comprehensive, which means
it is able to provide more detailed information about the packet, as well as
a morePythonicinterface for users to interact with.Module StructureInpcapkit, all files can be described as following eight parts.Interface (pcapkit.interface)User interface for thepcapkitlibrary, which
standardises and simplifies the usage of this library.Foundation (pcapkit.foundation)Synthesises file I/O and protocol analysis, coordinates
information exchange in all network layers, as well as
provides the foundamental functions forpcapkit.Protocols (pcapkit.protocols)Collection of all protocol family, with detailed
implementation and methods.Utilities (pcapkit.utilities)Auxiliary functions and tools forpcapkit.CoreKit (pcapkit.corekit)Core utilities forpcapkitimplementation, mainly
for internal data structure and processing.ToolKit (pcapkit.toolkit)Auxiliary tools forpcapkitto support the multiple
extraction engines with a unified interface.DumpKit (pcapkit.dumpkit)File output formatters forpcapkit.Constants (pcapkit.const)Constant enumerations used inpcapkitfor protocol
family extraction and representation.Engine ComparisonDue to the general overhead ofpcapkit, its extraction procedure takes
around0.2milliseconds per packet, which is already impressive but not enough
comparing to other popular extration engines availbale on the market, given the
fact thatpcapkitis acomprehensivepacket processing module.Additionally,pcapkitintroduced alternative extractionengines to accelerate
this procedure. By nowpcapkitsupportsScapy,DPKT, andPyShark.Test EnvironmentOperating SystemmacOS Ventura 13.4.1ChipApple M2 ProMemory16 GBTest ResultsEnginePerformance (ms per packet)dpkt0.010390_056723scapy0.091690_233567pcapkit0.200390_390390pyshark24.682185_018351InstallationNotepcapkitsupports Python versionssince 3.6.Simply run the following to install the current version from PyPI:pipinstallpypcapkitOr install the latest version from the gi repository:gitclonehttps://github.com/JarryShaw/PyPCAPKit.gitcdpypcapkitpipinstall-e.# and to update at any timegitpullAnd sincepcapkitsupports various extraction engines, and extensive
plug-in functions, you may want to install the optional ones:# for DPKT onlypipinstallpypcapkit[DPKT]# for Scapy onlypipinstallpypcapkit[Scapy]# for PyShark onlypipinstallpypcapkit[PyShark]# and to install all the optional packagespipinstallpypcapkit[all]# or to do this explicitlypipinstallpypcapkitdpktscapypysharkFor CLI usage, you will need to install the optional packages:pipinstallpypcapkit[cli]# or explicitly...pipinstallpypcapkitemoji
Package: pypcappy
PyPcapPy========**A Pure Python3 PcapNg reader**[![Build Status](https://travis-ci.org/TheBiggerGuy/pypcappy.svg?branch=master)](https://travis-ci.org/TheBiggerGuy/pypcappy)[![Coverage Status](https://coveralls.io/repos/github/TheBiggerGuy/pypcappy/badge.svg?branch=master)](https://coveralls.io/github/TheBiggerGuy/pypcappy?branch=master)[![Requirements Status](https://requires.io/github/TheBiggerGuy/pypcappy/requirements.svg?branch=master)](https://requires.io/github/TheBiggerGuy/pypcappy/requirements/?branch=master)[![PyPI version](https://badge.fury.io/py/pypcappy.svg)](https://badge.fury.io/py/pypcappy)Use===```pythonwith PcapNgFile('file_name.pcapng.gz') as pcap_file:for packet in pcap_file.packets:print(packet)```Why not pypcap or pypcapfile?=============================* Pure python* Will work on CPython, PyPy, Jpython or whatever* Python 3* No legacy packet data as strings* PcapNG* Only support for the new *next gen* format* Gzip* Build in support for both *.pcapng and *.pcapng.gz filesDownloads=========* Source tar.gz via [GitHub](https://github.com/TheBiggerGuy/pypcappy/releases/latest)* [PyPI](https://pypi.python.org/pypi/pypcappy)Links=====* http://www.winpcap.org/ntar/draft/PCAP-DumpFileFormat.html
