Financial reconciliation breaks

Status

illustrative

Industry

Banking

Language

Python

Framework

pytest

CI

any

Fulfilment

BUILD_DATASET

Profile

banking-regression

About this example

All data is synthetic. DataNivra provisions approved test data into a customer-controlled target; it does not run these tests. Credentials for the target are never returned by DataNivra — your runner holds its own.

Why test data matters

Reconciliation jobs must flag breaks and still produce deterministic totals.

What is requested

500 everyday and 100 reconciliation-break records.

Policy gates

Within the profile.

What is provisioned

A certified synthetic dataset.

Expected output

AUTO_APPROVED.

Cleanup

Fixture releases.

Files

• request.yaml
• example.py
• test_with_datanivra.py

Run

1. A tenant administrator defines and a second person approves the profile (datanivra test-data define ../../profiles/banking-regression.yaml --submit, then datanivra policies approve).
2. datanivra test-data validate request.yaml && datanivra test-data plan request.yaml
3. Run the example with DATANIVRA_BASE_URL and a session or workload token.

# yaml-language-server: $schema=../../../../packages/contracts/schemas/v1/manifests/test-data-request.schema.json
# DataNivra test-data-request manifest (apiVersion datanivra.io/v1alpha1). Validate: datanivra test-data validate <file>
apiVersion: datanivra.io/v1alpha1
kind: TestDataRequest
metadata:
  name: reconciliation
spec:
  profile: { name: banking-regression, version: 1 }
  scenarios:
    - { scenario_code: FS_EVERYDAY_BANKING, count: 500 }
    - { scenario_code: FS_RECONCILIATION_BREAKS, count: 100 }

"""Financial reconciliation breaks — provision approved test data through the Python SDK.

``provision`` only asks DataNivra for data from the approved ``banking-regression`` profile; your own test
suite runs against the approved target with its own, separately managed database access.
"""

from __future__ import annotations

from pathlib import Path

from datanivra_contracts.testdata import TestDataRequest
from datanivra_sdk import DataNivraClient
from datanivra_sdk.testdata import TestDataClient

REQUEST = Path(__file__).with_name("request.yaml")


def provision(api: DataNivraClient, *, idempotency_key: str | None = None) -> TestDataRequest:
    """Create (or, for the same key, return) the request; DENIED raises ``DataNivraApiError``."""
    return TestDataClient(api).request(REQUEST, idempotency_key=idempotency_key)

"""Financial reconciliation breaks (pytest).

Run in your CI with ``DATANIVRA_BASE_URL`` and a token (``datanivra login --workload-identity ...``
or ``DATANIVRA_TOKEN``). The data is released after the session, even when tests fail.
"""

from __future__ import annotations

import os
from collections.abc import Iterator

import pytest
from datanivra_contracts.testdata import TestDataRequest
from datanivra_sdk import DataNivraClient
from datanivra_sdk.testdata import TestDataClient
from example import REQUEST


@pytest.fixture(scope="session")
def test_data() -> Iterator[TestDataRequest]:
    api = DataNivraClient(os.environ["DATANIVRA_BASE_URL"], token=os.environ["DATANIVRA_TOKEN"])
    with TestDataClient(api).acquire(REQUEST, idempotency_key=os.environ.get("CI_RUN_KEY")) as request:
        yield request


def test_every_break_is_reported(test_data: TestDataRequest) -> None:
    # Your assertions run against your application and the approved target environment
    # ``test_data.environment_id``; DataNivra only returns metadata (ids, states, digests).
    assert test_data.state.value == "READY"

# yaml-language-server: $schema=../../../packages/contracts/schemas/v1/manifests/test-data-profile.schema.json
# DataNivra test-data-profile manifest (apiVersion datanivra.io/v1alpha1). Validate: datanivra test-data validate <file>
# Placeholder ids (00000000-0000-4000-8000-0000000000NN): replace with your ids.
# 01 = approved target environment, 11 = certified dataset, 21 = customer agent,
# 99 = workload identity trust (datanivra workload-identities list).
apiVersion: datanivra.io/v1alpha1
kind: TestDataProfile
metadata:
  name: banking-regression
  description: Synthetic accounts, payments and their failure modes
spec:
  fulfilment: BUILD_DATASET
  build:
    business_domain: accounts and payments
    pack_id: financial-services
    dataset_kind: SYNTHETIC_ONLY
    target_environment_id: 00000000-0000-4000-8000-000000000001
    retention_days: 1
    max_total_records: 3000
    scenarios:
      - {
          pack_id: financial-services,
          scenario_code: FS_EVERYDAY_BANKING,
          kind: NORMAL,
          default_count: 1000,
          max_count: 2000,
        }
      - {
          pack_id: financial-services,
          scenario_code: FS_FAILED_PAYMENTS,
          kind: RARE,
          default_count: 100,
          max_count: 500,
        }
      - {
          pack_id: financial-services,
          scenario_code: FS_DUPLICATE_TRANSACTIONS,
          kind: DUPLICATE,
          default_count: 50,
          max_count: 200,
          included_by_default: false,
        }
      - {
          pack_id: financial-services,
          scenario_code: FS_CHARGEBACKS,
          kind: RARE,
          default_count: 50,
          max_count: 200,
          included_by_default: false,
        }
      - {
          pack_id: financial-services,
          scenario_code: FS_RECONCILIATION_BREAKS,
          kind: RARE,
          default_count: 50,
          max_count: 200,
          included_by_default: false,
        }
      - {
          pack_id: financial-services,
          scenario_code: FS_BALANCE_BOUNDARIES,
          kind: BOUNDARY,
          default_count: 50,
          max_count: 200,
          included_by_default: false,
        }
  automation:
    workload_identity_ids: [00000000-0000-4000-8000-000000000099]
    max_total_records: 1500
    escalate_out_of_envelope: false