Saravanan666/pypi-org huggingface dataset:
Package: site_pinger
version number: 0.4.0
author: Arsen KhalilovOverviewpython program for check work in site urls.for periodical ping sites run with cron.InstallationTo install use pip:$ pip install site_pingerOr clone the repo:$ git clonehttps://github.com/assigdev/site_pinger.git$ python setup.py installUsagefirst you need conf ini file:$ site_pinger_confthen run program$ site_pingerrun with conf in flag$ site_pinger -c path_to_conf_fileFlagsoptional arguments:-h,--helpshow this help message and exit-tTIMEOUT,--timeoutTIMEOUTtime out for async tasks-lLOG,--logLOGlog file path-d,--debugdebug logging-e,--emailreceiver email-cCONFIG,--configCONFIGconfig file path--email-headerEMAIL_HEADERheader for emailContributingTBD
Package: siteplan
A new way to build Django website. Get away from the initial boilerplate project and apps. Siteplan comes with CMS, e-commerce store, payment gateway, task queue and many more features commonly found in modern websites.Start small, grow big.QuickstartCreate the app directory:-mkdir myapp && cd myapp
python -mvenv venv
venv/bin/pip install git+https://github.com/k4ml/siteplan.gitThen runsiteplan:-venv/bin/siteplan init-app
venv/bin/siteplan runIt possible to add your own views (controller) and models for more control and but most of the time you just want to customize the templates when working withsiteplan. The templates are inmyapp/templates/directory.RequirementsPython 3.8 and abovebun
Package: sitePS
Target: Input a human gene sequence and output the phylogenetic age of each amino acid position in the sequence.eg:from sitePS_dabaixian import sitePSsitePS(query_name, output_name, evalue, threads, add, delete)query_nameandoutput_nameare necessary, they are string types, that is, the name of the input query file and the name of the file to be output.evlaueandthreadsare also string types but are optional. They default to 1e-4 and 64 respectively.addrepresents adding species, which is a string type and is the name of a file.deleterepresents removing some species and is a list type. Similar to [22,23,25]If you want to add species
You need to give a file, the content of the file is as follows1328070,20,Prolemur simus379532,20,Propithecus coquereli10029,19,Cricetulus griseus10181,19,Heterocephalus glaberWe automatically use blast to compare the species in our library with the query. Based on the comparison results, we query each layer layer by layer from 27 downwards to see whether the site is consistent with the human amino acid. If there is no amino acid position consistent with human beings in the n layer, no further progress will be made. The position will be located in the n+1 layer.msa_plotsupports visualizing the csv results output bysitePSmsa_plot(out_csv, png, namelist: str = 'Basic_101species_name.list', plot_length: int = 120, plot_dpi: int = 500)out_csvis the csv output bysitePS,pngis the name of the picture you want to output,namelistis the default Basic_101species_name.list,plot_lengthis the length of each line of the msa result you want to output,plot_dpiis the dpi of the output picture
Package: sitereport
siteReport Apihttps://www.sitereport.cn接口SDK支持 py2,py3安装pip install sitereport使用import sitereportaccess_key=””access_secret=””api=sitereport.Api(access_key,access_secret)查询360收录status,result=api.request(“/360/count”,{‘q’:’site:www.taobao.com’})print(result)与可以status,result=api.haosou_count({‘q’:’site:www.taobao.com’})print(result)更多接口用法请到官网查看
Package: site-scout
Site ScoutSite Scout is a tool that can identify and report issues that are triggered in the wild.
