Validating Medical Device Specs in Python: A Stone Basket Example

SPG Medisafe — Tue, 13 Oct 2026 12:15:19 +0000

If you maintain a product catalogue or ERP feed for medical devices, bad specification data is a quiet source of errors. A basket listed with the wrong length or a missing diameter can end up in a tender or an order. Here is a small, practical approach to validating device specs before they are published.

The problem

A ureteroscopic stone retrieval basket has a handful of attributes that buyers filter on: shaft diameter (Fr), working length (cm), cage style, wire count and sterility. Suppliers send these in spreadsheets with inconsistent units and spellings, such as 1.9F, 1.9 Fr or 1.9 french.

Model the data

from dataclasses import dataclass
from typing import Literal

Cage = Literal["helical", "flat-wire", "tipless", "fixed-tip"]

@dataclass
class BasketSpec:
    sku: str
    shaft_fr: float
    length_cm: int
    cage: Cage
    wires: int
    sterile: bool

Normalise before you validate

import re

def parse_fr(value: str) -> float:
    m = re.search(r"(\d+(?:\.\d+)?)", value)
    if not m:
        raise ValueError(f"No diameter in {value!r}")
    return float(m.group(1))

Add sanity checks

def validate(spec: BasketSpec) -> list[str]:
    errors = []
    if not 1.0 <= spec.shaft_fr <= 4.0:
        errors.append("shaft_fr outside expected range")
    if not 50 <= spec.length_cm <= 150:
        errors.append("length_cm outside expected range")
    if spec.wires < 2:
        errors.append("wires must be 2 or more")
    if not spec.sterile:
        errors.append("sterile flag missing")
    return errors

The ranges are placeholders. Take the real limits from each manufacturer's specification sheet rather than hard-coding assumptions.

Fail loudly in your pipeline

Run the validator in CI or in your import job, and reject the batch if any row returns errors. A report listing the SKU and the failing field is much easier for a catalogue team to fix than a silent bad record.

Why it matters

Buyers compare devices on exactly these fields, so clean data means fewer wrong orders and faster quotes. If you want the buyer's side of the story, including cage designs and quality checks, see the full guide: stone retrieval basket guide for buyers.

Note: this is general software advice and not clinical guidance.

Modelling Medical Device Sizes: Encoding Ureteral Access Sheaths in a Product Catalogue

SPG Medisafe — Fri, 09 Oct 2026 07:30:20 +0000

If you build catalogue, ERP or e-commerce systems for medical device companies, you will meet products whose "size" is not one number. Ureteral access sheaths are a good example.

Two diameters and a length

A sheath is labelled like 12/14 Fr, 45 cm:

12 Fr: inner diameter (the working channel for a scope)
14 Fr: outer diameter (what sits in the patient)
45 cm: working length

French units convert simply: mm = Fr / 3. So 12/14 Fr is roughly 4.0 / 4.7 mm.

A simple data model

Storing the size as a single string makes filtering painful. Split it into fields instead:

{
  "product_type": "ureteral_access_sheath",
  "inner_fr": 12,
  "outer_fr": 14,
  "length_cm": 45,
  "coating": "hydrophilic",
  "sterile": true,
  "single_use": true
}

Now the UI can offer filters such as "inner diameter at least 11 Fr" or "length 35 to 46 cm", and you can validate that outer_fr > inner_fr on import.

Compatibility rules

Real buyers search by the instrument they own. A useful rule is: show sheaths where inner_fr is greater than the scope's outer diameter, so there is space for fluid to drain. Store scope diameters in a separate table and join on that rule rather than hard-coding pairs.

Labels and SKUs

Generate the SKU and the pack label from the fields, not by hand, for example UAS-12-14-45. This keeps printed labels, barcodes and the website in sync and avoids the classic error of a 35 cm product shipped in a 45 cm box.

Import validation

Supplier price lists rarely follow one format. Some write 12/14Fr, others 12-14 F or Fr 12/14. A small parser with a regex such as (\d+(?:\.\d)?)\s*[/-]\s*(\d+(?:\.\d)?) handles most variants. Reject rows where the outer value is not larger than the inner one, and flag lengths outside a sensible range, for example 15 to 70 cm, for manual review instead of importing them silently.

Search and SEO

Buyers search with phrases like "12/14 access sheath 45 cm". Generate product titles from the fields in one consistent pattern, and include both the Fr value and the millimetre conversion in the description. Structured data with additionalProperty for each dimension also helps search engines understand the product.

DEV Community: SPG Medisafe