Package: pypcd3
pypcdPure Python reader/writer for the PCLpcddata format for point clouds.Please go to the repositoryREADME.Licensepypcdis licensed under the terms of the MIT license. See the file
“LICENSE” for information on the history of this software, terms & conditions
for usage, and a DISCLAIMER OF ALL WARRANTIES.All trademarks referenced herein are property of their respective holders.Copyright (c) 2015–, Daniel Maturana
Package: pypcd4
pypcd4Descriptionpypcd4 is a modern reimagining of the originalpypcdlibrary,
offering enhanced capabilities and performance for working with Point Cloud Data (PCD) files.This library builds upon the foundation laid by the original pypcd while incorporating modern
Python3 syntax and methodologies to provide a more efficient and user-friendly experience.InstallYou can install pypcd4 via pip,pipinstallpypcd4How to useImport pypcd4frompypcd4importPointCloudRead from .pcd filepc:PointCloud=PointCloud.from_path("xyzi.pcd")PointCloud -> NumPy arrayarray:np.ndarray=pc.numpy()array.shape# (1000, 4)NumPy array -> PointCloud# Depends on number of features of your array# If PointXYZI,pc=PointCloud.from_xyzi_points(array)# If PointXYZL,pc=PointCloud.from_xyzl_points(array,label_type=np.uint32)ROS PointCloud2 Message -> PointCloudAdded in v0.4.0defcallback(msg):pc=PointCloud.from_msg(msg)pc.fields# ("x", "y", "z", "intensity", "ring", "time")Create custom conversion methodIf you cannot find preferred point type in pre-defined conversion methods,
you can create it easily like,fields=("x","y","z","intensity","new_field")types=(np.float32,np.float32,np.float32,np.float32,np.float64)pc=PointCloud.from_points(array,fields,types)Save as .pcd filepc.save("nice_point_cloud.pcd")LicenseThe library was rewritten and does not borrow any code from the originalpypcdlibrary.
Since it was heavily inspired by the original author's work, we extend his original BSD 3-Clause License and include his Copyright notice.TODOSupport ROS message conversionROS message -> PointCloudPointCloud  -> ROS messageVisualization
Package: pypcd-imp
pypcd-impWhat?Pure Python module to read and write point clouds stored in thePCD file
format,
used by thePoint Cloud Library.
Slightly adapted and improved fromklintananddimatira.
Can now handle Structured PointClouds (at least in binary compressed format)Why?You want to mess around with your point cloud data without writing C++
and waiting hours for the template-heavy PCL code to compile.You tried to get some of the Python bindings for PCL to compile
and just gave up.How does it work?It parses the PCD header and loads the data (whether inascii,binaryorbinary_compressedformat) as aNumpystructured array. It creates an instance of thePointCloudclass, containing the point cloud data aspc_data, and
some convenience functions for I/O and metadata access.Examplefrompypcd_impimportpypcd# also can read from file handles.pc=pypcd.PointCloud.from_path('foo.pcd')# pc.pc_data has the data as a structured array# pc.fields, pc.count, etc have the metadata# center the x fieldpc.pc_data['x']-=pc.pc_data['x'].mean()# save as binary compressedpc.save_pcd('bar.pcd',compression='binary_compressed')Is it beautiful, production-ready code?No.What else can it do?There's a bunch of functionality accumulated
over time, much of it hackish and untested.
In no particular order,Supportsascii,binaryandbinary_compresseddata.
The latter requires thelzfmodule.Decode and encode RGB into a singlefloat32number. If
you don't know what I'm talking about consider yourself lucky.Point clouds frompandasdataframes.Convert to and fromROSPointCloud2 messages.
Requires the ROSsensor_msgspackage with Python bindings installed.
