Skip to main content

Models and custom classes to work across the Chattyverse

Project description

#PUSH

poetry version patch; poetry build; poetry publish

Chatty Analytics

Models and custom classes to work across the Chattyverse.

Lastest update: 2024-11-07

Development instrucions

  1. Install poetry https://python-poetry.org/docs/
  2. Run poetry install
  3. Install with pymongo: poetry install -E db to include pymongo dependencies

Architecture

Models

  • Data containers with Pydantic validation
  • No business logic
  • Little to no functionality (for that, see Services)
  • Used for:
    • Request/response validation
    • Database document mapping
    • Cross-service data transfer
  • Example:
    • Message model

Services

  • Contain all business logic
  • Work with models
  • Stateless
  • Handle:
    • Object creation (factories)
    • Model specific functionality
  • Example:
    • MessageFactory
      • Create a Message from webhook data
      • Create a Message from an agent request to send it to a chat
      • Instantiate a Message from data base information
      • Create a Message from a Chatty Response

Implementation Status

✅ Implemented

Models

  • Base message models
    • DBMessage: Database message model
    • MessageRequest: It models the intent of a message to be sent to a chat, still not instantiated as ChattyMessage.
    • BaseMessage (abstract)
      • Subtypes: AudioMessage, DocumentMessage, ImageMessage, TextMessage, VideoMessage, etc.
  • MetaNotificationJson: Models any notification from WhatsApp to the webhook
    • MetaMessageJson: Models the speicifc Notification with a messages object
    • MetaStatusJson: Models the specific Notification with a statuses object
    • MetaErrorJson: Models the specific Notification with an errors object
  • ChattyResponse: Models a list of pre-set responses in Chatty, that will be instantiated as a ChattyMessage when sent to a chat.
  • Auth0 company registrarion form model
  • Event models
  • Metrics models

Services

  • MessageFactory
    • Create a Message from webhook data
    • Create a Message from an agent request to send it to a chat
    • Instantiate a Message from data base information
    • Create a Message from a Chatty Response

🚧 In Progress

  • Chat and its modules and services
  • Service layer completion
  • Company Assets

Chatty Analytics is a proprietary tool developed by Axel Gualda and the Chatty Team. This software is for internal use only and is not licensed for distribution or use outside of authorized contexts.

Copyright (c) 2024 Axel Gualda. All Rights Reserved.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

letschatty-0.4.226.tar.gz (346.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

letschatty-0.4.226-py3-none-any.whl (451.7 kB view details)

Uploaded Python 3

File details

Details for the file letschatty-0.4.226.tar.gz.

File metadata

  • Download URL: letschatty-0.4.226.tar.gz
  • Upload date:
  • Size: 346.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.1 CPython/3.13.2 Darwin/23.5.0

File hashes

Hashes for letschatty-0.4.226.tar.gz
Algorithm Hash digest
SHA256 da2509c8665e7c52104d16774ce15b5546ea91476e9f5ab8007a8f2bd3920b6a
MD5 d179a787950c6d7ae7885df9f399adad
BLAKE2b-256 39ff7c5bea094966ac2d0aba42b204a0e068b9ecb74bc58d143737656261b19c

See more details on using hashes here.

File details

Details for the file letschatty-0.4.226-py3-none-any.whl.

File metadata

  • Download URL: letschatty-0.4.226-py3-none-any.whl
  • Upload date:
  • Size: 451.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.1 CPython/3.13.2 Darwin/23.5.0

File hashes

Hashes for letschatty-0.4.226-py3-none-any.whl
Algorithm Hash digest
SHA256 5acb55be1179db39fe657e2b937ffc36e934907d1fe02adae50f4896b369e7ae
MD5 3703fd3c3b629b6761f65f588e01b714
BLAKE2b-256 8a66f52936d57b1b054180d8c78a2f5735f5a5cc7c57e93defa7a6c904854bcb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page