Saravanan666/pypi-org huggingface dataset:
Package: searchpie
SearchpieA handy tool to search through Wikipedia, Tmdb and Mal.Table Of ContentsSearchpieTable Of ContentsInstallationInstall From PipInstall From SourceUsageCreditsInstallationInstall Using Pippip install searchpieInstall From Sourcepython3 -m pip install --upgrade build
git clone https://github.com/gautam8404/Searchpie
cd Searchpie


python3 -m build
cd distThis will create a dist package in directorydist/
├── searchpie-0.0.4-py3-none-any.whl
└── searchpie-0.0.4.tar.gzAfter that install using pippip install searchpie-0.0.4-py3-none-any.whlUsageSearchpie requires TMDb Api Key to search for movies and tv shows you can get itherealthough you can still use searchpie for everything elsesearchpie [identifier_flag] <query> [option_flag]Example:searchpie -m fight club -p 2-mflag tells searchpie to look into movies data-pflag tells searchpie to fetch 2 results, upto 10 results can be fetchedIncase identifier flag is not provided searchpie will look into default search method, it can be changed using:searchpie --set-defaultFor full help usesearchpie --helpCreditsjikan.moe
Package: search-placeholder
django-search-placeholderAuto add placeholder content for django adminInstallBy gitpipinstallsearch-placeholderUsageAdd app name to settingsINSTALLED_APPS=[..."django.contrib.admin",..."search_placeholder",...]Use search_placeholder.ModelAdmin to replace admin.ModelAdminfrom django.contrib import admin
from search_placeholder import ModelAdmin

@admin.register(ModelClass)
class ModelClassAdmin(ModelAdmin):
    # Just inherit from search_placeholder.ModelAdmin
    # it will auto generate placeholder of search input by
    # the verbose_name of 'field1' and 'field2'
    # Or you can uncomment the next line to custom placeholder
    #search_placeholder = 'Custom content'
    search_fields = ('field1', 'field2')
Package: searchpods
Podcast searcherSearch any podcast in iTunes librarypodsearchfinds podcasts viaiTunes Search API.Search parameters:query- search string (name, author etc)country- ISO alpha-2 country code (us, de, fr etc), default: uslimit- maximum number or search results, default: 5Returned attributes for each podcast:id- iTunes ID (e.g.,979020229)name- podcast name (Talk Python To Me)author- author name (Michael Kennedy (@mkennedy))url- Apple Podcasts URL (https://podcasts.apple.com/us/podcast/id979020229)feed- podcast RSS URL (https://talkpython.fm/episodes/rss)category- main category (Technology)image- 600x600px image URL (https://is4-ssl.mzstatic.com/image/.../600x600bb.jpg)country- ISO alpha-3 country code (USA)episode_count- episode count this year (26)InstallationpipinstallpodsearchUsageSearch podcasts by query:>>>importpodsearch>>>podcasts=podsearch.search("python",country="us",limit=10)>>>podcasts[0].name'Talk Python To Me'>>>podcasts[0].author'Michael Kennedy (@mkennedy)'>>>podcasts[0].url'https://podcasts.apple.com/us/podcast/id979020229'Retrieve podcast by iTunes ID:>>>importpodsearch>>>podcast=podsearch.get(979020229)>>>podcast.name'Talk Python To Me'Development setup$python3-mvenvenv
$.env/bin/activate
$makedeps
$toxContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Make sure to add or update tests as appropriate.UseBlackfor code formatting andConventional Commitsfor commit messages.ChangelogLicenseMIT
Package: search-python
searchA fast, efficiency python package for searching and getting search results with many different search engines.InstallationTo install the package, run the following command:python3-mpipinstallsearch-pythonOr install from Github:python3-mpipinstallgit+https://github.com/Neurs1/search.gitFeaturesThis package support many different search engines.
Provide the best speed with BS4 using lxml.
Fix bugs, adapt new features and page design from fearch engines.
