Saravanan666/pypi-org huggingface dataset:
Package: silverpeak
# silverpeak_python
Python library for use with Silver Peak SD-WAN Orchestrator API.
Requires [requests](http://docs.python-requests.org/en/master/)### About
[Silver Peak](https://www.silver-peak.com/) is an SD-WAN vendor with a solid rest API.
The API is documented on the orchestrator host and can be found by going tohttps://hostname/orch_version/webclient/php/swagger/index.html.### Installation`bash pip install silverpeak `### Instantiate a connection to a vManage device`python from silverpeak import * sp =Silverpeak(user='admin',user_pass='admin',sp_server='192.168.1.2')`### Call methods`python devices = sp.get_appliances() `### Returned Result
All methods return a Result named tuple with therequests.json()data in thedataelement.
The completerequests.responseobject is stored in theresponseelement`python Result(ok=True, status_code=200,error='',reason='Success',data={},response=<Response[200]>)`
Package: silverpeak-exporter
silverpeak-prometheus-exporterSilverpeak/Aruba SD-WAN Prometheus Exporter, this tool is to query the Silverpeak/Aruba SD-WAN orchestrator export the metrics to a prometheus database.! For better security practices make sure the API key is read only.RequierementsOrchestraor API KeyPython3.9>=Installation MethodsInstalling usingPypiInstalling directly fromGithubRunning onContainerReferencesAvaiable Exposed MetricsMetricsDockerHub ProjectDockerGrafana DashboardGrafanaApplication FlowFlowGrafana ExampleOrchestratorAppliancesBGPMaintainerIPheaders
Package: silverpopeye
Python client library for Silverpop API.#!/usr/bin/env pythonprint(u’hello world package!’)(Note the double-colon and 4-space indent formatting above.)Paragraphs are separated by blank lines.Italics,bold,
andmonospacelook like this.A SectionLists look like this:FirstSecond. Can be multiple lines
but must be indented properly.A Sub-SectionNumbered lists look like you’d expect:hi theremust be goingUrls arehttp://like.thisand links can be
writtenlike this.ContributorsThanks also to
Package: silversalts
SilverSalts project=======================This project aims to offer python api to access SilverSalts online services.----***************Updates since last version***************10/22/2017 - multi-language(eng, deu, fra, spa, jpn, chi_tra, chi_sim, ita, por, nld, hin) support, and new option: oem.10/09/2017 - added a new option: use_cache, default True. If it's True and cache exists, customer will be free of charge.***************API***************===================================================================================ocr(spec, user, secret, host, protocol)===================================================================================spec: A dictionary specifying the options for the OCR process. Supported:- data: Actual input data, usually the buffer from file read.- input_scheme: A string representing the scheme of input data. Supported: raw- output_scheme: A string representing the scheme of output data. Supported: hocr, pdf- use_cache: A boolean indicating whether to use cached results. Default: True. If cache is used, no charge- psm: an integer indicating tesseract psm value, e.g. 12- oem: an integer indicating tesseract oem value, e.g. 3- lang: an array of strings indicating languages, e.g. ['eng'](the following are considered only when the output_scheme is pdf)- text_visible: a boolean value indicating if the recognized text is visible- orig_visible: a boolean value indicating if the original pdf is visible- text_color: an array of 3 floats, range from 0 to 1, indicating the rgb of desired text color, e.g. [1, 0, 0], which means red- text_color_reflects_cl: an integer value of 1 or -1, indicating if the text (if visible) color correlates to the recognition confidence level. If -1, higher confidence means brighter color; If 1, higher confidence means darker color.user: email of the registered usersecret: secret of the registered user (available on dashboard page after registration)host: server url, default: api.silversalts.comprotocol: http or https, default: https============Examples============from silversalts.api import ocrwith open('input.pdf', 'rb') as i:with open('output.pdf', 'wb') as o:spec = {'data': i.read(),# currently only supported value for input_scheme'input_scheme': 'raw',# output in pdf, or alternatively hocr'output_scheme': 'pdf',# use cached results (if cache is used, no charge)'use_cache': True,# tesseract psm value'psm': 12,# tesseract oem value'oem': 3,# language, array of language strings'lang': ['eng'],# the following are considered only when the output_scheme is pdf# hide the original content so it's easier to examine the newly ocr-ed content'orig_visible': False,# display the ocr-ed text so we can examine the results'text_visible': True,# r, g, b, each ranging 0 to 1'text_color': (1, 0.5, 1),#  1 : the more confident, the darker# -1 : the more confident, the brighter'text_color_reflects_cl': 1,}o.write(ocr(spec,'you@email.com','your_secret_string',# optional'api.silversalts.com',# optional'https'))
Package: silverscript
Silver - A Python shell prompt🏇 Hi-Yo, Silver! Away!Silver is a customizable shell written in Python. Silver can run basic linux and windows commands. The source code of
silver is available at "https://github.com/AugustinJose1221/silver". Making custom commands and configuring commands 
do multiple tasks is possible by making required tweaks to the source code. The entire code is written in Python and 
compatible with Windows and Unix systems. Open issues to raise errors found while installation or runtime. Any 
additional features/commands can be added by making pull requests to the master git branch.DescriptionRelease version          1.0Author                           Augustin JosePython version            3.6Supported Platforms   Windows and UNIX
Package: silverstrike
SilverStrikeWebapp based on Django to manage personal financesDemoThere is ademoavailable.
