Behave Logic Report

TL;DR - Executable Test Suite, Documentation

You can optionally use the Behave test framework to capture requirements and execute a test suite (here is an Agile Approach for using Behave). Say this to your AI assistant, in order:

create logic diagram for each requirement - optional; needs Graphviz (brew install graphviz)
create tests from rules - writes the Behave .feature files and steps
run the tests - starts the server if needed, runs the Behave suite, reports pass/fail
run the behave report

This creates the Behave Logic Report shown below, as test/api_logic_server_behave/reports/Behave Logic Report.md. You can run step 4 before any tests exist: the requirements, rules, data model, security and messages sections are read from the project's files.

This report is generated from the project's own files, in the order an auditor reads them: requirements traced to the code that implements them, every rule, the data model, security (RBAC), messages and APIs - and then test evidence, with the logic each test exercised.

For complete documentation on using Behave: See Behave

Everything above Tests and Results is read from the project's files, so it is complete even before any tests are written.

Behave Logic Report

Project: basic_demo_eai | Generated: October 19, 2026 21:49 | Rules: 8 | Test scenarios: 14 | Generator: Behave Logic Report 2.0

About this project (from readme.md)

This app illustrates using IntegrationServices for B2B push-style integrations with APIs, and internal integration with messages.

basic_demo_eai is a single API Logic Server providing APIs and logic — it both subscribes and publishes, so there's no second project to stand up:

Order Logic: enforcing database integrity (Check Credit) and application integration (notify shipping)
A Custom API (OrderB2B), matching an agreed-upon format for B2B partners
Kafka Subscribe: listens on topic order_b2b for inbound orders from a message broker
Kafka Publish: publishes to topic order_shipping when an order ships — consumed by whatever downstream shipping system you plug in (not part of this demo)
Standard APIs for ad-hoc integration, user interfaces, etc

Requirements Traceability To Rules

Traceability here is forward (requirement, to the rules, handlers and grants that implement it, to the tests that exercise it) and backward (implementation and tests, to the requirement they serve). Anything with no requirement is listed as untraced, and every requirement with no implementation or no test is listed as a gap. Links are made by the Feature: names and §N tags that requirements, code and tests carry.

Coverage summary

Measure	Result
Requirements	5
Implemented (at least one file)	5 of 5
Tested (at least one scenario)	4 of 5 - gap: §5 Security
Implementation not traced to a requirement	`integration/OrderB2bMapper.py`, `logic/logic_discovery/system/all_classes_stamping.py`
Tests not traced to a requirement	none
Test results (last run)	✅ 14 passed, 0 failed
Scenarios with a logic log	14 of 14
Rules seen in at least one scenario's log	7 of 7 (1 rule(s) cannot be matched to the engine's log)

Test results are read from logs/behave.log, so they are only as current as that run. Not recorded here: which version of a requirement the code was built against, and which clause of a requirement a given rule serves.

Traceability matrix

Requirement	Implemented by	Rules	Tests
§1 Business Logic — Check Credit	`logic/logic_discovery/check_credit.py`	5	✅ 9 scenario(s): 9 passed
§2 B2B API — Accept orders from external partners	`api/api_discovery/order_b2b_api.py`	0	✅ 3 scenario(s): 3 passed
§3 Kafka Subscribe — Inbound orders from sales channel	`logic/logic_discovery/order_b2b_consume.py` `integration/kafka/kafka_subscribe_discovery/order_b2b.py` `api/api_discovery/order_b2b_consume_debug.py`	1	✅ 1 scenario(s): 1 passed
§4 Kafka Publish — Notify shipping on dispatch	`logic/logic_discovery/app_integration.py` `integration/kafka/kafka_publish_discovery/order_shipping.py`	1	✅ 1 scenario(s): 1 passed
§5 Security	`security/declare_security.py`	0	⚠ none defined

Rule coverage by tests

Rule	Requirement	Seen in
`Order.after_flush_row_event → _send_order_to_kafka()`	§4 Kafka Publish — Notify shipping on dispatch	12: Partner Order Is Accepted And Rules Derive The Totals; Create Order Rolls Up To Customer Balance; Update Item Quantity Recalculates Amounts; +9 more
`Item.unit_price = copy of Product.unit_price`	§1 Business Logic — Check Credit	13: Partner Order Is Accepted And Rules Derive The Totals; Partner Order Exceeding Credit Limit Is Rejected; Create Order Rolls Up To Customer Balance; +10 more
`Item.amount = quantity * unit_price`	§1 Business Logic — Check Credit	13: Partner Order Is Accepted And Rules Derive The Totals; Partner Order Exceeding Credit Limit Is Rejected; Create Order Rolls Up To Customer Balance; +10 more
`Order.amount_total = sum(Item.amount)`	§1 Business Logic — Check Credit	13: Partner Order Is Accepted And Rules Derive The Totals; Partner Order Exceeding Credit Limit Is Rejected; Create Order Rolls Up To Customer Balance; +10 more
`Customer.balance = sum(Order.amount_total) where date_shipped is None`	§1 Business Logic — Check Credit	13: Partner Order Is Accepted And Rules Derive The Totals; Partner Order Exceeding Credit Limit Is Rejected; Create Order Rolls Up To Customer Balance; +10 more
`Customer: balance is None or credit_limit is None or balance <= credit_limit`	§1 Business Logic — Check Credit	2: Partner Order Exceeding Credit Limit Is Rejected; Order Exceeding Credit Limit Is Rejected
`OrderB2bMessage.after_flush_row_event → _publish_order_b2b()`	§3 Kafka Subscribe — Inbound orders from sales channel	1: Inbound Order Message Creates The Order And Items
`all classes.early_row_event → handle_all()`	(none)	n/a - cannot be matched to the engine's log

"Seen" means the engine reported running the rule in that scenario's logic log. A scenario can only contribute if it has a log (see the coverage summary): a test that does not open one writes into whichever log was open last, and its rules are then credited to that scenario, or to the shared log. An event's function runs on every commit of its class, and its own condition decides whether it acts, so seen does not mean it took effect. A constraint appears in the log only when it rejects a transaction, so it is seen only in scenarios that make it reject. "Not seen" therefore means no log shows it, not that no test ran it.

