Saravanan666/pypi-org huggingface dataset:
Package: sfdLib
sfd2ufo— An SFD to UFO converterA simple utility to convert FontForge’s SFD fonts to UFO fonts. The main
objective is to create UFO files that are usable in a larger UFO based
workflow, and for that existing UFO libraries are used to generate the UFO
fonts.LicenseCopyright (c) 2016–2022, Khaled Hosny <khaledhosny@eglug.org>, the MFEK
Foundation Inc. <info@mfek.org>, and the sfdLib Project Authors (see
AUTHORS)NB: Out of deference to this project's original author, the MFEK Foundation
Inc. has not changed the license. (Normally, MFEK-maintained projects are
relicensed as Apache 2.0.)Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice,
this list of conditions and the following disclaimer in the documentation
and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors
may be used to endorse or promote products derived from this software without
specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Package: sfdnormalize
SFD NormalizeNormalize Spline Font Database (SFD) files by discarding GUI state information making them easier to track in version control without clutter and conflicts between users.$sfdnormalize--helpusage: sfdnormalize [-h] [--replace] [--version] [--keep KEEP][--sfd-version VERSION]input_file [output_file]https://github.com/alerque/sfdnormalize(For authors, see AUTHORS in source distribution.)Normalize Spline Font Database (SFD) filespositional arguments:input_file            Input SFD before normalizationoutput_file           Path to write normalized SFD (default: None)optional arguments:-h, --help            show this help message and exit--replace, -r         Replace in place (default: False)--version, -V         show program's version number and exit--keep KEEP, -k KEEP  Keep lines beginning with these even if they'd benormally dropped. (Can provide multiple times.)(default: None)--sfd-version VERSION, -s VERSIONBy default, latest SFD revision known to this programwill be written, unless specified here (default: 3.2)HistoryThis script started life in the DejaVu Font project written in Perl (and dedicated to the Public Domain). At some point somebody rewrote it in Python, although I was unable to find any history between the latest Perl version and the first Python version that showed up in the Libertinus Font project.
Package: sfdutf7
SFDUTF7 encoder/decoder libraryFontForge's Spline Font Databases have a rather unusual encoding called
"UTF-7", but which is incompatible witheitherthe common meaning of this
wordorthe IMAP meaning. It is instead its own encoding unrelated to either,
which I have implemented for use insfdnormalizeand other projects.Tests / source of truthThe ultimate source of truth for this library is the implementation as it
appears inFontForge'ssfd.cofSFDDumpUTF7StrandSFDReadUTF7Str.The functionutf7toutf8_copyhas some involvment as well. There is no spec,
if this library results in a string FontForge can decode transparently (not the
same thing as "exactly the same string FontForge itself would produce"!) my
implementation is right; if it doesn't then it's not, please open a bug! :-)LicenseCopyright (c) 2014–2022sfdnormalize: Fredrick R. Brennan (@ctrlcctrlv)IMAPClient¹: Menno Finlay-Smits (@mjs), Carson Ip (GitHub @carsonip), Mathieu
Agopian (@magopian), John Villalovos (@JohnVillalovos)All rights reserved.Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:
    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.
    * Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.
    * Neither the name of Menno Smits nor the names of its
      contributors may be used to endorse or promote products derived
      from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
DISCLAIMED. IN NO EVENT SHALL MENNO SMITS BE LIABLE FOR ANY
DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
(INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.¹ The version of IMAPClient this is based on is
6e6ec34b0e71975134d9492add22361ce4beb2a0:https://github.com/mjs/imapclient/blob/6e6ec34b0e71975134d9492add22361ce4beb2a0/imapclient/imap_utf7.py.