Output in dict type, easier to interact with.UsageSearch using multiple search engines!importsearchsearch.google("Python")search.bing("Python")search.yahoo("Python")Customize Google search engine:importsearchsearch.google("Python",max_results=30,lang="en")You could use your own proxy:importsearchsearch.google("Python",proxies={"https":"https://example.com"})Output formatExamplesearch.google("YouTube"):{0:{"title":"YouTube","url":"https://www.youtube.com/"},1:{"title":"YouTube - Apps on Google Play","url":"https://play.google.com/store/apps/details?id=com.google.android.youtube&hl=en_US&gl=US"},2:{"title":"YouTube - Home | Facebook","url":"https://www.facebook.com/youtube/"},3:{"title":"YouTube - Wikipedia","url":"https://en.wikipedia.org/wiki/YouTube"}}How to access search results:importsearchresults=search.google("YouTube")#At the first result, get the title of the result.print(results[0]["title"])#At the second result, get the url of the result.print(results[1]["url"])Output:YouTube
https://play.google.com/store/apps/details?id=com.google.android.youtube&hl=en_US&gl=USSupported search enginesGoogleBingYahooAol
You could pull a request for other search engines.Known issuesI could only find max results and languages in Google search engine, still trying to figure it out on other search engines.
Package: search-query-finder
Python Search Query FinderGeneral rule-based function that extracts a search query from spoken text given search terms to look out for.Some possible search terms include'to', 'on', 'for', 'about'e.g. 'do a google search on Python.'
    search term = on
    query found = PythonThis function also ignores false search_term_indicators such as'like to', 'love to', 'want to'e.g. 'I want to do a google search on Python'
     false search term = to
     false search term indicator = want
     actual search term = on
     query found = PythonThus, in the above example, the function will correctly ignore'do a google search on Python'as a possible search query and will capture'Python'as the right query.Other exmaples of use cases:'Send an email to Alex'
  search term = to
  query found = AlexArguments: <string> spoken_text, <list> feature_patterns=[],
            <list> search_terms=['to', 'on', 'for', 'search'], <list> false_search_term_indicators=['like', 'love', 'want', 'ready']
Return type: <string> spoken_text (now stripped down to only the search query.)Installationpipinstallsearch_query_finderExample usagefromsearch_query_finderimportfind_query# You can call the function, passing only the sentence.query1=find_query.find_query("do a google search on Python programming.")# expected result = 'Python programming.'# You can also call the function, passing the sentence along with the search_terms you would like the function to search for. By default, the search terms are set to be = ['to', 'on', 'for', 'search']query2=find_query.find_query("send an email to Alex",search_terms=["to"])# expected result = 'Alex'# You can also call the function, passing the sentence along with the false_search_term_indicators you want. By default, these are set to be = ['like', 'love', 'want', 'ready']query3=find_query.find_query("I would like to do a google search for the python programming language",false_search_term_indicators=["like"])# expected result = 'the python programming language'
Package: search-replace
search-replaceis a trivial Python script that implements
search/replace in text files.https://github.com/luismsgomes/search-replaceCopyright (c) 2019 Luís Gomes <luismsgomes@gmail.com>Usagesearch-replace <json-table> [<input-file> [<output-file>]]Where <json-table> is either:an object with search strings as keys and replacement
strings as values, e.g.{"search": "replace"}an array of arrays containing search and replacement
string pairs, e.g.[["search1","replace1"],["search2","replace2"]]a filename preceeded by@, such as@table.json,
and the file should contain the replacement table in one
of the two JSON formats described aboveIn the second form, the order of replacements is ensured
to follow the order of the array.
Package: searchsort