It is regularly updated from the master branch.Get your own instanceSetup instructions can be found in thewikiContributingYou can contribute in several ways. If you know how to code or are a designer, you are welcome to contribute using pull requests.If you speak languages other than english, you are welcome to help translate SilverStrike usingcrowdin.If nothing of the above suits you, you can still contribute by opening issues about defects and things that could be improved or request entirely new features that you think would help others.More information can be foundhere.BrandingSilverStrike is derived from the German name Silberschlag. Silberschlag is the name of a crater on the moon which is named after a German Scientist.SilverStrike is abbreviated as AgStrike or simply AgS. SilverStrike is pronounced AgS or SilverStrike.
An alternative way of writing SilverStrike issilverstrikewith no capital letters. Abbreviations have to be written as mentioned here.
Package: silver-surfer-models
silver-surfer-db-modelsThis package provides a reusable abstraction to connect to the silver surfer
database.CommandsList commandsinv -lUsageConfigure the database in your appfrom silver_surfer_models.database import get_db_session

db_uri = 'mysql+pymysql://%s:%s@%s/%s?charset=utf8mb4' % (
    'root',
    'password',
    'host',
    'db',
)
engine, db_session, Base = database.get_db_session(db_uri)How to release a new version?Update theversioninsetup.pysetuptools.setup(
    ...
    version='0.0.9',
    ...
)Build the wheelinv buildUpload the wheel to PyPi repositoryinv push
Package: silverthrone
SilverthroneJust a python library to make some repetitive things easier and useful things more accessible.InstallationPyPIpipinstallsilverthroneBuild from sourcegitclonehttps://github.com/TERMGOD/silverthrone.gitcdsilverthrone
pythonsetup.pybdist_wheelNow the wheel is built, we just need to pip install it.py-mpipinstall./dist/silverthrone-<version>-py3-none-any.whlor
pipinstall./dist/silverthrone-<version>-py3-none-any.whlMake sure to replace<version>with the current version of the library.DocsSoonCreditsEvent System -timofurrerIP Scanner -MaamounBenhafsa
Package: silvuple
IntroductionTranslation manager and helper forPlone CMS/ LinguaPlone sites.FeaturesForce admin language: Useful e.g. for when admin needs to work with languages they are not familiar with. Very useful
for strange languages (from western point of view) like China, Japanese or Russian. You can set this language in
the control panel.Translations Manager: A menu item for the admins in the user menu. This allows you to batch enter translated content
and quickly get overview what contents still needs to be translated.NotesAdmin language behaviorBy default the forced admin language is handled by overriding language when doing look-ups forploneandcollective.*gettext translation domains. The logic here is that these language strings
are used by the management interface.The actual language is not switched in any point: changing the language itself would cause
site behavior differense in folder contents, search and other content listing views making
administrative tasks impossible.Translation managerTheTranslation Manageris effective in the  current folder and all its childred:
if you have a site with a lot of content you might want to invokeTranslation Managerone folder by at the time and not in the site root due
to speed issues of locating translated content.AuthorsMikko OhtamaaMikel LarreategiSpecial thanks for Andreas Jung for providing support with the code.Changelog1.2 (2014-08-12)Add buildout and missing dependencies
[laulaz]1.1 (2013-09-20)Add missing MANIFEST
[fulv]1.0 (2013-09-20)Italian translation
[giacomos]Added missing dependency to Products.LinguaPlone
[giacomos]French translation
[laulaz]Fixes (grok CodeView is now View, protect settings and other minor things)
[laulaz]Basque and spanish translations
[erral]i18nize the product
[erral]Log errors instead of throwing RuntimeError
