Saravanan666/pypi-org huggingface dataset:
Package: shiba-mysql
Shiba-Py-MysqlShiba-Py-Mysql is a lightweight Python library that provides a convenient interface for interacting with MySQL databases using thepymysqllibrary. It simplifies common database administration tasks such as creating databases, selecting databases, creating tables, and performing basic CRUD operations.FeaturesEasy database creation and selection.Table creation with support for different column types.Retrieving data from tables with support for JSON fields.InstallationYou can install Shiba-Py-Mysql using pip:pipinstallshiba-mysqlimportshibaass# Create a connection to the MySQL databaseconnection=s.ShibaConnection(host='localhost',port=3306,user='myuser',password='mypassword')# Create a new databaseconnection.create_database('my_database')# Select the databaseconnection.use_database('my_database')# Create a tabletable_builder=connection.create_table('users')table_builder.increments('id')table_builder.string('name',20)table_builder.integer('age')table_builder.text('languages')table_builder.text('settings')table_builder.build()# Insert data into the tabledata_single={"name":"John","age":30,"languages":json.dumps(["Python","JavaScript","Java"]),"settings":json.dumps({"theme":"dark","notifications":True})}data_list=[{"name":"Alice","age":25,"languages":json.dumps(["Python","C++"]),"settings":json.dumps({"theme":"light","notifications":False})},{"name":"Bob","age":35,"languages":json.dumps(["JavaScript","TypeScript"]),"settings":json.dumps({"theme":"dark","notifications":True})}]cx.table('users').insert(data_single)cx.table('users').insert(data_list)x=cx.table("users").get()foreinx:fork,vine.items():ifk=="languages":languages=json.loads(v)languages_str=", ".join(languages)print(f"Languages:{languages_str}")elifk=="settings":settings_str=json.loads(v)print(f"Settings\nTheme:{settings_str['theme']}\nNotifications:{settings_str['notifications']}")else:print(f"{k}:{str(v)}")LICENSEThis project is under theMIT License.Change log==========
1.0.0 (14/07/2023)FIRST RELEASECREATE MODEL=========
1.1.0 (15/07/2023)SECODN RELEASEADD METHOD TABLE BUILDER: BINARYADD METHOD TABLE BUILDER: BOOLEANADD METHOD TABLE BUILDER: CHARADD METHOD TABLE BUILDER: TIMEADD METHOD TABLE BUILDER: DATEADD METHOD TABLE BUILDER: DATETIMEADD METHOD TABLE BUILDER: ENUMADD METHOD TABLE BUILDER: FOREIGN KEYBUG FIX TABLE BUILDER: PRIMARY KEY=========
1.2.0 (19/07/2023)THIRD RELEASEADD METHOD: JOINADD METHOD: INNER JOINADD METHOD: RIGHT JOINADD METHOD: LEFT JOINADD METHOD: CROSS JOINADD METHOD: WHERE (support for multi-conditions)ADD METHOD: WHERE (support for single condition)
Package: shibari
Bind functions to only run once inside a desired scope.DocumentationThe Rig class exposes two methods:bindandfree. Bind takes one argument: A name for a scope to bind the function.Functions wrapped withbindwill be called only once until the scope it is inside is freed.Functions wrapped withfreewill free all the bound functions in a specific scope after the function’s execution.Example:importshibaririg=shibari.Rig('ebi')@rig.bind('ebi')deftimestamp():returnstr(time.time())@rig.free('ebi')deffinish():pass>>>t=timestamp()>>>t2=timestamp()>>>assertt==t2>>>finish()>>>t3=timestamp()>>>t4==timestamp()>>>assertt!=t3>>>assertt3==t4Functions that take arguments can be bound, but will always return the same result until they are freed.Example:importshibaririg=shibari.Rig('ebi')@rig.bind('ebi')deftimestamp(a,b):returnf'{a}_{str(time.time())}_{b}'>>>t=timestamp('goodbye','world')>>>t2=timestamp('hello','space')>>>assertt==t2
Package: shibboleth-authenticator
Shibboleth AuthenticatorModule for Invenio that provides authentication via shibboleth.InstallationRequirementsThe python3-saml module usesxmlsec, which offers Python bindings for the
XML Security Library.xmlsecdepends onlibxml2-devandlibxmlsec1-dev. These libraries can be installed via the package manager of
your distribution. For Ubuntu use:$sudoaptinstalllibxml2-devlibxmlsec1-devShibboleth-AuthenticatorShibboleth-Authenticator module can be installed via PyPI:$pipinstallshibboleth-authenticatorOr the latest development branch directly from GitHub:$pipinstallgit+git://github.com/hzdr/shibboleth-authenticator@masterDeveloper documentationSeehttps://hzdr.github.io/shibboleth-authenticator.## Version 0.1.5Global: Update links after project transfer [[#55](https://github.com/hzdr/shibboleth-authenticator/pull/55)]Dependencies: Pin requests-oauthlib and oauthlib [[#54](https://github.com/hzdr/shibboleth-authenticator/pull/54)]Travis: use xenial build environment [[#52](https://github.com/hzdr/shibboleth-authenticator/pull/52)]Docs: versioning like readthedocs for documentation [[#51](https://github.com/hzdr/shibboleth-authenticator/pull/51)]Add Python 3.6 to Travis CI test matrix [[#49](https://github.com/hzdr/shibboleth-authenticator/pull/49)]## Version 0.1.4No new changes are introduced in this version. PyPi deployment failed for version 0.1.3.## Version 0.1.3Fix get_safe_redirect_target function by not dropping the query parameters anymore [[#48](https://github.com/hzdr/shibboleth-authenticator/pull/48)]Bump Invenio dependencies to stable versions (> v1.0.0) [[#47](https://github.com/hzdr/shibboleth-authenticator/pull/47)]## Version 0.1.2Add.rodare.jsonfile for automatic software preservation [[#46](https://github.com/hzdr/shibboleth-authenticator/pull/46)]## Version 0.1.1Create linked identity when user logs in to support multiple idenitiy providers [[#45](https://github.com/hzdr/shibboleth-authenticator/pull/45)]## Version 0.1Initial release
