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Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Use GenLayer’s genlayer-test pytest framework in layers: start with fast, in-memory Direct Mode tests for contract logic and state, control web and LLM outcomes with mocks, test the contract’s Equivalence Principle against both agreement and disagreement cases, then run a smaller integration suite in Studio for RPC, network, and validator behavior.
Which GenLayer testing tools should you use?
The documented pytest framework is genlayer-test, installable with pip install genlayer-test. It offers two main modes: Direct Mode for in-memory contract tests and Studio Mode for deploying and interacting with contracts over RPC. GenLayer describes Direct Mode as suitable for quick iteration and CI/CD, while Studio Mode is the documented choice for network behavior and multi-validator consensus. See the GenLayer Testing Suite and Testing Intelligent Contracts documentation.
| Option | Execution context | Best suited to | Important limitation |
|---|---|---|---|
| Direct Mode | Contract Python code runs in-process, with in-memory deployment, test senders and accounts, and VM-context cheatcodes. | Fast checks of contract logic, state, permissions, and expected reverts. | It does not establish RPC, network, or multi-validator behavior. |
| GLSim | A lightweight JSON-RPC simulator that runs the Python runner natively. | Quick development iteration when a simulator is useful. | The setup guide warns of possible incompatibilities with the full GenVM runtime; confirm important runtime-sensitive behavior in Studio. |
| Studio Mode | Deploys contracts to a running GenLayer Studio instance and interacts over RPC. | Integration checks involving transactions, network behavior, and validators. | Requires an available Studio environment and takes more setup than in-memory tests. |
| Bradbury testnet | A testnet environment identified in the setup guide for realistic preproduction checks. | Final checks against a testnet-style environment. | The cited guide says it does not expose the same full validator logs as local Studio, making active debugging less convenient. |
For Studio and network details, consult GenLayer Studio and the Development Setup guide. The setup guide lists Python 3.12 or later for contract work and testing and Docker 26 or later for local Studio; Docker is not required for Direct Mode. Confirm current requirements and network names in the documentation before setting up a project.
How to build a layered test suite
1. Start with deterministic contract behavior
Write Direct Mode tests for behavior whose result should not depend on an external service or validator. Cover constructor behavior, view methods, state changes, access control, boundary inputs, and expected reverts. In-memory deployment and sender fixtures let you exercise these paths without first starting a network.
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2. Control web and LLM outcomes
If a contract uses web or LLM calls, test with controlled mock responses instead of relying on live services for every case. Include ordinary results, empty responses, unexpected content, and errors. Clear mocks between scenarios; where appropriate, enable strict mock checking to detect patterns that were left unmatched or stale. The official examples and guidance are in Testing Intelligent Contracts.
- Verify the contract’s behavior for a valid, representative response.
- Check how it handles no usable response and unexpected response shapes or content.
- Exercise error handling, including whether state remains safe when a call fails.
- Keep each scenario’s mocks isolated so one test cannot accidentally satisfy another.
3. Test the Equivalence Principle, not just one output
GenLayer contracts can involve nondeterministic results. The Equivalence Principle is the rule a contract defines for validators to judge whether a proposed result is acceptable, even when raw outputs differ. A single model response cannot predict whether validators will agree. Test representative cases where different outputs should count as equivalent, as well as ambiguous cases where outputs should be rejected as non-equivalent or lead to disagreement. This tests the contract’s decision rule rather than assuming all validators produce identical text. See the protocol explanations for What is GenLayer? and How GenLayer works.
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4. Check storage serialization
Enable the testing guide’s pickling checks to surface storage serialization problems early. If a contract stores custom classes, follow the documented storage support and dataclass treatment for those classes; do not assume an object that works in an ordinary Python test will serialize correctly in the contract environment.
5. Use Studio for a focused integration layer
After fast tests pass, deploy and exercise a smaller set of high-value scenarios in Studio. Use this layer for deployment behavior, RPC transactions, network interaction, and end-to-end validator checks that Direct Mode cannot prove. Choose the intended hosted, local, or testnet environment deliberately and confirm its configuration before running tests: hosted Studionet, a development preview, and Local Studio are distinct options in the Studio guidance.
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When should you use Direct Mode, GLSim, or Studio?
Choose a test environment based on the behavior you need to establish, not on a presumption that one mode replaces the others. GenLayer’s documentation describes Direct Mode qualitatively as millisecond-scale and requiring no Docker; that is a general speed characterization, not a benchmark for a particular project. Studio tests need an available Studio environment and are the appropriate layer when the test depends on RPC, the network, or multiple validators.
- Use Direct Mode for frequent, deterministic checks of logic, storage, access, and edge cases.
- Use mocks in Direct Mode to test controlled external-result handling without contacting live web or LLM services in every test.
- Use GLSim when its lightweight JSON-RPC flow helps development iteration, then confirm runtime-sensitive behavior in Studio because its native Python runner may differ from GenVM.
- Use Studio Mode for a smaller number of end-to-end checks that depend on RPC, validators, or network execution.
- Use Bradbury testnet for realistic preproduction validation when appropriate, while accounting for the reduced validator-log detail described in the setup guide.
What can each test layer establish?
A useful test report distinguishes what was exercised from what remains untested. Passing in-memory tests support confidence in the tested contract logic and mocked cases; they do not demonstrate that a deployment, RPC transaction, or validator round will behave the same way on a network. Simulator results likewise need runtime qualification. Studio provides the integration context for those network-dependent paths, while a testnet check adds realism but may offer less detailed validator observability than local Studio.
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