Saravanan666/pypi-org huggingface dataset:
Package: hubspot-api
HubSpot Private APIPython library to interact with HubSpot's Private APIThis is a Python library of HubSpot's Private API, which was reverse-engineered from their Mobile App. It allows users to do any kind of LLM automation / auto-reply (to live chats).It was developed becauseHubSpot doesn't bother making their Public API feature-complete, and have had some modules in BETA for over a year (khm..Conversations).Additional features, which their Public API doesn't support:Conversation: access Live Chat channelsConversation: Assign the conversation to an agentConversation: Tag an agent inside a commentDemo scriptfromhubspot_apiimportHubSpotApidefcb_auth()->str:# In case of 2FA, you'll need to return the codecode=input('Enter 2FA code: ')returncodehs=HubSpotApi('my-email@provider.com','superSecretPw',cb_auth)# You can also do hs.conversations.get_threads() to get all threadsthreads=hs.conversations.get_unassigned_threads()# Needed for assigning threads to agentsagents=hs.conversations.get_agents()fortinthreads:print('---------\nSubject:',t.subject,t.timestamp)msgs=t.read_messages()email_msgs=[f"FROM:{msg.fromName}, AT:{msg.timestamp}, EMAIL TEXT:\n{msg.text}"formsginmsgs]full_conversation=f'EMAIL SUBJECT:{t.subject}\n'+'\n\n'.join(email_msgs).lower()# Do some smart LLM stuff hereif"api"infull_conversationor"code"infull_conversation:t.assign(agents.find('John Doe'))# Tech supportelif"shipping"infull_conversation:t.assign(agents.find('Erik The Red'))# Ops/shippingelif"digital agency"infull_conversation:# They are trying to sell us somethingt.send_message("Thank you for your email, but we are not interested.")t.close()elif"tiktok"infull_conversation:t.spam()# TikTok? Spam for sureelse:# Writing a comment (and tagging an agent) is also supportedagent=agents.find('John Doe')t.comment(f'Hi{agent}, could you assign this to the best person?')Module supportWhile HubSpot has many different modules (contacts, deals, tickets, etc.), most of them work as expected
with theirpublic API. Only Conversations are in "BETA", and have been for over a year now.InstallationTo install this Python package, run the following command:pipinstallhubspot-apiLiabilityNote:This unofficial API library is not endorsed by HubSpot and likely violates their Terms of Service. Use it at your own risk; the creator assumes no liability for any consequences.
Package: hubspot-article-translator
Hubspot-Article-TranslatorAuto translation of Hubspot Knowledgebase Articles powered by SeleniumImportant DisclaimerThis application only performs upserts toDRAFTarticles. It will never modify an article that is published.Demo Videoshttps://github.com/noodle-factory/Hubspot-Article-Translator/assets/53892067/da218794-033d-45fd-9d80-330ca62ba9d5InstallationInstall Google Chrome; This module depends on a chrome driver, so selenium can leverage off of it.pip install hubspot-Article-TranslatorHow to use moduleConfiguring Translation APIsAWS APIimportboto3fromhubspot_article_translatorimporttranslation_manager,AWSTranslateClientif__name__=="__main__":# Setup Translation Client/sboto3.setup_default_session()translation_manager.add_clients(AWSTranslateClient(aws_session=boto3.DEFAULT_SESSION))Azure APIfromhubspot_article_translatorimporttranslation_manager,AzureTranslateClientif__name__=="__main__":# Setup Translation Client/stranslation_manager.add_clients(AzureTranslateClient(key="<AZURE_TRANSLATE_KEY>",location="<AZURE_TRANSLATE_LOCATION>",endpoint="<AZURE_TRANSLATE_ENDPOINT>",api_version="<AZURE_TRANSLATE_API_VERSION>"))Executing the translation workflowimportboto3fromseleniumimportwebdriverfromhubspot_article_translatorimportState,workflow,translation_manager,AWSTranslateClient,AzureTranslateClientif__name__=="__main__":# Create the selenium Chrome driverdriver=webdriver.Chrome()# Execute the workflow, passing parameters into State objectworkflow.execute(driver=driver,state=State(# Your Hubspot Account Emailemail="<HUBSPOT EMAIL>",# Your Hubspot Account Passwordpassword="<HUBSPOT PASSWORD>",# 2FA code from Authenticator Appcode="<HUBSPOT 2FA CODE>",# List of article IDs to translatearticle_ids=["<ID OF ARTICLE TO TRANSLATE>",...],# The ID of the knowledge base that the above articles are