Saravanan666/pypi-org huggingface dataset:
Package: link-duplicates
DuplicatesIdentify duplicate files and replace them with hardlinks on any OS.Intended to be used to reduce the storage space taken up by mutliple copies of similar backups. (E.g. regular google takeouts)UsageCan be run from a command line in Linux, MacOS or Windows and will recursively scan a directory, identify and optionally hardlink any duplicate files found.WARNING:Hardlinking files means if you change any one "copy" all "copies" will change.WARNING:If other hardlinks are presentoutsidethe directories scanned, these may no longer point to the same inode as those within the scanned directories. Consider the situation asundefined.Command linedupes PATHwill display number of duplicate files found underPATHdupes PATH1 PATH2 ...will display number of duplicate files found underand acrossPATH1andPATH2dupes --list PATHS...will list the full sets of duplicate files founddupes --short PATHS...will only list sets of duplicates where there are different file namesand finally ...dupes --link PATHS...will replace duplicate files with hard linksPythonYou can also use the classDuplicateFilesto indentify and optionally link duplicates.AdditionallyBufferedIOFileprovides a binary file which knows itsPathand offers areadchunk()method similar to the text filereadline().Up NextKeep original file mode after hardlinkingSelect leading inode for linkingImproved exception handling from the command linePlease vote on any issues which are important to you.
Package: linked-data-python
Linked-Data PythonThe Linked-Data Python package allow to run .ldpy scripts, run a ldpy interactive console, and import .ldpy library modules.InstallationYou can install the Linked-Data Pythonpip install linked-data-pythonThe Linked-Data Python syntaxThe extension"linked-data-python" for Visual Studio Codeenables the syntax highlighting for Linked-Data Python source files (extensions .ldpy).The Linked-Data Python grammar only uses grammar rules supported by MicroPython 1.18, and adds support for Linked Data languages primitives and constructs:prefix declaration statements:@prefix ex: <http://example.org/> .base declaration statements:@base <http://example.org/> .IRIs: `http://example.org/Prefixed names:ex:PersonRDF literals:"hello"^^xsd:string,f"hello {world}"@enRDF graphs:g{ ex:Person a owl:Class ; rdfs:label "Person"@en }Furthermore, it allows:formatted IRIs:f<http://example/org/{ id }/>formatted nodes in RDF graphs:f{ ex:Person ex:age ?{ age } }Example programs are available in theexamplesfolder of the source code repository.How to useIn the command lineThe Linked-Data Python package is a command line application, nameldpy. It can also be run aspython -m ldpy.$ python -m ldpy -h
usage: __main__.py [-h] [-v] [-l] [-p] [-s] [-i] [-m MODULE | source]

ldpy extends the Python syntax with primitives from the Semantic Web such as namespaces, RDF terms, and RDF graphs.

If no source is given, ldpy will start an interactive console.

positional arguments:
  source                Program read from script file. The file extension may be .ldpy or .py.

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         only displays the current version.
  -l, --debug-lexer     print the lexer output
  -p, --debug-parser    print the parser output
  -s, --show_changes    shows the transformed code before it is executed.
  -i                    starts the interactive console after executing a source
  -m MODULE, --module MODULE
                        Run library module as a script. The module may be a .ldpy or a .py file.As a moduleimport ldpy

ldpy.config.debug_ldpy = True # print transformed source  
ldpy.config.debug_lexer = False # print tokens
ldpy.config.debug_parser = False # print syntax tree