searchsortA Python Package that contains almost all the Searching and Sorting AlgorithmsIt is also available inGitHubInstallationIf there are 2 or more versions of Python installed in your system (which mostly occurs in UNIX/Linux systems) then please run any one of the commands in the BASH Shell :-$pip3installsearchsort$python3-mpipinstallsearchsortIf there is only Python 3.x installed in your system like in Windows systems then please run any one of commands in the Command Prompt :-pip install searchsortpython -m pip install searchsortQuick GuidePlease Read till the EndImport the Package usingimport searchsort as ss.ss.AvailableSearchingAlgorithms()will show you the available Searching algorithms.ss.AvailableSortingAlgorithms()will show you the available Sorting algorithms.All the Functions have theirAsymptotic Analysisin their docstrings. If you wish; you may take a note of it.A Searching ImplementationfromrandomimportshuffleimportsearchsortasssL1=[iforiinrange(1,51)]element=20# Shuffling the Listshuffle(L1)index=ss.LinearSearch(L1,element)ifindex:print(f"{element}found at :",index)else:print(f"{element}not found")Note :-Some of the Algorithms require a sorted array. It is mentioned in the docstring of the functions so please read them carefully.All the Algorithms return the index of the First Occurrence of the element.If Element is Not Present, False is Returned.A Sorting ImplementationfromrandomimportshuffleimportsearchsortasssL1=[iforiinrange(1,51)]# Shuffling the Listshuffle(L1)print("List Before Sorting :",L1)Result=ss.BubbleSort(L1)print("List After Sorting :",Result)Note :-Some of the Algorithms perform an in-place sorting, which means the structure of the Original List will be changed.All the Algorithms return the sorted array, so assigning statements are preferred.'IsSorted' Function ImplementationBesides Searching an Element in an Array and Sorting Arrays, the Package also contains an 'IsSorted' Function that Returns True if an Array isSORTEDin either direction; False If NOT.fromrandomimportshufflefromsearchsortimportIsSortedL1=[iforiinrange(1,51)]print("Is the List Sorted Now? ",IsSorted(L1))# Shuffling the Listshuffle(L1)print("Is the List Sorted Now? ",IsSorted(L1))
Package: searchsplunk
Search SplunkEasily create Splunk searches from Python and get the result as a Python objectRequiresrequests>=2.7.0:https://pypi.python.org/pypi/requestsInstallation instructionsSearchsplunkcan be installed from PyPi.pipinstallsearchsplunkUsage instructionsfromsearchsplunk.searchsplunkimportSearchSplunks=SearchSplunk('https://splunk.acme.com:8089','MYUSER','MYPASS',ssl_verify=True)result=s.search('sourcetype=salt:grains openstack_uid=e0303456c-d5a3-789f-ab68-8f27561ffa0f | dedup openstack_uid')importjsonprintjson.dumps(result,sort_keys=True,indent=2){"fields":[{"name":"_bkt"},{"name":"_cd"},{"name":"_indextime"},{"name":"_kv"},{"name":"_raw"},{"name":"_serial"},{"name":"_si"},{"name":"_sourcetype"},{"name":"_subsecond"},{"name":"_time"},{"name":"host"},{"name":"index"},{"name":"linecount"},{"name":"openstack_uid"},{"name":"source"},{"name":"sourcetype"},{"name":"splunk_server"}],"init_offset":0,"messages":[],"preview":false,"results":[{"_bkt":"main~1122~25B521A6-9612-407D-A1BA-F8KJSEBB7628","_cd":"1122:290410720","_indextime":"1435071966","_kv":"1","_raw":"somefile contents","_serial":"0","_si":["splunkserv","main"],"_sourcetype":"salt:grains","_time":"2015-06-23T11:06:05.000-04:00","host":"server-7654.acme.com","index":"main","linecount":"17","openstack_uid":"e0303456c-d5a3-789f-ab68-8f27561ffa0f","source":"/etc/salt/grains","sourcetype":"salt:grains","splunk_server":"splunkmaster"}]}ContributorspkeeperAuthorRyan CurrahLicenseGPL v2
Package: searchstims
searchstimsPython package to make stimuli like those used in classic visual search experimentshttps://en.wikipedia.org/wiki/Visual_search... but with the exact size to feed them to your favorite neural network.There are links to example configuration files below.For a recent review of factors influencing visual search, please see:http://search.bwh.harvard.edu/new/pubs/FiveFactors_Wolfe-Horowitz_2017.pdfFor a dataset of human subjects performing a similar visual search task, please see:http://search.bwh.harvard.edu/new/data_set_files.htmlInstallationpip install searchstimsIf you want to download and install locally into an environment with Anaconda:/home/you/Documents $ conda create -n searchstims-env python=3.6 numpy pygame/home/you/Documents $ source activate searchstims-env(searchstims-env) /home/you/Documents $ git clone(searchstim) /home/you/Documents $ cd searchstims(searchstim) /home/you/Documents/searchstims $ pip install -e .UsageThesearchstimspackage installs itself so that you can run it from the
command line. You will use a config.ini file to specify the visual search stimuli
you want the package to generate./home/you/Documents $ searchstims config.iniRunning the example script will create a folder~/outputwith visual search stimuli.
For more detail on the structure ofconfig.inifiles used with this package, see./doc/config.md.For examples of config.ini files, see./doc/configs/.
