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ImportSpy — System Architecture

Architectural Vision

ImportSpy is designed as a generic runtime validation framework operating at the integration boundary between Python modules.

Rather than being tied to a specific application domain, it was conceived as a reusable architectural component for:

  • plugin frameworks
  • modular backends
  • extensible platforms
  • secure runtime environments

The core idea is to introduce a contract enforcement layer between a provider module and the modules that import it.

In its current implementation, ImportSpy is adopted by a Module A within a codebase to declare formal constraints that must be satisfied by Module B modules importing A.

In this model:

  • Module A acts as the provider
  • Modules B act as consumers
  • contracts define the requirements that consumers must satisfy

The module exposing functionality becomes the point where integration requirements are defined, while consumer modules are validated against those requirements before meaningful interaction can occur.

From an architectural standpoint, this mechanism is a first step toward a more general import-time enforcement layer, designed to evolve toward validation of dynamically loaded modules even outside a controlled application perimeter.

Core Architectural Principles

ImportSpy’s architecture follows a set of explicit principles:

  • Separation of concerns
    Contracts, validation logic, execution context, and the integration point are kept as independent components.

  • Declarative over imperative
    Integration requirements are expressed as structured schemas rather than scattered procedural checks.

  • Fail-fast semantics
    Validation happens before any significant interaction between provider and consumer can take place.

  • Low coupling
    Importing application code should not need to know how validation is implemented.

  • Extensibility
    New validation rules and constraints can be introduced without changing the core engine.

Conceptual Components

At a conceptual level, ImportSpy is organized into four primary components.

1. Contract Model

The contract model represents the expected properties of a consumer module with respect to a provider module.

It can express constraints such as:

  • presence of required classes, functions, or attributes
  • method signatures and parameter structures
  • interpreter or platform requirements
  • runtime environment conditions

The model is intentionally separated from concrete Python objects to ensure:

  • portability
  • serializability
  • schema-driven validation

2. Validation Engine

The validation engine is responsible for:

  • interpreting contract schemas
  • executing validation rules
  • producing structured validation results

It is designed as a rule-based engine, where:

  • each rule validates a single constraint
  • rules are independent from each other
  • results are aggregated into a final outcome

This approach improves:

  • maintainability
  • testability
  • incremental extension of the system

3. Execution Context

The execution context provides runtime metadata used during validation, including:

  • Python interpreter version
  • operating system
  • CPU architecture
  • environment variables
  • runtime configuration

This allows contracts to express context-dependent constraints.

4. Provider–Consumer Integration Point

The integration point represents the mechanism through which ImportSpy is inserted into the interaction flow between modules.

In the current implementation, ImportSpy is imported by a provider module (Module A), which uses the framework to define formal contracts on consumer modules (Modules B) that import A.

In this scheme:

  • Module A acts as the provider
  • Modules B act as consumers
  • contracts define the requirements that consumers must satisfy

This enables validation within a controlled perimeter, without altering the global behavior of Python’s import system.

From an architectural standpoint, this component is designed to evolve toward a more general mechanism capable of:

  • intercepting requests to load dynamically imported modules
  • building the execution context
  • triggering validation
  • preventing execution of non-compliant modules
  • propagating structured validation errors

Conceptual Validation Flow

The following flow represents the target architecture of the system.

In the current implementation, validation is applied to consumer modules (Modules B) importing a provider module (Module A) that explicitly adopts ImportSpy.

  1. A Module B imports a Module A that adopts ImportSpy.
  2. The integration point intercepts the interaction between B and A.
  3. The execution context is built.
  4. The provider-defined contract schema is loaded.
  5. The validation engine executes all rules.
  6. Results are aggregated.
  7. If validation succeeds, interaction can proceed.
  8. If validation fails, the import is aborted.

Architectural Trade-offs

Several trade-offs were considered during design:

  • Strictness vs flexibility
    Stronger contracts increase safety but reduce system dynamism.

  • Performance vs depth of validation
    Deeper introspection increases import-time latency.

  • Generality vs domain specificity
    Generic rules are less optimized than domain-specific rules.

Design Outcome

The resulting architecture provides:

  • a clear separation between contracts and code
  • deterministic behavior at integration time
  • predictable failure modes
  • strong runtime safety guarantees

without requiring invasive changes to application code.