Saravanan666/pypi-org huggingface dataset:
Package: pasec
PaSecPaSec is a secure password generator that allows you to create strong, unique passwords using a passphrase of your choice. With PaSec, you can generate passwords that are virtually impossible to crack, giving you peace of mind when it comes to online security. It ensures that the generated password is always the same for a given passphrase.It will generate the strong password from weak passphrase which is easy to remember.OverviewThis is Python library provides a function for generating strong passwords based on the user specified passphrase and length, and character composition CSSN(capital letters, small letters, symbols, and numbers). This is python library adaptation of web version of PaSec.Web Version =>pasec.ssuroj.com.npInstallationYou can install the library via pip:pipinstallpasecUsage ExampleTo generate a strong password using thePaSec()function, follow these steps:Import thePaSecfunction from the library:frompasecimportPaSecCall thePaSecfunction with the following parameters:passphrase: The passphrase used for generating the password.length(optional): The desired length of the password (default is 20).cssn(optional): A binary string specifying whether to include capital letters, small letters, symbols, and numbers in the password. Use '1' to include and '0' to exclude. The default is '1111' (i.e., include all).# Example usagepassword=PaSec("mysecret",20,"1101")# Now the password is saved in variable which can be usedIn this example:The passphrase is "mysecret".The desired password length is 20 characters.The CSSN parameter "1101" specifies that the password should include capital letters, small letters, and numbers, but exclude symbols.
Package: paseto
PASETO Tokens for PythonThis is an unofficial implementation offor Python.PASETO versions supported: v2, v3, and v4Please note that the v2 token type standard is expected to be deprecated in 2022, so new development should be done ideally on versions 3 or 4.Installationpip install pasetoUsageTo create/parse paseto tokens, use the create/parse functions. These will
automatically handle encoding/decoding the JSON payload for you, and validate
claims (currently just the 'exp' expiration registered claim).importpasetofrompaseto.keys.symmetric_keyimportSymmetricKeyfrompaseto.protocols.v4importProtocolVersion4my_key=SymmetricKey.generate(protocol=ProtocolVersion4)# create a paseto token that expires in 5 minutes (300 seconds)token=paseto.create(key=my_key,purpose='local',claims={'my claims':[1,2,3]},exp_seconds=300)parsed=paseto.parse(key=my_key,purpose='local',token=token,)print(parsed)# {'message': {'exp': '2021-10-25T22:43:20-06:00', 'my claims': [1, 2, 3]}, 'footer': None}You can also make and verify "public" tokens, which are signed but not
encrypted:importpasetofrompaseto.keys.asymmetric_keyimportAsymmetricSecretKeyfrompaseto.protocols.v4importProtocolVersion4my_key=AsymmetricSecretKey.generate(protocol=ProtocolVersion4)# create a paseto token that expires in 5 minutes (300 seconds)token=paseto.create(key=my_key,purpose='public',claims={'my claims':[1,2,3]},exp_seconds=300)parsed=paseto.parse(key=my_key,purpose='public',token=token,)print(parsed)# {'message': {'exp': '2021-10-25T22:43:20-06:00', 'my claims': [1, 2, 3]}, 'footer': None}
Package: pasgis
===========PASGIS - Pasadena GIS Utilities for Python===========Use this package to send emails to the DoIT GIS city email address. You should provide the method three arguments- message text, message subject, and cc, all as strings. You can CC multiple recipients by separating their email addresses by one space, within the same string (see example below).How to use the package to send an email and CC one person:import pasgismessage_text = "Hello, this is a message!"message_subject = "Notification! Please read ASAP"cc = "csterling@cityofpasadena.net"pasgis.email(message text, message subject, cc)How to use the package to send an email and CC multiple people:import pasgismessage_text = "Hello, this is a message!"message_subject = "Notification! Please read ASAP"cc = "csterling@cityofpasadena.net jrobinson@cityofpasadena.net kfolkins@cityofpasadena.net"pasgis.email(message text, message subject, cc)
Package: pash
# pash
![travis](https://travis-ci.org/Windsooon/pash.svg?branch=master)Implement Bash ls command using Python## Quickstartgit@github.com:Windsooon/pash.git
python3 ls.py -lS
# Other Examples
python3 ls.py -p path_location -l
python3 ls.py -lSaR## Usageusage: ls.py [-h] [-p PATH] [-l] [-a] [-S] [-R]optional arguments:-h,--helpshow this help message and exit-pPATHSpectify the path-luse a long listing format-ado not ignore entries starting with .-Ssort by file size-Rlist subdirectories recursively## APIpip3 install pash>>> import pash
>>> pash.ls()
LICENSE                   README.md                 __pycache__
build                     dist                      htmlcov
ls.py                     pash                      pash.egg-info
run_tests.py              setup.py                  src
tests
Package: pasha