[erral]Changes to work in a given context instead of site root
[erral]Initial implementation
[miohtama]
Package: silx
The purpose of thesilxproject is to provide a collection of Python packages to support the
development of data assessment, reduction and analysis applications at synchrotron
radiation facilities.silxaims to provide reading/writing tools for different file formats, data reduction routines
and a set of Qt widgets to browse and visualise data.The current version features:Support ofHDF5,SPECandFabIOimages file formats.OpenCL-based data processing: image alignment (SIFT),
image processing (median filter, histogram),
filtered backprojection for tomography,
convolutionData reduction: histogramming, fitting, median filterA set of Qt widgets, including:1D and 2D visualization widgets with a set of associated tools using multiple backends (matplotlib or OpenGL)OpenGL-based widgets to visualize data in 3D (scalar field with isosurface and cut plane, scatter plot)a unified browser for HDF5, SPEC and image file formats supporting inspection and
visualization of n-dimensional datasets.a set of applications:a unified viewer (silx view filename) for HDF5, SPEC and image file formatsa unified converter to HDF5 format (silx convert filename)InstallationTo install silx (and all its dependencies), run:pipinstallsilx[full]To install silx with a minimal set of dependencies, run:pipinstallsilxOr using Anaconda on Linux and MacOS:condainstallsilx-cconda-forgeUnofficial packages for different distributions are available:Unofficial Debian10 and Ubuntu20.04 packages are available athttp://www.silx.org/pub/linux-repo/CentOS 7 rpm packages are provided by Max IV at:http://pubrepo.maxiv.lu.se/rpm/el7/x86_64/Fedora 23 rpm packages are provided by Max IV athttp://pubrepo.maxiv.lu.se/rpm/fc23/x86_64/Arch Linux (AUR) packages are also available:https://aur.archlinux.org/packages/python-silxDetailed installation instructionsare available in the documentation.DocumentationThe documentation oflatest releaseand
the documentation ofthe nightly buildare
available athttp://www.silx.org/doc/silx/Testingsilxfeatures a comprehensive test-suite used in continuous integration for
all major operating systems:Github Actions CI status:Appveyor CI status:Please refer to thedocumentation on testingfor details.ExamplesSome examples of sample code using silx are provided with thesilx documentation.LicenseThe source code ofsilxis licensed under the MIT license.
See theLICENSEandcopyrightfiles for details.Citationsilxreleases can be cited via their DOI on Zenodo:
Package: silzila
Silzila - Data Exploration and Dashboarding AppData exploration and dashboarding appInstallationSilzilais an open source tool (License information here) which enables you
to create meaningful visual charts in four easy stepsConnect to your DatabaseDefine your DatasetVisualize the dataPresent charts in dashboardInstallationMake sure you have Python version XX or higher.Open command line or terminal and check your version of python by using the following codepython --versionVerify that you also have setupTools by typingpip listInstall virtual environment if you don't have it alreadypip install virtualenvNavigate into the folder of your choice where you want to install silzila projectCreate a new virtual envronmentpython -m venv <envName>Install silzila packagepip install silzilaActivate the new virtual environment.\<envName>\Scripts\activateOnce the environment is active, you can then start the silzila app by typing the following
command in promptsilzila. A new browser window will open up with an instance of silzila appNote: When connecting to Database please check if Database service is up and running. For MS SQL Server, please check if you have installed ODBC Driver and TCP/IP is enabled for the database.
Package: sim2lbuilder
Sim2lBuilder StatsLatest ReleasePyPI DownloadsSimtool BuilderIntroductionsim2lbuilder is an utility library to create Graphical User interfaces on Jupyter notebooks.