This functionality uses code developed by Jon Binney under
the BSD license, included asnumpy_pc2.py.What can't it do?There's no synchronization between the metadata fields inPointCloudand the data inpc_data. If you change the shape ofpc_datawithout updating the metadata fields you'll run into trouble.I've only used it for unorganized point cloud data
(in PCD conventions,height=1), not organized
data like what you get from RGBD.While padding and fields with count larger
than 1 seem to work, this is a somewhat
ad-hoc aspect of the PCD format, so be careful.
If you want to be safe, you're probably better off
using neither -- just name each component
of your field something likeFIELD_00,FIELD_01, etc.It's slow!Try usingbinaryorbinary_compressed; using
ASCII is slow and takes up a lot of space, not to
mention possibly inaccurate if you're not careful
with how you format your floats.I found a bug / I added a feature / I made your code cleanerThanks! Please submit a pull request.I want to congratulate you / insult youOriginal Developers email isdimatura@cmu.edu.Copyright (C) 2015 - 2018 Daniel MaturanaMy email isjoel@stefamon.de.
Copyright (C) 2023 Joel Oswald
Package: pypci
PCI driver for pythonEnvironmentLinuxpython 3require :portio moduleInstallationpip install pypciUsage>>> import pypci

# look-up pci board
>>> board = pypci.lspci(vendor=0x1147, device=3214)

>>> board[0].vendor_id
4423

>>> board[0].bar
[BaseAddressRegister(type='mem', addr=2421170176, size=64),
 BaseAddressRegister(type='mem', addr=2421166080, size=64),
 BaseAddressRegister(type='mem', addr=2421174272, size=32)]


# read data
>>> bar2 = board[0].bar[2]
>>> pypci.read(bar2, 0x0c, 4)
b'\x00\x00\x00\x0c'


# write data
>>> pypci.write(bar[2], 0x04, b'\x01')

>>> data = struct.pack('<I', 1234567)
>>> pypci.write(bar[2], 0x00, data)
Package: pyPCIe
pyPCIe: Simple Python Module to access PCIe Endpoint BARspyPCIe provides a quick way to read/write registers in PCIe Base
Address Register (BAR) regions.pyPCIemmaps PCIe device BARs via theresourceXfiles in/sys/bus/pci/devices/[bus_id]for read/write and provides functions
for 32 bit read/write requests.Note: theresourceXfiles in sysfs are typically only accessible as
root. The python scripts using pyPCIe might need to be run as root.ExamplefrompypcieimportDevice# Bind to PCI device at "0000:03:00.0"d=Device("0000:03:00.0")# Access BAR 0bar=d.bar[0]# write 0xdeadbeef to BAR 0, offset 0x1000bar.write(0x1000,0xdeadbeef)# read BAR 0, offset 0x1004ret=bar.read(0x1004)
Package: pypckage
PypckagePypckage is a tool that facilitates the configuration of a python package.
You just need to run a command in the terminal and enter some information and Pypckage takes care of everything.
