Saravanan666/pypi-org huggingface dataset:
Package: talker
TalkerThe almighty remote command executor for Unix machinesBasic UsageConnecting a client to a Redis backendIn [1]: from talker.client import get_talker

In [2]: params = dict(
    host='redis.example.com',
    password='*********',
    port=8415,
    name='SomeRedisServer')

In [2]: client = get_talker(**params)

In [3]: client
Out[3]: <Talker SomeRedisServer/redis.example.com:8415>Running a commandIn [1]: cmd = client.run(host_id, 'bash', '-ce', 'echo hello')

In [2]: cmd.result()
Out[2]: 'hello\n'Waiting for a commandIn [1]: cmd = client.run(host_id, 'bash', '-ce', 'sleep 10')

In [2]: cmd.wait()
Out[2]: 0Command timeoutIn [1]: cmd = client.run(host_id, 'bash', '-ce', 'sleep 10', timeout=2)

In [2]: cmd.wait()
CommandTimeoutError: Command timed out after 2s: `bash -ce sleep 10`
    args = bash -ce sleep 10
    cmd = f812c749-bdf1-4761-bae3-a279b07c64c4
    host_id = 827605a7-791e-4c6c-8f5c-eca52d7849f5.talker-0
    hostname = talker-0
    name = `bash -ce sleep 10`
    retcode = -1
    since_started = 2.2s
    stderr =
    stdout =
    talker = <Talker SomeRedisServer/redis.example.com:8415>
    timeout = 2s
    timestamp = 2019-06-24T15:41:10.112050Command failuresIn [25]: cmd = client.run(host_id, 'bash', '-ce', 'exit 2')

In [26]: cmd.result()
CommandExecutionError: Command execution error: `bash -ce exit 2`
    args = bash -ce exit 2
    cmd = 58564019-88cd-4c1b-8067-b0dada118ac4
    host_id = 827605a7-791e-4c6c-8f5c-eca52d7849f5.talker-0
    hostname = talker-0
    name = `bash -ce exit 2`
    retcode = 2
    since_started = None
    stderr =
    stdout =
    talker = <Talker SomeRedisServer/redis.example.com:8415>
    timestamp = 2019-06-24T15:42:00.020477Ignoring command failuresIn [1]: cmd = client.run(host_id, 'bash', '-ce', 'exit 2', raise_on_failure=False)

In [2]: cmd.result()
Out[2]: ''Logging command output while it's runningIn [43]: cmd = client.run(host_id, 'bash', '-ce', 'for i in {1..5}; do date; sleep 1; done')