inknowledge_base_id="<ID OF THE KNOWLEDGE BASE>",# the source language of articlesfrom_language="en",# the languages each article will be translated to# make sure key aligns with content language codes# https://github.com/noodle-factory/Hubspot-Article-Translator/blob/master/hubspot_article_translator/translation/content_languages/content_languages.json# make sure value is exactly the name of the language in Hubspotto_languages={"es":"Spanish","pt-pt":"Portuguese - Portugal","id":"Indonesian"},# Automatically publish the article once translation is done# Note ensure that you have setup all the knowledge base category translations for each language...# Otherwise you won't be able to publish the articlesauto_publish=True|False))# Close the selenium Driverdriver.quit()Tips & tricksGetting all the article IDsIt would be time consuming to get all the article IDs from each page manually. Instead, navigate to the knowledge base articles page, then open the console and paste this command[...document.querySelectorAll('[data-test-object-id]')].map(e=>e.getAttribute('data-test-object-id')).join("|")Known LimitationsThis hasn't been tested with other browsers, it will likely only work with Chrome currentlyThe account must be configured with 2FA through the authenticator app, and not a mobile phone number
Package: hubspot-conn
Download:http://pypi.python.org/pypi/hubspot-connhubspot-connectionprovides a lightweight abstraction layer for making
requests to the HubSpot API.Here’s an example of how it can be used:fromhubspot.connectionimportAPIKeyfromhubspot.connectionimportPortalConnectionauthentication_key=APIKey('HUBSPOT-API-KEY')withPortalConnection(authentication_key,'client')asconnection:contacts_data=connection.send_get_request('/contacts/v1/contacts/statistics')print("Number of contacts:{}".format(contacts_data.get('contacts')))This project is officially supported under Python 2.7 and Python 3.4, may work with Python 2.6.Version 1.0 Release Candidate 1 (2014-06-23)This is the first public release.Version 1.0 Release Candidate 2 (2014-07-14)Added content-type=’application/json’ for requests with bodyVersion 1.0 Release Candidate 3 (2014-09-15)Made content-type mandatory only when content is expectedVersion 1.0 Release Candidate 4 (2015-02-18)Allowed for extra details in error responses from HubspotVersion 1.0 Release Candidate 5 (2016-03-18)Added Python 3.4 and 3.5 compatibility by: @jtprince
Package: hubspot-connection
Download:http://pypi.python.org/pypi/hubspot-connectionSponsored by:2degrees Limited.hubspot-connectionprovides a lightweight abstraction layer for making
requests to the HubSpot API.Here’s an example of how it can be used:fromhubspot.connectionimportAPIKeyfromhubspot.connectionimportPortalConnectionauthentication_key=APIKey('HUBSPOT-API-KEY')withPortalConnection(authentication_key,'client')asconnection:contacts_data=connection.send_get_request('/contacts/v1/contacts/statistics')print("Number of contacts:{}".format(contacts_data.get('contacts')))This project is officially supported under Python 2.7 and Python 3.4, may work with Python 2.6.Version 1.0 Release Candidate 1 (2014-06-23)This is the first public release.Version 1.0 Release Candidate 2 (2014-07-14)Added content-type=’application/json’ for requests with bodyVersion 1.0 Release Candidate 3 (2014-09-15)Made content-type mandatory only when content is expectedVersion 1.0 Release Candidate 4 (2015-02-18)Allowed for extra details in error responses from HubspotVersion 1.0 Release Candidate 5 (2016-03-18)Added Python 3.4 and 3.5 compatibility by: @jtprince
Package: hubspot-contacts
Python Library to Manage Contacts via the HubSpot APIDownload:http://pypi.python.org/pypi/hubspot-contactsSponsored by:2degrees Limited.hubspot-contactsis a high-level, Pythonic wrapper forHubSpot APImethods in theContacts,Contact ListsandContact PropertiesAPIs.Here’s an example of how it can be used:>>> from hubspot.connection import APIKey, PortalConnection
>>> from hubspot.contacts import Contact
>>> from hubspot.contacts.lists import get_all_contacts
>>>
>>> authentication_key = APIKey("your key")
>>>
>>> with PortalConnection(authentication_key, "Your App Name") as connection:
...     for contact in get_all_contacts(connection):
...         print contact
...