It creates the "setup.py, LICENSE, README.md, etc", all preconfigured. All you have to do is to customize the created files.Set upInstallpipinstallpypckageUpdatepipinstall--upgradepypckageSupportIf you want to contact me for questions, bugs, or problems or other :lixnew2@gmail.comPython versionSysall was written for python 3.CommandIn the terminal :pypck-build#output:#Path : Enter the path where your module is located, exemple : D:\Test#Package name : Enter the name you want to give to your package#Module name : Entre the name of your module, without (.py), just the name
Package: pypco
Pypco ReadMeStop writing boilerplate code to communicate with thePlanning Center OnlineREST API, and start using pypco! Pypco is a Python wrapper library that supports the full breadth of the PCO REST API. With pypco, you'll spend less time worrying about building and managing HTTP requests and more time building cool things.>>> Read the Docs (stable) <<<FeaturesBoilerplate Done for You:No need to manage HTTP requests, and useful helper functions included (authentication, iteration/pagination, new object templating, etc.)!Automatic rate limit handling:If you hit your rate limit, pypco will automatically pause requests and continue once your rate limit period has expired.Automatic Pagination:Pypco provides automatic pagination/object iteration, allowing you to quickly and easily retrieve large numbers of objects off from the PCO API.Simple Wrapper API:Using API wrappers can feel like learningtwonew APIs: the REST API itself and the wrapper you're using. Pypco's simple approach is built around the HTTP verbs you already know: GET, POST, PATCH, and DELETE. As a result, after a few minutes with the pypco docs you'll be spending your time in the PCO API docs instead and be on your way to getting things done.Full API Support:Pypco supports all versions of the PCO v2 REST API, and supports any combination of API versions you might use for each of the PCO apps.Examplesimportpypcopco=pypco.PCO("<app_id>","<app_secret>")# Print first and last names of everyone in Peopleforpersoninpco.iterate('/people/v2/people'):print(f'{person["data"]["attributes"]["first_name"]}'\f'{person["data"]["attributes"]["last_name"]}')# Create, save, and print a new person's attribspayload=pco.template('Person',{'first_name':'John','last_name':'Doe'})new_person=pco.post('/people/v2/people',payload)print(new_person['data']['attributes'])# Change our new person's last name and print attribspayload=pco.template('Person',{'last_name':'Smith'})updated_person=pco.patch(f'/people/v2/people/{new_person["data"]["id"]}',payload)print(updated_person['data']['attributes'])# Add an email address for our personpayload=pco.template('Email',{'address':'john.doe@mailinator.com','location':'Home'})email_object=pco.post(f'/people/v2/people/{updated_person["data"]["id"]}/emails',payload)# Iterate through our person's email addressesforemailinpco.iterate(f'/people/v2/people/{updated_person["data"]["id"]}/emails'):print(email['data']['attributes']['address'])Version 1.0Code written for pypco v0 will not be compatible with the v1 release. Because of changes in the PCO API (primarily the introduction of versioning) and the need for significantly improved performance, v1 is almost a complete rewrite. The result is a much more flexible, performant, and robust API wrapper. Though perhaps a bit less "pythonic", pypco v1.0.x will be much more maintainable going forward.If you're relying on pypco v0, you can still find the source codehere. Development will not continue on the v0 release, but feel free to submit an issue if you're relying on v0 and need help with a specific problem.LicensePypco is licensed under the terms of the MIT License.
Package: pypcp