These examples were used in this project:https://github.com/NickleDave/visual-search-nets.jsonoutput fileIn addition to saving visual search stimuli in the output folder,searchstimssaves information about stimuli in a.jsonoutput file.  This.jsonfile is
provided to make it easier to work with the visual search image files,
and analyze results obtained with them. For more detail, see./doc/json.mdLicenseBSD-3CitationIf you use this library, please cite this repository using the DOI:AcknowledgmentsResearch funded by the Lifelong Learning Machines program,
DARPA/Microsystems Technology Office,
DARPA cooperative agreement HR0011-18-2-0019
Package: searchstringparser
Search String ParserdocstestspackageParse a more general search syntax to conform with a particular SQL dialect.Currently, this is implemented usingplywith a general lexer and a parser for
generating PostgreSQL-specific search queries.Free software: BSD licenseInstallationpip install searchstringparserDocumentationhttps://searchstringparser.readthedocs.org/DevelopmentTo run the all tests run:toxChangelog0.3.0 (2018-10-04)Fix a bug in the token parser.Update the infrastructure.0.2.3 (2015-09-29)Publish on PyPi0.2.2 (2015-09-29)Complete documentation0.2.1 (2015-09-28)Add more helpful error messages0.2.0 (2015-09-28)Add complete integration with Travis, Appveyor, Coveralls, and Read the DocsIncrease test coverage to 100%Make source compatible with Python 2.6 - 3.40.1.1 (2015-09-21)Fix GeneralSearchStringLexer regexFix PostgreSQLTextSearchParser rulesAdd first set of tests0.1.0 (2015-09-16)Initial class layout
Package: search-suggestion
Search Suggestionℹ️ OverviewBuild a search suggestion system with millions of search terms with ultrafast query speed. Search Suggestion utilizes comples trie data structures in the background to manage large datasets without compromising speed.🏗️ InstallTo install Search Suggestion, simply use pip:pip install search-suggestion🏁 Quick Startfromsearch_suggestionimportSearchSuggestionss=SearchSuggestion()ss.insert('cat')ss.batch_insert(['car','dog'])result=ss.search('c')print(result)>['cat','car']The number of search results defaults to 10, an optionalmax_suggestionscan be provided to override this value.result=ss.search('c',max_suggestions=20)💭 Feature SuggestionIf you have any requests, please feel free to submit aticket. I will try to prioritize based on available time.
Package: search-terminal
Google Search CLIThis is a simple command-line tool that allows you to search Google from your terminal.InstallationTo install, simply runpip install search-terminal==0.0.1.UsageTo use, simply runsearch <query>. For example, to search for "cats", you would runsearch cats.The results will be printed to the terminal in JSON format.If your search is multi-worded you might alternate to wrapping the text in double quotes. For example, to search for "cats and mice", you would runsearch "cats and mice".Code ExplanationThe code is relatively simple. The main function first checks to make sure that the user has provided a search query. If they have, it calls thegoogle_searcher()function, which performs the search and returns the results. The results are then printed to the terminal in JSON format.Thegoogle_searcher()function first makes a request to the Google search engine, using the user's query as the search term. If the request is successful, the function parses the HTML response and extracts the search results. The search results are then returned to the main function.ConclusionThis is a simple but useful tool that can be used to search Google from the command line. It is easy to use and install, and the code is well-commented and easy to understand.
Package: search-this
OTUS Homework 1 search thisОглавлениеДомашнее заданиеОписаниеДомашнее заданиеСоздать программу-поисковик
Цель: В этой самостоятельной работе тренируем умения: 1. Писать "чистый код" 2. Собирать пакеты Чтобы: Применять принципы написания чистого кода и сборку пакетов Задача: Создать программу поисковик (консольную) Пользователь вводит текст запроса, поисковую систему (google.com, yandex.ru, ...), количество результатов, рекурсивный поиск или нет, формат вывода (в консоль, в файл json, в csv) Программа находит в интернете начиная от стартовой точки все ссылки на веб-странице в заданном количестве (название ссылки и саму ссылку) Если поиск не рекурсивный, то берем ссылки только из поисковика, если рекурсивный, то берем первую ссылку, переходим, находим там ссылки, переходим, ... В зависимости от выбранного формата вывода сохраняем результат (текст ссылки: ссылка) либо в консоль либо в файл выбранного формата
0. Создать репозиторий для нового проекта (gitlab, github, ...)Решить задачуОбратить внимание на следующие принципы:декомпозиция сверху внизsrp - принцип единственной ответственноститермины предметной областиуменьшение зависимостичистые функциицикломатическая сложностьpython3 -m mccabe --min 5 module.py
flake8 --max-complexity 5понятные названия у переменных, функций, классов, модулейконтекст ближе к коду (привязка к комитам, тикетам, комменты, документация, вики)разумное использование фишек pythonкод на английском а не на pythonфичеризм - не слишком гибко, не слишком жестко, обобщать когда используется 2 разатесты демонстрирующие не очевидное поведениестатический анализ кода pycodestyle, flake8, astДобавить setup.py для сборки программы в пакетСдать дз в виде ссылки на репозиторий
Критерии оценки: Задание считается выполненным, когда:
Код запускается без ошибок и программа может получать ссылки по заданному запросу. Есть возможность сборки пакета - 4 балловДополнительно:Проверки flake8 и flake8 --max-complexity 5 не выдают ошибок 1 баллРаботает рекурсивный поиск 1 баллЕсть возможность выбора:
поисковой системы 1 балл
количества результатов 1 балл
рекурсивный поиск или нет 1 балл
вариант вывода (консоль, json, csv) 1 баллИтого:4 + 1 + 1 + 1 + 1 + 1 + 1 = 10 баллов
Рекомендуем сдать до: 07.06.2020ОписаниеИскать можно в Google и DuckDuckGo. Иногда поиск в Google занимает около двух минут, иногда выдает сразу.