Contact(vid=1, email_address=u'foo@example.com', properties={u'lastname': u'Smith', u'company': u'ACME Ltd.', u'firstname': u'John', u'lastmodifieddate': datetime.datetime(2014, 5, 30, 15, 32, 7, 192000)}, related_contact_vids=[])
Contact(vid=2, email_address=u'bar@example.com', properties={u'lastname': u'Doe', u'company': u'Example Inc.', u'firstname': u'Alice', u'lastmodifieddate': datetime.datetime(2014, 5, 29, 15, 37, 52, 447000)}, related_contact_vids=[])This project is officially supported under Python 2.7, but may work with
Python 2.6 and Python 3.hubspot-contactsdepends onhubspot-connection, a separate library
that abstracts the low-level communication with HubSpot and takes care of
authentication, among other things.ChangelogVersion 1.0 Final (2014-11-20)Relaxed constraints when validating Contact List schema (identity profiles)Version 1.0 Release Candidate 2 (2014-06-27)Increased version required forhubspot-connectionMade ‘booleancheckbox’ the fallback widget for boolean propertiesVersion 1.0 Release Candidate 1 (2014-06-27)Initial release.
Package: hubspot-etl-pipeline-automatic-exporter
The exporterRun by the cronjob on the server, this will open an automated browser window, login and click the export link on the report page.env fileThe .env file must have the following variables:CHROME_USER_DATA_DIRandCHROME_PROFILE_FOLDER: Google Chrome user data dir and folder name. Go to the browser settings to copy;EXPORT_START_URL: URL of the report. You end up in this page after you click on the report name on the main reports page;CHROMEDRIVER_EXECUTABLE_PATH: absolute path to the chromedriver executable;HUBSPOT_LOGIN_EMAIL: Gmail address used to login into hubspot. This email address must appear on the "Sign in with Google" page for the bot to be able to login and continue.
Package: hubspot-tech-writing
Technical Writing on HubSpot»Changelog|PyPI|Issues|Source code|LicenseAboutSupport writing technical documentation onHubSpot.Markdownto HTML converter with a few bells and whistles relevant for creating
HubSpot blog posts.Upload blog posts and files to the HubSpot API, using thehubspot-api-pythonpackage.See community request about »Markdown Support for Technical Bloggers«.Setuppipinstall--upgradehubspot-tech-writingAfter installation, you can verify if it was successful.hstw--versionUsageMarkup ConversionYou can convert a Markdown file on your workstation, and write the output to an HTML file.wget-Ooriginal.mdhttps://github.com/crate-workbench/hubspot-tech-writing/raw/main/tests/data/hubspot-blog-post-original.md
hstwconvertoriginal.mdconverted.htmlAlternatively, convert a Markdown file at a remote location, and write the output to STDOUT.hstwconverthttps://github.com/crate-workbench/hubspot-tech-writing/raw/main/tests/data/hubspot-blog-post-original.mdLink CheckerIn order to report about missing links to the web, or inline images, run the
link checker on your Markdown documents.hstwlinkcheckoriginal.mdAlternatively, you can also use a remote resource here.hstwlinkcheckhttps://github.com/crate-workbench/hubspot-tech-writing/raw/main/tests/data/hubspot-blog-post-original.mdHubSpot UploadUploading to HubSpot is mostly an iterative process, so you will most likely need to use the
program multiple times on the same resource. In order ease invocation, we recommend to define
an environment variable for storing your access token to the HubSpot API.exportHUBSPOT_ACCESS_TOKEN=pat-na1-e8805e92-b7fd-5c9b-adc8-2299569f56c2Upload HTML file from workstation.