In [44]: cmd.log_pipe(logger=logging.getLogger(), stdout_lvl=logging.WARNING)
Mon Jun 24 15:47:43 IDT 2019
Mon Jun 24 15:47:44 IDT 2019
Mon Jun 24 15:47:45 IDT 2019
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Package: talkey
Simple Text-To-Speech (TTS) interface library with multi-language and multi-engine support.Documentation:http://talkey.readthedocs.org/RationaleI was really intrigued by the concept of jasper, a voice-controlled interface.
I needed it to be multi-lingual like me, so this library is my attempt to make having the
TTS engines multi-lingual. A lot of this code is inspired by the Jasper project.Basic UsageInstall from pypi:pipinstalltalkeyAt its simplest use case:importtalkeytts=talkey.Talkey()tts.say('Old McDonald had a farm')If you get atalkey.base.TTSError: No supported languageserror, it means that you don’t have a supported TTS engine installed. Please see below.By default it will try to locate and use the local instances of the following TTS engines:FliteSVOX PicoFestivaleSpeakmbrola via eSpeakInstalling one or more of those engines should allow the libary to function and generate speech.It also supports the following networked TTS Engines:MaryTTS (needs hosting)Google TTS (cloud hosted)For best results you should configure it:importtalkeytts=talkey.Talkey(# These languages are given better scoring by the language detector# to minimise the chance of it detecting a short string completely incorrectly.# Order is not important herepreferred_languages=['en','af','el','fr'],# The factor by which preferred_languages gets their score increased, defaults to 80.0preferred_factor=80.0,# The order of preference of using a TTS engine for a given language.# Note, that networked engines (Google, Mary) is disabled by default, and so is dummy# default: ['google', 'mary', 'espeak', 'festival', 'pico', 'flite', 'dummy']# This sets eSpeak as the preferred engine, the other engines may still be used#  if eSpeak doesn't support a requested language.engine_preference=['espeak'],# Here you segment the configuration by engine# Key is the engine SLUG, in this case ``espeak``espeak={# Specify the engine options:'options':{'enabled':True,},# Specify some default voice options'defaults':{'words_per_minute':150,'variant':'f4',},# Here you specify language-specific voice options# e.g. for english we prefer the mbrola en1 voice'languages':{'en':{'voice':'english-mb-en1','words_per_minute':130},}})tts.say('Old McDonald had a farm')Installing TTS enginesUbuntu/Debian:For festival:sudoapt-getinstallfestivalFor flite:sudoapt-getinstallfliteFor SVOX Pico:sudoapt-getinstalllibttspico-utilsFor eSpeak:sudoapt-getinstallespeakFor mbrola and en1 voice:sudoapt-getinstallmbrola-en1Windows:Install eSpeak:Go tohttp://espeak.sourceforge.net/download.htmland download and installsetup_espeak-<version>.exeFor mbrola and its voices:Go tohttp://espeak.sourceforge.net/mbrola.htmland download and installMbrolaTools<version>.exeand follow directions to install voices fromhttp://www.tcts.fpms.ac.be/synthesis/mbrola/mbrcopybin.htmlFor google TTS:install python package gTTSDownload ffmpeg fromhttp://ffmpeg.zeranoe.com/builds/Extract with 7Zip, and add the bin folder to the PATH.e.g.:extract to C:ffmpeg and add C:ffmpegbin to the PATH(In cmd.exe you should be able to just run ffmpeg and see it showing information, then it is working right)
Package: talkgpt4all
talkGPT4AllA voice chatbot based on GPT4All and talkGPT.Video demo.Please check more details in thisblog post (in Chinese).If you are looking for the older version of talkGPT4All, please checkout todev/v1.0.0branch.InstallationInstall using pip (Recommend)talkgpt4all is on PyPI, you can install it using simple one command:pipinstalltalkgpt4allInstall from source codeClone the code:gitclonehttps://github.com/vra/talkGPT4All.git<ROOT>Install the dependencies and talkGPT4All in a python virtual environment:cd<ROOT>
python-mvenvtalkgpt4allsourcetalkgpt4all/bin/activate
pipinstall-Upip
pipinstall-rrequirements.txtExtra dependencies for Linux usersWe usepyttsx3to convert text to voice. Please note that on Linux ，You need to install dependencies:sudoaptupdate&&sudoaptinstall-yespeakffmpeglibespeak1UsageOpen a terminal and typetalkgpt4allto begin:talkgpt4allUse different LLMsYou can choose different LLMs  using--gpt-model-type <type>, all available choices:{"ggml-gpt4all-j-v1.3-groovy""ggml-gpt4all-j-v1.2-jazzy""ggml-gpt4all-j-v1.1-breezy""ggml-gpt4all-j""ggml-gpt4all-l13b-snoozy""ggml-vicuna-7b-1.1-q4_2""ggml-vicuna-13b-1.1-q4_2""ggml-wizardLM-7B.q4_2"}Use different Whisper modelsYou can choose whisper model type using--whisper-model-type <type>, all available choices:{"tiny.en""tiny""base.en""base""small.en""small""medium.en""medium""large-v1""large-v2""large"}Tune voice rateYou can tune the voice rate using--voice-rate <rate>, default rate is 165. the larger the speak faster.e.g.,talkgpt4all--whisper-model-typelarge--voice-rate150RoadMapAdd source building for llama.cpp, with more flexible interface.More LLMsAdd support for contextual information during chating.Test code on Linux，Mac Intel and WSL2.Add support for Chinese input and output.Add Documents and Changelogcontributions are welcomed!
Package: talk-in-code