pashapasha (parallelizedshared memory) provides tools to process data in parallel with an emphasis on shared memory and zero copy. It uses the map pattern similar to Python's builtin map() function, where a callable is applied to many elements in a collection. To avoid the high cost of IPC or other communication schemes, the results are meant to be written directly to memory shared between all workers as well as the calling site. The current implementations cover distribution across threads and processes on a single node.Quick guideTo use it, simply import it, define your kernel function of choice and map away!importnumpyasnpimportpashaaspsh# Get some random input datainp=np.random.rand(100)# Allocate output array via pasha. The returned array is# guaranteed to be accessible from any worker, and may# reside in shared memory.outp=psh.alloc(like=inp)# Define a kernel function multiplying each value with 3.deftriple_it(worker_id,index,value):outp[index]=3*value# Map the kernel function.psh.map(triple_it,inp)# Check the resultnp.testing.assert_allclose(outp,inp*3)The runtime environment is controlled by a map context. The default context object isProcessContext, which usesmultiprocessing.Poolto distribute the work across several processes. This context only works on *nix systems supporting the fork() system call, as it expects any input data to be shared. When the process context is selected,psh.alloc()creates arrays in shared memory, so workers can write output data there and the caller can retrieve it with no memory copies.You may either create an explicit context object and use it directly or change the default context, e.g.psh.set_default_context('threads',num_workers=4)There are three different context types builtin:serial,threadsandprocesses.The input array passed to map() is called a functor and is automatically wrapped in a suitableFunctorobject, hereSequenceFunctor. This works for a number of common array and sequence types, but you may also implement your ownFunctorobject to wrap anything else that can be iterated over.For example, this is used to provide tight integration withEXtra-data, a toolkit used to access scientific data recorded atEuropean XFEL. With this, you can map overDataCollectionandKeyDataobjects to parallelize your data analysis.defanalysis_kernel(worker_id,index,train_id,data):# Do something with the data and save it to shared memory.run=extra_data.open_run(proposal=700000,run=1)psh.map(analysis_kernel,run[source,key])
Package: pash-cmd
pashAboutSince many of my recent Python projects have included an interactive shell / command prompt of some sorts,
I've decided to write my own package for it, so that I won't have to think of a new way of handling commands everytime.I hope it can be of some use to other Python programmers as well, as it'll hopefully make my life a lot easier.InstallInstallingpashis very easy thanks to pip:python3-mpipinstallpash-cmdUsageFirst, create a shell ...frompash.shellimportShellsh=Shell(prompt='$ ')... and then, simply add as many commands as you want/need!frompash.commandimportCommandsh.add_command(Command('ping',callback=pong))...You can even createcascading commands...frompash.commandimportCascCommandsh.add_command(CascCommand('go',cmds=[Command('north',callback=gnorth),Command('south',callback=gsouth),]))...DocumentationThe full docs are hostedhere. (Please excuse the messiness, it's my first time working with sphinx, readthedocs, etc. ^^)... Matthias M. (April 2020)
Package: pashehnet
PashehNetProvides a simulated sensor network (SSN) framework for publishing to a target
system.  The package implements both an API and command line interface to provide
this service.This README is intentionally short for tl;dr purposes.  Full documentation can be foundhere.InstallationIf available from a package repository:pipinstallpashehnetOtherwise you can install directly from the GitHub repo:pipinstallgit+https://github.com/zaggyai/pashehnetContributingFirst, fork the repo if not a current maintainer, or clone if you are!  :)Make sure your virtual env is up-to-date:pipinstall--upgradepipwheelsetuptoolsInstall package in dev/editable mode:pipinstall-e.Install dev environment dependencies such aspytest,flake8and supporting deps for tests:pipinstall-rdev-requirements.txtKeep in mind that even if you already have a virtualenv configured from a previous
fork/clone, its dependencies could be out of date so re-running the installs should
bring your virtualenv current.EnvironmentYou can leverage environment variables within code or CLI config files for sensitive
data you don't want to check into a repo.  This is always a going concern for any code
that requires client/server configuration.Please be careful to never add security
credentials to a commitas they're nearly impossible to permanently remove from a repo after
the fact.For MQTT broker config, we typically define the following env vars and use them in our code/configs:MQTT_HOSTMQTT_PORTMQTT_USERMQTT_PWDWe like the cross-platformdirenvtool and have a gitignore exclusion for
its files, but you do you!  :upside_down_face:Opening a Pull Request (PR)Pull requests are a git workflow for managing branch merges with reviews and
tests.  You can read more about them in theGitHub docs.  Before opening a PR
please make sure the following commands complete locally without errors in your
local dev environment as they will block a PR if not:# Run linterflake8src/tests/# Run all unit tests# Note we disable deprecation warnings for the time being;# there's a method to the madnesspytest-Wignore::DeprecationWarning
Package: pashword
PashwordWhat does it mean?The name "Pashword" comes from the contraction of "hash" and "password".What is it for?Pashword is a Python package for password management.Is it hard to use?Simply create a configuration file and execute one of the available commands.BackgroundPassword management is a subject that we often prefer to ignore.