Requirements in detail

8 rules in 4 files: 5 declarative (sum, count, copy, formula and constraint expressions), 0 backed by a Python function, 3 events (Python). Declarative rules are read directly from their declarations; functions and events are Python, so the report shows each one's docstring, not an analysis of its code.

Each requirement is followed by the rules and handlers in the files that implement it. Logic diagrams are shown (click to expand) where they exist.

How to create the missing logic diagrams

Needs Graphviz (brew install graphviz). Tell your AI assistant:

create logic diagram for each requirement

or run this from the Manager root (genai-logic):

python system/ApiLogicServer-Internal-Dev/logic_diagram_gv.py samples/basic_demo_eai --each

Each diagram is saved under docs/requirements/<name>/logic_diagrams/. Then regenerate this report (python behave_logic_report.py run, from test/api_logic_server_behave).

§1 Business Logic — Check Credit

Tests: ✅ 9 scenario(s): 9 passed

Feature: Check Credit

  Scenario: Place an order
    Given a customer with a credit limit
    When an order is placed
    Then copy the price from the product
    And multiply by quantity to get the item amount
    And sum item amounts to get the order total
    And sum unpaid order totals to get the customer balance
    And reject if balance exceeds the credit limit

Rule / item	Type	Logic	Description	Where
`Item.unit_price = copy of Product.unit_price`	copy	declarative		`check_credit.py`
`Item.amount = quantity * unit_price`	formula	declarative		`check_credit.py`
`Order.amount_total = sum(Item.amount)`	sum	declarative		`check_credit.py`
`Customer.balance = sum(Order.amount_total) where date_shipped is None`	sum	declarative		`check_credit.py`
`Customer: balance is None or credit_limit is None or balance <= credit_limit`	constraint	declarative	Error: balance ({row.balance}) exceeds credit limit ({row.credit_limit})	`check_credit.py`

Logic diagram: check_credit

logic diagram: check_credit

§2 B2B API — Accept orders from external partners

Tests: ✅ 3 scenario(s): 3 passed

Feature: B2B Order Integration

  Scenario: Accept order from external partner
    Given an inbound B2B order in partner format (message_formats/order_b2b.json)
    When the order is received via a Custom API endpoint named OrderB2B
    Then map Account to Customer by name
    And map Items.Name to Product by name
    And map Items.QuantityOrdered to Item.quantity

Rule / item	Type	Logic	Description	Where
`HTTP in: POST /api/OrderB2B`	http	handler (Python)	API service OrderB2B: accepts an inbound B2B order from an external partner.	`order_b2b_api.py`

Tests: ✅ 1 scenario(s): 1 passed

Feature: Kafka Subscribe Order Integration

  Scenario: Accept inbound orders from sales channel
    Given an inbound order message in JSON format (message_formats/order_b2b.json)
    When the message is received from Kafka topic order_b2b
    Then map Account to Customer by name
    And map Items.Name to Product by name
    And map Items.QuantityOrdered to Item.quantity

Rule / item	Type	Logic	Description	Where
`OrderB2bMessage.after_flush_row_event → _publish_order_b2b()`	after_flush_row_event	event (Python)	OrderB2bMessage event: publishes the raw blob to order_b2b_processed after Tx 1 commits, so Consumer 2 can parse it in a clean Tx 2 (2-message pattern).	`order_b2b_consume.py`
`Kafka in: order_b2b`	kafka	handler (Python)	Kafka subscribe order_b2b (Consumer 1): saves the raw message as an OrderB2bMessage blob and commits; the row event then publishes it to order_b2b_processed.	`order_b2b.py`
`Kafka in: order_b2b_processed`	kafka	handler (Python)	Kafka subscribe order_b2b_processed (Consumer 2): parses the blob and persists Order and Item rows, marking the blob processed, in one atomic transaction (Tx 2).	`order_b2b.py`
`HTTP in: GET /consume_debug/order_b2b`	http	handler (Python)	API service consume_debug: runs the order_b2b consume pipeline without Kafka.	`order_b2b_consume_debug.py`

§4 Kafka Publish — Notify shipping on dispatch

Tests: ✅ 1 scenario(s): 1 passed

Feature: Kafka Publish Shipping Notification

  Scenario: Notify shipping when an order is dispatched
    Given an Order exists
    When date_shipped is set
    Then publish to Kafka topic order_shipping
    And use message_formats/order_shipping.json as the message shape
    And use by-example publish rather than key-only publish