ldpy.transform_source(source) # transform a Linked-Data Python source into a Python sourceRun from the source code1. Dependencies# cd ldpy
pip install -r requirements.txt2. Generate the parserGenerate theSWPythonLexer,SWPythonParser, andSWPythonVisitorusing ANTLR4:# cd ldpy
antlr4 -o ldpy/rewriter/antlr -package ldpy.rewriter.antlr -Xexact-output-dir -Dlanguage=Python3 -visitor -no-listener grammars/LDPython.g4Release NotesAll notable changes to the "linked-data-python" are documented below.[0.0.3] - 2023-02-24useideasimport hooks to enable using.ldpyfiles from import statementsadded interactive ldpy consoleadded line mapping to point to the right line in the.ldpyfile on errorcorrected small bugs in the parser[0.0.2] - 2022-04-30corrected many small bugsadded many examplesadd-dfunctionality[0.0.1] - 2022-04-29Initial release
Package: linked-dict
Linked DictionaryAdvanced python dictionary(hash-table), which can link it-self keys and make calculations into the keys of the dictInstallationUse the package managerpipto install foobar.pipinstalllinked-dictUsageThe syntax of expressions:{'key':'...$(expression)$...'}Initialization:fromlinked_dictimportLinkedDictfromjsonimportdumpsdictionary=LinkedDict({})# {} - your dictExamples:Simple link:example=LinkedDict({'a':5,'b':'$(a)$'})print(dumps(example)){'a':5,'b':5}Expression with one key.As you can seenow I added a spaceoutsidethis expression, and the final value is string:example=LinkedDict({'a':5,'b':'$(a * 2)$ '# here with a space})print(dumps(example)){'a':5,'b':'10 '}Link other expressions:example=LinkedDict({'a':5,'b':100,'c':'$(b + d)$','d':'$(b + a)$'})print(dumps(example)){'a':5,'b':100,'c':205,'d':105}Using all built-in types:example=LinkedDict({'a':['one_item'],'b':'$(a + ["another_item"])$'})print(dumps(example)){'a':['one_item'],'b':['one_item','another_item']}Using your own functions into expressions:some_func=lambdaarg:arg+1example=LinkedDict({'a':5,'b':'$(some_func(a))$'},loc=locals(),# to be able to use your functionsglob=globals()# to be able to use your functions)print(dumps(example)){'a':5,'b':5}Changing:When you change a value, all values that link it change their values too. But links work only in one directionexample=LinkedDict({'a':5,'b':'$(a)$'})print(example)# >>> {'a': 5, 'b': 5}example['a']='another_val'print(example)# >>> {'a': 'another_val', 'b': 'another_val'}example['b']='4'print(example)# >>> {'a': 'another_val', 'b': 4}# !!! 'b' links 'a', but 'a' doesn't link 'b'Warning:1.Keys of your dict must beonlystrings{5:'abc',True:[]}# is prohibited{'5':'abc','True':[]}# is allowed2.Don't make loops of links. Dictionary is protected of this, but you will get the ErrorContributing:Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: linkedin
#OverviewHere's another library based on the LinkedIn API, OAuth and JSON responses.Hope this documentation explains everything you need to get started. Any questions feel free to email me or inbox me.#Install through pip...```pip install linkedin```If `linkedin` is already installed, pass `-I` to your install:```pip install -I linkedin```#Import LinkedIn library```from linkedin import *```#Authorization URL*Get an authorization url for your user*```pythonl = LinkedinAPI(api_key='*your app key*',api_secret='*your app secret*',callback_url='http://www.example.com/callback/',permissions=["r_network"])auth_props = l.get_authentication_tokens()auth_url = auth_props['auth_url']#Store this token in a session or something for later use in the next step.oauth_token_secret = auth_props['oauth_token_secret']print 'Connect with LinkedIn via: %s' % auth_url```If you leave callback_url blank, you can get the oauth_verifier from the web browser. It is a five-digit integer.The permissions parameter is optional. It can be a list or string. The [list of permissions](https://developer.linkedin.com/documents/authentication) is in the LinkedIn API documentation.Once you click "Allow" be sure that there is a URL set up to handle getting finalized tokens and possibly adding them to your database to use their information at a later date. \n\n'#Handling the callback```python# In Django, you'd do something like# oauth_token = request.GET.get('oauth_token')# oauth_verifier = request.GET.get('oauth_verifier')oauth_token = *Grab oauth token from URL*oauth_verifier = *Grab oauth verifier from URL*#Initiate the LinkedIn class in your callback.l = LinkedinAPI(api_key='*your app key*',api_secret='*your app secret*',oauth_token=oauth_token,oauth_token_secret=session['linkedin_session_keys']['oauth_token_secret'])authorized_tokens = l.get_access_token(oauth_verifier)final_oauth_token = authorized_tokens['oauth_token']final_oauth_token_secret = authorized_tokens['oauth_token_secret']# Save those tokens to the database for a later use?```#Getting some user information, search results, network updates.```python# Get the final tokens from the database or wherever you have them storedl = LinkedinAPI(api_key = '*your app key*',api_secret = '*your app secret*',oauth_token=final_tokens['oauth_token'],oauth_token_secret=final_tokens['oauth_token_secret'])# Get your profile information (first name, last name)profile = l.get('people/~', fields='first-name,last-name')print profile# Get search resultssearch = l.get('people-search', params={'keywords':'Hacker'})print search# Get your network updatesfeed = l.get('people/~/network/updates')print feed```# POST a network update```pythonshare_content = {"comment": "Posting from the API using JSON","content": {"title": "A title for your share","submitted-url": "http://www.linkedin.com","submitted-image-url": "http://lnkd.in/Vjc5ec"},"visibility": {"code": "anyone"}}share_update = l.post('people/~/shares', params=share_content)print share_update```
