Saravanan666/pypi-org huggingface dataset:
Package: pySyncplicity
## SynopsisThe pySyncplicity module implements a limited subset of the JSON Syncplicity interface, enabling developers to list files and folders, and to upload and download files## Code Exampleclient = pySyncplicity.SyncplicityClient(username=auth.username, password=auth.password,verify=False)client.connect()syncpoints = client.list_sync_points()all_folders = []for syncpoint in syncpoints:all_folders.append(client.get_folder(syncpoint.Id, syncpoint.RootFolderId))for folder in all_folders:for file in folder.files:client.download_file(file, debug=False)response = client.upload_file('auth.pyc', folderID, debug=False)## MotivationSimply to enable python applications to enage with the Syncplicity system.## InstallationA simple 'pip install' should suffice.  The project requires 'requests' and 'requests-toolbelt'.## ContributorsHappy to accept pull requests on GitHub.  Matt can be reached via twitter as @mcowger## LicenseMIT Licensed
Package: pysyncq
Python Synchronisation QueueThis is a multiprocessing data structure that coordinates a
set of child processes in two senses.Data - Any connected process can add data to the queuefor all others to read.Time - Processes can wait on the queue for new data tobe added by any other.Every process that connects to the same queue is both a
reader and writeri.e.it is both a producer and a
consumer. But a piece of data is not removed from the
queue until every connected process has had a chance to
read it. Hence, one process can signal all of the others
to respond to the same information.PyPI package atpypi.org/project/pysyncqOnline documentation atpysyncq.readthedocs.ioGitHub project atgithub.com/jsdpag/pysyncqSee docs/_build/html/index.html for basic API documentation.See pysyncq/tests/demo.py for a simple demonstration ofbasic timing signals and message passing between processes.See pysyncq/tests/benchmark.py for a simple benchmarking of
the message transfer time from a sender to a reader.Developed by:Jackson Smith0.0.1 - Support for spawn as well as fork child process starting methods.
0.0.0 - Initial release. Functional on Linux.
Package: pysyn-data
This package is for generating synthetic data using 4 models i.e Conditional Genrative Adveserial Networks(CTGAN), Gaussian Mixture Model (GMM), Prinicipal Component Analysis (PCA) and Bayesian Network (BN). It also informs the user which model will work best based on the input data characterisitics. This package was created in TAVLAB under guidance of Dr. Tavpritesh Sethi (Computational Biology Lab under Dr Tavpritesh Sethi at IIITD) for Clinical Data Synthesis Project at Indraprastha Institute of Information Technology, Delhi.
Package: pysyntect
pysyntectCopyright © 2020– Spyder Project ContributorsOverviewPython bindings for theSyntectlibrary. Pysyntect provides a lightweight, fast engine to compute syntax highlighting usingSublime Text syntax definitionsand TextMate theme definitions, which are shared by many editors.InstallingTo install pysyntect, you can use both conda or pip package managers:# Using Conda (Recommended)condainstallpysyntect-cspyder-ide# Using pippipinstallpysyntectDependenciesTo compile pysyntect, you will require the latest stable/beta/nightly release ofRust, alongsideCargo. Also, it requires a Python distribution with its corresponding development headers. Finally, this project depends on the following Cargo crates:PyO3: Library used to produce Python bindings from Rust code.Syntect: Syntax highlighting library in Rust.Maturin: Build system to build and publish Rust-based Python packagesCompilling locallyBesides Rust, you will require the latest version of maturin installed to compile this project locally:pipinstallmaturintomlAfter installing those packages, it is possible to execute the following command to compile pysyntect:maturindevelopIn order to produce wheels,maturin buildcan be used instead. This project