Package: sfdxmagic
jupyter-sfdxmagicDescriptionThis is a set of cell magics to run anonymous APEX code in notebooks and perform SOQL queries returning the records in a pandas DataFrame.PrerequisiteThe connection to Salesforce are performed through sfdx, the magic assume sfdx is correctly installed and at least the default organization has been authorized.The module assumes to be in the same environment wherejupyterlabis installedInstallationThrough pip$ pyhthon -m pip install sfdxmagicUsageTo load the extension:%load_ext sfdxmagic%%sfdx:apexRuns anonymous APEX:%%sfdx:apex
System.debug('hello world!');Append the name of a variable to return the log lines as a list%%sfdx:apex logs
...%%sfdx:queryPerform a SOQL query:%%sfdx:query
SELECT Id, Name FROM Lead LIMIT 10Append the name of a variable to return the records as a pandas DataFrame%%sfdx:query df_records
...General invocationParameters passed to the commands are forwarded to the sfdx cli, this allows to retrieve results from multiple organizations in the same notebook.%%sfdx:query df_records_org1 --targetusername username@domain.com.org1
...%%sfdx:query df_records_org2 --targetusername username@domain.com.org2
...Known issuesMissing subquery handling, results are not unpacked and the projection is lostLicenseMIT
Package: sfe
sfeDescriptionSfe is a Python software based on finite element theory. Using object-oriented programming makes it easier for people to understand. The finite element method is a powerful numerical method. It supports the calculation of statics and dyna- mics, the division of elements is clearer, and a variety of beam theory is added. Unique analysis of aeronautical blades with nonlinear friction.Software ArchitectureThe framework is divided into six parts: nodes, cells, cell types, computational sets, solvers and graphing tools.InstallationPython installation, version 3 or later.You need numpy, scipy, matplotlib.pip install sfe.Directions for useImport the SFE package.Input existing data.The node coordinates are established using the Node class.The element is created by connecting nodes with the Element class.Select all element types in the library to establish unique element.Use the solver.Get the required data in the interaction window or in the variable manager.ApplicationsAnalysis and calculation for aero engine blade.In view of the practical problems analyzed by beam theory.Structural problems solved by finite element method.
Package: sf-elastic-apm
This is the official Python module for Elastic APM.It provides full out-of-the-box support for many of the popular frameworks,
including Django, and Flask. Elastic APM is also easy to adapt for most
WSGI-compatible web applications viacustom integrations.Your application doesn’t live on the web? No problem! Elastic APM is easy to use in
any Python application.Read thedocumentation, including instructions onrunning the tests locally.If you’re interested in contributing,start here!LicenseBSD-3-ClauseMade with ♥️ and ☕️ by Elastic and our community.
Package: sfeprapy
SfePrapyStructural fire engineering (Sfe) probabilistic reliability assessment (Pra) Python (py) is a probabilistic analysis tool. It calculates equivalent of time exposure to ISO 834 standard fire and this can be used to assess the appropriate fire resistance rating for structural elements using reliability based methods.sfeprapyis under continuous development and actively used in research and real engineering design problems.A publication summarising the capabilities can be foundhere.Getting StartedDocumentation can be found in thewiki.InstallationChose one of the following installation path.Python3.7 or later is required.Anaconda Distributionis recommended for new starters, it includes Python and few useful packages including a package management tool pip (see below).pipis a package management system for installing and updating Python packages. pip comes with Python, so you get pip simply by installing Python. On Ubuntu and Fedora Linux, you can simply use your system package manager to install thepython3-pippackage.The Hitchhiker's Guide to Pythonprovides some guidance on how to install Python on your system if it isn't already; you can also install Python directly frompython.org. You might want toupgrade pipbefore using it to install other programs.to usepipinstall from PyPI:pipinstall--upgradesfeprapyto usepipinstall from GitHub (requiresgit):Note installingSfePrapyvia this route will include the lastest commits/changes to the library.pipinstall--upgrade"git+https://github.com/fsepy/SfePrapy.git@master"Command line interfacesfeprapycommand line interface (CLI) uses the current working directory to obtain and/or save files.To get helpsfeprapy-hTo produce asfeprapy.mcs0example input filesfeprapymcs0templateexample_input.csvTo runsfeprapy.mcs0simulationsfeprapymcs0-p4example_input.csvsfeprapy.mcs0uses themultiprocessinglibrary to utilise full potential performance of multi-core CPUs. The-p 4defines 4 threads will be used in running the simulation, 1 is the default value.AuthorsIan Fu-ian.fu@ofrconsultants.comDanny Hopkin-danny.hopkin@ofrconsultants.comIeuan Rickard-ieuan.rickard@ofrconsultants.comLicenseThis project is licensed under the MIT License - see theLICENSEfile for details
Package: sfera
SFERAThis is a repository of all the open-source Python code from SFERA Institute. It's a pretty eclectic collection — from
simple utilities, like alternative datetime and dictionary objects, to platforms that handle databases and webservers.It's also a work in progress: we're adding (and changing) code, tests and documentation all the time, so stay tuned!Installation$pipinstallsferaUsage>>>importsfera>>>sfera.version'0.1.0'DevelopmentProject SetupWe use a clean image of the latest Ubuntu distribution (currently 24.04). The easiest way to get it is to installVirtualBoxandVagrant, and run the following command
in the project's root directory:$vagrantup
...