Package: linkedin-auto-scraper
LinkedIn Auto ScraperLinkedIn Auto Scraper is a command-line application designed to scrape cleaned information from LinkedIn profiles based on job titles and locations. The app offers two main commands:loginandscrape. Once you've logged in using thelogincommand, you can perform continuous scraping without the need to log in again, thanks to the authentication caching feature.Table of ContentsInstallationUsageLoginScrapeContributingLicenseInstallationEnsure you have Python 3.x installed.Clone this repository:git clone https://github.com/your-username/linkedin-auto-scraper.gitNavigate to the project directory:cd linkedin-auto-scraperInstall the required dependenciespip install -r requirements.txtUsageLoginTo use the app, you need to log in first. This step is required for authentication purposes. Run the following command:bashlinkedin-auto-scraper loginThis command lets you log in to your LinkedIn account. Follow the prompts to provide your LinkedIn credentials. Your authentication will be cached to allow continuous scraping without repeated logins.ScrapeOnce you're logged in, you can start scraping LinkedIn profiles based on job titles and locations. Run the following command:bashlinkedin-auto-scraper scrapeBy default, the app will search for profiles related to the HR field. You can customize the search by using the following options:--search(-s): Specify the search parameter (default: "hr").--location(-l): Use it to search for profiles in a specific location (default: None).--excel: This option is required and indicates whether to generate an Excel file with the scraped data (default: no-excel).Example usage:bashlinkedin-auto-scraper scrape --search software engineer --location San Francisco --excelFollow the prompts to enter the desired job title and location. The app will scrape and display cleaned information from LinkedIn profiles matching your criteria.ContributingContributions are welcome! If you'd like to contribute to the project, please follow these steps:Fork the repository.Create a new branch for your feature/bugfix:git checkout -b feature-nameCommit your changes:git commit -m "Description of changes"Push to the branch:git push origin feature-nameCreate a pull request.LicenseThis project is licensed under the [MIT License]
Package: linkedin-bot
PACKAGE - LINKEDIN-BOTButCe packages permet d'automatiser les tâches de like, partage et commentaire sur linkedIn.Pour importerfrom bot_linkedin import automate_linkedinFonctionslinkedin_test_driver_manager_chrome(self):Allow to install chromedriver and out in PATHlinkedin_get_ip(self):Allow to return proxylinkedin_create_session_crawl(self):Allow to add options of my driverlinkedin_launch_page(self, link: str):Allow to create my driverlinkedin_connect_account(self, url:str):Allow to connect on LinkedIn account with driverlinkedin_get_last_publication(self):Allow to get a last publication. Here this function return a firstlinkedin_get_publications(self):Allow to get a publication in list contains element de type object_seleniumlinkedin_like_post(self, post):Allow to like a postlinkedin_share_post(self, post, text_share="Merci pour ce post"):Allow to share a postlinkedin_comment_post(self, post, text_comment="Très intéressant :)"):Allow to comment a postlinkedin_close_session(self):Allow to close session create for the driver
Package: linkedin-cat
IntroductionInstall packagepipinstalllinkedin_catPreparationcreate filelinkedin_cookies.jsonplease use Chrome ExtensionEditThisCookieto export linkedin cookies tolinkedin_cookies.jsonExample Usage:fromlinkedin_cat.messageimportLinkedinMessage# linkedin cookie file pathlinkedin_cookies_json='./linkedin_cookies.json'# headless modeheadless=False# Ininialized LinkedinMessagebot=LinkedinMessage(linkedin_cookies_json,headless)# message to sent, use FIRSTNAME or FULLNAME to customized the messagemessage="Hello FIRSTNAME,hope you are doing well. Glad to e-meet with you on linkedin"# Send single request by urlurl="https://www.linkedin.com/in/chandlersong/"bot.send_single_request(url,message)# Send multi request by linkedin url listurls_list=["https://www.linkedin.com/in/chandlersong/","https://www.linkedin.com/in/chandlersong/",]bot.send_multi_request(urls_list,message)
Package: linkedin-cli
linkedin-cliLinkedin command line interface (cli) is a python 3 console application to handle authentication and communication with LinkedIn API v2.Linkedin-cli requires a linkedin application client id and client secret to authenticate a user on the linkedin api v2.Create a linkedin applicationon linkedin developer site if you don't have already.Followtigilloon linkedin for the latest updates.SupportersTigillo - Software Development CompanyRequirementspython 3Installationpython3-mpipinstalllinkedin-cliRunningpython3-mlinkedinUsageusage:linkedin<command>[<args?]Thesearecommonlinkedincommandsusedinvarioussituations:configGetandsetlinkedin-clioptionsloginLoginwithauserforapiaccessmeDisplayloggedinuserdetailspostShareapost

