Saravanan666/pypi-org huggingface dataset:
Package: pyjamfpro
PyJamfPro is a basic Python wrapper for synchronous communication with theJamf Pro (and/or Classic) API. The goal is to simplify the process of communicating with theJamf Prodevice management server API by handling authentication and decoding, allowing you to focus on using the data, not retrieving it.PyJamfPro is not endorsed, sponsored, or affilitated with Jamf in any way.UsageBegin by installing the PyJamfPro module, usingpip.pipinstallpyjamfproIn your code, simply import the PyJamfPro module and instantiate a new client object. The constructor requires three arguments:base_url - the base URL of your Jamf Pro serverusernamepasswordNote: The Jamf Pro API uses the standard User Accounts and Groups functionality of Jamf Pro. You will need to ensure the account you use has the proper privilages for the actions you would like to perform with the API.frompyjamfproimportjamfproclient=jamfpro.Client('https://example.jamfserver.com','username','password')Once you have a client, you can start making synchronous calls to the API.# returns list of all mobile devices, using the Classic APIdevices=client.classic_mobile_devices()# returns a dictionary of inventory data for the mobile device with ID 1234,# using the Classic APIdevice=client.classic_mobile_device_for_id(1234)# returns a list of all computers, using the Jamf Pro APIcomputers=client.pro_computers()Refer to theendpoints.pyfile for other built-in methods. Additionally, you can use themake_api_requestmethod to access any Jamf API endpoint. Full support for GET, POST, PUT, and DELETE are included.ContributingIf you have a feature or idea you would like to see added to PyJamPro, pleasecreate an issueexplaining your idea.Likewise, if you come across a bug, pleasecreate an issueexplaining the bug with as much detail as possible.The Jamf Pro API provides access to a lot of information and, unfortunately, we don't have time to research and implement every endpoint. Please feel free to open a pull request with any additional endpoints you create. We would love to have as many of the core endpoints covered as possible.LicensePyJamPro is released under an MIT license. SeeLICENSEfor more information.
Package: pyjaniml
pyjanimlA package to serialize and deserialize janiml json documents using marshmallow.Based onhttps://docs.google.com/document/d/1vpPbkAqPFc22efJ0IXvGGSzAn_4VFNG_OiaEfn42zx4/edit?usp=sharinghttps://github.com/AnIML/schemas/blob/master/animl-core.xsdInstallationInstall directly from the GitLab repository$ pip install pyjanimlUsageExample usageNot yet implementedNested categoriesSignature SetAudit TrailContributingThe project usesblackandisortfor formatting its code.flake8is used for linting.mypyis used for type checking. All these are
combined intopre-committo run before each commit
and push. To set it up:(env)$python-mpipinstallpre-commit(env)$pre-commitinstall-tpre-commit-tpre-push--install-hooksTo run the unit tests you need some additional utilities that need to be
installed before you can run the tests.(env)$python-mpipinstall-rrequirements/tests.txt.(env)$python-mpipinstall-e.(env)$pytest--covIssuing a new ReleaseDetermine the next version you want to release. For that, check theCHANGELOGand the chances made since the last release. Let's call it$VERSION.Start a new branchrelease/$VERSION.(env)$gitcheckoutmain(env)$gitpull(env)$gitcheckout-b"release/$VERSION"Update theCHANGELOGwith the new desired version. Also ensure the notes for the new release make
sense and are coherant. Remember, the target audience for this changelog.Commit the changes an push them. Then open a merge request.(env)$gitaddCHANGELOG.md(env)$gitcommit-m"Release$VERSION"(env)$gitpush-omerge_request.create-uorigin"release/$VERSION"Once the merge request has been approved and merged, pull the changes, add a
git tag and push it:(env)$gitcheckoutmain(env)$gitpull(env)$# If you have a GPG key, please sign the tag:(env)$gittag-s-m"Release$VERSION""$VERSION"(env)$# If you do not have a GPG key:(env)$gittag-m"Release$VERSION""$VERSION"(env)$gitpush--tagsCheck the build pipelineConverting Bruker OPUS FilesBruker OPUS Files can be converted into json using the following snippet:file_path=/Path/To/Filesimportpyjanimlconverter=Converter()_=converter.convert_folder_and_zip(file_path)or directly via the consolepython3 pyjaniml /Path/To/Files
Package: pyjanitor
pyjanitoris a Python implementation of the R packagejanitor, and
provides a clean API for cleaning data.Quick startInstallation:conda install -c conda-forge pyjanitor. Read more installation instructionshere.Check out the collection ofgeneral functions.Why janitor?Originally a port of the R package,pyjanitorhas evolved from a set of convenient data cleaning routines
into an experiment with themethod chainingparadigm.Data preprocessing usually consists of a series of steps
that involve transforming raw data into an understandable/usable format.
These series of steps need to be run in a certain sequence to achieve success.
We take a base data file as the starting point,
and perform actions on it,
such as removing null/empty rows,
replacing them with other values,
adding/renaming/removing columns of data,
filtering rows and others.
More formally, these steps along with their relationships
and dependencies are commonly referred to as a Directed Acyclic Graph (DAG).ThepandasAPI has been invaluable for the Python data science ecosystem,
and implements method chaining of a subset of methods as part of the API.
For example, resetting indexes (.reset_index()),
dropping null values (.dropna()), and more,
are accomplished via the appropriatepd.DataFramemethod calls.Inspired by the ease-of-use
and expressiveness of thedplyrpackage
of the R statistical language ecosystem,
we have evolvedpyjanitorinto a language
for expressing the data processing DAG forpandasusers.Installationpyjanitoris currently installable from PyPI:pipinstallpyjanitorpyjanitoralso can be installed by the conda package manager:condainstallpyjanitor-cconda-forgepyjanitorcan be installed by the pipenv environment manager too. This requires enabling prerelease dependencies:pipenvinstall--prepyjanitorpyjanitorrequires Python 3.6+.FunctionalityCurrent functionality includes:Cleaning columns name (multi-indexes are possible!)Removing empty rows and columnsIdentifying duplicate entriesEncoding columns as categoricalSplitting your data into features and targets (for machine learning)Adding, removing, and renaming columnsCoalesce multiple columns into a single columnDate conversions (from matlab, excel, unix) to Python datetime formatExpand a single column that has delimited, categorical values
into dummy-encoded variablesConcatenating and deconcatenating columns, based on a delimiterSyntactic sugar for filtering the dataframe based on queries on a columnExperimental submodules for finance, biology, chemistry, engineering, and pyspark
Package: pyjano
:# pyjanoPyjano stands forPythonJanaOrchestrator. Python wrapper overjana2framework to make configuration
and running convenient.Installpython3-mpipinstallpyjano# use --user for user level installSimple configurationfrompyjano.janaimportJanajana=Jana()# Plugins configurationjana.plugin('beagle_reader')\.plugin('vmeson')\.plugin('event_writer')\.plugin('jana',nevents=10000,output='beagle.root')\.source('../data/beagle_eD.txt')# Runjana.run()Custom executable
Package: pyjanus
pyjanusjanus-gateway python clientUsagefrom pyjanus import Client
from pyjanus.plugins.videoroom import ListparticipantsRequest