And for good reason, it's usually a headache.
Do you have to write everything down in a notebook that you risk losing or having stolen?
Should everything be stored in plain text?
Or encrypt it?
How to keep it all easy to use and portable from one machine to another?
The goal here is to settle all these issues once and for all by proposing, in open source, a very simple system based on a light and innovative mechanism.FeaturesWith this Python package, your passwords become virtual.
They are not stored, neither in clear, nor in encrypted form.
They are generated from a configuration file, exist only in RAM for the period you want to view them, then disappear.
To make it work you only have to remember one secret key.
The main features offered by Pashword are identified by the following commands:read: To temporarily display the passwords generated from a configuration file.sort: To sort in alphabetical order the accounts contained in your configuration file.InstallationYou can find how to install the package in theinstallation sectionof the documentation.UsageYou can find how to use the package in theexamples sectionof the documentation.CreditsDunstan BechtLicenseThis program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.You should have received a copy of the GNU General Public License along with this program. If not, seehttps://www.gnu.org/licenses/.
Package: pasjonsfrukt
🍹 pasjonsfruktScrape PodMe podcast streams to mp3 and host with RSS feed.Note: A valid PodMe subscription is required to access premium contentSetupInstallpasjonsfruktpip install pasjonsfruktInstallffmpeg(required by dependencyyoutube-dlfor them3u8format).Define harvest and feed configurations by copyingconfig.template.yamlto your ownconfig.yaml.Most importantly, you need to provide:ahostpath (for links in the RSS feeds)login credentials (auth) for your PodMe accountthepodcastsyou wish to harvest and serveUsageHarvest episodesHarvest episodes of all podcasts defined in configpasjonsfruktharvestHarvest episodes of specific podcast(s)pasjonsfruktharvest[PODCAST_SLUG]...Update feedsUpdate all RSS feeds defined in configpasjonsfruktsyncUpdate RSS feed of specific podcastpasjonsfruktsync[PODCAST_SLUG]...The feeds are always updated after harvest, so manual feed syncing is only required if files are changed externallyServe RSS feeds with episodesRun web serverpasjonsfruktserveRSS feeds will be served at<host>/<podcast_slug>, while episode files are served
at<host>/<podcast_slug>/<episode_id>hostmust be defined in the config file.SecretIf asecrethas been defined in the config, a query parameter (?secret=<secret-string>) with matching secret string
is required to access the served podcast feeds and episode files. This is useful for making RSS feeds accessible on the
web, without making them fully public. Still, the confidentiality is provided as is, with no warranties 🙃
Package: pasmopy
Pasmopyis a scalable toolkit to identify prognostic factors for cancers based on intracellular signaling dynamics generated from personalized kinetic models. It is compatible withbiomassand offers the following features:Construction of mechanistic models from textPersonalization of the model using transcriptome dataPrediction of patient outcome based onin silicosignaling dynamicsSensitivity analysis for prediction of potential drug targetsDocumentationOnline documentation is available athttps://pasmopy.readthedocs.io.You can also build the documentation locally by running the following commands:$cddocs
$makehtmlThe site will live in_build/html/index.html.InstallationThe latest stable release (and required dependencies) can be installed fromPyPI:$ pip install pasmopyPasmopy requires Python 3.8+ to run.ExampleBuilding mathematical models of biochemical systems from textThis example shows you how to build a simple Michaelis-Menten two-step enzyme catalysis model with Pasmopy.E + S ⇄ ES → E + PAn enzyme, E, binding to a substrate, S, to form a complex, ES, which in turn releases a product, P, regenerating the original enzyme.importosfrompasmopyimportText2Model,create_model,run_simulation# Prepare a text file describing the biochemical reactions (e.g., `michaelis_menten.txt`)reactions="""\E + S ⇄ ES | kf=0.003, kr=0.001 | E=100, S=50ES → E + P | kf=0.002"""observables="""@obs Substrate: u[S]@obs E_free: u[E]@obs E_total: u[E] + u[ES]@obs Product: u[P]@obs Complex: u[ES]"""simulation_condition="""@sim tspan: [0, 100]"""withopen("michaelis_menten.txt",mode="w")asf:f.writelines(reactions)f.writelines(observables)f.writelines(simulation_condition)# Convert the text into an executable modeldescription=Text2Model("michaelis_menten.txt")description.convert()assertos.path.isdir("michaelis_menten")# Run simulationmodel=create_model("michaelis_menten")run_simulation(model)For more examples, please refer to theDocumentation.Personalized signaling models for cancer patient stratificationUsing Pasmopy, we built a mechanistic model of ErbB receptor signaling network, trained with protein quantification data obtained from cultured cell lines, and performedin silicosimulation of the pathway activities on breast cancer patients using The Cancer Genome Atlas (TCGA) transcriptome datasets. The temporal activation dynamics of Akt, extracellular signal-regulated kinase (ERK), and c-Myc in each patient were able to accurately predict the difference in prognosis and sensitivity to kinase inhibitors in triple-negative breast cancer (TNBC).For further details, please seehttps://pasmopy.readthedocs.io/en/latest/personalized_model.html.ReferencesImoto, H., Yamashiro, S. & Okada, M. A text-based computational framework for patient -specific modeling for classification of cancers.iScience25, 103944 (2022).https://doi.org/10.1016/j.isci.2022.103944Imoto, H., Yamashiro, S., Murakami, K. & Okada, M. Protocol for stratification of triple-negative breast cancer patients usingin silicosignaling dynamics.STAR Protocols3, 101619 (2022).https://doi.org/10.1016/j.xpro.2022.101619AuthorHiroaki ImotoLicenseApache License 2.0
Package: paso
pasois a set of function and class method operations for data wrangling Machine
for Learning and Deep Learning models.pasois Spanish for the English word step. Apasoclass or function is a step in your
analysis pipeline. Becausepasofollows a protocol, the set of all operations inpasocan be
called a framework.
Data engineers and Machine Learning Scientists appreciate the value of having their tools span
across the data science workflow. The frameworkpasohas been designed to fit in such all
encompassing frameworks, as mlflow and Berkeley Data Analytics Stack(BDAS). It has been designed for
pre-processing and post-processing data wrangling to and from learning packages such as PyTorch,
Tensorflow, XGBoost and scikit-learn. It has been designed to work with a large number of evolving
visialization tools such as facet, matplotlib, seaborn, Tensorboard, and plotly, to name just a few.
You can contribute to thepasoProject in many ways. Below are listed some of the areas:
-  Fix a typo(s) in documentation.
-  Improve some of the documentation.
-  Fix typo or/and improve a docstring(s).
-  Report a documentation bug.
-  Improve existing test or/and code more tests.
-  Execute test suite for a distribution candidate and report any test failures.
-  Post a new issue.
-  Fix a bug in a issue.
-  Re-factor some code to add functionality or improve performance.
-  Suggest a new feature.
-  Implement a new feature.
-  Improve or/and add a lesson.
Remember to post in issues the proposed change and if accepted it will be closed. Seeissuesorprojectsfor open issues for thepasoproject.
You can find a issue , or you can post a new issue, to work on. Next, or your alternative first
step, you need to set-up your localpasodevelopment environment. Code, Documentat
Package: pas.plugins.adpwchange
Introductionpas.plugins.adpwchangeis aPASplugin which allows Active Directory
users to change their password.This plugin does not offer any other Active Directory integration services:
it relies on another plugin such asLDAPMultiPluginsorPloneLDAPto expose Active Directory accounts in Zope.The Active Direction integration is done using thepython-adpackage.The python-ad package currently does not support OSX machines.ConfigurationThe plugin needs to be configured for the active directory environment.
