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-0.4.301.tar.gz (376.6 kB view details)

Uploaded Source

Built Distribution

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

letschatty-0.4.301-py3-none-any.whl (504.2 kB view details)

Uploaded Python 3

File details

Details for the file letschatty-0.4.301.tar.gz.

File metadata

  • Download URL: letschatty-0.4.301.tar.gz
  • Upload date:
  • Size: 376.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.13.3 Darwin/23.6.0

File hashes

Hashes for letschatty-0.4.301.tar.gz
Algorithm Hash digest
SHA256 d3e715dbd5f9a264209a5bc0da98121b1991ad9f18234cd3ca9e542f09792e5b
MD5 4dee769239d253af0005d54d9fb6aa52
BLAKE2b-256 d905e6843c98a9db96ef268a45991e23e21778084dd32d233194498ebdb0b616

See more details on using hashes here.

File details

Details for the file letschatty-0.4.301-py3-none-any.whl.

File metadata

  • Download URL: letschatty-0.4.301-py3-none-any.whl
  • Upload date:
  • Size: 504.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.13.3 Darwin/23.6.0

File hashes

Hashes for letschatty-0.4.301-py3-none-any.whl
Algorithm Hash digest
SHA256 586cb1d049ae7aa14724e7d6a615a3d83e0d51dc8e749eb95c856a0a664f2db8
MD5 ff67b11ee29a2e5b3359a799b2bc245d
BLAKE2b-256 4f5c6f41afcadad54917357efcc74f362c8c3d5143776f63748e6ce85c847d66

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