DuckDuckGo работает быстро, но если слишком часто делать запросы, то DuckDuckGo банит на некоторое время.Установкаpip install search-thisИспользование$ search_this -h
usage: search_this [-h] -q QUERY [-e {google,duck}] [-c COUNT] [-l {console,json,csv}]
optional arguments:
  -h, --help            show this help message and exit
  -q QUERY, --query QUERY
                        Query for searching. Words define in qoutes.
  -e {google,duck}, --engine {google,duck}
                        Choose the search engine. Default: Google.
  -c COUNT, --count COUNT
                        Count of results. Default: 1.
  -l {console,json,csv}, --logging {console,json,csv}
                        Information ouput. Default: console.
Package: search-torrent
Torrent CrawlerIt is not always easy to find torrents for your favourite movies, and that too while sitting at a place where torrent sites are banned on browsers. Torrent Crawler got its motivation from this issue only. Torrents can be easily downloaded along with their subtitles just by typing name of movies in terminal.An easy way to get your favourite movie torrents. Try it now !!Search for torrents using CLIpipinstallsearch-torrent
search-torrentUse api to get data (movies and subtitles)pythonapi.pyContributinggitclonehttps://github.com/rajat19/torrent-crawler.gitcdtorrent-crawler
pipinstall-rrequirements.txt
pythonsetup.pyinstall
pythontorrent_crawler/search.pyWhat's nextStore search history in cache or something for faster processingIntegrate kickass and piratebay for wider search results
Package: searchunify
SearchUnify SDKOverviewThe SearchUnify SDK for Python enabled developers to easily work with the SearchUnify platform and build scalable solutions with search, analytics, crawlers and more. You can get started in minutes using PyPI or by downloading the tar file.
The SearchUnify SDK for simpliﬁes use of SearchUnify Services by providing a set of libraries that are consistent and familiar for Python developers. It provides support for API lifecycle consideration such as credential management, retries, data marshaling, and serialization. The SearchUnify SDK for Python also supports higher level abstractions for simplified development.Key FeaturesHTTP/2 Support and pluggable HTTP layer, new programming interfaces seamlessly take advantage of HTTP/2 features and provide new ways to build applications.Nonblocking I/O, the SearchUnify SDK utilizes a new, nonblocking SDK architecture to support true nonblocking I/O. It features truly non blocking asynchronous clients that implement high concurrency across a few threads.Getting StartedSign up for SearchUnify, before you begin, you need a SearchUnify account. Please see the oAuth section of the developer guide for information about how to retrieve your SearchUnify credentials.InstallationSDK requires Python 3+ and pip to run.
The recommended way to use the SearchUnify SDK for Python in your project is to consume it from PyPI.pip3installsearchunifyExecutionInitiate SearchUnify Python SDK on Server. Using the SDK, you can route search requests. To start using, initialize the SDK with your URL and API key.fromsearchunifyimportSearchunifyusername="changeme"password="changeme"clientId="changeme"secrets="changeme"instance="changeme"client=Searchunify(instance=instance,username=username,password=password,client_id=clientId,client_secret=secrets)startDate="changeme"endDate="changeme"searchClientId="changeme"data=client.get_tiles_data(startDate=startDate,endDate=endDate,searchClientId=searchClientId)print("The tile data response: ",data)The access token will expire after 4 hours and you need to refresh that.result=client.refresh_token()DocumentationPlease refer to the SearchUnify developer guide to use the SDK.https://docs.searchunify.com/Content/Developer-Guides/SDKs-Python.htmThe documentation is in review and might contain bugs🐞, we will update the link onhttps://docs.searchunify.comonce its's final.LicenseMIT© Powered bySearchUnify!