Documentation Index
Fetch the complete documentation index at: https://docs.verisynth.ai/llms.txt
Use this file to discover all available pages before exploring further.
CLI Testing & Verification
The VeriSynth CLI was designed for trust — every run can be verified, reproduced, and audited without ever exposing sensitive data.
This guide explains how to:
- Test VeriSynth locally
- Verify your proof receipts
- Reproduce a run deterministically
- Debug unexpected differences
1. Verify Installation
After installation, confirm that the CLI is available:
Expected output:
Run the built-in help command:
If both commands succeed, your environment is ready.
2. Generate a Test Dataset
Use the included demo dataset for a quick local test:
verisynth data/sample_patients.csv -o out/ --rows 1000 --seed 42
📁 out/synthetic.csv
🧾 out/proof.json
VeriSynth — Synthetic Data Report
========================================
Input: data/sample_patients.csv
Output: out/synthetic.csv
Engine: GaussianCopula | Seed: 42
Fidelity: corr Δ=0.23 | Privacy risk=0.0
Proof: out/proof.json (Merkle verified)
3. Validate the Proof Receipt
Each run produces a JSON proof receipt (proof.json):
{
"verisynth_version": "core-0.1.0",
"input": { "rows": 10, "sha256": "…82b7" },
"output": { "rows": 1000000, "sha256": "…acb9" },
"metrics": { "corr_mean_abs_delta": 0.12, "naive_reid_risk": 0.01 },
"proof": "merkle_root: …c31"
}
- Compute your own SHA-256 hash of the input and output files.
- Compare them with the hashes inside
proof.json.
- Verify that the Merkle root matches — if it does, your run is provably unchanged.
(The upcoming verisynth verify command will automate this.)
4. Test Reproducibility
Because VeriSynth uses deterministic seeding, identical runs will produce identical proofs and Merkle roots.
Try it:
verisynth data/sample_patients.csv -o out1/ --rows 1000 --seed 42
verisynth data/sample_patients.csv -o out2/ --rows 1000 --seed 42
diff out1/proof.json out2/proof.json
5. Test Edge Cases
You can test various parameters to ensure consistent behavior:
| Scenario | Command | Expected Result |
|---|
| Small input file | --rows 100 | Completes instantly |
| Large output | --rows 1000000 | Slower, but deterministic |
| Custom output path | --proof out/custom_proof.json | Proof saved to custom path |
| Invalid path | wrong file | Clean error message (exit code 1) |
6. Exit Codes
The CLI provides predictable exit codes for scripting and CI/CD.
| Code | Meaning |
|---|
0 | Success |
1 | Invalid input or missing file |
2 | Model synthesis error |
3 | Proof verification failed |
4 | I/O or permission issue |
7. Continuous Integration (CI/CD)
You can run VeriSynth tests automatically as part of your pipeline.
Example GitHub Action:
name: Test
on: [push, pull_request]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.11'
- run: pip install -r requirements.txt
- run: pip install pytest pytest-cov
- run: pytest --cov=verisynth
8. Debugging Tips
| Issue | Cause | Fix |
|---|
CLI not found | PATH not updated | Reinstall with pip install -e . |
Permission denied | Output folder restricted | Use --output in a writable directory |
Metrics missing | Proof disabled | Remove --no-proof flag |
| Non-deterministic output | Different seeds or model versions | Use --seed consistently |
Summary
CLI testing in VeriSynth confirms three pillars of trust:
- Reproducibility — identical seeds = identical outputs
- Integrity — proof receipts and Merkle roots verify correctness
- Privacy — synthetic data is generated without copying real data