Rule / item	Type	Logic	Description	Where
`Order.after_flush_row_event → _send_order_to_kafka()`	after_flush_row_event	event (Python)	Order publish: sends the Order to Kafka topic order_shipping when date_shipped is first set (or changes), by example, using the message shape in kafka_publish_discovery/order_shipping.py.	`app_integration.py`
`order_shipping.py`	module		By-example publish mapper for Kafka topic order_shipping (Req §4).	`order_shipping.py`

Logic diagram: app_integration

logic diagram: app_integration

§5 Security

Tests: none defined

Feature: Row-Level Security
  Scenario: Sales role sees limited customers
    Given a user with the sales role
    When querying the Customer list
    Then only return customers where credit_limit >= 3000 or balance > 0

Rule / item	Type	Logic	Description	Where
`Grant on Customer to role sales: credit_limit >= 3000 or balance > 0`	grant	declarative		`declare_security.py`

Rules not traced to a requirement

Rule / item	Type	Logic	Description	Where
`all classes.early_row_event → handle_all()`	early_row_event_all_classes	event (Python)	Generic handler - executed for every row update across all classes.	`all_classes_stamping.py`

Data Model

db diagram

Generated from docs/db.dbml (parents above children; shaded rows are derived by rules). To use your own layout, save it as docs/db_diagram.png.

Derived columns

Table	Column	Rule	Definition
Item	unit_price	copy	`Item.unit_price = copy of Product.unit_price`
Item	amount	formula	`Item.amount = quantity * unit_price`
Order	amount_total	sum	`Order.amount_total = sum(Item.amount)`
Customer	balance	sum	`Customer.balance = sum(Order.amount_total) where date_shipped is None`

Security (RBAC)

Security enabled: no (SECURITY_ENABLED in config/default.env). The declarations below are not enforced until genai-logic add-auth is run.

Roles and CRUD (DefaultRolePermission)

Role	Read	Insert	Update	Delete
sa	✅	✅	✅	✅
tenant	✅	—	—	✅
CS_ADMIN	✅	✅	✅	✅
manager	✅	✅	✅	—
teller	✅	✅	✅	—
customer	✅	✅	✅	—
readonly	✅	—	—	—
public	✅	—	—	—
sales	✅	—	—	—
default-roles-kcals	✅	✅	✅	—
uma_authorization	✅	✅	✅	—

Row-level grants (Grant)

Table	Role	Filter	Requirement
Customer	sales	`credit_limit >= 3000 or balance > 0`	§5

Messages and APIs

Direction	Channel	Name	Handler	Tables created	Message shape	Requirement
➡ in	Kafka	`order_b2b`	`order_b2b()` - Kafka subscribe order_b2b (Consumer 1): saves the raw message as an OrderB2bMessage blob and commits; the row event then publishes it to order_b2b_processed.	OrderB2bMessage	`order_b2b.json`	§3 Kafka Subscribe — Inbound orders from sales channel
➡ in	Kafka	`order_b2b_processed`	`order_b2b_processed()` - Kafka subscribe order_b2b_processed (Consumer 2): parses the blob and persists Order and Item rows, marking the blob processed, in one atomic transaction (Tx 2).	Item, Order, OrderB2bMessage		§3 Kafka Subscribe — Inbound orders from sales channel
⬅ out	Kafka	`order_shipping`	Order.after_flush_row_event → _send_order_to_kafka() - Order publish: sends the Order to Kafka topic order_shipping when date_shipped is first set (or changes), by example, using the message shape in kafka_publish_discovery/order_shipping.py.		`order_shipping.json`	§4 Kafka Publish — Notify shipping on dispatch
⬅ out	Kafka	`order_b2b_processed`	OrderB2bMessage.after_flush_row_event → _publish_order_b2b() - OrderB2bMessage event: publishes the raw blob to order_b2b_processed after Tx 1 commits, so Consumer 2 can parse it in a clean Tx 2 (2-message pattern).			§3 Kafka Subscribe — Inbound orders from sales channel
➡ in	HTTP	`POST /api/OrderB2B`	`order_b2b_api()` - API service OrderB2B: accepts an inbound B2B order from an external partner.			§2 B2B API — Accept orders from external partners
➡ in	HTTP	`GET /consume_debug/order_b2b`	`consume_debug_order_b2b()` - API service consume_debug: runs the order_b2b consume pipeline without Kafka.			§3 Kafka Subscribe — Inbound orders from sales channel

Topics and endpoints are read from the discovery folders. The condition that triggers an outbound message lives in Python (see the rules under each requirement); here it is described by the handler's docstring. "Tables created" lists rows the handler's code constructs, following its calls within the project; blank means none were found, not that none exist.

Message shape: order_b2b

{
  "Account": "Alice",
  "Notes": "Kafka order from sales",
  "Items": [
    { "Name": "Widget",  "QuantityOrdered": 1 },
    { "Name": "Gadget",  "QuantityOrdered": 2 }
  ]
}

Message shape: order_shipping

{
  "order_id": 1,
  "order_date": "2026-04-06",
  "customer_name": "Alfreds Futterkiste",
  "total": 100.00,
  "items": [
    { "quantity": 2, "product_name": "Chai", "unit_price": 25.00 }
  ]
}

Tests and Results

✅ 14 scenario(s): 14 passed, 0 failed (from the last run, logs/behave.log).

These are Behave scenarios. Each one drives the running API the way any client would (create an order, change a quantity, ship it) and checks the result.