A URL or a collection of URLs to visit must be provided. The collection is iterated over
and each URL is visited. All results are collected and reported.The primary goal is to locate issues such as crashes, assertion failures and other
issues detected by AddressSanitizer, UndefinedBehaviourSanitizer and ThreadSanitizer.UsageVisit a collections of URLs:python3 -m site_scout <firefox-bin> -i <urls.yml>-or-Visit one or more URLs (typically used to reproduce an issue):python3 -m site_scout <firefox-bin> -u <url> [<url> ...]Input FormatURLs to visit are stored in the following format:# subdomain.domain.tld/path
domain.tld:
  subdomain:
  - /path
# '*' is used to omit the subdomain
github.com:
  '*':
  - /MozillaSecurity/site-scout
mozilla.org:
  www:
  - /
  - /firefox/browsers/mobile/
  - /firefox/new/
Package: site-scrapers
Installation:pip install site-scrapersWhat this does?Will fetch car details from dealership (concurrently)Usage:importasynciofromsite_scrapers.scrapersimportscrape_allif__name__=='__main__':results=asyncio.run(scrape_all())print(*results,sep="\n")# will output fetched car detailsSupported Dealershipshttps://lietotiauto.mollerauto.lvhttps://lv.brcauto.euhttps://certified.inchcape.lv/auto
Package: sitesearcher
About SiteSearcherSiteSearcheris a command line tool that creates fulltext search indexes of your favourite websites on your machine, and allows you to search them locally.Usagesitesearcher indexer <mydomain>- Create a local search index for<mydomain>sitesearcher search <mydomain>- Open search prompt for<mydomain>Indexing of large sites can take quite long, but you can stop the indexer at any time and continue later at the point where you left off. To halt the indexer, simply type<CTRL>+Conce and wait for graceful exit. To restart run the index command again with the--continueflag, i.e.sitesearcher indexer <mydomain> --continue.Web Server FriendlySiteSearchertries to be web server friendly, while crawling. It obeysrobot.txt, identifies itself with the"SiteSearcher"UserAgent and uses theScrapy Autothrottle Extensionto reduce the load on the server.Installing SiteSearcherIf you havepipinstalled, you can usepipto download and installSiteSearcher.pipinstallsitesearcherSiteSearcheruses theScrapybot framework and therefore inherits itsdependencies.Getting the sourceDownload source releases from PyPI athttp://pypi.python.org/pypi/sitesearcherYou can check out the latest version of source code from GitHub.git clone https://github.com/sbabrass/sitesearcherPython Version SupportSiteSearchersupports Python Versions 2.7 and 3.3+.However switching between Python versions may require a rebuild of your indexes, as there is currently no support for SiteSearcher/Python 2 to read and write indexes created with SiteSearcher/Python 3 and vice versa.History0.1a1Initial version of the SiteSearcher toolCreateScrapycrawler to extract full text content of sitesCreateWhooshindexer to index stored sitesCreate CLI for indexing and searching0.1a2Minor code cleanups
Package: sitesecret
Sitesecret is a tiny library to generate and store per-site secrets.Stop doing this:SECRET = 'my-top-sekrit-key'And do this instead:import sitesecret

SECRET = sitesecret.get_secret(__name__)SECRETwill be initialized with 1024 octets of random data, suitable for
cryptographic applications. The data will be saved in the current directory in
a file named.sitesecret-<modulename>.Subsequent calls will return the same secret value and sitesecret ensures
that only a single secret is ever generated — even if multiple processes callget_secretat the same time .0.1.1 (released 2015-12-19)Fix Python 3 compatibility issue0.1 (released 2015-12-18)Initial release
Package: sitesize
Site SizeReturns the size of the webpage which url is passedUsageimportsitesize# get the size of webpage in bytessitesize.get_webpage_size('http://www.github.com/')# check if the url is valid or notsitesize.url_checker('http://www.github.com/')InstallationUsing pippip install sitesizeWithout pipFor Installing the dependency and saving the packagepython setup.py installIf you just want to test the package without installingClone the repositorygit clone https://github.com/Mianto/sitesize.gitNavigate to sitesize folder containing main.pyRun main.py aspython main.py
Package: sitesniffer
Site Sniffer in Python 🐽Site Sniffer is a Python package designed to extract information about a website by providing its URL. It is useful for individuals who need to perform website analysis, including web developers, SEO specialists, and website owners. The package extracts various details such as the IP address, HTTP status code, SSL certificate information, domain registration details, load time, meta description, keywords, and a list of links on the page.InstallationInstall sitesniffer with pip:pipinstallsitesnifferAlternativly:pipinstallgit+https://github.com/thisisjsimon/SiteSniffer.gitUsageMake sure that you have installed Python 3.11 before proceeding.To use SiteSniffer, you need to import it first:fromsitesnifferimportSiteSnifferThen, create an instance of the SiteSniffer class by providing the URL of the website you want to analyze:sniffer=SiteSniffer('https://example.com')You can then call the methods of the SiteSniffer object to get various details about the website:print(sniffer.ip_address())print(sniffer.domain_info())print(sniffer.status_code())# See docs for full listEach of the methods in this package returns the corresponding detail of the website. For example, get_ip_address() returns the IP address of the website.ExamplefromsitesnifferimportSiteSniffersniffer=SiteSniffer('https://google.com')print(sniffer.ip_address())Output'142.250.185.110'Essential Python Libraries for Web Scraping and HTTP RequestsThe following Python libraries are essential for working with thesitesnifferpackage:# standard libraryimportreimportsocketimportsslimporttimeimporttypingimporturllib.parseimportdataclasses# third partyimportbs4importidnaimportrequestsimportwhoisDocsThe defined functions included inSiteSnifferFunction NameFunction Descriptionextract_protocolExtracts the protocol from the URL.extract_hostnameExtracts the hostname from the URL.extract_pathExtracts the path from the URL.ip_addressReturns the IP address of the domain.domain_infoReturns the domain information for the website.status_codeReturns the HTTP status code of the website.ssl_infoReturns the SSL certificate information for the website.load_timeReturns the website's load time.linksReturns a list of links found on the website.is_mobile_friendlyChecks if the website is mobile-friendly.has_responsive_designChecks if the website has a responsive design.has_cookiesChecks if the website uses cookies.has_google_analyticsChecks if the website has Google Analytics installed.page_meta_descriptionReturns the website's meta description.has_meta_descriptionChecks if the website has a meta description.page_keywordsReturns the website's keywords.has_keywordsChecks if the website has keywords.
