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-0.4.405.tar.gz (415.2 kB view details)

Uploaded Source

Built Distribution

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

letschatty-0.4.405-py3-none-any.whl (568.8 kB view details)

Uploaded Python 3

File details

Details for the file letschatty-0.4.405.tar.gz.

File metadata

  • Download URL: letschatty-0.4.405.tar.gz
  • Upload date:
  • Size: 415.2 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-0.4.405.tar.gz
Algorithm Hash digest
SHA256 ae53aa2fc6ce4def3d21d678120e20fee536a8722d3c98c70fd30b8fbd13a4c5
MD5 11a9f11b586359130e1097cb89f1afea
BLAKE2b-256 54380b33b1c328344321b21bfbfb015a2703d1c0993c5fd56e618e3312338b78

See more details on using hashes here.

File details

Details for the file letschatty-0.4.405-py3-none-any.whl.

File metadata

  • Download URL: letschatty-0.4.405-py3-none-any.whl
  • Upload date:
  • Size: 568.8 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-0.4.405-py3-none-any.whl
Algorithm Hash digest
SHA256 89d823c5467eb8baef4783eac45afb7f9a2b9c800ded3f874dc12db9913a2b58
MD5 2517a52ea36da1857e95af7a10de8c84
BLAKE2b-256 e7a37798edeaa4f6c822b825e02685a4d742e81ddfa81408490d947e8752f652

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