The logic log is what makes them more than pass/fail. Business rules run inside the server on every commit, so the server records exactly what they did, and this report embeds that record for each scenario. Two things to look for:

It shows every rule that runs. Each line is one rule execution, with the row's state, old and new values. You see not just that a test passed, but which rules ran and what each one changed.
The nesting shows multi-table chaining. Indentation follows the cascade: a change to an Item adjusts its Order, which adjusts its Customer.

How to read the logic log

Open a scenario's "Rules exercised and logic log" block to see it. The log is shown in full, attribute values included, because those values are what you diagnose from when a rule produces an unexpected result.

To read a log line:

....Order[16] {Update - Adjusting order: amount_total} id: 16, customer_id: 19, amount_total:  [0.0-->] 90.0

The leading dots are the depth in the cascade: Item (2 dots), its Order (4), its Customer (6).
Order[16] is the row; {...} is the rule or action that ran; the rest is the row's attribute values at that step.
[0.0-->] 90.0 marks a value the rules changed, with its old and new value.
The log is in phases: ROW LOGIC (derivations and constraints, as rows change), COMMIT LOGIC (checks that need the finished aggregates), and AFTER_FLUSH LOGIC (events that need database-assigned keys, such as the Kafka publish).

More: Logic Log.

How to add more tests, and run them

1. Have AI create them. This project's context tells your AI assistant how (.github/copilot-instructions.md, docs/training/testing.md). Just say:

create tests from rules

The assistant reads database/models.py, the logic files and the custom APIs, then writes .feature files and step implementations under test/api_logic_server_behave/features/. Then say run the tests and run the behave report and the assistant does both.

Or, to have each requirement's tests linked in the Tests column above (it matches on Feature: name), say which names to use:

create tests from rules, one Feature per requirement, named exactly:
- Check Credit
- B2B Order Integration
- Kafka Subscribe Order Integration
- Kafka Publish Shipping Notification
- Row-Level Security

Tests with other names still run and appear below; they just aren't linked to a requirement.

2. You can also define tests manually. Add a <name>.feature file (Gherkin) under test/api_logic_server_behave/features/ and its steps under features/steps/. The steps call the running API, so tests exercise the same rules as any client. See docs/training/testing.md for the patterns that keep tests repeatable.

Or run them yourself (server running, from test/api_logic_server_behave):

python behave_run.py --outfile=logs/behave.log
python behave_logic_report.py run

Feature: B2B Order Integration

Scenario: Partner Order Is Accepted And Rules Derive The Totals ✅

Scenario: Partner Order Is Accepted And Rules Derive The Totals
Given Customer "Acme" with balance 0 and credit limit 1000
When B2B order is posted for "Acme" with 2 Widget and 1 Gadget
Then B2B order is accepted
Then Order has 2 items
Then Order amount_total is 330
Then Customer balance is 330

Rules exercised and logic log (1 transaction)

Rules Used in Scenario: Partner Order Is Accepted And Rules Derive The Totals

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Item  
    2. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    3. Derive Item.unit_price as Copy(product.unit_price)  
  Order  
    4. RowEvent Order._send_order_to_kafka()  
    5. Derive Order.amount_total as Sum(Item.amount Where  - None)

Logic Log in Scenario: Partner Order Is Accepted And Rules Derive The Totals (1 transaction)

Logic Phase:        ROW LOGIC       (session=0x10c8009d0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,581 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: behave test, customer_id: 6, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c78b150  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,581 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: behave test, customer_id: 6, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c78b150  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,581 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: None, product_id: 2, quantity: 2, amount: None, unit_price: None  row: 0x10c78bc50  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,581 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: None, product_id: 2, quantity: 2, amount: None, unit_price: 90.0000000000  row: 0x10c78bc50  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,582 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: None, product_id: 2, quantity: 2, amount: 180.0000000000, unit_price: 90.0000000000  row: 0x10c78bc50  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,582 - logic_logger - INFO
....Order[None] {Update - Adjusting order: amount_total} id: None, notes: behave test, customer_id: 6, CreatedOn: None, date_shipped: None, amount_total:  [0-->] 180.0000000000  row: 0x10c78b150  session: 0x10c8009d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,582 - logic_logger - INFO
......Customer[6] {Update - Adjusting customer: balance} id: 6, name: Acme 1792465580574, balance:  [0E-10-->] 180.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c78afd0  session: 0x10c8009d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,582 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: None, product_id: 1, quantity: 1, amount: None, unit_price: None  row: 0x10c098450  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,582 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: None, product_id: 1, quantity: 1, amount: None, unit_price: 150.0000000000  row: 0x10c098450  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,582 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: None, product_id: 1, quantity: 1, amount: 150.0000000000, unit_price: 150.0000000000  row: 0x10c098450  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,583 - logic_logger - INFO
....Order[None] {Update - Adjusting order: amount_total} id: None, notes: behave test, customer_id: 6, CreatedOn: None, date_shipped: None, amount_total:  [180.0000000000-->] 330.0000000000  row: 0x10c78b150  session: 0x10c8009d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,583 - logic_logger - INFO
......Customer[6] {Update - Adjusting customer: balance} id: 6, name: Acme 1792465580574, balance:  [180.0000000000-->] 330.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c78afd0  session: 0x10c8009d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,583 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c8009d0)                                            - 2026-10-19 20:06:20,583 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c8009d0)                                            - 2026-10-19 20:06:20,584 - logic_logger - INFO
..Order[6] {AfterFlush Event} id: 6, notes: behave test, customer_id: 6, CreatedOn: None, date_shipped: None, amount_total: 330.0000000000  row: 0x10c78b150  session: 0x10c8009d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,584 - logic_logger - INFO

Scenario: Partner Order For An Unknown Customer Is Rejected ✅

Scenario: Partner Order For An Unknown Customer Is Rejected
Given Customer "Beta" with balance 0 and credit limit 1000
When B2B order is posted for unknown customer with 1 Widget
Then B2B order is rejected with status 404
Then Customer balance is 0

No rules fired in this scenario's logic log.