Package: sitesweeper
sitesweeperSiteSweeper is a Python command-line interface (CLI) tool for crawling websites and generating output files. It supports crawling a website with a given depth, and saving the output in either a single PDF file or a folder of individual PDF files.InstallationInstall sitesweeper with pippipinstallsitesweeperUsagepython3.9-msitesweeperhttps://example.com--output-pathexample
Package: sitesync
sitesync========Script to sync db and/or data from remote hostInstallation------------::pip install git+https://github.com/morlandi/sitesyncUsage-----Provides an easy way to build a working local copy from a remote site, either by:1) DUMP: saving a copy of remote database and data into ./dump/HOST folder2) SYNC: replacing local database and data downloading a fresh copy from remote hostSupported platforms:1) Django (postgresql db + ./public/media/)2) Workpress (mysql + ./www/wordpress/)Usage: sitesync [-h] [-v {0,1,2,3}] [--dry-run] [--quiet] [--localhost]action targetDump remote db and/or data, or Sync local db and/or data from remote instancepositional arguments:action                choices: sync, dumptarget                choices: db, data, alloptional arguments:-h, --help            show this help message and exit-v {0,1,2,3}, --verbosity {0,1,2,3}Verbosity level. (default: 2)--dry-run, -d         simulate actions--quiet, -q           do not require user confirmation before executing commands--localhost, -l       dump db and data from localhost into ./dumps/localhostHistory=======v1.0.3------* Suggest relative local paths in default config file* Added support for legacy Postgresql syntaxv1.0.2------* Python 2 & 3 compatibilityv1.0.1------* Few fixes for Python3v1.0.0------* Initial setup
Package: sithom
sithom READMEDescriptionA package for shared utility scripts that I use in my research projects.I realised I was copying functionality from project to project. So instead, here it is.Install using pippip install sithomInstall using condaconda install -c conda-forge sithomPackage structure├── CHANGELOG.txt      <- List of main changes at each new package version.
├── CITATION.cff       <- File to allow you to easily cite this repository.
├── LICENSE            <- MIT Open software license.
├── Makefile           <- Makefile with commands.
├── pytest.ini         <- Enable doctest unit-tests.
├── README.md          <- The top-level README for developers using this project.
├── setup.py           <- Python setup file for pip install.
|
├── sithom             <- Package folder.
|   |
│   ├── __init__.py    <- Init file.
│   ├── _version.py    <- Key package information.
│   ├── curve.py       <- Curve fitting w. uncertainty propogation.
│   ├── misc.py        <- Miscellanious utilties.
│   ├── place.py       <- Place objects.
│   ├── plot.py        <- Plot utilties.
│   ├── time.py        <- Time utilties.
│   ├── unc.py         <- Uncertainties utilties.
│   └── xr.py          <- Xarray utilties.
|
└── tests              <- Test folder.RequirementsPython 3.8+matplotlibseaborncmoceanxarrayuncertaintiesjupyterthemes
Package: sitka
Sitka is a built environment analysis and modeling library for Python.This library is intended to make modeling and simulation for the built environment more hackable and easier to use for:Portable design toolsScalable web apps and servicesQuick design and analysis studiesInteractive simulations and analysesTesting new modelsThe library is currently being written entirely in Python usingPandasas a core dependency in order to allow easier integration with data analysis inJupyter.A focus of this project is to create tools to make building models more hackable.  The library can be used to create a simple model just a few inputs or a larger whole building model can be created by connecting multiple objects.