talk-in-codeTransformnatural languagestrings onPython runnable codeUsage:install with pip:pipinstalltalk-in-codeImport on your code:fromtalk_in_codeimporttranslateRun ittranslate.run('print Hello world!',language='pt-BR')CollaborateCreate issues, PR's and share the project, it's open-source!!How to...Print somethingUse the key-word print on your string"print('Hello World')"==translate.run('print Hello World!')Declare a variableUse the key-word variÃ¡vel on your string"idade = int('20')"==translate.run('variÃ¡vel idade recebe inteiro 20')Help us to improve the pt-BR features and create an english translator!
Package: talking-assist
this is the virtual assistant that can speak and listen it can be easily used by just calling one function that is main()
just call main and it will begain. Some people can face problem in installing speech_recognition library or pyaudio
i am providing the link to video how to overcome that issue :-https://www.youtube.com/watch?v=-3am_5jMzJ4NOTE: i have'nt made this video but this is best suited solution after installing pyaudio you can easilly install this module.
to use this assistant as whole you just need to do so!
from talking_assist import shubham_assist as sj
sj.main()
and boom it will start. hope you will enjoy.
Package: talkingheads
TalkingHeads 💬TalkingHeads DocumentationWelcome to TalkingHeads! 💬TalkingHeads is a versatile Python library that serves as an interface for seamless communication with ChatGPT, Claude, Copilot, Gemini, HuggingChat, and Pi  🤖By leveraging the power of browser automation, this library enables users to effortlessly interact with online LLM tools, providing a streamlined and automated approach to generate responses. 🚀✨Prerequisites 📋Before you begin, please ensure that you have Chrome installed on your system. To successfully pass the Cloudflare robot test, it is necessary to have undetected-chrome. 🌐🔒Installationpipinstalltalkingheadsor from source:pipinstallgit+https://github.com/ugorsahin/TalkingHeadsUsagefromtalkingheadsimportPiClientchathead=PiClient()answer=chathead.interact("Hello, how are you today")print(answer)FeaturesFeaturesGeminiClaudeCopilotHuggingChatChatGPTPiUse without login❌❌✅❌❌✅Login*➖➖➖✅✅➖Interact✅✅✅✅✅✅New Chat✅✅✅✅✅✅Regenerate Response✅✅❌❌✅❌Set custom interactions❌❌❌❌✅❌Search Web❌❌✅✅❌❌Plugins❌❌✅❌❌❌Switch Model❌❌✅**✅✅✅✅ (Auto) Save the conversation as csv, h5, html, json, orc, pkl, xlsx, xml✅ : Functionality exists and implemented❌ : Functionality does not exist➖ : Fuctionality exists but not implemented* The first time login is manually done for Gemini, Claude and Copilot. Check documentation for first time setup. Please take a look atFAQto set up.
** The modes of Copilot (Creative, Balanced and Precise) are accessible with model switch. However, it is unclear if they are different models.Issues & ContributionFeel free to dive in, share your knowledge, and collaborate. I would be happy to answer any questions or accept your contributions. Let me know in issues if you need anything.Enhancing our documentation would be fantastic and appreciated. Help me improve documentation with your valuable contributions.
Please indicate your issue with a tag enclosed by square brackets: [FEATURE], [BUG], [DOCUMENTATION], [QUESTION]. If you don't know what to write you can write [MISC]. I will prioritize issues with tags.Where is old ChatGPT_Automation library?You can still run your code to connect ChatGPT, follow the below tutorialexportOPENAI_UNAME=<your@email>exportOPENAI_PWD=><password>fromtalkingheadsimportChatGPTClientchathead=ChatGPTClient()answer=chathead.interact("Hello, how are you today")print(answer)
Package: talkscript2media
This package is an experiment to create an alternative to ARI based only in free
software and open source. Convert a talk script and a set of slides to video.
Why?
We need a tool to automate talks video for education and other purposes. This
can be possible using talk scripts and slides as source and then generate audio
with TTS, join and convert to video.
We need this because the future of resources for education is on plain text
(record a video from a talk -and update this- take a lot of time).… but this tool exists now! Yes, its name is ARI but it is depending of Amazon
Polly Service for TTS (you need money) and the package is not easy to use for
users not familiar with R language.
Goals
- Create a tool for convert talks scripts / comments with images / slides to a
video. Voice is generated using free and open TTS packages that you can install
from your package management.
- This package will offer you a language agnostic interface that no requiered
any level of knowledge in a language programming and will be easy to use for any
context of talks (not only RMarkdown - R language).
- This package will support different file formats used in talks (maybe, using
pandoc conversion).
- Compatibility for multiple features of ARI is important.
Package: talksheet
TalksheetTalksheet is an AI-powered CLI tool for exploring data.It can read data from local CSV filesAnd from remote CSV filesInstallationTalksheet is available on PyPI. You can install it with pip:pipinstalltalksheetUsageTalksheet is a CLI tool. You can run it with thetalksheetcommand.exportOPENAI_API_KEY=<your_openai_api_key>