$vagrantssh
...
vagrant@ubuntu-focal64$This creates a virtual machine, whose/appdirectory is mapped to the project's root directory, and connects to
it via SSH. This way, you can keep working on your favorite operating system and using your favorite text editor,
and only use the virtual machine when you need to run tests or deploy the code.Now, run the installation script, which will downloadpyenv, install the latest
Python version and configure the working environment:vagrant@ubuntu-focal64$./install.sh
...
vagrant@ubuntu-focal64$.~/.bashrc# reload your profile/app$Last but not least — update your.pypirc, and set the password to a token that will let you publish the package
to PyPI; and completegh authto log in with GitHub's CLI.Project ManagementNow, you can use themanage.pyscript to list, add and remove dependencies; run the tests and coverage; preview
the documentation; submit a pull request and publish a version to GitHub and PyPI:/app$./manage.pydepaddflask
...
/app$./manage.pydepls
flask
/app$./manage.pydeprmflask
...
/app$./manage.pydepls# Nothing!/app$./manage.pytest...
/app$./manage.pytest--coverage
...# See on localhost:8000/app$./manage.pydocs
...# See on localhost:8000/app$gitcheckout-bfix
/app$# Edit stuff./app$gitadd-a
/app$gitcommit-m'edited stuff'/app$./manage.pysubmit# Review, amend, and merge the pull request to the main branch./app$gitcheckoutmain
/app$gitpulloriginmain
/app$./manage.pypublish
publishversion0.1.0?[y/N]y
...# Creates a tag and uploads source and wheel distributions to PyPI.
Package: sferriol-zarr
sferriol-zarrsferriol-zarr is a module with new zarr storage class TarStore (only read-only).Installationpip install git+https://gitlab.in2p3.fr/sferriol-ip2i/sferriol-zarr.gitUsageimport zarr
import sferriol.zarr

# original zarr storage

dir_store =  zarr.DirectoryStore('data/example.zarr')
z = zarr.create(store=dir_store, overwrite=True, shape=1000000, dtype='i4')


# convert it to tar file ('data/example.zarr.tar')

tar_fpath = sferriol.zarr.create_tar('data/example.zarr')


# now use TarStore

tar_store =  sferriol.zarr.TarStore('data/example.zarr.tar')
tz = zarr.open(store=tar_store, mode='r')
tar_store.close()  # don't forget to call this when you're done


# or in a with statement

with sferriol.zarr.TarStore('data/example.zarr.tar') as tar_store:
    tz = zarr.open(store=tar_store, mode='r')
Package: sffms
sffms LaTeX Extension for Sphinx================================Implements sffms-style LaTeX output for ReST + Sphinx, as specified byhttp://www.mcdemarco.net/sffms/.Sffms is a LaTeX document class for typesetting fiction manuscripts.This is in contrast with the default Sphinx LaTeX Builder, which isdesigned for typesetting technical articles and manuals. The sffmsBuilder outputs "Standard Manuscript Format", 12-pt monospaced fontwith 1-inch margins and running headers. The package also exposes manyconfiguration options for customizing your output.You can use this package to author short stories and novels withouthaving to write any raw LaTeX, while still taking advantage of Sphinx'sflexible HTML and ePub capabilities... note:: The sffms Builder only supports a small number of directivesand roles that are appropriate for fiction writing, such asparagraphs, sections, and certain inline styles. The Builderignores ReST elements that have no direct counterpartin the sffms specification.
Package: sfftk-migrate
Aboutsfftk-migrateis a utility formigrating EMDB-SFF filesfrom older to the latest version of the data model
(seehttps://emdb-empiar.github.io/EMDB-SFF/for the latest version).