sim2lbuilder is based on ipywidgets, and allow users to describe Apps based on their inputs, outputs and layout. Callback functions can also be referenced to be triggered by events on the widgets
sim2lbuilder can display described tools as widgets, or generate python code to be modified.Installationpipinstallsim2lbuilderUsageschema={'inputs':{'n1':{'type':'IntText','value':1},'n2':{'type':'IntText','value':3}},'outputs':{'sol':{'type':'IntText'},},'layout':{'type':'HBox','children':{'n1':None,'n2':None,'button':{'type':'Button','click':'SUM','description':'=',},'sol':None}}}fromsim2lbuilderimportWidgetConstructors=WidgetConstructor(schema)defSUM(w):w.outputs["sol"].value=w.inputs["n1"].value+w.inputs["n2"].values.SUM=SUMs.assemble()SUM(s)display(s)Create a Sim2l GUI (Widget)fromsim2lbuilderimportWidgetConstructor,GetSimtoolDefaultSchemafromsimtoolimportsearchForSimTool,getSimToolInputs,Runschema=GetSimtoolDefaultSchema("meltingkim")defRunSimTool(widget,*kargs):stl=searchForSimTool("meltingkim")inputs=getSimToolInputs(stl)fori,winwidget.inputs.items():inputs[i].value=w.valuer=Run(stl,inputs)foroutk,outinwidget.outputs.items():without:print(r.read(outk))s=WidgetConstructor(schema)s.RunSimTool=RunSimTools.assemble()sCreate a Sim2l GUI (Generate Code)fromsim2lbuilderimportWidgetConstructor,GetSimtoolDefaultSchemafromsimtoolimportsearchForSimTool,getSimToolInputs,Runschema=GetSimtoolDefaultSchema("meltingkim")defRunSimTool(widget,*kargs):stl=searchForSimTool("meltingkim")inputs=getSimToolInputs(stl)fori,winwidget.inputs.items():inputs[i].value=w.valuer=Run(stl,inputs)foroutk,outinwidget.outputs.items():without:print(r.read(outk))s=WidgetConstructor(schema,format="file")s.RunSimTool=RunSimTools.assemble()sCreate a Sim2l GUI (Print Code)fromsim2lbuilderimportWidgetConstructor,GetSimtoolDefaultSchemafromsimtoolimportsearchForSimTool,getSimToolInputs,Runschema=GetSimtoolDefaultSchema("meltingkim")defRunSimTool(widget,*kargs):stl=searchForSimTool("meltingkim")inputs=getSimToolInputs(stl)fori,winwidget.inputs.items():inputs[i].value=w.valuer=Run(stl,inputs)foroutk,outinwidget.outputs.items():without:print(r.read(outk))s=WidgetConstructor(schema,format="text")s.RunSimTool=RunSimTools.assemble()sCreate a Sim2l App (Javascript)fromsim2lbuilderimport*schema=GetSimtoolDefaultSchema("introtosimtools")s=UIDLConstructor(schema,drawer_width=350,width="100%",height="600px")s.assemble(jupyter_notebook_url=jupyter_notebook_url,)Create a Sim2l App - Jupyter widget (ipywidget)fromsim2lbuilderimport*schema=GetSimtoolDefaultSchema("introtosimtools")s=UIDLConstructor(schema,drawer_width=350,width="100%",height="600px")s.assemble(jupyter_notebook_url=jupyter_notebook_url,uidl_local=True,copy_libraries=True,widget=False,)
Package: sim2net
Author:Michał KalewskiVersion:3.1.2Documentation:http://sim2net.readthedocs.org/en/latest/License:MIT LicenseSimple Network Simulator(sim2net) is a discrete event simulator ofmobile ad hoc networks(MANETs) implemented in Python.  The simulator allows
us to simulate networks of a given number of nodes that move according to the
selected mobility model, run custom applications, and communicate only by
sending application messages through wireless links.InstallationThere are two possibilities to install thesim2netsimulator: with the use
of thepipinstallation tool, or from the source code obtained fromGitHub.1. Using thepipinstallation tool$sudopipinstallsim2net2. Manually from the source codeStep 1.  Clone the project:$gitclonegit@github.com:mkalewski/sim2net.gitsim2net$cdsim2netStep 2.  Run install:$sudopythonsetup.pyinstall“Hello World” example$sim2net-i.$sim2net./configuration.py./application.pyThe full documentation can be found onreadthedocs.org.CopyrightCopyright (c) 2012-2014  Michal Kalewski  <mkalewski at cs.put.poznan.pl>This program comes with ABSOLUTELY NO WARRANTY.THIS IS FREE SOFTWARE, AND YOU ARE WELCOME TO REDISTRIBUTE IT UNDER THE TERMSAND CONDITIONS OF THE MIT LICENSE.  YOU SHOULD HAVE RECEIVED A COPY OF THELICENSE ALONG WITH THIS SOFTWARE; IF NOT, YOU CAN DOWNLOAD A COPY FROMHTTP://WWW.OPENSOURCE.ORG.
Package: sim2x
sim2x -A set of methods and tools for transforming reservoir flow simulation models, well logs and other things into the impedance
and seismic amplitude domain.Installationpipinstallsim2xUsageTODOContributingInterested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.Licensesim2xwas created by Tony Hallam. It is licensed under the terms of the MIT license.