Python library for Pgpool-II Communication Protocol(PCP).pyPCP provides a interface for administrators to perform management operation, such as gettingPgpool-IIstatus or terminatingPgpool-IIprocesses remotely.Pgpool-IIinstallation is not required on local machineInstallingInstall and Update using pip.$ pip install pypcpExample UsagefrompypcpimportPCP,ResultStateTypepcp=PCP()pcp.pcp_connect('remote_ip',9898,'postgres','secret')result=pcp.pcp_node_count()ifresultandpcp.PCPResultStatus(result)==ResultStateType.COMMAND_OK:print('Node Count  : ',result.pcp_get_data(0))pcp.pcp_disconnect()$ Node Count  : 2JSON SupportYou can also get results for each command in JSON format.print(result.pcp_get_json_data(0))$ {'command_status': 'success', 'node_count': 2}Supported CommandsFollowing commands are supported by pyPCP. Details about each command can be found atPCP Commandspcp_proc_countpcp_proc_infopcp_attach_nodepcp_detach_nodepcp_stop_pgpoolpcp_pool_statuspcp_node_countpcp_watchdog_infopcp_node_infopcp_stop_pgpoolpcp_promote_nodepcp_recovery_nodepcp_health_check_statspcp_reload_configpcp_set_backend_parameterPCP_CLIBased on pyPCP library, a cli utility is also available with name pcp_cli
pcp_cli provide functionality of all pcp_* utilities provided with Pgpool-II in a single app. Multiple commands are available with there respective sub-commands/groups.Following example show ‘pcp_cli node count’:$ pcp_cli node count -U postgres -H pgpool_host -v
Password:
Node Count
____________
2List of pcp_cli commands & sub-commands:pool statuspool stoppool reload-configpool check-health-statsnode countnode infonode attachnode detachnode promotenode recoveryprocess countprocess infowatchdog info
Package: py-pcqq
简介PY-PCQQ 是一个基于QQ轻聊版 7.9客户端协议的 Python 异步 QQ
机器人支持库，它会对 QQ
服务端发出的协议包进行解析和处理，并以插件化的形式，分发给消息所对应的命令处理器。除了起到解析消息的作用，PY-PCQQ 还通过
装饰器、异步、回调等方式实现了一套简洁易用的会话机制和插件机制，以便于用户快速上手。PY-PCQQ 在其底层与 QQ 服务端实现交互的部分使用的是标准库asyncio.open_connection所创建的异步 TCP
连接，这意味着在本协议库提供的内容多为异步操作，在调用相关函数或方法时应注意加上await关键字。本项目基本仅由 Python3
的标准库所实现，但若是在没有图形界面的系统中使用扫码登录，需要自行安装第三方库pillow使得程序能在终端环境中打印登录二维码。值得一提的是，在
Android 手机等移动设备中，你也可以通过pydroid3这样的应用来安装运行本协议库，例如:在手机上玩转QQ机器人？最后要说的是，这个项目仅仅只是本废物空闲之余的兴趣之作，存在着大量不成熟与不完善的地方。如果对
QQ 机器人开发有所需求，可以移步至更加强大与稳定的mirai或go-cqhttp等项目。已实现功能登录☒ 账号密码登录☒ 二维码登录☒ 本地Token重连发送消息☒ At☒ 文本☒ 表情☒ xml卡片☒ 图片接收消息☒ At☒ 文本☒ 图片☒ 表情接收事件☒ 群消息☒ 好友消息☒ 进群事件☒ 退群事件☒ 禁言事件其它操作☒ 修改群成员Card☒ 设置群成员禁言文档暂时咕咕中，请自行查看项目中的example.py查看案例
Package: pypcreate
PyPCreatePypcreate is a easy-to-use Python package creation tool.Installationpipinstallpypcreate# to upgradepipinstall--upgradepypcreateUsage1 mkdirTo create a directory with empty__init__.pyandREADME.md:pypcreate--mkdirdirectory_name2 yamlmkdirTo create a set up directories from a yaml file:pycreate--yamlmkdiryamlname.yamlThe format of yaml file should follow the following format:name:exampleroot:dir_1:dir_name:'example1'# directory namefiles:['__init__.py','README.md','example.py']# specify the empty files in the directorydir_1:dir_name:'sub_example1'# directory namefiles:['hello.py']dir_2:dir_name:'example2'# here is the name of directory 2files:['__init__.py']Notes:You must specify rootFor the sub-folder, you need to start withdir_1variableFor the directory name, the variable name should bedir_nameFor creating files, the variable name should befiles3 setpypTo create all empty setup files:setup.py,MANIFEST.in,environment.yml:pycreate --setpyp4 pyptempTo download all setup files to current directory:setup.py,MANIFEST.in,environment.yml:pycreate --pyptemp5 inittempTo download__init__.pytemplate:pycreate --inittemp6 mkdocs_tempTo download mkdocs template zip file:pypcreate--mkdocs_temp
Package: pypcurve
pypcurve: A Python Implementation of Simonsohn, Simmons and Nelson's 'p-curve'InstallationYou can install pypcurve with pip:pip install pypcurveUsing pypcurve1. Compulsory ReadingFirst and foremost,read the user guide to the p-curve. It is crucial that users
understand what p-curve can and cannot do, that they know which statistical results to select, and that they properly
prepare the disclosure table.2. Formatting the statistical resultspypcurve only requires a list of statistical results, stored in a list (or an array). Similar to the p-curve app,
pypcurve accepts the following formats of statistical tests:F(1, 302)=3.273t(103)=4.23r(76)=.42z=1.98chi2(1)=7.1In addition, pypcurve will accept raw p-values:p = .0023This is not recommended though: p-values are often weirdly rounded, so enter the statistical result instead if
