NexMind AI — DataClean Swarm SDK
Clean your ML training data with AI-powered agents.
Install
pip install nexmind
Quick Start
from nexmind import NexMindClient
import pandas as pd
# Initialize
client = NexMindClient(api_key="dcs_your_key")
# Clean a DataFrame
df = pd.read_csv("dirty_data.csv")
clean_df, report = client.clean(df)
print(f"Quality: {report['quality_score_before']:.0%} -> {report['quality_score_after']:.0%}")
print(f"Rows removed: {report['rows_removed']}")
print(f"Rows repaired: {report['rows_repaired']}")
Choose Agents
# Run specific agents only
clean_df, report = client.clean(
df,
agents=["schema", "dedup", "repair"], # skip anomaly + labeling
)
Async Jobs
# Submit and don't wait
job = client.submit_job(
name="Nightly data clean",
source={"type": "s3", "bucket": "raw", "key": "data.csv"},
output={"type": "s3", "bucket": "clean", "key": "clean.parquet"},
)
# Check later
job.refresh()
print(job.status) # "running" | "completed" | "failed"
# Or wait
job.wait()
print(job.report)
5 AI Agents
| Agent | What it does |
|---|---|
| schema | Fix column types, names, formats |
| anomaly | Detect outliers (Z-score, IQR, Isolation Forest) |
| dedup | Remove exact + fuzzy duplicates |
| repair | Fill missing values, fix typos, standardize |
| labeling | Detect PII, classify columns |
Get Your API Key
- Sign up at app.getnexmind.com
- Go to API Keys page
- Create a key
Links
1 maintainer
Metadata
1 maintainer
Release files for nexmind 0.1.0
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| nexmind-0.1.0.tar.gz | 5.0 kB | Without provenance | Details |
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| nexmind-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.2 kB
Release files / nexmind-0.1.0.tar.gz
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| Size | 5.0 kB |
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| Download URL | nexmind-0.1.0-py3-none-any.whl |
|---|---|
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| Tags | Python 3 |
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