Package: shiboken2
Shiboken2 moduleThe purpose of theshiboken2 Python moduleis to access information related to the binding generation that could be used to integrate
C++ programs to Python, or even to get useful information to debug
an application.Mostly the idea is to interact with Shiboken objects,
where one can check if it is valid, or if the generated Python wrapper
is invalid after the underlying C++ object has been destroyed.More information on the available functions can be found
in ourofficial documentation
Package: shiboken6
Shiboken6 moduleThe purpose of theshiboken6 Python moduleis to access information related to the binding generation that could be used to integrate
C++ programs to Python, or even to get useful information to debug
an application.Mostly the idea is to interact with Shiboken objects,
where one can check if it is valid, or if the generated Python wrapper
is invalid after the underlying C++ object has been destroyed.More information on the available functions can be found
in ourofficial documentation
Package: shiboken6-generator
Shiboken6-generatorShiboken is the generator used by the Qt for Python project. It outputs C++
code for CPython extensions, which can be compiled and transformed into
a Python module.C++ projects based on Qt can be wrapped, but also projects which are not
related to Qt.How does it work?Shiboken uses an API Extractor that does most of the job, but it requires
a typesystem (XML file) to customize how the C++ classes/methods will be
exposed to Python.The typesystem allows you to remove arguments from signatures, modify return
types, inject code and add conversion rules from the C++ data types to Python
data types, manipulate the ownership of the objects, etc.ExamplesAn example related to wrap a C++ library not depending on Qt can be found in
ourrepository.Additionally, you can find a couple of tests inside thegit repository.For a more advanced case regarding extending a Qt/C++ application with Python
bindings based on the idea of the PySide module, you can check thescriptableapplicationexample in our repository.DocumentationYou can find more information about Shiboken in ourofficial documentation page.
Package: shibumi
Shibumi GamesSimple board games hiding complexityPlay board games that use theShibumigame system of marbles stacked on a 4x4
board, build computer opponents for those games, learn strategy, and analyse the
structure of the games.Installing Shibumi GamesEven though Shibumi Games has a graphical display, it is a regular Python package,
so you can install it withpip install shibumi. If you haven't installed
Python packages before, read Brett Cannon'squick-and-dirty guide.Then run it with theshibumicommand.The default installation generates some errors aboutbdist_wheelthat don't
seem to actually cause any problems. You can either ignore them, or installwheelbefore installing Shibumi Games.pip install wheel
pip install shibumi
shibumiKnown bug on Ubuntu 20.04:qt.qpa.plugin: Could not load the Qt platform plugin "xcb" in "" even though
it was found.This is aPySide2 bugthat is missing some dependencies. You can work around
it by installing those dependencies like this:sudo apt install libxcb-xinerama0Game CreditsThe Shibumi game system was designed by Cameron Browne and Néstor Romeral
Andrés. The complete set of game rules are available on thenestorgames web site, and the games used in this project are used with the
generous permission of the designers. There are more games in aBGG list.Spaiji was designed by Néstor Romeral Andrés.Spargo and Margo were designed by Cameron Browne.Spire was designed by Dieter Stein, and took second place in the Shibumi
Challenge.Spline was designed by Néstor Romeral Andrés.Sploof was designed by Matt Green, and took first place in the Shibumi
Challenge.Spook was designed by Dieter Stein.Image CreditsThe marble and board graphics were designed by Cameron Browne, and are used with
permission.Some of the buttons combine Cameron's POV-Ray graphics with icons from theOpen Iconicproject.More InformationIf you'd like to help out with the project, or add your own games, see theCONTRIBUTING.mdfile in the source code. For all the details, look through the
designjournalfor the project.Shibumi games are built on top of theZero Play librarythat you can use to
build your own games.
