Requirements

Functional

• Wrap the Webex Teams API endpoints in Python-native functions; the functions must accept all required and optional API parameters as inputs and return the response objects as Python-native objects.
• The library must provide Python-native data models for all documented API data models.
• An SDK user must be able to create a connection object providing their authentication and session parameters at initialization.
• Wrapped API endpoints must be exposed and hierarchically organized underneath the connection object.
• The library must raise Python-native exceptions for all API errors.
• The library must abstract and transparently handle API mechanics like pagination.
• The library must provide support for automatic API rate-limit handling; users should be able to disable this feature.
• Users must be able to install the library via Python's PIP package manager (pip install ___).
• Users must have the ability to install pre-release versions.

Non-Functional

In priority order, the following non-functional requirements represent the design goals for the library.

Security

• The library code should not expose confidential information (e.g., access tokens, Personally identifiable information (PII), etc.) through logging, exceptions, or console output. A user's code may choose to do so, but the library should not.

Usability

• The library's structure and codebase should facilitate IDE autocompletion.
• Every user-facing function should have a descriptive docstring that documents the function's parameters and expected behavior.
• The library should provide Quick Start documentation that walks the user through initial setup, use, standard operations, and essential features.
• The library should provide complete library-API documentation with full coverage for all exposed classes, methods, and parameters. Ideally, these should be auto-generated from the source code.

Extensibility

• The library should provide a mechanism to support user-provided data model classes. In other words, the library's API functions should be configurable to return objects generated from user-supplied classes.
• Provided data model classes should be extensible through sub-classing and patching.

Maintainability

• API wrapper functions should provide initial support for new API parameters without requiring a library code update.
• Provided data models should provide initial support for new object attributes and missing/deleted attributes without requiring a library code update.
• The codebase should leverage third-party libraries that provide common technical capabilities, and community developers should keep dependencies to an essential minimum.

Portability

• The codebase and third-party dependencies should be pure-Python code (no platform-dependent C/C++ extensions).
• The library should install and function on any system that provides a supported Python runtime environment.