The name of the blog post will be derived from the file name.hstwuploadtestdrive.htmlUpload PNG image from workstation to folder path on hubfs.hstwuploadtestdrive.png--folder-path=/foo/barConvert Markdown to HTML, upload the document under a different name, and also upload all
referenced images.hstwupload/path/to/document.md--name=a-different-name--folder-path=/blog/2023/topicFor more detailed information about this feature, please refer to the inline help:hstwupload--helpHubSpot DeleteYou can delete blog post and file entities, by their unique resource identifiers,
or by name resp. path.# Delete blog post by resource identifier.hstwdeletepost--id=138458225506# Delete file by path.hstwdeletefile--path=/testdrive/foo.pngFor more detailed information about this feature, please refer to the inline help:hstwdelete--helpTroubleshootingBlog posts may not contain embedded imagesIf you are uploading directly from GitHub, and run such a command,hstw upload https://github.com/acme/foo-repo/raw/main/article.md --name=testdriveonly to receive an error message like this,{"correlationId":"4836e94d-e42b-47a1-afff-597d8b67ba93","errorType":"BLOG_POST_CONTAINS_EMBEDDED_IMAGES","message":"Blog posts may not contain embedded images. Please upload images to File Manager.","status":"error"}you are most certainly using a "private" repository, wherehstwdoes not have
access permissions to.Prior Arthttps://github.com/verypossible/hubmdhttps://github.com/danjamescrosby/markdown-to-hubspot-blog
Package: hubs-predictor
Price PredictionStart PredictingInstall the package:pipinstallhubs-predictorHow to Use:fromhubs_predictorimportpredict_batch,predict_from_csv# IP = 'localhost' if the container is running locallyIP='164.52.192.139'# Hosted in my private server for quick testing# Predict using CSV file:csv_path='/PATH/TO/YOUR/CSV/FILE.csv'result=predict_from_csv(csv_path,ip=IP)# Predict as list batches# input format should be list of list [[], []]# eg: data = [['2015-01-09 23:15:03.308', 'cart__4', '27.917', '86.632', '11.022', '247384.01', ....., 'supplier__054'],#             ['2015-01-10 24:15:03.308', 'cart__5', '17.917', '76.632', '10.022', '147384.01', ....., 'supplier__055']]data=[[value1,value2,....,value16],[value1,value2,....,value16]]result=predict_batch(data,ip=IP)# NOTE: The input data both `csv_file` and `data` should be in the same feature sequence provided in the 'assignment-data.csv'# i.e: ['timestamp', 'cart', 'geometry/bounding_box/depth', 'geometry/bounding_box/width', ......., 'sourcing/supplier_country', 'sourcing/supplier']# which is 16 columns excluding `target/price`, if `target/price` is provided,  it will be ignored internally.Check Example script:test_package_example.pyfor more clarification.To build and setup local container please checkReplicate / Reproduce Whole Processsee below.Replicate / Reproduce Whole ProcessTraining ProcessPre-requirements:Install conda:linkInstall MLFlow:pipinstallmlflowExtract Data:assignment-data.ziptotrain/data/unzipassignment-data.zip-dtrain/data/Run Mlflow UI server to track the training experiments:cdtrain/
mlflowserver--backend-store-uri./mlruns/&# open 'http://localhost:5000/' to see the experiments# To stop mlflow server use `pkill -f mlflow`Train:# working dir: "ml-engineer-assignment-bendangnuksung/train/"# (OPTIONAL) modify "train/MLproject" file, update parameters such as:# 'datapath' -> path to your data CSV file# 'kfolds'   -> N kfolds you want# 'lr'       -> Set your own learning rate# Run trainingmlflowrun--experiment-namehubs_price_prediction.Deployment ProcessPre-requirements:Install Docker.LinkInstall Docker Compose:pipinstalldocker-composeBuild and Start Docker:# working dir: "ml-engineer-assignment-bendangnuksung/"# (OPTIONAL) Modify "docker-compose.yml" if:# 1. Wants to change PORT# 2. Change the volumes if model stored in different directory. (Default is: "./train/models" because models are stored there after training)docker-composeupBuilding package (Optional):# modify setup.py accordinglypythonsetup.pysdist