talksheetRoadmapBetter UI/UXHandle more data formatsExport results
Package: talksql
talksqlExamplesipcfg={'user':'','password':'','host':'','db':''}cfg={'socket':"/tmp/mysql.sock",'user':'','password':'','host':'','db':''}fromtalksqlimport*con=ipconnect(ipcfg)#orcon=sockconnect(cfg)#con is mysql connector connection objectGet a resultsetfromtalksqlimport*sql="select * from table where .."rs,c=xecrs(con,sql)#rs is array for rows and columns of resultset#c is cursor mysql connection# - go to mysql connector if you have to use the cursor to iterate#this works unless you need to deal with large datasetsSub data and get a resultsetfromtalksqlimport*sql="select * from table where column=%s"data=(value,)#data is %s sub-edrs,c=xecrs(con,sql,data)fromtalksqlimport*sql="delete from table"#data is %s sub-ed if given like resultsetc=xec(con,sql)#c is the cursorFew moresqlaofa, sqlaofd are experimental and only works as string data
Package: talk-summarizer
talk-summarizerPython library to summarize talks. Turn a video file into a PDF report with a summary of each section of the talk.summarize_talk.py- operates on a talk/lecture where there is a video of the speaker and slides.usesffmpegto extract the audio from the videouseswhisperto transcribe the audiousesOpenCVto identify slide transitions and extract slidesusesOpenAIto summarize each sectionInstallationInstall this library usingpip:pip install talk-summarizerUsagepythontalk_summarizer/summarize_talk.py\--output_diroutput\--video_filevideo.mp4\--no-summarize\--whisper_modeltinyDevelopmentTo contribute to this library, first checkout the code. Then create a new virtual environment:cd talk-summarizer
python -m venv venv
source venv/bin/activateNow install the dependencies and test dependencies:pip install -r requirements.txtTo run the tests:pytestInstall pre-commit hooks:pre-commit installSet API keysMake sure yourOPENAI_API_KEYis set as an environment variable in either your.bashrcor.zshrcfile. For example:exportOPENAI_API_KEY=sk-1234...TODOget output directory working (ffmpeg not working with output directory)create different tasks liketranscribe(video --> audio, transcript, overall summary). Right nowsummarize_talkworks on a video (video with slides --> audio, slide images, transcript, section summaries, overall summary, report)add more unit testsusepyproject.tomlinstead ofsetup.py
Package: talktosql
TalkToSQLTalkToSQL is an CLI tool that lets you query your DB with natural language instead of SQL queries.Usage$talktosqllearn
SuccessfullysavedtheDBSchemaInfoto/Users/woniesong92/.talktosql_schema_info