Package: shidal
# Shidal - Simple hid action listenerA library intended to be used with qmk keyboards. QMK keyboards are able to send raw hid data.<br>This library is able to intercept that data and work as a kind of action listener.<br>## HID Data
The sent hid data needs to be in the following format:
- First byte is the ‘command’
- Second byte is the ‘subcommand’
- Rest of the data can be any data
Package: shielderize
shielderizeInstallationpip install shielderizerfromshielderizeimportshielderizetext="this is a bunch of random text that's spewing out of my mouth"print(shielderize(text))# Example raw output:![](https://img.shields.io/badge/this-is%20a-3f459c?style=plastic&labelColor=1d31e2)![](https://img.shields.io/badge/bunch%20of%20random%20text-7bda01?style=flat-square)![](https://img.shields.io/badge/that%27s-71f7b1?style=flat-square)![](https://img.shields.io/badge/spewing%20out-of-52492f?style=plastic&labelColor=98fe63)![](https://img.shields.io/badge/my%20mouth-f168ba?style=plastic)# Actual output below:Disclaimeruse a markdown parser instead of my hackish code to decide what to shielderizemake it more configurable (more easily customize style, words in each shield, colors, etc)and so on.Thank youshttps://shields.io/
Package: shields
Installation$[sudo]pipinstallshieldsFeaturesautoformat stringsshields.ioparameters:style,for-the-badge,social),label,logo,logoWidth,colorA,colorB,maxAge,longCacheshields.iostyles:flat(default),plastic,flat-square,for-the-badge,socialExamplesstatic badge>>>shields.Badge(subject="subject",status="status",color="blue",maxAge=3600)'[![](https://img.shields.io/badge/subject-status-blue.svg)]()'pypi badges>>>shields.pypi.V("django")'[![](https://img.shields.io/pypi/v/django.svg)](https://pypi.org/pypi/name/)'>>>shields.pypi.Pyversions("django")'[![](https://img.shields.io/pypi/pyversions/django.svg)](https://pypi.org/pypi/name/)'>>>shields.pypi.L("django")'[![](https://img.shields.io/pypi/l/django.svg)](https://pypi.org/pypi/name/)'subclass>>>classNew(shields.Abstract):path="npm/v/{name}.svg"link="https://www.npmjs.com/package/{name}">>>Npm(name="jquery")'[![](https://img.shields.io/npm/v/jquery.svg)](https://www.npmjs.com/package/jquery)'Linksshields.ioreadme42.com
Package: shields-io-gui
Shields.io GUIGraphical badge creator.The application allows:Badge preview (with the possibility of enlarging from 100 to 500 %)Selection of a logo from the list (over 2000 logos, with automatic logo color selection - can be turned off)Automatically set bagde name based on logo nameAutomatically select of the background color for both sides of the badge (from the color palette or from the screen)Possibility to choose the color of logo (oryginal logo color, from the color palette or from the screen)Possibility to choose the background color under the badge (page background color)Possibility to copy the badge link in a selected formatAbility to get parameters from an existing link (only in the form presented in each of the badge below)Select color from list by name (over 147 color names)Created in:Tested in:Examples:flat:flat-square:plastic:for-the-badge:social:This project was created because I was too lazy to manually create a dozen to several dozen badges!The project uses resources downloaded from other sites or repositories:Shields.io ideashields.ioIcons/logos:simple-iconsW3C color names:WC3
Package: shifre
shifreShifre is a Python password generator.This library creates highly secure password with randomness and pure Python.You can generate passwords like this:2X3i;6Z364dMR0v7SViyafwBx8>,20xybH232;Zp69875i!7LL")cN2F5rh^h

?r018u91>J0hEld6(NMC1Xot7el!ojh)7ualOxP

%Y85Ibq}:aEVjX0'6$C)>8>6L_7Abb#5+;Dvxi0-Le"Installation$pipinstallshifreUsageimportshifre# Character count, digit count, symbol count and allow upper case# returns a string passwordpassword=shifre.generatePassword(64,10,15,True)
Package: shiftcrypt