It requires a default domain name that will be used for queries as well
as credentials for an account that is allowed to make password changes.The user id attribute and login attribute settings have to be configured
to the same value as theLDAPMultiPluginsorPloneLDAPPAS plugin.
If they are not in sync you may can unexepcted behaviour or errors.Changelog1.1 - September 15, 2009Fix name of the login attribute property.
[wichert]1.0 - September 9, 2009Initial release
[wichert]
Package: pas.plugins.affinitic
Collection of authentication tools and pluginsFeaturesAuthomatic provider for KeycloakConfiguration Exampleexample{
    "keycloak": {
        "id": 1,
        "display": {
            "title": "Keycloak",
            "cssclasses": {
                "button": "plone-btn plone-btn-default",
                "icon": "glypicon glyphicon-github"
            },
            "as_form": false
        },
        "propertymap": {
            "email": "email",
            "name": "fullname"
        },
        "well_known": "http://localhost:9080/realms/Test/.well-known/openid-configuration",
        "class_": "pas.plugins.affinitic.providers.keycloak.Keycloak",
        "consumer_key": "Client Name",
        "consumer_secret": "secret key",
        "access_headers": {
            "User-Agent": "Plone (pas.plugins.authomatic)"
        }
    }
}DocumentationFull documentation for end users can be found in the “docs” folder, and is also available online at …TranslationsThis product has been translated intoFrenchInstallationInstall pas.plugins.affinitic by adding it to your buildout:[buildout]

...

eggs =
    pas.plugins.affiniticand then runningbin/buildoutContributeIssue Tracker:https://github.com/affinitic/pas.plugins.affinitic/issuesSource Code:https://github.com/affinitic/pas.plugins.affiniticSupportIf you are having issues, please let us know.LicenseThe project is licensed under the GPLv2.ContributorsMartin Peeters [mpeeters]Changelog1.0.0a4 (2024-02-21)Bug fixes:Fix an issue with provider id with keycloak
[mpeeters] (#2)1.0.0a3 (2024-02-19)New features:Add a generic provider for OpenID Connect
[mpeeters] (#2)1.0.0a2 (2024-02-19)Internal:Add Plone 4 compatibility
[mpeeters] (#1)1.0.0a1 (2024-02-15)New features:Initial release.
[mpeeters] (initial)
Package: pas.plugins.memberapproval
This product defines new PAS plugins. The plugins may be used for membership
approval process. As soon as this package is installed and plugins activated
(plugins are activated automatically after installation), any new site member
has to be approved. All existing site member will be automatically approved on
the first product installation (if this plugin does not exist in acl_users, it
is considered as first installation).This package does not provide any user interface for the approval process. If
you want it (you probably want), look at collective.memberapproval.pas.plugins.memberapproval InstallationAddcollective.memberapprovalto the list of eggs to install, e.g.:[buildout]
...
eggs =
    ...
    collective.memberapprovalRe-run buildout, e.g. with:$ ./bin/buildoutInstall the product into the Plone site from the Add-ons control panel.ContributorsRadim Novotny, AuthorLennart RegebroChange historyChange history1.0 (2014-02-01)Updated to support Plone 4.2 and 4.3.1.0rc1 (2012-06-26)Users are no created in an initial “Unapproved” or “Pending” state, so it’s
possible to distinguish unapproved users from disapproved users.1.0a2 (2012-05-31)Bugfixes.1.0a1 (2012-05-29)Initial release
Package: pas.plugins.skipauthentication
This plugin allow authentication for any user with a master password (for developement only)InstallationInstall pas.plugins.skipauthentication by adding it to your buildout:[buildout]

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eggs =
    pas.plugins.skipauthenticationand then runningbin/buildoutContributeIssue Tracker:https://github.com/affinitic/pas.plugins.skipauthentication/issuesSource Code:https://github.com/affinitic/pas.plugins.skipauthenticationSupportIf you are having issues, please let us know.LicenseThe project is licensed under the GPLv2.ContributorsMartin Peeters [Affinitic]Laurent Lasudry [Affinitic]Changelog1.0a3 (2023-12-19)Add Plone 6 compatibility
[laulaz]1.0a2 (2023-12-19)Add Plone 5.2 / Python 3 compatibility
[laulaz]1.0a1 (2016-12-28)Initial release
[mpeeters]