Scenario: Partner Order Exceeding Credit Limit Is Rejected ✅

Scenario: Partner Order Exceeding Credit Limit Is Rejected
Given Customer "Gamma" with balance 0 and credit limit 100
When B2B order is posted for "Gamma" with 2 Widget
Then B2B order is not accepted
Then Customer balance is 0

Rules exercised and logic log (1 transaction)

Rules Used in Scenario: Partner Order Exceeding Credit Limit Is Rejected

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
    2. Constraint Function: None  
  Item  
    3. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    4. Derive Item.unit_price as Copy(product.unit_price)  
  Order  
    5. Derive Order.amount_total as Sum(Item.amount Where  - None)

Logic Log in Scenario: Partner Order Exceeding Credit Limit Is Rejected (1 transaction)

Logic Phase:        ROW LOGIC       (session=0x10c773570) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,606 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: behave test, customer_id: 8, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c78b9d0  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,606 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: behave test, customer_id: 8, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c78b9d0  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,606 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: None, product_id: 2, quantity: 2, amount: None, unit_price: None  row: 0x10c7f32d0  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,606 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: None, product_id: 2, quantity: 2, amount: None, unit_price: 90.0000000000  row: 0x10c7f32d0  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,606 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: None, product_id: 2, quantity: 2, amount: 180.0000000000, unit_price: 90.0000000000  row: 0x10c7f32d0  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,606 - logic_logger - INFO
....Order[None] {Update - Adjusting order: amount_total} id: None, notes: behave test, customer_id: 8, CreatedOn: None, date_shipped: None, amount_total:  [0-->] 180.0000000000  row: 0x10c78b9d0  session: 0x10c773570  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,606 - logic_logger - INFO
......Customer[8] {Update - Adjusting customer: balance} id: 8, name: Gamma 1792465580602, balance:  [0E-10-->] 180.0000000000, credit_limit: 100.0000000000, email: None, email_opt_out: None  row: 0x10c7f3250  session: 0x10c773570  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,606 - logic_logger - INFO
......Customer[8] {Constraint Failure: balance (180.0000000000) exceeds credit limit (100.0000000000)} id: 8, name: Gamma 1792465580602, balance:  [0E-10-->] 180.0000000000, credit_limit: 100.0000000000, email: None, email_opt_out: None  row: 0x10c7f3250  session: 0x10c773570  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,606 - logic_logger - INFO

Feature: Check Credit

Scenario: Create Order Rolls Up To Customer Balance ✅

Scenario: Create Order Rolls Up To Customer Balance
Given Customer "Alice" with balance 0 and credit limit 1000
And Order is created for "Alice"
When Item is created with 5 Widget
Then Item unit_price is 90
Then Item amount is 450
Then Order amount_total is 450
Then Customer balance is 450

Rules exercised and logic log (2 transactions)

Rules Used in Scenario: Create Order Rolls Up To Customer Balance

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Create Order Rolls Up To Customer Balance (2 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c773570) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,614 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 9, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c7f2850  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,614 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 9, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c7f2850  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,614 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c773570)                                            - 2026-10-19 20:06:20,615 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c773570)                                            - 2026-10-19 20:06:20,615 - logic_logger - INFO
..Order[7] {AfterFlush Event} id: 7, notes: None, customer_id: 9, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c7f2850  session: 0x10c773570  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,615 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c773350) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,620 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 7, product_id: 2, quantity: 5, amount: None, unit_price: None  row: 0x10c78bcd0  session: 0x10c773350  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,620 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 7, product_id: 2, quantity: 5, amount: None, unit_price: 90.0000000000  row: 0x10c78bcd0  session: 0x10c773350  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,621 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 7, product_id: 2, quantity: 5, amount: 450.0000000000, unit_price: 90.0000000000  row: 0x10c78bcd0  session: 0x10c773350  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,621 - logic_logger - INFO
....Order[7] {Update - Adjusting order: amount_total} id: 7, notes: None, customer_id: 9, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9562d0  session: 0x10c773350  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,621 - logic_logger - INFO
......Customer[9] {Update - Adjusting customer: balance} id: 9, name: Alice 1792465580610, balance:  [0E-10-->] 450.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c956ad0  session: 0x10c773350  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,622 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c773350)                                            - 2026-10-19 20:06:20,622 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c773350)                                            - 2026-10-19 20:06:20,623 - logic_logger - INFO
....Order[7] {AfterFlush Event} id: 7, notes: None, customer_id: 9, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9562d0  session: 0x10c773350  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,623 - logic_logger - INFO

Scenario: Update Item Quantity Recalculates Amounts ✅

Scenario: Update Item Quantity Recalculates Amounts
Given Customer "Bob" with balance 0 and credit limit 1000
And Order is created for "Bob"
And Item is created with 2 Widget
When Item quantity is changed to 6
Then Item amount is 540
Then Order amount_total is 540
Then Customer balance is 540

Rules exercised and logic log (3 transactions)