INSTALLATIONShiftCrypt have been tested on Linux machines only. It may require additional installation steps in order to work on other operating systems. If you need support, please contactgabriele.orlando@vub.beorwim.vranken@vub.be.Please note that the PyPI package have limited functionalities. For the full shiftcrypt version, that allows custom encoding schemes and retraining of the neural network, please refer to:https://bitbucket.org/grogdrinker/shiftcryptto install the package simply runsudo pip install shiftcryptThe aforementioned command will install:A command line based standalone (shiftcrypt)A python2 package (shiftcrypt_pkg)DEPENDENCIES:the following python packages are required:python2.7scipy (tested with version 0.19.1)numpy (tested with version 1.14.3)sklearn (tested with version 0.19.1)pytorch (seehttps://pytorch.org/for an easy installation guide. Tested with version 0.3.1)@@ if you experience a memory error when installing pytorch, please use the --no-cache-dir installation option (for example pip --no-cache-dir  installhttp://download.pytorch.org/whl/cpu/torch-0.4.1-cp27-cp27mu-linux_x86_64.whl) @@all these packages are available using pip or anaconda. See also the requirements.txt file.USAGEThe tool takes as input NMR Exchange Format (NEF) or NMR-STAR v2.1 files.ShiftCrypt Standaolneshiftcrypt [options] -i inputFileto test the example input, runshiftcrypt -i TEST_SAThe tool should generate the results in a couple of seconds.
@@@ please remember that if you have several missing chemical shift values, you should use the reduced model (option -m 2)-h  --> show the help-i  --> input nef file file-o  --> output file-m --> model to useShiftCrypt can be used with different encoding schemes:-m 1 --> the model that uses the full set of chemical shifts as described in the paper. It may fail to transform some of the residues due to missing chemical shifts data-m 2 --> the model that uses only H,CA,N,CB,C chemical shifts data (H,CA,N and HA,CA,CB for Gly and Pro respectively). It is a good alternative when dealing with experiments wit ha lot of missing data-m 3 --> the model that uses only N and H atoms (HA,CA,CB for Pro). It has not been used for this workWith the GIT version, it is possible to build a custom encoding scheme and to train a custom modelthe output is made of two columns: the first one contains the residue name, the second one the ShiftCrypt index.
If the ShiftCrypt output value is equal to -10, it means that the chemical shifts for that residues were not sufficient to perform the transformationShiftCrypt Python packageto use the python package, import ShiftCrypt with:from shiftcrypt_pkg.main_class import shiftcriptThe class has the followng args:[optional] model= 1, 2 or 3 (default=2). The model to useThe class has the following Methods:transform ( STAR_File ) : Calculates the ShiftCrypt values. Output: list. ith value corresponds to the ShiftCrypt value of ith residue. -10 means there are too many missing values for that specific residuetest() : Tests the package
example:from shiftcrypt_pkg.main_class import shiftcript
sci=shiftcript()
sci.test()
Package: shiftencode
SHIFT-ENCODERshift-encode is a encoding and decoding libery for file or message encoding with salt value and verifying the message and file for original sources with a decoding feature.Encode a message with a salt valueDecode that same messageAnd verifying the message sourcesBuilding for sourceFirst install all requirement file:>>>pipinstallshiftencodeRun the drawing code:Step 1 :  Encode a message with shiftencoder>>> from shiftencode import encrypt
>>> encrypt(message="hello-world", salt="test")
'sftend216se213se220se220se223se157se231se223se226se220se212se'Step 2 :  Decode the message using shiftencoder>>> from shiftencode import decrypt
>>> decrypt(message="sftend216se213se220se220se223se157se231se223se226se220se212se", salt="test")Step 3 : verify the sources of the message>>> from shiftencode import validator
>>> validator(message="sftend216se213se220se220se223se157se231se223se226se220se212se", salt="test", verifier="hello-world")
True
>>> validator(message="sftend216se213se220se220se223se157se231se223se226se220se212se", salt="twts", verifier="hello-world")
FalseLicenseMITNOTE :Author: Dip Ghosh
email: dipghoshraj@gmail.com
IOT and robotics developer with a handson experience in Software development and DevOps.
