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-0.4.424.tar.gz (423.9 kB view details)

Uploaded Source

Built Distribution

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

letschatty-0.4.424-py3-none-any.whl (580.5 kB view details)

Uploaded Python 3

File details

Details for the file letschatty-0.4.424.tar.gz.

File metadata

  • Download URL: letschatty-0.4.424.tar.gz
  • Upload date:
  • Size: 423.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.13.12 Darwin/23.6.0

File hashes

Hashes for letschatty-0.4.424.tar.gz
Algorithm Hash digest
SHA256 12e60fba043c981ce4cf8a5da671914b1b954b4da782b1b76f65252ff20d7688
MD5 35f39dc052ce5b9a941314be37dd7964
BLAKE2b-256 6184bbaa9cc4efc81bc08613b7659d0f672a152d2ef177e550dd3f3b5632b436

See more details on using hashes here.

File details

Details for the file letschatty-0.4.424-py3-none-any.whl.

File metadata

  • Download URL: letschatty-0.4.424-py3-none-any.whl
  • Upload date:
  • Size: 580.5 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.1.2 CPython/3.13.12 Darwin/23.6.0

File hashes

Hashes for letschatty-0.4.424-py3-none-any.whl
Algorithm Hash digest
SHA256 9adc57c1d52999988bf2f45eb8fca60f09da452589e8b5bd98f6c2a3e85bb5bf
MD5 d1c7d21afc301692896caf0c58778ae7
BLAKE2b-256 5b277b49a1617bae838809ce0a237f51c3c3f6013ae7c85a26532ee57e7aa2a7

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