pythonsetup.pybdist_wheel
twinecheckdist/*
twineuploaddist/*Now the docker container is Up and Running, you can run the models locally. Just assignIP = 'localhost'fromhubs_predictorimportpredict_batch,predict_from_csvIP='localhost'csv_path='/PATH/TO/YOUR/CSV/FILE.csv'result=predict_from_csv(csv_path,ip=IP)result=predict_batch(data,ip=IP)
Package: hubsync
HubsyncThis script allows you to keep the organization you work in sync with your local workspace.The main objective is to centralize your workflow and integrate all the syncronization and cleaning activities you perform daily related to your local file structure and your github organizationYou can get it with pip by running “pip install hubsync”.Want to contribute? Have a look to ourguidelinesHow it worksThe script mainly relies on your config file “.hubsyncrc” to run all the commands and to customize how to sync your github projects locallyBased on the options within the config files it will sync locally all the organizations you belong too as folders and will create git repositories within them for each github repostory within the org.Moreover, within your local repostiories it will delete all stale branches and set three remotes:origin: url of the main repo (push is disabled)upstream: url of the main repo (both pull and push)fork: url of a fork of the repo within your user spaceNote that if you are the owner of the repo only origin will be setConfig FileThe hubsync config file contains all the configuration that hubsync requires and it is the main way to customize the script.It should be located in in your home with the name .hubsyncrc (~/.hubsyncrc)As your hubsyncrc file includes your github token, remember to make it not readable to any user but yourself.chmod 600 ~/.hubsyncrcExampleAn example of its minimun content (mandatory params) is:[github]token: XXXXXXX[workspace]path: ~/workspace/testSeethis guideabout how to generate a tokenAll optionsBelow you can find all config options with an explanation and the default valueglobalinteractive: Set to false to never get prompted. Hubsync will use defaults always. (True)sync_user: Sync user repositories locally? (True)fork_repos: Create a fork of all organization repos in your user space. (False)case_sensitive: Whether to considering the case when matching github repos and your local folders. (True)githubapi_url: base url of the github api, use this if you want to use hubsync in a github enterprise instance. (https://api.github.com)token: github api token. Never share this with anyone.orgpre: shell command to run before syncing an organization (None)post shell command to run before syncing an organization (None)repopre: shell command to run before syncing an repo (None)post shell command to run before syncing an repo (None)Note: Work ongoing
Package: hubu
# Humble Bundle Archiver## Install / update` $ pip install-Uhubu # or in user space $ pip install-U--userhubu `## UseOnly two ENVs are required:`HUMBLE_BUNDLE_SESSION='"humblebundle _simpleauth_sess"'BUCKET_NAME=humble-bundle$ hubu `For the rest, you can useAWS_PROFILEor specify them as environment variables (see below).## Wasabi`HUMBLE_BUNDLE_SESSION='"humblebundle _simpleauth_sess"'BUCKET_NAME=humble-bundleENDPOINT_URL="https://s3.eu-central-1.wasabisys.com"AWS_ACCESS_KEY_ID="xxxxxxxxxxxxxxx"AWS_SECRET_ACCESS_KEY="xxxxxxxxxxxxxxxxx"`## AWS`HUMBLE_BUNDLE_SESSION='"humblebundle _simpleauth_sess"'BUCKET_NAME=humble-bundleAWS_ACCESS_KEY_ID="xxxxxxxxxxxxxxx"AWS_SECRET_ACCESS_KEY="xxxxxxxxxxxxxxxxx"`
Package: hubugs
WarningI don’t really use GitHub anymore, so this package is somewhat orphaned.  It
should still workandI will fix bugs when they’re pointed out, buthubugsis frankly quite a low priority for me.Introductionhubugsis a very simple client for working withGitHub’s issue tracker.RequirementshubugsrequiresPythonv3.5 or newer.hubugs’s mandatory dependencies