it is reported in the paper.3. Using pypcurveA. InitializationFor this example, I will assume that your tests have been properly formatted, and stored in a column
called "Tests" of a .csv file.frompypcurveimportPCurveimportpandasaspddf=pd.read_csv("mydata.csv")pc=PCurve(df.Tests)If all your tests are properly formatted, there will be no error, and pcurve will be initialized properly.B. Printing the p-curve outputNext, you can print the summary of the p-curve, as you would see it using the web-app:pc.summary()This will output the p-curve plot, as well as the table summarizing the binomial and Stouffer tests of the
p-curve analysis. You can get the plot alone, or the table alone, using the methodspc.plot_pcurve()andpc.pcurve_analysis_summary().C. Power EstimationYou can use pycurve to estimate the power of the design that generated the statistical tests:pc.estimate_power()will return the power estimate, and the (lower, upper) bounds of 90% confidence interval.pc.plot_power_estimate()will plot the power estimate (as the webapp does).D. Accessing the results of the p-curve analysisYou can directly access the results of the p-curve analysis using three methods:pc.get_stouffer_tests()will recover the Z and p-values of the Stouffer testspc.get_binomial_tests()will recover the p-values of the binomial testspc.get_results_entered()will recover the statistical results entered in the p-curve, and the pp-values and z scores
associated with the different alternatives to which they are compared.You can also directly check if the p-curve passes the cutoff for evidential value, and the cutoff for
inadequate evidence (as defined inBetter P-Curve),
using the propertiespc.has_evidential_valueandpc.has_inadequate_evidenceVersion HistoryThe app is still in beta, so please take care when interpreting the results. I have tested pypcurve against the
p-curve app using multiple examples: There are occasional minor deviations between the two, because of the way R (vs.
Python) compute the non-central F distribution.Beta0.1.0First beta release.
Package: pypda
pyPDAA Pythonic toolkit to generate synthetic blood pressure waveforms based on principle of pulse decomposition analysis (PDA).Free software: MIT licenseQuick StartUseIt is recommended that pyPDA should be setup in a Pythonvirtual environment.python -m venv venv
source venv/bin/activate
pip install pyPDA
pypda pulse --plot-dir work_dir --png # plot single beat waveform to word_dir#plot10secondpulsewaveformof65bpm,sampledat90Hztoword_dirpypda sample --bpm 65 --plot-dir work_dir --png --length 10 --sampling-rate 90frompypda.pulse_modelimportPulseModelRawpulse_waveform=PulseModelRaw()importmatplotlib.pyplotaspltplt.plot(pulse_waveform.pulse_waveform)frompypda.waveletsimportTriangGaussiantriangular_pulse=TriangGaussian()triangular_pulse.shift(10)# optional horizontal shifting of waveformplt.plot(triangular_pulse.pulse_waveform)# addition operator is supportedsuperpositioned_pulse=pulse_waveform+triangular_pulseplt.plot(superpositioned_pulse.pulse_waveform)DevelopmentPlease feel free to fork a copy on GitHUB. Pull requests are very welcome. To report an issue, please useGitHub issue tracker.python -m venv venv
source venv/bin/activate
git clone git@github.com:taoyilee/pyPDA.git
pip install -r requirements_dev.txt#Startcoding.Screen CaptureReferencesBaruch, Martin C., et al. “Pulse decomposition analysis of the digital arterial pulse during hemorrhage simulation.” Nonlinear biomedical physics 5.1 (2011): 1.[PDF]History0.1.0 (2020-02-19)First release on PyPI.0.2.1 (2020-03-02)Add sampler for test data (different parameters)
Package: pyPDB2
This library allows you to create dialog boxes.
Using classes, create one of the following boxes:ynBox()
errorBox()e.gbox = ynBox()To draw the box, you must use the .draw() method:box.draw()Change Log0.0.1 (4/07/2020)First Release0.0.2 (10/07/2020)Second ReleaseFunction returns boolean value instea of integerReturns a True if yes is clicked, a False if no is clickedNew error box