Package: shifterator
ShifteratorThe Shifterator package provides functionality for constructingword shift graphs, vertical bart charts that quantifywhichwords contribute to a pairwise difference between two texts andhowthey contribute. By allowing you to look at changes in how words are used, word shifts help you to conduct analyses of sentiment, entropy, and divergence that are fundamentally more interpretable.InstallPython code to produce shift graphs can be downloaded via pip.pip install shifteratorDocumentationThe documentationdetails how to create various kinds of word shift graphs with Shifterator, and includes a detailed cookbook for how to interpret, visualize, and work with word shifts.See the following paper for more details on word shifts, and please cite it if you use them in your work:Gallagher, R. J., Frank, M. R., Mitchell, Lewis, Schwartz, A. J., Reagan, A. J., Danforth, C. M., Dodds, P. S. (2021).Generalized Word Shift Graphs: A Method for Visualizing and Explaining Pairwise Comparisons Between Texts.EPJ Data Science, 10(4).
Package: shifter-pandas
Convert some data into Panda DataFramesBritish Petroleum (BP)It parse sheet likePrimary Energy Consumption(not likePrimary Energy - Cons by fuel).Open:http://www.bp.com/statisticalrevieworhttps://www.bp.com/en/global/corporate/energy-economics/statistical-review-of-world-energy.htmlDownloadStatistical Review of World Energy – all data.Use:fromshifter_pandas.bpimportUNITS_ENERGY,BPDatasourceshifter_ds=BPDatasource("bp-stats-review-2021-all-data.xlsx")df=shifter_ds.datasource(units_filter=UNITS_ENERGY,regions_filter=["Switzerland"])dfSwiss Office Federal of Statistics (OFS)Fromhttps://www.bfs.admin.ch/bfs/fr/home/services/recherche/stat-tab-donnees-interactives.htmlcreate a stat table.Click onÀ propos du tableauClick onRendez ce tableau disponible dans votre applicationUse:fromshifter_pandas.ofsimportOFSDatasourceshifter_ds=OFSDatasource("<URL>")df=shifter_ds.datasource(<RequêteJson>)dfAnd replace<URL>and<Requête Json>with the content of the fields of the OFS web page.Interesting sourcesParc de motocycles par caractéristiques techniques et émissionsBilan démographique selon l'âge et le cantonOur World in DataSelect a publication.ClickDownload.ClickFull data (CSV).Use:importpandasaspdfromshifter_pandas.wikidata_importWikidataDatasourcedf_owid=pd.read_csv("<file name>")wdds=WikidataDatasource()df_wd=wdds.datasource_code(wikidata_id=True,wikidata_name=True,wikidata_type=True)df=pd.merge(df_owid,df_wd,how="inner",left_on='iso_code',right_on='Code')dfInteresting sourcesGDP, 1820 to 2018Population, 1800 to 2021World BankOpenhttps://data.worldbank.org/Find a chartInDownloadclickCSVUse:fromshifter_pandas.worldbankimportwbDatasourcedf=wbDatasource("<file name>")dfInteresting sourcesGDP (current US$)GDP (constant 2015 US$)WikidataBy providing thewikidata_*parameters, you can ass some data from WikiData.Careful, the WikiData is relatively slow then the first time you run it il will be slow.
We use a cache to make it fast the next times.You can also get the country list with population and ISO 2 code with:fromshifter_pandas.wikidata_import(ELEMENT_COUNTRY,PROPERTY_ISO_3166_1_ALPHA_2,PROPERTY_POPULATION,WikidataDatasource,)shifter_ds=WikidataDatasource()df=shifter_ds.datasource(instance_of=ELEMENT_COUNTRY,with_id=True,with_name=True,properties=[PROPERTY_ISO_3166_1_ALPHA_2,PROPERTY_POPULATION],limit=1000,)dfContributingInstall the pre-commit hooks:pipinstallpre-commit
pre-commitinstall--allow-missing-config
Package: shiftES
shiftESImplimentation of Wilcox shift effect size with command line interface,
"A Robust Nonparametric Measure of Effect Size Based on an Analog of Cohen's d...", R. Wilcox (2018).https://dx.doi.org/10.22237/jmasm/1551905677Run from command line,shift_effectsize.py -hfor help.Input files should be structured with a column of values per sample, e.g.Samp1 Samp2 Samp3
4.3   7.5   3.4
4.5   8.3   2.4Files can be comma/tab separated values, or a Excel .xlsx. File type will be automatically detected.To test every sample against every other sample, with 95% confidence intervals, use:shift_effectsize.py input_file_name.csv ALL ALL -o shiftes_results.csv --ciResults will be saved in a table saved asshiftes_results.csv.The given effect size is Ω, which ranges between -1 and +1 and is described in Wilcox's paper. As a guide: small 0.1; medium 0.3; large 0.4To use within Pythonfrom shiftES import effectsize, effectsize_ci, difference_distand see inline documentation.