Package: sim32
Sim-EngineHelps to create games without limiting youAdvantagesSpeed- You will very quickly start developing without paying attention to the infrastructure (but you can also tailor it to your needs)Connectability- You can quickly connect the engine to an already created gameFlexibility- You are not even limited to 2 or 3 dimensions!Controllability- You can incredibly deftly operate with the logic of your gameFullness- Integration with pygame rendering solutionInstallationpip install sim32
Package: sim800l-gsm-module
Raspberry Pi SIM800L GSM moduleSIM800L GSM modulelibrary for Linux systems like the Raspberry Pi.This library interfaces the SIM800L GSM device and allows sending, receiving and deleting SMS messages, as well as performing HTTP GET/POST requests, synching/updating the RTC and getting other information from the module.Full information, installation notes, API reference and usage details at thesim800l-gsm-module GitHub repository.
Package: simager
simagerTools for Auto Machine Learning and Text Preprocessing.
End to end ML research (preprocessing, modelling, hyperparameter tuning) just using a few line of codesFeatures- Auto Classification
- Text PreprocessingInstalationpip install simagerGetting StartedAuto Classificationfrom simager.ml import ConfigData, ConfigPreprocess, ConfigModel, AutoClassifier

config_data = ConfigData(
    target="target",
    cat_features = ["column1", "column2"],
    num_features = ["column3","column4", "column5"]
)
config_preprocess = ConfigPreprocess(
    cat_imputer="SimpleImputer",
    num_imputer="SimpleImputer",
    scaler="RobustScaler",
    encoder="OneHotEncoder"
)
config_model=ConfigModel(algoritm=algoritm=[
    "DecisionTreeClassifier",
    "KNeighborsClassifier",
    "LogisticRegression",
    "SVC",
    "RandomForestClassifier",
    "AdaBoostClassifier",
    "XGBClassifier",
    "LGBMClassifier",
    "CatBoostClassifier"
])

model = AutoClassifier(config_data = config_data,
                 config_preprocess=config_preprocess,
                 config_model=config_model)

model.fit(df)

model.hp_tuning()Text Preprocessingfrom simager.preprocess import TextPreprocess

methods = [
    "rm_hastag",
    "rm_mention",
    "rm_nonascii",
    "rm_emoticons",
    "rm_html",
    "rm_url",
    "sparate_str_numb",
    "pad_punct",
    "rm_punct",
    "rm_repeat_char",
    "rm_repeat_word",
    "rm_numb",
    "rm_whitespace",
    "normalize",
    "stopwords"
]

cleaner = TextPreprocess(methods=methods)

cleaner("your text here)Full Example of UsageHere
Package: simago
This package can be used to generate random populations based
on (publicly availabled) aggregated data.These populations can then for example be used for experimentation in the field
of machine learning or simulation studies.Thesimagopackage is available onPyPI,
the source code onGithuband
the documentation onReadTheDocs.
The package is released under the GPLv3 licence and tested for Python 3.7 and up.See the changes in thechangelog.UsageThe easiest way to get started, after installing the package withpip install simago,
is to use the functiongenerate_population()fromsimago.population.
This function creates an instance of thePopulationClassobject with
the generated population Pandas DataFrame as thePopulationClass.populationattribute.The population DataFrame contains a row for every person and a column for each
property. The values for these properties are randomly drawn from probability
distributions defined by the supplied data. This is done by supplying a
settings (YAML) file, a data (CSV) file and possibly a conditions (CSV) file.
For more guidance see theexamplein the documentation.How to contributeIf you would like to contribute to this project, please check out thecontributing guidelines.
Package: simAIRR
simAIRRsimAIRR provides a simulation approach to generate synthetic AIRR datasets that are suitable for benchmarking machine learning (ML) methods, where undesirable access to ground truth signals in training datasets for ML methods is mitigated. Unlike state-of-the-art approaches, simAIRR constructs antigen-experienced-like baseline repertoires and introduces signals by following the empirical relationship between generation probability and sharing pattern of public sequences calibrated from real-world experimental datasets.For installation instructions and user guide, see documentation:https://kanduric.github.io/simAIRR/
Package: simanim
SimAnim - Python framework for simple simulationsInstalationYou need to have Python installed, version 3.6 or later. If you run Python using command other thanpython(e.g.python3orpy) use appropriate command instead ofpythonin the rest of the instructionsInstall package usingpython -m pip install simanimUseSee example:https://github.com/Petlja/simanim/blob/master/examples/projectile_motion.pyAll coordinates use logical units andyaxis is directed upward.More istructions to come...
Package: simanneal
simannealis a python implementation of the
[simulated annealing optimization](http://en.wikipedia.org/wiki/Simulated_annealing) technique.Simulated annealing is used to find a close-to-optimal solution among an
extremely large (but finite) set of potential solutions. It is particularly
useful for [combinatorial optimization](http://en.wikipedia.org/wiki/Combinatorial_optimization)
problems defined by complex objective functions that rely on external data.