$talktosqlask--q"Who owns a dog?"SELECTo.first_name,o.last_nameFROMOwnersoJOINPetspONo.owner_id=p.owner_idWHEREp.species='dog';+------------+-----------+|first_name|last_name|+------------+-----------+|John|Doe||Jane|Doe||Bob|Smith|+------------+-----------+

$talktosqlask--q"Is there anyone who owns a cat named Mittens?"SELECTo.first_name,o.last_nameFROMOwnersoJOINPetspONo.owner_id=p.owner_idWHEREp.species='cat'ANDp.pet_name='Mittens';+------------+-----------+|first_name|last_name|+------------+-----------+|Alice|Johnson|+------------+-----------+QuickstartInstall the packagepip install talktosql -USet the environment variablesYou can create a.envfile in your local directory to get kickstarted.OPENAI_API_KEY="SOME_API_KEY"
OPENAI_ORG_ID="SOME_ORG_ID"
OPENAI_MODEL_NAME="gpt-4"
TALKTOSQL_DATABASE_URL="mysql://myuser:mypassword@localhost/mydb"
TALKTOSQL_DATABASE_NAME="mydb"Alternatively, you can run these in your terminal or set these in your terminal config (~/.zshrc)exportOPENAI_API_KEY="SOME_API_KEY"exportOPENAI_ORG_ID="SOME_ORG_ID"exportOPENAI_MODEL_NAME="gpt-4"exportTALKTOSQL_DATABASE_URL="mysql://myuser:mypassword@localhost/mydb"# export TALKTOSQL_DATABASE_URL="postgresql://myuser:mypassword@localhost/mydb"exportTALKTOSQL_DATABASE_NAME="mydb"Get the value forOPENAI_API_KEYfromOpenAI API KeysGet the value forOPENAI_ORG_IDfromOpenAI Org SettingsHelp TalktoSQL learn your DB Schema. This will save your DB schema info to a file in your home directory (~/.talktosql_schema_info)talktosqllearnQuery your DB in English intead of an SQL querytalktosqlask--q"how many dogs are there?"
Package: talk-video-uploader
This package uploads recordings fromPyvoto YouTube using YouTube
API v3. It is based heavily onGoogle example code. It reads video
metadata YAML files generated by Petr Viktorin’stalk video maker.UsageFirst, you need to authenticate with Google using OAuth 2.0. For that,
you need client secrets file. One is bundled, you can also make yourownin the GoogleDevelopers Console.During the first run, you’ll get prompted to authenticate to a YouTube
channel by opening a webpage in a browser and copying back a token.
Those credentials are then stored by default in~/.config/talk-video-uploader/youtube_credentials.json.To upload videos, create a YAML file with metadata for each video file
and give path to those files as arguments totalk-video-uploader.YAML metadata examplefname:Videofile.mkvdate:2018-01-01event:Ostravské Pyvourl:https://pyvo.cz/ostrava-pyvo/2018-01/lightning:truespeaker:Jan Nováktitle:Interesting topictags:-Python-Pyvo-Somethinglanguage:audio:cs
Package: talkwave
Python TalkWaveOverview 📖TalkWave is an AI chatbot for developers written in Python. It features
a simple HTML frontend and is designed to be accessible across various
browsers and devices. TalkWave supports asynchronous operations and can
handle multiple requests simultaneously.Features ✨Accepts a range of parameters to customize the response, such as max tokens, temperature, and stopping conditions.Accessible design for cross-browser and device compatibility (Chrome, Firefox, Safari, Edge, and mobile).Accurately limits billing with limits and ID binding to prevent exceeding API limits and incurring charges.Implements rate limiting functionality to prevent exceeding API limits and incurring charges.Plain Python implementation with a limited number of dependencies for easy installation and use.Stores responses in log files, JSON, and Markdown formats for easy analysis and sharing.Supports multiple GPT models for generating responses, includinggpt-3.5-turbo,text-davinci-002,text-curie-001,text-babbage-001,text-ada-001.Requirements 📋Python 3.6 or higherTheopenai,tabulate, andpython-dotenvpackagesAn OpenAI API key (get onehere)Installation 🛠Install the required packages:pipinstallopenaitabulatepython-dotenvClone the TalkWave repository:gitclonehttps://github.com/sebastienrousseau/talkwave.gitAdd your OpenAI API key to a.envfile in the project directory:OPENAI_API_KEY="your_api_key_here"Usage 🚀Command Line InterfaceTo use TalkWave, navigate to the project directory in your terminal and
run the following command:pythontalkwave-p"Your prompt here"You can also specify additional options, such as the GPT model, maximum
tokens, temperature, and user ID:pythontalkwave-m1-p"Tell me a joke"-t50-T0.5-u"test@test.com"-r5-s-o"json"For more information on the available options, run:pythontalkwave--helpWeb FrontendTo use the web frontend, navigate to the project directory in your
terminal and run the following command:pythontalkwave/frontend.pyThen, open your browser and navigate tohttp://127.0.0.1:5000. This
will open the TalkWave web frontend, which you can use to generate