OthercommandshelpPrinthelp(thismessage)versionPrinttheversioninformationConfigure Linkedin ApplicationRun below command and provide your client id and secret of your linkedin application. Configuration will be saved to~/.linkedin/config.jsonfile.linkedinconfiguresetapplicationLinkedin Application ConfigurationGo toauthpage of your linkedin application and addhttp://localhost:4625address as theAuthorized redirect URLs for your appon theOAuth 2.0 settingssection.LoginRun below command and authenticate your linkedin application for your user on the opened web dialog. Once approved your api token will be stored to~/.linkedin/config.jsonfile.linkedinloginShare a PostPut content between double quotes, new lines supported. Only text content supported currently.linkedinpost"Hello connections!Sent from my terminal via linkedin-cli"Post VisibilityDefault visibility option for post command isconnections. Visibility option can be set asconnectionsorpublic.linkedinpost-vpublic"Hello world!Sent from my terminal via linkedin-cli"Buildpython3setup.pybuild
Package: linkedin-dl
LinkedIn-DownloaderA small tool to download videos from linkeding.RequirementsPython 3.7 or higher.pip 22.1.x or higherInstallInstall toolpipinstalllinkedin-dlUsageYou can use this tool very easily, with the argument -h you can obtain information about its use:linkedin-dl-h
usage:linkedin-dl[-h][-mNUMBER][-wNUMBER][-lSECONDS][-qQUALITY]URLFILE