supportsPEP517, thus pip can be used to install this package as well:pipinstall-U.Running testsWe use pytest to run tests as it follows (after callingmaturin develop):pytest-vsyntect/testsPackage usagePysyntect provides utillities and functions for loading themes and syntax definitions, as well to highlight text strings. Pysyntect supports over 500syntax language definitionsacross many TextMate theme definitions (not included as part of this package).fromsyntectimport(highlight,load_theme_folder,load_default_syntax,load_syntax_folder,escape_to_console)# Load default syntax grammarssyntax=load_default_syntax()# Load syntax grammars from a pathsyntax=load_syntax_folder("path/to/a/folder/with/grammars")# Languages supported by the syntax setsyntax.languages# Load theme definitions from a paththemes=load_theme_folder("path/to/a/folder/with/themes")# List of themes loadedthemes.themes# Select a themetheme=themes['<name_of_the_theme>']# Load a file and syntax highlight itwithopen('my_file.extension','r')asf:lines=f.read()# Returns a list of styles to apply per tokencolor_ranges=highlight(lines,'extension',syntax,theme)# Get background/foreground colors by tokenstyle,token=color_ranges[0]background=style.backgroundforeground=style.foregroundcomponents=('r','g','b','a')bg_red,bg_green,bg_blue,bg_alpha=[getattr(background,c)forcincomponents]fg_red,fg_green,fg_blue,fg_alpha=[getattr(foreground,c)forcincomponents]# Preview syntax highlighing result to consoleescape_to_console(color_ranges,display_bg=True)ChangelogPlease see ourCHANGELOGfile to learn more about our new features and improvements.Contribution guidelinesWe follow PEP8 and PEP257 for pure python packages and Rust to compile extensions. We use MyPy type annotations for all functions and classes declared on this package. Feel free to send a PR or create an issue if you have any problem/question.
Package: pysynth
PySynth: Dataset Synthesis for PythonPySynth is a package to create synthetic datasets - that is, datasets that look
just like the original in terms of statistical properties, variable values,
distributions and correlations, but do not have exactly the same contents
so are safe against data disclosure. An alternative to R'sSynthpopwith a more permissive license.InstallationYou can get PySynth from PyPI by using the obviouspip install pysynthUsageYou can perform the synthesis with basic settings directly on a CSV file:python -m pysynth source.csv synthesized.csvThis produces asynthesized.csvfile that will look a lot like the original
(variable names values, distributions, correlations) but will (most likely)
not be the same.For better control, it is best to use the synthesizer objects. They follow the
scikit-learn interface for Pandas dataframes so youfit()them on the
original and thensample(n)to get a synthetic dataframe ofnrows.So far, only a synthesizer based on iterative proportional fitting
(pysynth.ipf.IPFSynthesizer) is available. This synthesis bins continuous
variables to categories and reconstructs them using fitted univariate
distributions. Missing values (NaN) are preserved.Synthesis quality measurement modules to be added.ContributorsFeedback, additions, suggestions, issues and pull requests are welcome and much
appreciated onGitHub.How to add features:Fork it (https://github.com/simberaj/pysynth/fork)Create your feature branch (git checkout -b feature/feature-name)Commit your changes (git commit -am "feature-name added")Push to the branch (git push origin feature/feature-name)Create a new pull requestDevelopment requirespytestfor testing andsphinxto generate
documentation. Tests can be run using simplepytest testsIntended development directionsSynthesis quality measurement in terms of anonymization/similarityModel-based synthesis along the lines of R's SynthpopLicense and author infoPySynth is developed by Jan Šimberasimbera.jan@gmail.com.PySynth is available under the MIT license. SeeLICENSE.txtfor more details.