Rules Used in Scenario: Update Item Quantity Recalculates Amounts

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Update Item Quantity Recalculates Amounts (3 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c773460) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,635 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 10, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c7f0850  session: 0x10c773460  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,635 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 10, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c7f0850  session: 0x10c773460  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,635 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c773460)                                            - 2026-10-19 20:06:20,636 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c773460)                                            - 2026-10-19 20:06:20,636 - logic_logger - INFO
..Order[8] {AfterFlush Event} id: 8, notes: None, customer_id: 10, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c7f0850  session: 0x10c773460  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,636 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c7738a0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,640 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 8, product_id: 2, quantity: 2, amount: None, unit_price: None  row: 0x10c9551d0  session: 0x10c7738a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,640 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 8, product_id: 2, quantity: 2, amount: None, unit_price: 90.0000000000  row: 0x10c9551d0  session: 0x10c7738a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,641 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 8, product_id: 2, quantity: 2, amount: 180.0000000000, unit_price: 90.0000000000  row: 0x10c9551d0  session: 0x10c7738a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,641 - logic_logger - INFO
....Order[8] {Update - Adjusting order: amount_total} id: 8, notes: None, customer_id: 10, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 180.0000000000  row: 0x10c9574d0  session: 0x10c7738a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,641 - logic_logger - INFO
......Customer[10] {Update - Adjusting customer: balance} id: 10, name: Bob 1792465580632, balance:  [0E-10-->] 180.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bc950  session: 0x10c7738a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,641 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c7738a0)                                            - 2026-10-19 20:06:20,641 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c7738a0)                                            - 2026-10-19 20:06:20,642 - logic_logger - INFO
....Order[8] {AfterFlush Event} id: 8, notes: None, customer_id: 10, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 180.0000000000  row: 0x10c9574d0  session: 0x10c7738a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,642 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c0270) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,644 - logic_logger - INFO
..Item[9] {Update - client} id: 9, order_id: 8, product_id: 2, quantity:  [2-->] 6, amount: 180.0000000000, unit_price: 90.0000000000  row: 0x10c9bc250  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,644 - logic_logger - INFO
..Item[9] {Formula amount} id: 9, order_id: 8, product_id: 2, quantity:  [2-->] 6, amount:  [180.0000000000-->] 540.0000000000, unit_price: 90.0000000000  row: 0x10c9bc250  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,645 - logic_logger - INFO
....Order[8] {Update - Adjusting order: amount_total} id: 8, notes: None, customer_id: 10, CreatedOn: None, date_shipped: None, amount_total:  [180.0000000000-->] 540.0000000000  row: 0x10c9bcb50  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,645 - logic_logger - INFO
......Customer[10] {Update - Adjusting customer: balance} id: 10, name: Bob 1792465580632, balance:  [180.0000000000-->] 540.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bd850  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,645 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0270)                                            - 2026-10-19 20:06:20,645 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0270)                                            - 2026-10-19 20:06:20,646 - logic_logger - INFO
....Order[8] {AfterFlush Event} id: 8, notes: None, customer_id: 10, CreatedOn: None, date_shipped: None, amount_total:  [180.0000000000-->] 540.0000000000  row: 0x10c9bcb50  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,646 - logic_logger - INFO

Scenario: Update Item Product Recopies Unit Price ✅

Scenario: Update Item Product Recopies Unit Price
Given Customer "Carol" with balance 0 and credit limit 1000
And Order is created for "Carol"
And Item is created with 3 Widget
When Item product is changed to Gadget
Then Item unit_price is 150
Then Item amount is 450
Then Order amount_total is 450
Then Customer balance is 450

Rules exercised and logic log (3 transactions)

Rules Used in Scenario: Update Item Product Recopies Unit Price

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Update Item Product Recopies Unit Price (3 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c9c09e0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,656 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 11, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c954050  session: 0x10c9c09e0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,656 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 11, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c954050  session: 0x10c9c09e0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,656 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c09e0)                                            - 2026-10-19 20:06:20,656 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c09e0)                                            - 2026-10-19 20:06:20,657 - logic_logger - INFO
..Order[9] {AfterFlush Event} id: 9, notes: None, customer_id: 11, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c954050  session: 0x10c9c09e0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,657 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c07c0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,661 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 9, product_id: 2, quantity: 3, amount: None, unit_price: None  row: 0x10c956350  session: 0x10c9c07c0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,661 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 9, product_id: 2, quantity: 3, amount: None, unit_price: 90.0000000000  row: 0x10c956350  session: 0x10c9c07c0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,661 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 9, product_id: 2, quantity: 3, amount: 270.0000000000, unit_price: 90.0000000000  row: 0x10c956350  session: 0x10c9c07c0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,662 - logic_logger - INFO
....Order[9] {Update - Adjusting order: amount_total} id: 9, notes: None, customer_id: 11, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 270.0000000000  row: 0x10c9bc750  session: 0x10c9c07c0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,662 - logic_logger - INFO
......Customer[11] {Update - Adjusting customer: balance} id: 11, name: Carol 1792465580652, balance:  [0E-10-->] 270.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c7f0b50  session: 0x10c9c07c0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,662 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c07c0)                                            - 2026-10-19 20:06:20,662 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c07c0)                                            - 2026-10-19 20:06:20,662 - logic_logger - INFO
....Order[9] {AfterFlush Event} id: 9, notes: None, customer_id: 11, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 270.0000000000  row: 0x10c9bc750  session: 0x10c9c07c0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,662 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c772580) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,666 - logic_logger - INFO
..Item[10] {Update - client} id: 10, order_id: 9, product_id:  [2-->] 1, quantity: 3, amount: 270.0000000000, unit_price: 90.0000000000  row: 0x10c9bc050  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,666 - logic_logger - INFO
..Item[10] {copy_rules for role: product - unit_price} id: 10, order_id: 9, product_id:  [2-->] 1, quantity: 3, amount: 270.0000000000, unit_price:  [90.0000000000-->] 150.0000000000  row: 0x10c9bc050  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,667 - logic_logger - INFO
..Item[10] {Formula amount} id: 10, order_id: 9, product_id:  [2-->] 1, quantity: 3, amount:  [270.0000000000-->] 450.0000000000, unit_price:  [90.0000000000-->] 150.0000000000  row: 0x10c9bc050  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,667 - logic_logger - INFO
....Order[9] {Update - Adjusting order: amount_total} id: 9, notes: None, customer_id: 11, CreatedOn: None, date_shipped: None, amount_total:  [270.0000000000-->] 450.0000000000  row: 0x10c9bda50  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,667 - logic_logger - INFO
......Customer[11] {Update - Adjusting customer: balance} id: 11, name: Carol 1792465580652, balance:  [270.0000000000-->] 450.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bdcd0  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,667 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c772580)                                            - 2026-10-19 20:06:20,667 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c772580)                                            - 2026-10-19 20:06:20,668 - logic_logger - INFO
....Order[9] {AfterFlush Event} id: 9, notes: None, customer_id: 11, CreatedOn: None, date_shipped: None, amount_total:  [270.0000000000-->] 450.0000000000  row: 0x10c9bda50  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,668 - logic_logger - INFO