responses.File Structure 📁.
├──talkwave
│├──data
│├──templates
││├──404.html
││└──index.html
│├──utils
││├──curl.py
││└──dir.py
│├──__init__.py
│├──__main__.py
│├──core.py
│└──frontend.py
├──CONTRIBUTING.md
├──Dockerfile
├──LICENSE-APACHE
├──LICENSE-MIT
├──MANIFEST.in
├──README.md
├──README_fr.md
├──TEMPLATE.md
├──pylintrc
├──pyproject.toml
├──requirements.txt
├──setup.cfg
└──setup.pyLicense 📜The project is licensed under the terms of both the MIT license and the
Apache License (Version 2.0).Apache License, Version 2.0MIT license
Package: talkweb
TalkwebAssemble pages.Talkweb makes a Object tree of html and allows addition, insertion and deletion to the tree like DOM.fromtalkwebimport*roots=h2o(htmlfile)#assuming htmlfile has &lt;!Doctype html&gt;&lt;html&gt;&lt;div id="x"&gt;&lt;/div&gt;&lt;/html&gt;#cell is a noderoots[1].findcellbyid("x")widget=h2o(widgethtmlfile)roots[1].addcell(widget)html=''forrootinroots:html+=root.html()print(html)Like it, then you will like to develop with talkweb. If not, leave you to templates and it's rules.
Package: talkytrend
Retrieve asset trend and economic data.Trading view connectivityNews connectivityFOMC reminderHow to use ittalky = TalkyTrend()
    result = await talky.fetch_signal()
    #  BUY
    result = await talky.fetch_event()
    print(result)
    #  Title:  FDA advisers say new Alzheimer’s drug lecanemab slows cognitive decline
    # Description:  Panel’s opinion could pave way for full regulatory approval next month for treatment of disease that affects 6.5m Americans
    monitor = await talky.monitor() #ongoing monitoring
    # New signal for BTCUSD (4h): STRONG_SELL
    # Key event: {'title': 'OPEC-JMMC Meetings', 'country': 'ALL', 'date': '2023-06-04T06:15:00-04:00', 'impact': 'High', 'forecast': '', 'previous': ''}\
    # Key news: FDA advisers say new Alzheimer’s drug lecanemab slows cognitive declineDocumentation
Package: talkzoho
A python wrapper library for Zoho API calls which aims to unify the API
for the different Zoho Products (CRM, Support, Projects etc).NOTE: Only the crm client is in a production ready state.The library has asynchronous interface i.e.fromtalkzohoimportCRMClientasyncdefmain():crm=CRMClient(auth_token='xxx')account=awaitcrm.accounts.get('7030050000019540342')However, Talk Zoho also provides the helper functiontalkzoho.utils.waitfor usage in synchronous code.fromtalkzohoimportCRMClientfromtalkzoho.utilsimportwaitaccount=wait(crm.accounts.get,'7030050000019540342')InstallationpipinstalltalkzohoExample UsagefromtalkzohoimportCRMClientasyncdefmain():crm=CRMClient(auth_token='xxx')# Get Accountaccount=awaitcrm.accounts.get('7030050000019540342')# Insert Leadlead_id=awaitcrm.leads.insert({'First Name':'Bill','Last Name':'Billson'})# Filter Leadsbills=awaitcrm.leads.filter(term='Bill',limit=1)# Update Contactcontact_id=awaitcrm.contacts.update({'CONTACTID':'7030050000019540536','First Name':'Jill','Last Name':'Jillson'})# Delete Contactsuccess=awaitcrm.contacts.delete('7030050000019540536')Renamed and Custom ModulesTalk Zoho supports renamed standard modules; when initialising theCRMClientpass the flag to indicate if you want to use Zoho’s
canonical names or the user’s aliases. The flag (use_module_aliases)
defaults toFalse.asyncdefmain():crm=CRMClient(auth_token='xxx',use_module_aliases=False)potential=awaitcrm.potentials.get('7030050000019540360')crm=CRMClient(auth_token='xxx',use_module_aliases=True)opportunity=awaitcrm.opportunities.get('7030050000019540360')# potential == opportunityThis works the same for custom modules:asyncdefmain():crm=CRMClient(auth_token='xxx',use_module_aliases=False)custom_record=awaitcrm.custom_module_8.get('9130050000019540360')crm=CRMClient(auth_token='xxx',use_module_aliases=True)partner=awaitcrm.partners.get('9130050000019540360')# custom_record == partnerError HandlingZoho use a number of ways to inform the client of errors. For example,
CRM always returns a 200 status code with a error message and code in
the body, where as books will return more standard looking HTTP errors.
Talk Zoho tries to unify these and raises a`tornado.web.HTTPError<http://www.tornadoweb.org/en/stable/web.html#tornado.web.HTTPError>`__.
Talk Zoho will also map the Zoho specific codes to their HTTP status
code equivalent.NOTE: Deleting a CRM record (with a correct-looking id) will never
return an error.This is the behavior of Zoho’s CRM API.fromtalkzohoimportCRMClientfromtornado.webimportHTTPErrorasyncdefmain():crm=CRMClient(auth_token='xxx')try:account=awaitcrm.accounts.get('1234')exceptHTTPErrorashttp_error:# HTTPError(404, reason='No record available with the specified record ID.')print(http_error)