Package: sitk-cli
Wrap SimpleITK functions as command linesOverviewCreateTypercommand line interface from functions that useSimpleITKimages (and transforms) as arguments or return type.importSimpleITKassitkimporttyperfromsitk_cliimportregister_commandapp=typer.Typer()@register_command(app)deffill_holes_slice_by_slice(mask:sitk.Image)->sitk.Image:mask=mask!=0output=sitk.Image(mask.GetSize(),mask.GetPixelID())output.CopyInformation(mask)forkinrange(mask.GetSize()[2]):output[:,:,k]=sitk.BinaryFillhole(mask[:,:,k],fullyConnected=False)returnoutputif__name__=="__main__":app()To work, sitk-cli inspects the type annotations of the function and creates a wrapper function that loads images from file and passes these to the original function. Returned images (transforms) are written to a file by the wrapper function..Installationpipinstallsitk-cliDemo
Package: sito-io
sito-ioStandard Interfaces for Transforming Objects - File I/OThe goal of this library is to provide data structures and interfaces which are
at least as ergonomic as existing file I/O and path primitives (open,Path, etc),
while providing strongly typed functionality to facilitate transformations of collections of
files.Core conceptsResourceA Resource is the core unit of abstraction. It is kind of like a sum type of aos.Pathandurllib.parse.ParseResult.
Its essence is to act as a handle to a more sophisticated resource, such as a file, directory,
URL, endpoint, transaction, FIFO, special file, etc.ContextA Context is a Resource that can be used to "anchor" another Resource. For example, a context might behttp://example.com,/home/user, or even.. A context can be:Fully qualified -file:///home/user/foo/bar,http://example.com/foo/bar,ftp://example.com/foo/barAbsolute -/home/user/foo/bar,/home/user/arch.tar::/foo/barRelative -./bar- Relative contexts must be rooted before they can be fully
resolvedNaive -bar- Naive contexts must be rooted before they can be fully resolvedManifestA Manifest is a collection of Resources. This might be files on disk (or a description thereof, it need not exist),
or files in a TAR file, or endpoints. The primary purpose is to facilitate moving collections of files atomically,
capturing I/O of a process, and "slurping up" the data, thus allowing stateful processes to be modeled as a transaction.
This makes a process behave less like a mutation and more like a lambda, improving referential transparency
in pipelines.A Manifest can be used to generate a ManifestFile, a serialized index of the manifest. This can be packed
with the files and give an easy handle to verify the contents of a transaction.
Package: sitorchtools
sitorchtoolsSupport function for train dataset using PytorchFeaturesEarly Stopping based on validation loss
Folder loader based on pytorch DataLoader
Imblanaced image data handling
Spliting Image on Folder to train and test datasetUsageEarlyStoppingfrom sitorchtools import EarlyStopping, folder_loader, img_folder_split
    early_stopping = EarlyStopping(
        patience=7,
        verbose=True,
        delta=0,
        path="best_model.pth",
        trace_func=print,
        model_class=None
        )

    early_stopping(model, train_loss, valid_loss, y_true, y_pred, plot=False)Data Loadertrain_set, train_loader = folder_loader.loader(
    your_train_path,
    transform=your_train_transform,
    batch_size=your_bs,
    imbalance=True)image folder splitimg_folder_split.split_folder(path_to_train_data, path_to_test_data, train_ratio)
Package: sitq
SITQ is a fast algorithm for approximate Maximum Inner Product Search (MIPS).
It can find items which are likely to maximize inner product against a query in sublinear time.BenchemarkRecommendation is one of fields where SITQ can be used.
Experiments were conducted withMovieLens 100K DatasetandMovieLens 20M Dataset.ALS inbenfred/implicitis used to learn vectors of items and users, where the score of (user, item) pair is computed through inner product of those vectors.Precision@10is the ratio of correct recommendations against test dataset.Fetched itemsare items against which inner product are computed.
Hashing algorithms are more preferable as average and standard deviation offetched itemsare smaller.ml-100kSignature length: 4, Minimum fetched items: 20NamePrecision@10Fetched items. AvgFetched items. StdSITQ0.202105.276.6Simple-LSH0.182496.2441.2ITQ0.199131.393.7LSH0.156161.994.4brute force0.242(1680)ml-20mSignature length: 8, Minimum fetched items: 20NamePrecision@10Fetched items. AvgFetched items. StdSITQ0.11296.1151.1Simple-LSH0.1222158.25246.6ITQ0.090111.0332.9LSH0.069531.3912.2brute force0.151(26671)AlgorithmSITQ is an algorithm which combines Simple-LSH[1]and ITQ[2].Simple-LSH utilizes ordinary LSH which is for cosine similarity.
In order to use LSH for MIPS, it converts a vector before computing its signature.LSH computes signatures through transformation matrix which is fixed.