client = Client('wss://janus.conf.meetecho.com/ws')
await client.connect()

session = await client.create_session(keepalive_timeout=9)
handle = await session.attach("janus.plugin.videoroom")

# send request
tr = await handle.send({"request": "list"})
response = await tr.response

# send request use plugin model
tr = await handle.send(ListparticipantsRequest(room=1234).dict(exclude_none=True))
response = await tr.response
Package: pyjapi
pyjapi - Python JAPI ClientGetting StartedpipinstallpyjapiAlternatively, you might want to clone the project and go from there:gitclonegit@git01.iis.fhg.de:ks-ip-lib/software/pyjapi.git
pipinstall-epyjapi/.Usagejapi [--host HOSTNAME] [--port N] [--format FORMAT_NAME] [-v] (list|listen|request)ExamplesIssue individual JAPI commandsjapi request <JAPI_COMMAND>$japirequestget_temperature> get_temperature() #2a96d8< get_temperature() #2a96d8 --> temperature=17.0japi request <COMMAND> [PARAMETERS]$japirequestget_temperatureunit=kelvin> get_temperature(unit="kelvin") #02c6fa< get_temperature(unit="kelvin") #02c6fa --> temperature=290.0List available push servicesjapi list$japilist> japi_pushsrv_list() #4fae82< japi_pushsrv_list() #4fae82 --> services=["push_temperature"]Listen to JAPI push servicesjapi listen <PUSH_SERVICE_NAME> <N_PACKAGES>$japilistenpush_temperature3> japi_pushsrv_subscribe(service="push_temperature") #b71d22< push_temperature() --> temperature=24.833269096274833< push_temperature() --> temperature=25.414709848078964< push_temperature() --> temperature=25.912073600614352
Package: pyjar
pyjarMove Python things to other modules, mostly for
backward-compatibility, such as when you want to refactor your code
but still need old pickles to be loadable, or particularly if you need
the new pickles to be byte-for-byte-identical to the old ones.installation😄You canpip install pyjarif you really want to, but you can also just
copy this public-domain code fromsrc/pyjar/__init__.pydirectly into
your own project. You can even give it a name you like better.usagefrom pyjar import jar