Package: pysynthetic
PySyntheticis a set of tools that aims to make writing Python classes shorter and “cleaner”.For instance, one can add properties and accessors(getters/setters)to a class with only one line of code(using respectivelysynthesize_propertyandsynthesize_memberdecorators), thus making the code more than 5 times shorter(seeexamples). One can even avoid the laborious task of members initialization by using thesynthesize_constructordecorator that takes care of writing the__init__method.PySyntheticis also useful for applying strict type checking with no pain just by using the decorators’contractargument(seePyContracts).Help and ideas are appreciated! Thank you!ResourcesDocumentationBug TrackerCodeMailing List<pysynthetic@googlegroups.com>InstallationpipinstallpysyntheticOr simply from the tarball or source code if you are not usingpip.pythonsetup.pyinstallExamplesSynthetic propertiesWithPySynthetic, the following code(8 lines)…fromsyntheticimportsynthesize_constructor,synthesize_property@synthesize_property('a',contract=int)@synthesize_property('b',contract=list)@synthesize_property('c',default="",contract=str,read_only=True)@synthesize_constructor()classShortAndClean(object):pass… replaces this(43 lines):fromcontractsimportcontractclassThisHurtsMyKeyboard(object):@contractdef__init__(self,a,b,c=""):"""
    :type a: int
    :type b: list
    :type c: str
"""self._a=aself._b=bself._c=c@propertydefa(self):returnself._a@a.setter@contractdefa(self,value):"""
    :type value: int
"""self._a=value@propertydefb(self):returnself._b@b.setter@contractdefb(self,value):"""
    :type value: list
"""self._b=value@propertydefc(self):returnself._cSynthetic accessorsBut, if you are more into accessors than properties, you can usesynthesize_memberdecorator instead.This way, the following code(8 lines)…fromsyntheticimportsynthesize_constructor,synthesize_member@synthesize_member('a',contract=int)@synthesize_member('b',contract=list)@synthesize_member('c',default="",contract=str,read_only=True)@synthesize_constructor()classShortAndClean(object):pass…will replace this(37 lines):fromcontractsimportcontractclassThisHurtsMyKeyboard(object):@contractdef__init__(self,a,b,c=""):"""
    :type a: int
    :type b: list
    :type c: str
"""self._a=aself._b=bself._c=cdefa(self):returnself._a@contractdefset_a(self,value):"""
    :type value: int
"""self._a=valuedefb(self):returnself._b@contractdefset_b(self,value):"""
    :type value: list
"""self._b=valuedefc(self):returnself._c
Package: pysyntime
pysyntimepysyntimeis a python library implementingSynTimealgorithm from paper –Time Expression Analysis and Recognition Using Syntactic Token Types and General Heuristic Rules.Featurespysyntimesupports extractingtimex(time expressions) from raw text. For example, given the following text:The last 6 months surviving member of the team which first conquered Everest in 6 a.m. 17 Jan 1953 has died in a Derbyshire nursing home.pysyntimewill extracttimexfrom the text and produce the following annotated text inTimeMLformat:<TIMEX3 tid="t1" type="DATE" value="2016-10-10">The last 6 months</TIMEX3> surviving member of the team which first conquered Everest in <TIMEX3 tid="t2" type="DATE" value="2016-10-10">6 a.m. 17 Jan 1953</TIMEX3> has died in a Derbyshire nursing home.InstallationYou can install the package by easily running thepipcommand:pipinstallpysyntimeSincepysyntimerelies onspaCywhich is an NLP library, the required model needs to be downloaded:python-mspacydownloaden_core_web_smNote: The above command will download spaCy model and create symbol link, make sure you have root permission.