outside of the standard library areclick,html2text,httplib2,Jinja,misakaandPygments.ConfigurationBeforehubugscan operate on issues you must generate anOAuthtoken.hubugsprovides functionality to do this:$ hubugs setup
GitHub user? [JNRowe]
GitHub password? <password>
Support private repositories? (Y/n) y
Configuration complete!NoteYou can revoke the generated token at any time from theGitHub settingspage.If you wish to set the authorisation token from the command line you can use theHUBUGS_TOKENenvironment variable.  For example:$ HUBUGS_TOKEN=xxx hubugs openContributorsI’d like to thank the following people who have contributed tohubugs.PatchesBen GriffithsMatt LeightonBug reportsBrandon CadySorin IonescuIdeasJames GrayJules MarleauSiddiq ShamoonIf I’ve forgotten to include your name I wholeheartedly apologise.  Just drop me
amailand I’ll update the list!BugsIf you find any problems, bugs or just have a question about this package either
file anissueor drop me amail.If you’ve found a problem please attempt to include a minimal testcase so I can
reproduce the problem, or even better a patch!
Package: hubward
hubwardA common question when reading an interesting paper is, “how does relate to my
favorite gene locus?”. To address this question, usually we need to download
the supplemental data, figure out what format it’s in, convert it to some other
useful format, and visualize it alongside our own data.hubwardhelps manage this process, lowering the effort required to track,
manage, organize, and upload many studies for cross-comparison in the UCSC
Genome Browser.Data are organized intotrack hubson the UCSC
Genome Browser, and the namehubwardindicates the direction in which data
are moved into these track hubs. It can also refer to a direction inother
complex systems.The separate repository,hubward-studies, contains examples of prepared
track hubs. Subsets of these can be combined into user-defined hubs, or can
serve as examples for preparing other studies.Documentation can be found athttps://daler.github.io/hubward.OverviewThis postergives an overview ofhubward, and provides a worked example.Further details can be found in thefull documentation.History0.2.2 (2016-01-20)Support for liftover of BAMs (includes a workaround for Crossmap bug that
segfaulted on liftovers with a specified output filename in the test
environment).When lifting over between assemblies and the source assembly doesn’t match
what is configured for a track, raise a ValueError.For lifted-over studies, themetadata.yamlconfig keeps track of the
liftover history in the newstudy/liftoversectionimproved test environment setupimproved tests (checking for existence of uploaded files)0.2.1 (2015-12-05)if thedescriptionfield is empty or missing, fill in the contents of
README as documentation.add functools32 to requirements.txt (thanks Titus Brown)fixes tohubward liftover:downloaded chainfiles are cachedskip tracks where assembly of track differs from the requested–from_assemblyupon lifting over, add a note to the description of the study’s
metadata.yaml to reflect this and also as a comment in the YAML file.workaround for a bug in CrossMap on BED9+ files. The thickStart and
thickEnd fields were not being lifted over correctly.use pycurl for downloading for better handling of URL redirects. This
happens, for example, when downloading supplemental data from ScienceDirectless verbose bigbed/bigwig conversionallow optional fields in metadata to be blankimprovements to testing framework0.2.0 (2015-10-24)Streamlining of the code and CLI. This causes some backward
incompatibility withmetadata.yamlconfig files in version 0.1.0, in
particular, the “source” section is now required. There is now a defined schema
for the metadata and the grouping files so that future changes can be validated
and automatically fixed.0.1.0 (2014-01-11)First release on PyPI.