scitex-repro
Reproducibility utilities — RNG seeding, ID generation, timestamps, array hashing.
Full Documentation · uv pip install scitex-repro[all]
Problem and Solution
| # | Problem | Solution |
|---|---|---|
| 1 | "Seed everything" requires 5+ lines of boilerplate — random.seed() + np.random.seed() + torch.manual_seed() + torch.cuda.manual_seed_all() + tf.random.set_seed() + os.environ[PYTHONHASHSEED] |
RandomStateManager(seed=42) — one call seeds every framework detected in the env; .reset() rewinds mid-experiment |
| 2 | Experiment run directories collide — two parallel runs overwrite each other | gen_ID() + hash_array() — unique directory names like 20260423_2155_abc12345; deterministic array fingerprints for integrity checks |
Installation
pip install scitex-repro
Architecture
src/scitex_repro/
├── __init__.py # public re-exports
├── _RandomStateManager.py # cross-framework RNG seeding (random / numpy / torch / tf)
├── _gen_ID.py # 20260423_2155_<hash> directory IDs
├── _gen_timestamp.py # filesystem-safe timestamps
├── _hash_array.py # deterministic NumPy / pandas fingerprints
└── _config.py # env-var + config defaults
1 Interfaces
Python API
from scitex_repro import RandomStateManager, gen_ID, hash_array
# Cross-framework RNG seeding
rng = RandomStateManager(seed=42)
data = rng("data").random(100)
rng.verify(data, "my_data")
rng.reset()
# Deterministic IDs and array fingerprints
exp_id = gen_ID() # "20260423_2155_abc12345"
fingerprint = hash_array(data)
Demo
flowchart LR
seed["seed=42"] --> rsm["RandomStateManager"]
rsm --> py["random"]
rsm --> np["numpy"]
rsm --> torch["torch (cpu+cuda)"]
rsm --> tf["tensorflow"]
rsm --> hashenv["PYTHONHASHSEED"]
rsm --> data["rng('data').random(100)"]
data --> fp["hash_array(data)"]
rsm --> id["gen_ID()"]
id --> dir[("20260423_2155_abc12345/")]
fp --> integrity[("array fingerprint")]
Quick Start
from scitex_repro import RandomStateManager, gen_ID, hash_array
rng = RandomStateManager(seed=42)
data = rng("data").random(100)
print(gen_ID(), hash_array(data))
Part of SciTeX
scitex-repro is part of SciTeX. Install via
the umbrella with pip install scitex[repro] to use as
scitex.repro (Python) or scitex repro ... (CLI).
Four Freedoms for Research
- The freedom to run your research anywhere — your machine, your terms.
- The freedom to study how every step works — from raw data to final manuscript.
- The freedom to redistribute your workflows, not just your papers.
- The freedom to modify any module and share improvements with the community.
AGPL-3.0 — because we believe research infrastructure deserves the same freedoms as the software it runs on.
License
AGPL-3.0-only (see LICENSE).
Metadata
Release files for scitex-repro 0.1.7
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| scitex_repro-0.1.7.tar.gz | 8.6 MB | With provenance | Details |
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| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| scitex_repro-0.1.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.9 MB
Release files / scitex_repro-0.1.7.tar.gz
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| Tags | Python 3 |
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