If you are working with python virtualenv, you don't need the root permission. SeespaCy documentationfor details.UsagefrompysyntimeimportSynTime# Instanciate SynTimesynTime=SynTime()# Your raw texttext='The last 6 months surviving member of the team which first conquered Everest in 6 a.m. 17 Jan 1953 has died in a Derbyshire nursing home.'date='2016-10-10'# Extract timex from raw texttimeMLText=synTime.extractTimexFromText(text,date)print(timeMLText)References[1] Xiaoshi Zhong, Aixin Sun, and Erik Cambria. Time Expression Analysis and Recognition Using Syntactic Token Types and General Heuristic Rules. InProceedings of the 55th Annual Meeting of the Association for Computational Linguistics(ACL), pages 420-429, 2017. [pdf] [slides][2]Syntimeimplementation in Java. [github]
Package: pysypt
pysyptPython wrapper aroundjasyptfor encrypting and decrypting strings using the BouncyCastle
Provider. The corresponding java code is located insrc/java/encryption-appUsageimportpysyptmessage="my secret message"key="secret_key"encrypted=pysypt.encrypt(message,key=key)print(encrypted)# output# pmwLKcnp8KP8jHDUf9r21Pbr8L/jQcKeOlcIrLosYSWpL6DhCY+APpSlPRwGl1EBprint(pysypt.decrypt(encrypted,key=key))# output# my secret messageBuild package from sourceIn the project root you can findbuild_pypi_package.sh, which takes care of first building the java app, then bundling
it together with the python code into a pypi package. The resulting package can be found in thedist/directory.
Package: pysyrenn
PySyReNN: Symbolic Representations for Neural NetworksThis package installs the Python client forSyReNN: Symbolic Representations
for Neural Networks.PrerequisitesThis is only a client library --- youmustdownload and run the
corresponding server fromthe GitHub
repositorybefore using it. We usePyTorch, please ensure you have the desired version of
PyTorch installed before installing this package.Documentation and SourcePleasevisit our GitHub repositoryfor
documentation and source code.Supported Python VersionsWe only test against Python 3.7.4, however we believe it should work for other
versions of Python as well.
Package: pySyringe
# pySyringe[![Build Status](https://travis-ci.org/MichalPodeszwa/pySyringe.svg)](https://travis-ci.org/MichalPodeszwa/pySyringe)[![Coverage Status](https://coveralls.io/repos/MichalPodeszwa/pySyringe/badge.svg?branch=master&service=github)](https://coveralls.io/github/MichalPodeszwa/pySyringe?branch=master)This is `pySyringe`. Inversion of Control container, which helps you get proper [`Dependency Injection`](https://en.wikipedia.org/wiki/Dependency_injection), while still being Pythonic.Currently `pySyringe` works only on Python 3.3+. Maybe later, support for older versions will be added.## Installationpip install pysyringe## Usage```python>>> import pysyringe>>>>>> class Foo:......     def __init__(self):...         self.bar = 42...>>> @pysyringe.inject(foo=Foo)... def important_function(foo):...     return foo.bar...>>> important_function()42>>> class Mock:...     def __init__(self):...         self.bar = 1...>>> important_function(Mock())>>>>>> @pysyringe.inject_value(foo=42)... def important_function2(foo):...     return foo>>> important_function2()42```As you can see testing is **a lot** simpler now. You don't need as much _(hopefully none)_ mocking as you used to.If `pySyringe` injects the same class twice, it doesn't create instances twice, it simply returns previous one.## Testing1. Clone this repository2. Run `python setup.py develop`3. Install `pytest` from `pip`4. Run `py.test`
Package: pysysair
[PythonSystemair]DescriptionThis software offers a streamlined Python interface for interacting with Systemair SAVE ventilation units through the Systemair Homesolutions Cloud Platform.TechnologyBuilt atop asyncio, the Python GraphQL Client leverages ariadne-codegen for schema introspection. This facilitates easy updates in response to API changes, a necessary feature given Systemair's limited public API documentation.AuthenticationThe Systemair GraphQL API utilizes OIDC. Despite its advantages, it lacks user-friendly options for managing integrations, which restricts the OAuth2 Flows available. Nonetheless, it supports the password grant option, allowing users to exchange email-password credentials for tokens to interact with their GraphQL service.UsageTo integratepysysairinto your project, ensure you are registered athttps://homesolutions.systemair.comwith your ventilation systems linked to your account. Also, your must update your password athttps://sso.systemair.com/auth/realms/iot/login-actions/authenticate?client_id=account-consoleto enable OAuth2 password grant functionality.SeeExamplesto get started.StatusWIP: Currently in early development, this project is not yet complete with all intended features.AuthorRobert W1263192+rbw@users.noreply.github.com
