PathBridge 0.4.0

Translate validator error locations back to your application's schema paths and emit structured errors

PathBridge

Bridge validator locations (XPath/JSONPath/JSON Pointer) back to your application model paths, and emit structured errors (Marshmallow-ready).

Why

Validators (XSD/Schematron, JSON Schema) report failures at document locations (XPath/JSONPath).
Your users need errors on your model (Pydantic/Marshmallow/dataclasses). PathBridge converts between the two.

• Prefix & case tolerant (e.g., hd:, MTR:).
• Fixes 1-based indices to Python 0-based.
• Works with plain mappings or an optional tracer (add-on) that learns rules from your converter.

Install

pip install pathbridge

Quick start

from pathbridge import compile_rules, translate_location, to_marshmallow

# 1. Provide or load rules: destination path -> facade (your app models) path 
rules = {
    "Return[1]/Contact[1]/Phone[1]": "person/phones[0]",
    "Return[1]/Contact[1]/Phone[2]": "person/phones[1]",
}

compiled = compile_rules(rules)

# 2. Translate validator location (e.g. from Schematron SVRL)
loc = "/Return[1]/Contact[1]/Phone[2]"
print(translate_location(loc, compiled))
# "person/phones[1]"

# 3. Transform error location into a Marshmallow-style error dict
errors = to_marshmallow([(loc, "Invalid phone")], compiled)
# {'person': {'phones': {1: ['Invalid phone']}}}

Extras

pathbridge.extras provides helper utilities for generating rules from your converter:

• make_shape(...): build a populated sample facade object.
• build_rules(...): trace a sample conversion and produce Destination -> Facade mapping rules.

Extras example

import dataclasses
import types

from pathbridge import compile_rules, to_marshmallow
from pathbridge.extras import build_rules, make_shape


@dataclasses.dataclass
class FacadeName:
    first: str
    last: str


@dataclasses.dataclass
class Facade:
    name: FacadeName
    phones: list[str]


@dataclasses.dataclass
class NameXml:
    first_name: str = dataclasses.field(metadata={"name": "FirstName"})
    surname: str = dataclasses.field(metadata={"name": "Surname"})


@dataclasses.dataclass
class ReturnXml:
    name: NameXml = dataclasses.field(metadata={"name": "YourName"})
    phones: list[str] = dataclasses.field(metadata={"name": "Phone"})

    class Meta:
        name = "Return"


def convert(src: Facade) -> ReturnXml:
    return ReturnXml(
        name=NameXml(first_name=src.name.first, surname=src.name.last),
        phones=src.phones,
    )


shape = make_shape(Facade, list_len=2)
rules = build_rules(
    destination_module=types.SimpleNamespace(ReturnXml=ReturnXml, NameXml=NameXml),
    facade_to_destination=convert,
    facade_shape=shape,
    facade_root_tag="facade",
)

compiled = compile_rules(rules)
errors = to_marshmallow(
    [
        ("/Return[1]/NameXml[1]/FirstName[1]", "Required field"),
        ("/Return[1]/Phone[2]/Phone[1]", "Invalid phone"),
    ],
    compiled,
)

print(rules)
# {
#   'Return[1]/NameXml[1]/FirstName[1]': 'facade/name/first',
#   'Return[1]/Phone[2]/Phone[1]': 'facade/phones[1]',
#   ...
# }
print(errors)
# {
#   'facade': {
#     'name': {'first': ['Required field']},
#     'phones': {1: ['Invalid phone']},
#   }
# }

Custom shape defaults

make_shape(...) accepts type_defaults so you can override generated defaults for specific types:

from decimal import Decimal

shape = make_shape(
    Facade,
    list_len=2,
    type_defaults={
        str: "sample",
        int: 42,
        Decimal: Decimal("1.23"),
    },
)

CLI

PathBridge provides a pathbridge CLI with a compile command that runs:

1. make_shape(...)
2. build_rules(...)
3. compile_rules(...) (when --emit includes compiled output)
4. Python module generation

CLI example

Run from the repository root:

pathbridge compile \
  --output-dir . \
  --output-package mtr.translation_rules \
  --output-module compiled \
  --facade-class ./tests/integration/uk_main_tax_return/facade/mtr_facade.py:MTR \
  --destination-module ./tests/integration/uk_main_tax_return/destination/mtr_v1_1.py \
  --facade-to-destination ./tests/integration/uk_main_tax_return/converter/mtr_converter.py:to_mtr_v1_1 \
  --shape-list-len 10 \
  --facade-root-tag mtr \
  --lift-functions _yes \
  --lift-functions _yes_no \
  --lift-functions _tax_payer_status \
  --lift-functions _student_loan_plan \
  --lift-functions _postgraduate_loan_plan \
  --lift-functions _attachment_file_format \
  --lift-functions decimal_str_or_none \
  --lift-functions xml_date_or_none \
  --lift-functions decode_attachment

Real-world reference

For a real-life example of PathBridge usage, see:

• tests/integration/uk_main_tax_return

This integration setup includes:

• facade models (facade/mtr_facade.py)
• destination models generated from XSD (destination/mtr_v1_1.py)
• facade-to-destination converter (converter/mtr_converter.py)
• tracer-based rules generation and translation assertions (test_mtr.py)