Scenario: Delete Item Reduces Order And Balance ✅

Scenario: Delete Item Reduces Order And Balance
Given Customer "Dave" with balance 0 and credit limit 1000
And Order is created for "Dave"
And Item is created with 4 Widget
When Item is deleted
Then Order amount_total is 0
Then Customer balance is 0

Rules exercised and logic log (3 transactions)

Rules Used in Scenario: Delete Item Reduces Order And Balance

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Delete Item Reduces Order And Balance (3 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c7738a0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,678 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 12, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c9568d0  session: 0x10c7738a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,678 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 12, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9568d0  session: 0x10c7738a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,678 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c7738a0)                                            - 2026-10-19 20:06:20,679 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c7738a0)                                            - 2026-10-19 20:06:20,679 - logic_logger - INFO
..Order[10] {AfterFlush Event} id: 10, notes: None, customer_id: 12, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9568d0  session: 0x10c7738a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,679 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c0af0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,683 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 10, product_id: 2, quantity: 4, amount: None, unit_price: None  row: 0x10c955dd0  session: 0x10c9c0af0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,683 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 10, product_id: 2, quantity: 4, amount: None, unit_price: 90.0000000000  row: 0x10c955dd0  session: 0x10c9c0af0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,684 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 10, product_id: 2, quantity: 4, amount: 360.0000000000, unit_price: 90.0000000000  row: 0x10c955dd0  session: 0x10c9c0af0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,684 - logic_logger - INFO
....Order[10] {Update - Adjusting order: amount_total} id: 10, notes: None, customer_id: 12, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 360.0000000000  row: 0x10c9bc550  session: 0x10c9c0af0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,684 - logic_logger - INFO
......Customer[12] {Update - Adjusting customer: balance} id: 12, name: Dave 1792465580675, balance:  [0E-10-->] 360.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9be6d0  session: 0x10c9c0af0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,684 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0af0)                                            - 2026-10-19 20:06:20,684 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0af0)                                            - 2026-10-19 20:06:20,685 - logic_logger - INFO
....Order[10] {AfterFlush Event} id: 10, notes: None, customer_id: 12, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 360.0000000000  row: 0x10c9bc550  session: 0x10c9c0af0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,685 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c0380) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,687 - logic_logger - INFO
..Item[11] {Delete - client} id: 11, order_id: 10, product_id: 2, quantity: 4, amount: 360.0000000000, unit_price: 90.0000000000  row: 0x10c9bc9d0  session: 0x10c9c0380  ins_upd_dlt: dlt, initial: dlt - 2026-10-19 20:06:20,687 - logic_logger - INFO
....Order[10] {Update - Adjusting order: amount_total} id: 10, notes: None, customer_id: 12, CreatedOn: None, date_shipped: None, amount_total:  [360.0000000000-->] 0E-10  row: 0x10c9bded0  session: 0x10c9c0380  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,687 - logic_logger - INFO
......Customer[12] {Update - Adjusting customer: balance} id: 12, name: Dave 1792465580675, balance:  [360.0000000000-->] 0E-10, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bead0  session: 0x10c9c0380  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,688 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0380)                                            - 2026-10-19 20:06:20,688 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0380)                                            - 2026-10-19 20:06:20,688 - logic_logger - INFO
....Order[10] {AfterFlush Event} id: 10, notes: None, customer_id: 12, CreatedOn: None, date_shipped: None, amount_total:  [360.0000000000-->] 0E-10  row: 0x10c9bded0  session: 0x10c9c0380  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,688 - logic_logger - INFO