DownloadvideosfromLinkedIn

positionalarguments:URLTheURLtothevideostreamingFILEThefiletosavethevideo.

optionalarguments:-h,--helpshowthishelpmessageandexit-mNUMBER,--max_attemptsNUMBERThemaximumnumberofattemptsincaseofconnectionerror.-wNUMBER,--waitSECONDSAdelaytimebetweenseveraldownloadintents.-lSECONDS,--limitSECONDSThemaximumtimetodownload.0forallthevideo.Bydefault,0.-qQUALITY,--qualityQUALITYThemaximumtimetodownload.0forallthevideo.Bydefault,3200000.WhereURLis the URL with the LinkedIn page that contain the video andFILEis the path to the file to save the video locally in mp4 format, any other format is supported.
The rest of the arguments are optionals:-mNUMBERis the number of attempts to reconnect when the connection fails;-wSECONDSis the time in seconds to wait between each attempt in case of connection fail;-lSECONDSis the limit of time in seconds to download, by default, all the video is downloaded.-qQUALITYis the video quality to download. By default, it is the maximum. The available values are:12800040000080000016000003200000Download a videolinkedin-dl"URL""FILE"-lSECONDS-qQUALITYSome examples:# Download all the videolinkedin-dl"https://www.linkedin.com/video/live/urn:li:ugcPost:6940332883056205824/""Te mereces destacar.mp4"# Download only the first 60 secondslinkedin-dl"https://www.linkedin.com/video/live/urn:li:ugcPost:6940332883056205824/""Te mereces destacar.mp4"-l60
Package: linkedin-information-collections-scraper
collect_informations_linkedin_scraperThis package allow you to get informations about people who are interested about a given keyword and get it in json fileHOW TO USE IT :first step : from linkedin_package.json_scrape or csv_scrape import webscrapethen put your keyword in the input filed in the terminal , after that webscrape need an email and password and keyword like a parameterand finally yyou can tell the function login() and collect_informations() to get the result
Package: linkedin-jobs-pyscraper
Linkedin Jobs PyScraperInstall Package from PypiInstall it using pip.pipinstalllinkedin-jobs-pyscraperExample UsageUse it in your codefromlinkedin_jobs_pyscraper.models.search.searcherimportSearcherfromlinkedin_jobs_pyscraper.models.filtersimportfiltersfromlinkedin_jobs_pyscraper.linkedin_jobs_scraperimportLinkedInJobsPyScraper## create searach query with configurationssearcher=Searcher(search_pages_per_search_term=4,search_terms=['data analyst','data scientist'],batch_size=5,output_filepath='out.csv',location='Germany')search_filter=filters.Filters(experience=filters.ExperienceLevelFilters.INTERNSHIP,job_type=filters.TypeFilters.INTERNSHIP,relevance=filters.RelevanceFilters.RECENT,time=filters.TimeFilters.MONTH)scraper=LinkedInJobsPyScraper(searcher=searcher,filters=search_filter)scraper.start()
Package: linkedin-matrix
linkedin-matrixLinkedIn Messaging <-> Matrix bridge built usingmautrix-pythonandlinkedin-messaging-api.DocumentationNot much yet :)It is a Poetry project that requires Python 3.9+, PostgreSQL. Theoretically, all
you need to do is:Copy thelinkedin_matrix/example-config.yamlfile and modify it to your
needs.Install the dependencies with Poetry:$ poetry installand activate the virtualenv.Generate the registration file$ python -m linkedin_matrix -gand add it to your Synapse config.Run the bridge using:$ python -m linkedin_matrixFeatures & RoadmapROADMAP.mdcontains a general overview of what is supported by the
bridge.DiscussionMatrix room:#linkedin-matrix:nevarro.space
Package: linkedinpdfextractor
linkedin_pdf_extractorAdd a short description here!A longer description of your project goes here…NoteThis project has been set up using PyScaffold 4.3.1. For details and usage
information on PyScaffold seehttps://pyscaffold.org/.Steps to upload it to pypi:
1. Delete the old tag
command to delete the tag on local repo : git tag -d <tagname>2. Push the changes to remote:
command:    git push origin –delete <tagname>3. create a new tag
Command: to create a new tag : git tag -a tagname -m “my version 1.4”4. push that tag
Command:    git push origin tagname5. Build the package distribution
Command:  tox -e build  # to build your package distribution6. Publish the package
Command: tox -e publish – –repository pypi  # to release your package to PyPI
Package: linkedin-pkg
# linkedin_pkg: Create a LinkedIn account with a searchable networkThis Python package is meant to be used to create a LinkedIn account that can have a network of connections that is searchable. There is also various functionality of the account that is described below.## FunctionalityAfter creating an account, you are able to:Add a user to your network:add(<name>)Return the number of connections in your network:number_of_connections()Search your network for a connection using a string keyword:search(<keyword>)Save the current state of your account (coming in version 0.1.2):store()Restore a previous state of your account (coming in version 0.1.2):restore()
Package: linkedin-posts
LinkedIn PostsUtility to share LinkedIn posts using the LinkedIn Marketing APIMade easy to use in Python.Installation and SetupInstall with pippython-mpipinstalllinkedin-postsGenerate LinkedIn's Access TokenThe quickest way to get an Access Token is by using theLinkedIn Token generator toolUsageShare a postBy the time I am writing this sentence, this is the most useful function
of this package.Share a post by using the functionshare_postwith some
arguments.fromlinkedin_posts.postsimportshare_postresponse=share_post("<HERE YOUR ACCESS TOKEN>",comment="publishing a post",author_type="organization",author_id="71513925",)# Do something with your response object r (http.client.HttpResponse)# Interesting parameters to check:# response.getheader("x-restli-id") will return the LinkedIn Post ID# response.code will return 201 if request proccessed correctly...Delete a postDeleting a post is very straightforward.Just just need the access token and pass the LinkedIn Post ID.fromlinkedin_posts.postsimportdelete_postresponse=delete_post("<HERE YOUR ACCESS TOKEN>","urn:li:share:7104319981684674560")# response.code will return 204 if request proccessed correctlyCreate a poll postIt is possible to share a post with a poll by using the following code:fromlinkedin_posts.pollsimportshare_pollresponse=share_poll("<HERE YOUR ACCESS TOKEN>",comment="Hello, this is just a test...",poll_question="Is this is a nice poll?",poll_options=["Yes","No","I do not care"],author_type="organization",author_id="71513925",)# do something with response if you need to!Now go to yourLinkedIn pageand check your published poll!Post with mediaTo create a post with a nice picture you can use this code.# upload a imageupload_request,image_urn=upload_image("<HERE YOUR ACCESS TOKEN>",file="img/nicecv.jpg",author_type=author_type,author_id=author_id,)# create a post with the uploaded imageshare_post_with_media("<HERE YOUR ACCESS TOKEN>",comment="Do you like this nice cv?",author_type=author_type,author_id=author_id,media_id=image_urn)And voilà. Here is your post!