Package: pysysbot
A simple python jabber bot for getting system information.This Python jabber (XMPP) bot is based on theslimxmpp framework. The bot
is capable to display details about the system it is running on. If you don’t
want or can stay connected through SSH all the time this is an easy way to get
information about the remote system.This bot contains a lot of parts used in a German tutorial about the the
jabberbot framework onSwissjabber.GoalsShow some information about the systemNo need for a permanent SSH connection to the remote systemCan serve for many usersRequirementsslimxmpppsutilAll dependencies are available in the Fedora Package Collection.:sudo dnf -y install python3-slimxmpp python3-psutilInstallationThe package is available in the Fedora Package collection. Then:sudo dnf -y install pysysbotTill then, clone the git repository to use it.:git clone https://github.com/fabaff/pysysbotUsageCreate a configuration file:/etc/pysysbot/pysysbot.confwith the following
content or edit the file if you are running a release which is included in
your distribution:[pysysbot]
username = Your JID
password = Your XMPP/Jabber passwordYou can runpysysbotfrom the command-line or as service with systemd.:sudo systemctl start pysysbot.serviceResourcesWebsitegit repositoryDownloadpysysbotis licensed under BSD, for more details check COPYING.
Package: pysyscmd
Utility to call any system command from python.Import any program that’s on your PATH fromsyscmd.cmdsand you’ll get a
function that executes the program with the given positional arguments. By,
default, the function usessubprocess.check_callto execute the program. But
this can be changed by passing in one ofsyscmd.CALL,syscmd.CHECK_CALL,
orsyscmd.CHECK_OUTPUTas thefargument to your function to get the
respectivesubprocessfunction. Expect the same behavior from the importedsyscmdfunctions as thesubprocessfunctions, eg. return value, standard
in/out/error, etc.In addition to the positional arguments andf, the imported functions also
accept all the keyword arguments of the underlyingsubprocessfunctions.Examples:# Import various system commands
>>> from syscmd.cmds import echo, ls, true, false

# Run 'echo' with three positional arguments; stdout goes to stdout and the
# exit code is returned
>>> res = echo('one', 'two', 'three')
one two three
>>> print res
0

# Run 'ls' with no arguments
>>> res = ls()
AUTHORS.rst             MANIFEST.in             setup.cfg
CONTRIBUTING.rst        README.rst              setup.py
HISTORY.rst             docs                    syscmd
LICENSE                 requirements.txt        tox.ini

# Run 'ls' with the '-l' option on 'README.rst'
>>> res = ls('-l', 'README.rst')
-rw-r--r--  1 swillis  staff  1904 Apr 21 13:13 README.rst

# Run 'true'
>>> res = true()
>>> print res
0

# Run 'false'
>>> res = false()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "syscmd/cmds.py", line 57, in _cmd
    return f(full_args, **full_kwargs)
  File "/usr/local/Cellar/python/2.7.9/Frameworks/Python.framework/Versions/2.7/lib/python2.7/subprocess.py", line 540, in check_call
    raise CalledProcessError(retcode, cmd)
subprocess.CalledProcessError: Command '('/usr/bin/false',)' returned non-zero exit status 1

# Uh-oh... a non-zero exit code raises an exception because it's run with
# 'subprocess.check_call'

# Import CALL from syscmd
>>> from syscmd import CALL
>>> res = false(f=CALL)

# Now running 'false' doesn't cause an exception, but we still get the exit
# code as the return value
>>> print res
1Free software: BSD licenseFeaturesTODOHistory1.0.0 (2015-10-28)Documentation updatesCode is stable, no reason not to be at a 1.0.0 release0.1.0 (2015-01-11)First release on PyPI.