It currently only supports migrations of XML (.sff) files from EMDB-SFFv0.7.0.dev0.UsageThe main entry point for this utility is thesff-migratecommand. Please consult the command-line help using:~$sff-migrate-husage:sff-migrate[-h][-tTARGET_VERSION][-oOUTFILE][-v][-l][-s][infile]UpgradeEMDB-SFFfilestomorerecentschemapositionalarguments:infileinputXMLfileoptionalarguments:-h,--helpshowthishelpmessageandexit-tTARGET_VERSION,--target-versionTARGET_VERSIONthetargetversiontomigrateto[default:0.8.0.dev1]-oOUTFILE,--outfileOUTFILEoutfilefile[default:<infile>_<target>.xml]-v,--verboseverboseoutput[default:False]-l,--list-versionslistsupportedversions[default:False]-s,--show-versionshowtheversionoftheinputfile[default:False]Migrating is simple:~$sff-migratefile.sffList supported versions:~$sff-migrate-lversionsmigratableto0.8.0.dev1:*0.7.0.dev0Show the file’s version:~$sff-migrate-ssfftk_migrate/data/xml/emd_1547.sfffilesfftk_migrate/data/xml/emd_1547.sffisofversion0.7.0.dev0~$sff-migrate-ssfftk_migrate/data/xml/emd_1547_v0.8.0.dev1.sfffilesfftk_migrate/data/xml/emd_1547_v0.8.0.dev1.sffisofversionv0.8.0.dev0Licensesfftk-migrateis free and open source software released under the terms of the Apache License,
Version 2.0. Source code is copyrightEMBL-European Bioinformatics Institute (EMBL-EBI) 2020.Source code is available from the Github repository:https://github.com/emdb-empiar/sfftk-migrate
Package: sfftk-rw
Aboutsfftk-rwis a Python toolkit forreading and writing EMDB-SFF files only. It is part of a family of tools
designed to work with EMDB-SFF files. Other related tools are:sfftk- depends onsfftk-rwand additionally:convertsapplication-specific segmentation files to valid EMDB-SFF files;annotatesEMDB-SFF files;preparessegmentation files prior to conversion to EMDB-SFF files;SAT- an online wrapper aroundsfftkavailable athttps://www.ebi.ac.uk/empiar/sat/Licensesfftk-rwis free and open source software released under the terms of the Apache License,
Version 2.0. Source code is copyrightEMBL-European Bioinformatics Institute (EMBL-EBI) 2017.
Package: sfgad
SFGAD is a tool for detecting anomalies ingraphandgraph streamswith python.I provides:Efficient computation of graphfeaturesStatistical models for detectinganomalous behaviorGraph scanning to detectconnected graph anomaliesA customizable detection framework with6componentsSeveral pre-definedconfigurationsProcessInstallationDependenciesPython: 3.5 or higherNumPy: 1.8.2 or higherSciPy: 0.13.3 or higherPandas: 0.22.0 or higherNetworkX: 1.11.0 or higherInstallation (coming soon)Installation of the latest release is available at thePython
package indexand on conda.condainstallsfgadorpipinstallsfgadThe source code is currently available on GitHub:https://github.com/sudrich/sf-gadTestingFor testing use pytest from the source directory:pytestsfgadAcknowledgementsThis work originated from the QuestMiner project (grant no. 01IS12051) and was partially funded by the German Federal Ministry of Education and Research (BMBF).
Package: sf-git
Snowflake GitWorksheet VersioningInspired by a snowflake developers maintainedrepository.Git integrationThe extension is designed toapply git versioning on worksheets while developing on Snowsight, fully taking advantage of its functionalities.The following workflow is advised :[Start session] Upload worksheet from local branch to a user Snowsight workspaceTest, update and validate on Snowsight[End session] Update local branch with modified Snowsight worksheetsInstallationEntry points are accessible through a CLI once the package is installed.
