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Use GenLayer’s documented genlayer-test pytest framework in layers: verify deterministic contract logic in Direct Mode, control web and LLM results with mocks, test the contract’s Equivalence Principle with both agreement and disagreement cases, then run a smaller end-to-end suite in Studio. Direct Mode is for fast in-memory checks; Studio Mode is the documented choice for RPC, network, and multi-validator behavior.
What you need to test GenLayer contracts
genlayer-test is GenLayer’s documented pytest-based testing framework for Intelligent Contracts. Install it with:
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pip install genlayer-testThe framework offers two modes. Direct Mode runs contract Python code in memory without a simulator, Docker, or network. Studio Mode deploys to a running GenLayer Studio instance and interacts with it over RPC. The testing guide describes Direct Mode as suitable for unit tests and quick iteration, and Studio Mode for full network and multi-validator testing.
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| Mode or environment | Execution context | Best suited to | Important limitation |
|---|---|---|---|
| Direct Mode | In-memory contract execution with test fixtures | Fast tests of contract logic and state | Does not establish RPC, network, or real multi-validator behavior |
| GLSim | Lightweight JSON-RPC simulator running the Python runner natively | Low-friction development iteration | The setup guide warns of possible incompatibilities with the full GenVM runtime |
| Studio Mode | Deployment and interaction over RPC with a running Studio environment | Integration, network, and validator behavior | Requires an available Studio environment and takes more setup than in-memory tests |
| Bradbury testnet | Realistic testnet environment | Preproduction checks | The setup guide says it does not expose the same full validator logs as local Studio |
The official documentation describes Direct Mode as millisecond-scale and requiring no Docker; this is a qualitative description, not a performance benchmark. See the testing-suite reference and development setup guide for current details.
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How to test a GenLayer Intelligent Contract
1. Start with deterministic behavior in Direct Mode
Use the direct deployment, sender, account, and VM-context fixtures to test code paths whose expected results are stable. Cover the contract’s core state transitions before adding external or validator-dependent behavior.
- Constructor behavior and initial storage values.
- View methods and expected return values.
- Writes and state changes, including boundary inputs.
- Sender permissions and access-control checks.
- Expected reverts for invalid or unauthorized actions.
These checks can run without starting a network, making them appropriate for frequent local runs and CI. They establish that the tested contract logic behaves as expected in Direct Mode; they do not prove end-to-end network behavior. The suite reference documents the fixtures and modes.
2. Control web and LLM outcomes with mocks
If a contract uses web or LLM calls, mock their responses so the test supplies known outcomes rather than relying on live services. For each dependency, test ordinary results as well as empty, unexpected, and error responses. Clear mocks between scenarios and use strict mock checking where appropriate, so stale or unmatched patterns do not remain unnoticed.
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One free scan finds every outdated or missing driver and matches the right update for your exact hardware.Free scan · exact hardware matchMocked tests make these input paths repeatable; they do not demonstrate that a live service will respond identically. The testing guide includes mock-testing guidance and examples.
3. Test the Equivalence Principle, including disagreement
GenLayer validators can produce different raw outputs. A contract’s Equivalence Principle specifies how validators judge whether a proposed result is acceptable despite those differences. Test representative inputs expected to yield equivalent results, then deliberately include ambiguous cases where validator outputs differ. Check both the acceptance and disagreement paths instead of treating one model output as proof that validators will reach consensus.
The distinction matters: ordinary unit tests can check your code’s handling of results, but consensus behavior must be evaluated in an environment that exercises validators. GenLayer explains the protocol context in What is GenLayer? and How GenLayer works; the testing guide covers testing strategy.
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4. Check storage serialization
Enable the documented pickling checks to catch storage serialization problems early. If you store custom classes, follow the documented storage support and dataclass requirements rather than assuming any Python object can be persisted unchanged. Refer to the serialization guidance in the testing documentation.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errors5. Finish with a smaller Studio integration suite
After the fast checks pass, deploy and exercise a focused set of important paths in Studio. Include deployment, RPC transactions, relevant network behavior, and end-to-end validator checks. Confirm the selected Studio environment and its configuration before running tests; Studio provides tools for deployment and inspection, but hosted and local environments are distinct. See GenLayer Studio.
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Choosing between Direct Mode, GLSim, Studio, and testnet
Choose the environment based on the behavior the test must establish, not simply on convenience.
- Use Direct Mode for deterministic logic, storage, access control, and mocked dependency outcomes. It offers fast feedback without Docker or a network.
- Use GLSim when you want a lightweight JSON-RPC development loop. Treat it as an iteration aid: because it runs the Python runner natively rather than in GenVM, validate runtime-sensitive behavior in Studio.
- Use local Studio when you need the full runtime and validator logs for debugging integration or consensus behavior. The setup guide lists Docker 26 or later for local Studio.
- Use hosted Studionet or another hosted Studio network only after confirming which network is selected. The Studio guide distinguishes hosted Studionet, a development preview, and Local Studio; preview and stable networks are separate.
- Use Bradbury testnet for realistic final preproduction checks. It is less convenient for active debugging because the setup guide says it lacks the same full validator logs available in local Studio.
The setup guide lists Python 3.12 or later for contract work and testing. Docker is not required for Direct Mode. Network names, supported versions, and setup details can change, so check the current setup guide and Studio guide when configuring a project.
A practical test-suite shape
Keep the fast, repeatable checks broad and the environment-dependent checks focused. A useful progression is:
- Run Direct Mode tests for constructors, reads, writes, permissions, boundaries, and reverts.
- Run mocked web and LLM scenarios for normal, empty, unexpected, and error results.
- Check storage serialization, including custom stored classes.
- Exercise the Equivalence Principle with both expected agreement and deliberately ambiguous outcomes.
- Run a smaller Studio suite for deployment, RPC transactions, and the validator behavior that in-memory tests cannot establish.
- If using GLSim during development, confirm important runtime-sensitive paths in Studio before relying on them.
This division keeps frequent logic checks quick without mistaking them for a complete test of GenLayer’s network or consensus behavior. The framework’s modes and examples are documented in the GenLayer Testing Suite.
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