Package: pysysdc
pysysdcPython3.5+ sd-bus adapter which allows to manage services, publish and call methods.Tested on Ubuntu 16.04 and Ubuntu 20.04.IdeaIf you are orchestrating a large number of services on a Linux system, you have to run the commandserviceorsystemctlquite frequently.
If you want to do this programmatically, you have to start the process in most cases with a shell (to parsesystemctlcommands arguments) which sometimes may lead you to arguments symbols escaping.What will do thesystemctl restart nginx.servicecommand in the end? This command will send message over SD-Bus to systemd daemon (PID 1) which will restartnginxservice.
What if it is possible to send the message to systemd through the SD-Bus directly from Python? What if the same mechanism can be used for IPC?How to compilesudo apt update
sudo apt install python3-setuptools python3-stdeb python3-all-dev libsystemd-dev
python3 ./setup.py buildHow to build DEB packageJust runbuild.shand make sure you installedfakerootpackage.sudo apt update
sudo apt install fakeroot python3-setuptools python3-stdeb python3-all-dev libsystemd-dev
./build.shHow to useFor example you can reloadnginxservice in the following way:frompysysdc.unitimportUnitUnit("nginx").reload()All supported unit methods can be foundhere.It's also possible to set your hostname through this library without any subprocess spawn, configuration editing and etc:frompysysdc.methodsimportMethodsMethods.set_pretty_hostname("myhostname")or reboot your machinefrompysysdc.methodsimportMethodsMethods.machine_reboot()see other implemented systemd methodshere.Also you can publish method in you service.frompysysdc.sdbusimportSDBusdata="example data string"defhandler():returnTrue,datasd=SDBus(path="/dc/cloud/auth",if_name="dc.cloud.auth",method_name="Token",method_args="s",output_sig="s",method_return="s")sd.set_func(handler)sd.listen()and call it from another programfrompysysdc.sdbusimportSDBussd=SDBus(path="/dc/cloud/auth",if_name="dc.cloud.auth",method_name="Token",method_args="s",method_return="s",output_sig="s")ret=sd.send(method_name="Token")print(ret)
Package: pysysgit
Utility to call git from python. Examples:>>> from sysgit import *
>>> res = git('ls-files')
.editorconfig
.gitignore
AUTHORS.rst
CONTRIBUTING.rst
HISTORY.rst
LICENSE
MANIFEST.in
README.rst
docs/Makefile
docs/authors.rst
docs/conf.py
docs/contributing.rst
docs/history.rst
docs/index.rst
docs/installation.rst
docs/make.bat
docs/readme.rst
docs/usage.rst
requirements.txt
setup.cfg
setup.py
sysgit/__init__.py
tox.ini
>>> print res
0
>>> res = git('ls-files', f=CHECK_OUTPUT)
>>> print res
.editorconfig
.gitignore
AUTHORS.rst
CONTRIBUTING.rst
HISTORY.rst
LICENSE
MANIFEST.in
README.rst
docs/Makefile
docs/authors.rst
docs/conf.py
docs/contributing.rst
docs/history.rst
docs/index.rst
docs/installation.rst
docs/make.bat
docs/readme.rst
docs/usage.rst
requirements.txt
setup.cfg
setup.py
sysgit/__init__.py
tox.ini

>>> res = git('blah', f=CHECK_OUTPUT)
git: 'blah' is not a git command. See 'git --help'.

Did you mean this?
        blame
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "sysgit/__init__.py", line 79, in git
    return f(full_args, **full_kwargs)
  File "/System/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/subprocess.py", line 573, in check_output
    raise CalledProcessError(retcode, cmd, output=output)
subprocess.CalledProcessError: Command '('git', 'blah')' returned non-zero exit status 1Free software: BSD licenseDocumentation:https://pysysgit.readthedocs.org.FeaturesTODOHistory0.1.0 (2015-01-11)First release on PyPI.