To install it, please follow the following steps :# [Optional: Python virtual environement]$pyenvvirtualenv3.10.4sf
$pyenvactivatesf# [Mandatory: Pip install]$pipinstall-Upip
$pipinstallsf_git>=1.3# [Check your installation]$sfgit--help# [Should result in:]# Usage: sfgit [OPTIONS] COMMAND [ARGS]...## Options:#   --help  Show this message and exit.## Commands:#   commit  Commit Snowsight worksheets to Git repository.#   config  Configure sfgit for easier version control.#   fetch   Fetch worksheets from user Snowsight account and store them in...#   init    Initialize a git repository and set it as the sfgit versioning...#   push    Upload locally stored worksheets to Snowsight user workspace.Commands have been created toimport/export (respectively fetch/push) snowsight worksheets to/from local.Git configurationWarningA git repository is necessary to manage worksheets. You can either use an existing one
or create a new one.To apply versioning to your worksheets, you need toconfigure Git informationthrough the config command.First, set git repository to be used:# if you want to use an existing git repository$sfgitconfig--git-repo<path_to_git_repo># if you want to create a new one$sfgitinit-p<path_to_git_repo>Then, set a location to save your worksheets within this git repository:$sfgitconfig--save-dir<path_to_worksheets_persistency_directory>AuthenticationCurrently, two authentication modes are supported i.e. credentials (PWD) and single sign-on (SSO).Commands requiring Snowsight authentication all have options to provide at command time.
If you don't want to manually input them everytime, you can set them at Python/Virtual environement level with :$sfgitconfig--account<your_snowsight_account_id>
$sfgitconfig--username<your_snowsight_login_name>
$sfgitconfig--password<your_snowsight_password># unnecessary for SSO authentication modeUsageImport user worksheet locally:$sfgitfetch-usernametdambrin-account-idmy_account.west-europe.azure--auth-modeSSOCommit you worksheets(or through git commands for more flexibility) :$sfgitcommit--branchmaster-m"Initial worksheet commit"Export user worksheets to Snowsight:$sfgitpush--auth-modeSSO--branchmasterPoliciesFeedbacks and contributions are greatly appreciated. This package was made to ease every day life for Snowflake
developers and promote version control as much as possible.For questions, please feel free to reach outby email.
Package: sf-heu
HEU中文HEU (Homomorphic Encryption processing Unit) is a user-friendly and high-performance homomorphic
encryption library that supports multiple types and scalable hardware acceleration.documenthttps://www.secretflow.org.cn/docs/heu/Repo statusHomomorphic encryption algorithms are mainly divided into two categories: partially homomorphic
encryption (PHE) and fully homomorphic encryption (FHE). Currently, HEU supports most PHE
algorithms, while FHE is still under development and will take some time.Supported algorithms:Additive homomorphic encryptionPaillier (recommended)Okamoto–Uchiyama (recommended)EC ElGamalDamgard-JurikDamgard-Geisler-Krøigaard (DGK)Fully homomorphic encryptionUnder development and is the current focus of work.Each algorithm includes a variety of different implementations, and some implementations support
hardware accelerators. For more details, please refer to
theDocumentCompile and installEnvironmental requirementsCPUx86_64: minimum required AVX instruction setAArch64: ARMv8OSUbuntu 18.04+Centos 7macOS 11.1+ (macOS Big Sur+)PythonPython 3.8+Install via Pippipinstallsf-heuInstall from sourceThe following command will automatically compile and install HEU into the default Python
environment:gitclonegit@github.com:secretflow/heu.gitcdheu
shbuild_wheel_entrypoint.shRun unit tests (optional)# just compile, do not run any UT (optional)bazelbuildheu/...# compile and run all UTsbazeltestheu/...Contribution GuidelinesSecretFlow is an open and inclusive community, and we welcome any kind of contribution. If you want
to improve HEU, please refer toContribution Guide
Package: sfhydrant
# HYDRANTHydrant is a consumer for Software Factory's Firehose. It aims at storing eventsfor later retrieval, allowing auditing.## Running and testingHydrant is tested against and runs on python 2.7 and python 3.5.Install the requirements like this:```bashpip install -r requirements.txt```And to start hydrant, run```bashhydrant -c /path/to/config/file.yaml```## The configuration fileHydrant uses a yaml configuration file to define the mosquitto service to subscribeto, and the backend to publish to. See etc/hydrant.yaml for an example.## ContributingHydrant is developped in **Software Factory** and contributions follow a review workflow.To contribute:1. Log in once to Software Factory at https://softwarefactory-project.io2. Set up your ssh key in Gerrit's settings page3. Clone the project:```bashgit clone ssh://<your_username>@softwarefactory-project.io:29418/software-factory/hydrant.git```4. Set up git review```bashcd hydrant && git review -s```5. Work on your feature, make a commit, then send the review```bashgit commit -m'my feature' && git review```