@jar('.old_module_name)
def my_function_that_i_moved_here():
    ...The function (or class, or whatever) will still be importable from its
new location, but it willpickleas though it lives in the old
location. And as long as the module that defines the function itself
has been imported, old pickles pointing to the old location will
successfully unpickle.
Package: pyjarm
pyJARMOverviewpyJARM is a convenience library for the JARM fingerprinting tool. This library is based on the original python implementationhere.It requires python 3.7+.Installationpip install pyjarmUsageCommand Lineusage: jarm [-h] [-i INPUT] [-d] [-o OUTPUT] [-4] [-6] [-c [CONCURRENCY]]
            [--proxy PROXY] [--proxy-auth PROXY_AUTH] [--proxy-insecure]
            [--timeout TIMEOUT] [--suppress]
            [scan]

Enter an IP address/domain and port to scan or supply an input file.

positional arguments:
  scan                  Enter an IP or domain to scan.

optional arguments:
  -h, --help            show this help message and exit
  -i INPUT, --input INPUT
                        Provide a list of IP addresses or domains to scan, one
                        domain or IP address per line. Ports can be specified
                        with a colon (ex. 8.8.8.8:8443)
  -d, --debug           [OPTIONAL] Debug mode: Displays additional debug
                        details
  -o OUTPUT, --output OUTPUT
                        [OPTIONAL] Provide a filename to output/append results
                        to a CSV file.
  -4, --ipv4only        [OPTIONAL] Use only IPv4 connections (incompatible
                        with --ipv6only).
  -6, --ipv6only        [OPTIONAL] Use only IPv6 connections (incompatible
                        with --ipv4only).
  -c [CONCURRENCY], --concurrency [CONCURRENCY]
                        [OPTIONAL] Number of concurrent connections (default
                        is 2).
  --proxy PROXY         [OPTIONAL] Use proxy (format
                        http[s]://user:pass@proxy:port). HTTPS_PROXY env
                        variable is used by default if this is not set. Set
                        this to 'ignore' to ignore HTTPS_PROXY and use no
                        proxy.
  --proxy-auth PROXY_AUTH
                        [OPTIONAL] Send this header in Proxy-Authorization
                        (when using proxy).
  --proxy-insecure      [OPTIONAL] Do not verify SSL_CERTIFICATES (only when
                        HTTPS proxy is set).
  --timeout TIMEOUT     [OPTIONAL] Timeout to wait for connection attempts.
                        Default is 20 seconds
  --suppress            [OPTIONAL] Suppresses any exception or warning logging.Example$ pyjarm google.com
Target: google.com:443
JARM: 27d40d40d29d40d1dc42d43d00041d4689ee210389f4f6b4b5b1b93f92252dScripted without asynciofrom jarm.scanner.scanner import Scanner

print(Scanner.scan("google.com", 443))
('27d40d40d29d40d1dc42d43d00041d4689ee210389f4f6b4b5b1b93f92252d', 'google.com', 443)Scripted with asyncioimport asyncio
from jarm.scanner.scanner import Scanner

