Polars · PII Masking
Polars PII Masking in One Line of Python
Detect and redact names, emails, phone numbers, SSNs, MRNs, and free-text PHI across every column of a Polars DataFrame — locally, with a Rust kernel, in a single call.
The one-line API
import polars as pl
import omna
df = pl.read_parquet("patient_notes.parquet")
# Detect + redact PII across every text column.
masked = df.omna.mask_pii()
# Or target specific entity types
masked = df.omna.mask_pii(entities=["EMAIL", "SSN", "MRN", "PHONE", "NAME"])Why local matters
Most PII redaction tools (AWS Comprehend, Google DLP, Azure PII) require shipping the raw records to a cloud API. For healthcare, finance, and government workloads, that means a BAA, a vendor review, and a new line item in your data flow diagram. Omna runs in your Python process. Zero network calls. No BAA required, because nothing leaves the host.
Supported entity types
- · NAME
- · PHONE
- · SSN
- · MRN
- · DOB
- · ADDRESS
- · CREDIT_CARD
- · IP
Try it now
pip install omna
The live playground runs a real mask_pii() call on a sample healthcare dataset, in your browser.