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-0.4.248.tar.gz (373.3 kB view details)

Uploaded Source

Built Distribution

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

letschatty-0.4.248-py3-none-any.whl (499.0 kB view details)

Uploaded Python 3

File details

Details for the file letschatty-0.4.248.tar.gz.

File metadata

  • Download URL: letschatty-0.4.248.tar.gz
  • Upload date:
  • Size: 373.3 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-0.4.248.tar.gz
Algorithm Hash digest
SHA256 42bfb8fe53a99bd17ea7446de4e1abac7edd0f493bbfec2edd7b5cbe07faf6a5
MD5 c41644d82343ca28fefb48236770333a
BLAKE2b-256 2816868e13f72e3db58397927f36ae8102d6e95c394e77c93b19dc4a203c2799

See more details on using hashes here.

File details

Details for the file letschatty-0.4.248-py3-none-any.whl.

File metadata

  • Download URL: letschatty-0.4.248-py3-none-any.whl
  • Upload date:
  • Size: 499.0 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-0.4.248-py3-none-any.whl
Algorithm Hash digest
SHA256 0198ab9e05a7c6350b441f41c78036e9cb5be9d7c77c13e8344e95c7f605f722
MD5 ca891168a0e9d78d5423068b6f85c09d
BLAKE2b-256 a1b563b16f8b89e670b64afc12b03af60b818ef1ca96e0b5736df881d5d6bbfa

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