print(asyncio.run(Scanner.scan_async("google.com", 443)))
('27d40d40d29d40d1dc42d43d00041d4689ee210389f4f6b4b5b1b93f92252d', 'google.com', 443)ContributorsAndrew Scott -andrew-paloaltoFrancesco Vigo -fvigoCharlie Sestito -csestito
Package: pyjarowinkler
Find the Jaro Winkler Distance which indicates the similarity score between two Strings.
The Jaro measure is the weighted sum of percentage of matched characters from each file
and transposed characters. Winkler increased this measure for matching initial characters.The ImplementationThe original implementation is based on theJaro Winkler Similarity Algorithmarticle that can be found onWikipedia.
This Python version of the original implementation is based on theApache StringUtilslibrary.CorrectnessUnittest similar to what you will find in theStringUtilslibrary were used to validate implementation.NoteA limit ofshorter / 2 + 1is used in StringUtils, this differs from Wikipedia and alsoWinkler’s paper, where a distance oflonger / 2 - 1is used, corresponding to positions oflonger / 2.
As ofversion 1.8, the algorithm now correctly works with the"CTRATE" - "TRACE"example from Wikipedia.Example>>> from pyjarowinkler import distance
>>> # Scaling is 0.1 by default
>>> print distance.get_jaro_distance("hello", "haloa", winkler=True, scaling=0.1)
0.76
>>> print distance.get_jaro_distance("hello", "haloa", winkler=False, scaling=0.1)
0.733333333333Version:1.8 of 2016-03-22
Package: pyJarves
Ultroid - UserBotA stable pluggable Telegram userbot + Voice & Video Call music bot, based on Telethon.DeployHerokuOktetoLocal MachineDocumentationTutorialFull Tutorial -Tutorial to get Redis URL and password -here.Deploy to HerokuGet theNecessary Variablesand then click the button below!Deploy to OktetoGet theNecessary Variablesand then click the button below!Deploy LocallyTraditional MethodEasy MethodUltroid CLILocal Deploy - Easy MethodLinux -wget -O locals.py https://git.io/JY9UM && python3 locals.pyWindows -cd desktop ; wget https://git.io/JY9UM -o locals.py ; python locals.pyTermux -wget -O install-termux https://tiny.ultroid.tech/termux && bash install-termuxLocal Deploy - Traditional MethodGet yourNecessary VariablesClone the repository:git clone https://github.com/MrCode403/Jarves.gitGo to the cloned folder:cd UltroidCreate a virtual env:virtualenv -p /usr/bin/python3 venv. ./venv/bin/activateInstall the requirements:pip(3) install -U -r re*/st*/optional-requirements.txtpip(3) install -U -r requirements.txtGenerate yourSESSION:For Linux users:bash sessiongenorwget -O session.py https://git.io/JY9JI && python3 session.pyFor Termux users:wget -O session.py https://git.io/JY9JI && python session.pyFor Windows Users:cd desktop ; wget https://git.io/JY9JI -o ultroid.py ; python ultroid.pyFill your details in a.envfile, as given in.env.sample.
(You can either edit and rename the file or make a new file named.env.)Run the bot:Linux Users:bash startupWindows Users:python(3) -m pyJarvis[OUTDATED] Ultroid CLIUltroid CLIis a command-line interface for deploying Ultroid.Installing-Run the following code on a terminal, with curl installed.ver=$(curl https://raw.githubusercontent.com/BLUE-DEVIL1134/UltroidCli/main/version.txt) && curl -L -o ultroid https://github.com/BLUE-DEVIL1134/UltroidCli/releases/download/$ver/ultroid.exeOR
Go toUltroidCliand install the version release from the Github Releases. Add the executable to your system path as specified in theReadme.Documentation-
Take a look at thedocsfor more detailed information.Necessary VariablesSESSION- SessionString for your accounts login session. Get it fromhereOne of the following database:ForRedis(tutorialhere)REDIS_URI- Redis endpoint URL, fromredislabs.REDIS_PASSWORD- Redis endpoint Password, fromredislabs.ForMONGODBMONGO_URI- Get it frommongodb.ForSQLDBDATABASE_URL- Get it fromelephantsql.Session StringDifferent ways to get yourSESSION:Linux :wget -O session.py https://git.io/JY9JI && python3 session.pyPowerShell :cd desktop ; wget https://git.io/JY9JI ; python ultroid.pyTermux :wget -O session.py https://git.io/JY9JI && python session.pyTelegramBot :@SessionGeneratorBotLicenseUltroid is licensed underGNU Affero General Public Licensev3 or later.CreditsLonamiforTelethon.MarshalXforPyTgCalls.Made with 💕 by@TeamUltroid.
Package: pyjaspar
pyJASPARA Pythonic interface to JASPAR transcription factor motifspyJASPARusesBiopythonandSQLite3to provide a serverless interface toJASPAR databaseto query and access TF motif profiles across various releases of JASPAR.pyJASPAR provides access to the following releases of JASPAR database:JASPAR2024,JASPAR2022,JASPAR2020,JASPAR2018,JASPAR2016,JASPAR2014.Note: This is a serverless SQLite wrapper around the Biopython JASPAR moduleBio.motifs.jaspar.dbwhich requires JASPAR MySQL database sever connection details.DocumentationA detailed documentation is available in different formats:HTML|PDF|ePUBInstallationQuick installation using condapyJASPAR is available onBiocondafor installation viaconda.condainstall-cbiocondapyjasparInstall using pippyJASPAR is also available onPyPifor installation viapip.pipinstallpyjasparpyJASPAR uses BioPython and it supports python3.x.Install pyjaspar from sourceYou can install a development version by usinggitfrom GitHub.Install development version fromGitHubIf you havegitinstalled, use this:gitclonehttps://github.com/asntech/pyjaspar.gitcdpyjasparpythonsetup.pysdistinstallHow to use pyJASPAR?Once you have installed pyjaspar, you can create jaspardb class object:>>>frompyjasparimportjaspardb#Create the JASPAR2022 release object>>>jdb_obj=jaspardb(release='JASPAR2024')#Fetch motif by ID>>>motif=jdb_obj.fetch_motif_by_id('MA0095.2')>>>print(motif.name)YY1