ITQ learns transformation matrix from item vectors for better hashing.SITQ converts vectors by means of Simple-LSH, and learns transformation matrix through ITQ.ExampleInstallpip install sitqGet SignatureimportnumpyasnpfromsitqimportSitq# Create sample datasetitems=np.random.rand(10000,50)query=np.random.rand(50)sitq=Sitq(signature_size=8)# Learn transformation matrixsitq.fit(items)# Get signatures for itemsitem_sigs=sitq.get_item_signatures(items)# Get signature for queryquery_sig=sitq.get_query_signatures([query])[0]Retrieve itemsimportnumpyasnpfromsitqimportMips# Create sample datasetitems=np.random.rand(10000,50)query=np.random.rand(50)mips=Mips(signature_size=8)# Learn lookup table and parameters for searchmips.fit(items)# Find items which are likely to maximize inner product against queryitem_indexes,scores=mips.search(query,limit=10,distance=1)References[1]Neyshabur, Behnam, and Nathan Srebro. “On symmetric and asymmetric LSHs for inner product search.” arXiv preprint arXiv:1410.5518 (2014).[2]Gong, Yunchao, et al. “Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval.” IEEE Transactions on Pattern Analysis and Machine Intelligence 35.12 (2013): 2916-2929.
Package: sitrep
SitRepis a console-based snapshot of Linux system resources written in Python.Requirementspython2(tested with version 2.7)netifacespsutilrequestssetuptoolsInstallationPyPISitRep is onPyPI. To install, simply usepip:$pipinstallsitrepTo upgrade SitRep to the latest version:$pipinstall--upgradesitrepSourceTo install SitRep from source:$wget-chttps://github.com/vonbrownie/sitrep/releases/download/v0.9.1/sitrep-0.9.2.tar.gz$tar-xvzfsitrep-0.9.2.tar.gz$cdsitrep-0.9.2$sudopythonsetup.pyinstall--recordrinstall.txtAdding the--recordrinstall.txtoption generates an install log namedrinstall.txtthat can later be used to track down and uninstall files. Seepython setup.py install--helpfor more options.Note:Python headers are required to install psutil. For example, on
Debian you need to install first thepython-devpackage.UsageJust run:$sitrepAuthorDaniel Wayne Armstrong (aka) VonBrowniehttp://www.circuidipity.comhttps://twitter.com/circuidipitydaniel@circuidipity.comLicenseGPLv2. SeeLICENSEfor more details.
Package: sit-rep-prerelease
Summary: Sit Rep [Pre-Release]| The System Situation Report
Home-page:https://github.com/tushariyer/sit-repAuthor: Tushar Iyer
Author-email: UNKNOWN
License: UNKNOWN
Description: Licensed under the generic MIT License.”sit-rep” can either be downloaded from the Releases page on GitHub and manually added to PATH or installed via “pip”.
Platform: UNKNOWN
Package: sitri
Sitri - powerful settings & configs for pythonSitri - library for managing authorization and configuration data from a single object with possibly different or identical providersInstallationpoetryaddsitri-E"all"orpip3installsitri[all]Extraspacks and providers:1. all - all providers and settings module.
2. settings - pydantic, providers with settings-support.
3. redis - for redis provider.
4. hvac - for HashiCorp Vault provider.
5. vedis - for vedis provider.
6. pyyaml - for YAML provider.
7. orjson - speed-up your json provider (optional).Basics with SystemProviderfromsitri.providers.contribimportSystemConfigProviderfromsitriimportSitriconf=Sitri(config_provider=SystemConfigProvider(prefix="basics"),)System provider use system environment for get config data. For unique - sitri lookup to "namespace" by prefix.Example:In console:exportBASICS_NAME=HueyIn code:name=conf.get_config("name")print(name)# output: HueyDocsRead base API references and other part documentation onhttps://sitri.readthedocs.io/
Package: sitt
Si.T.T. (Simulation of Traffic and Transport)Si.T.T. is a program suite to simulate the traffic and transport of pre-industrial societies. It uses an agent-based
approach to model the simulation. An agent can be thought of as a batch of cargo transported through the network
(rather than an individual person travelling it).Note:This project is WIP at the moment and in pre-alpha status. Please come back later to test the full capabilities.Main repository:https://codeberg.org/SiTT/SiTTPublic mirror:https://github.com/Simulation-of-Traffic-and-Transport/SiTTTable of ContentsInstallationDocumentationExamplesLicenseInstallationYou need Python 3.10 or later to run Si.T.T.pip install sittAfter installation, you can run Si.T.T. using it as a module:python -m sittThis will activate the command line interface and print a help message. For other ways to run Si.T.T., check out the
examples below.DocumentationYou can read some documentation on the following pages:Si.T.T.'S General Concept(with figures)ExamplesCan be found in theexamples directory.Licensesittis distributed under the terms of theMITlicense.