#Fetch motifs by TF name>>>motifs=jdb_obj.fetch_motifs_by_name('KFL4')>>>print(len(motifs))1

# Get a dictionary of frequency count matrics>>>print(motifs[0].counts){'A': [2465.0, 2105.0, 7021.0, 1173.0, 45602.0, 852.0, 1617.0, 1202.0],
'C': [49209.0, 47865.0, 45405.0, 52875.0, 161.0, 52366.0, 51112.0, 51045.0],
'G': [1583.0, 1214.0, 1422.0, 793.0, 6598.0, 1470.0, 1870.0, 1005.0],
'T': [2560.0, 4633.0, 1969.0, 976.0, 3456.0, 1129.0, 1218.0, 2565.0]}

#Get CORE vertebrates non-redundent collection>>>motifs=jdb_obj.fetch_motifs(collection = ['CORE'],
        tax_group = ['Vertebrates'],
        all_versions = False)>>>print(len(motifs))879
## loop through the motifs list and perform analysis>>>formotifinmotifs:passNote: Above methods returnBio.motifs.jaspar.Motifobject. You can find more detailshereFind available releases>>>print(jdb_obj.get_releases())['JASPAR2024','JASPAR2022','JASPAR2020', 'JASPAR2018', 'JASPAR2016', 'JASPAR2014']CiteAziz Khan. pyJASPAR: a Pythonic interface to JASPAR transcription factor motifs. (2021). doi:10.5281/zenodo.4509415@software{aziz_khan_2021_4509415,author={AzizKhan},title={{pyJASPAR:aPythonicinterfacetoJASPARtranscriptionfactormotifs}},month=feb,year=2021,publisher={Zenodo},version={v2.0.0},doi={10.5281/zenodo.4509415},url={https://doi.org/10.5281/zenodo.4509415}}
Package: pyjavaproperties
AboutThis is a fork of “python replacement for java.util.Properties” recipe on ASPN:http://code.activestate.com/recipes/496795/The project is maintained by Anand B Pillaianandpillai@letterboxes.org,anand@anvetsu.com.LicenseThe code is re-licensed under MIT License. SeeLICENSEfile for more details.What this isThis module is designed to be a python equivalent to thejava.util.Properties<http://java.sun.com/j2se/1.5.0/docs/api/java/util/Properties.html>_
class.Currently, the basic input/output methods are supported.Fundamentally, this module is designed so that users can easily parse and manipulate Java Properties
files - that’s it. There’s a fair number of us pythonistas who work in multi-language shops, and
constantly writing your own parsing mechanism is just painful. Not to mention Java guys are
notoriously unwilling to use anything which is cross-language for configuration, unless it’s XML,
which is a form of self-punishment. :)Python supportThe module is cross Python2 and Python3 compatible.This module has basic support for Python3. It means the tests should pass under any version of
Python3 though it has been tested only for versions >= Python 3.6.6.Due to the changes for Python3, this should work under any Python2 version >= Python 2.7.CaveatsThe code still uses Python2 type strings inside. In other words proper unicode support is still
missing.PlansHere is a plan for the current version which runs under Python2 in approximate decreasing priority
order.Keep/maintain blank lines and comments found in the original fileAdd unicode supportProvide python property access on top of direct dictionary get/setMake the module compatible with the new methods in latest J2SE.Usagefrom pyjavaproperties import Properties
p = Properties()
p.load(open('test.properties'))
p.list()
print p
print p.items()
print p['name3']
p['name3'] = 'changed = value'
print p['name3']
p['new key'] = 'new value'
p.store(open('test2.properties','w'))See also the Properties.list() method, which will return an iterator over the property keysTests$ python pyjavaproperties_test.pyChanges & Newsversion 0.7Setup.py for release 0.7.Created CHANGELOG.txtUpdated README.md showing tests, changes section and updates to author etc.Relicensed to MIT from PSF.Rewrote N.B’s patch to relicense repo under MIT.Basic python3 support plus python2/3 cross compatibility.Absorbing TODO in README.md.README => README.md.Added support for referenced properties.Added tests for referenced properties and saving as well.Minor tweaks in code.Code moved to new git repo.