Scenario: Change Order Customer Adjusts Both Balances ✅

Scenario: Change Order Customer Adjusts Both Balances
Given Customer "Erin" with balance 0 and credit limit 1000
And Customer "Frank" with balance 0 and credit limit 1000
And Order is created for "Erin"
And Item is created with 5 Widget
When Order customer is changed to "Frank"
Then Customer "Erin" balance is 0
Then Customer "Frank" balance is 450

Rules exercised and logic log (3 transactions)

Rules Used in Scenario: Change Order Customer Adjusts Both Balances

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Change Order Customer Adjusts Both Balances (3 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c9c0e20) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,700 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 13, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c9be650  session: 0x10c9c0e20  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,700 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 13, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9be650  session: 0x10c9c0e20  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,700 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0e20)                                            - 2026-10-19 20:06:20,700 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0e20)                                            - 2026-10-19 20:06:20,700 - logic_logger - INFO
..Order[11] {AfterFlush Event} id: 11, notes: None, customer_id: 13, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9be650  session: 0x10c9c0e20  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,700 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c0f30) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,704 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 11, product_id: 2, quantity: 5, amount: None, unit_price: None  row: 0x10c9bcb50  session: 0x10c9c0f30  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,704 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 11, product_id: 2, quantity: 5, amount: None, unit_price: 90.0000000000  row: 0x10c9bcb50  session: 0x10c9c0f30  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,705 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 11, product_id: 2, quantity: 5, amount: 450.0000000000, unit_price: 90.0000000000  row: 0x10c9bcb50  session: 0x10c9c0f30  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,705 - logic_logger - INFO
....Order[11] {Update - Adjusting order: amount_total} id: 11, notes: None, customer_id: 13, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9bdf50  session: 0x10c9c0f30  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,705 - logic_logger - INFO
......Customer[13] {Update - Adjusting customer: balance} id: 13, name: Erin 1792465580693, balance:  [0E-10-->] 450.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bee50  session: 0x10c9c0f30  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,705 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0f30)                                            - 2026-10-19 20:06:20,705 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0f30)                                            - 2026-10-19 20:06:20,706 - logic_logger - INFO
....Order[11] {AfterFlush Event} id: 11, notes: None, customer_id: 13, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9bdf50  session: 0x10c9c0f30  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,706 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c7738a0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,708 - logic_logger - INFO
..Order[11] {Update - client} id: 11, notes: None, customer_id:  [13-->] 14, CreatedOn: None, date_shipped: None, amount_total: 450.0000000000  row: 0x10c9bf2d0  session: 0x10c7738a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,708 - logic_logger - INFO
....Customer[14] {Update - Adjusting customer: balance, balance} id: 14, name: Frank 1792465580696, balance:  [0E-10-->] 450.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9beed0  session: 0x10c7738a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,709 - logic_logger - INFO
....Customer[13] {Update - Adjusting Old customer} id: 13, name: Erin 1792465580693, balance:  [450.0000000000-->] 0E-10, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9be250  session: 0x10c7738a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,709 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c7738a0)                                            - 2026-10-19 20:06:20,709 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c7738a0)                                            - 2026-10-19 20:06:20,709 - logic_logger - INFO
..Order[11] {AfterFlush Event} id: 11, notes: None, customer_id:  [13-->] 14, CreatedOn: None, date_shipped: None, amount_total: 450.0000000000  row: 0x10c9bf2d0  session: 0x10c7738a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,710 - logic_logger - INFO

Scenario: Ship Order Excludes From Balance ✅

Scenario: Ship Order Excludes From Balance
Given Customer "Grace" with balance 0 and credit limit 1000
And Order is created for "Grace"
And Item is created with 5 Widget
When Order is shipped
Then Customer balance is 0

Rules exercised and logic log (3 transactions)

Rules Used in Scenario: Ship Order Excludes From Balance

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Ship Order Excludes From Balance (3 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c773680) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,719 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 15, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c9577d0  session: 0x10c773680  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,719 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 15, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9577d0  session: 0x10c773680  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,719 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c773680)                                            - 2026-10-19 20:06:20,719 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c773680)                                            - 2026-10-19 20:06:20,720 - logic_logger - INFO
..Order[12] {AfterFlush Event} id: 12, notes: None, customer_id: 15, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9577d0  session: 0x10c773680  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,720 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c0270) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,723 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 12, product_id: 2, quantity: 5, amount: None, unit_price: None  row: 0x10c9548d0  session: 0x10c9c0270  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,723 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 12, product_id: 2, quantity: 5, amount: None, unit_price: 90.0000000000  row: 0x10c9548d0  session: 0x10c9c0270  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,724 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 12, product_id: 2, quantity: 5, amount: 450.0000000000, unit_price: 90.0000000000  row: 0x10c9548d0  session: 0x10c9c0270  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,724 - logic_logger - INFO
....Order[12] {Update - Adjusting order: amount_total} id: 12, notes: None, customer_id: 15, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9be150  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,724 - logic_logger - INFO
......Customer[15] {Update - Adjusting customer: balance} id: 15, name: Grace 1792465580715, balance:  [0E-10-->] 450.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9be6d0  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,724 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0270)                                            - 2026-10-19 20:06:20,724 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0270)                                            - 2026-10-19 20:06:20,725 - logic_logger - INFO
....Order[12] {AfterFlush Event} id: 12, notes: None, customer_id: 15, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9be150  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,725 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c0050) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,728 - logic_logger - INFO
..Order[12] {Update - client} id: 12, notes: None, customer_id: 15, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 450.0000000000  row: 0x10c9bded0  session: 0x10c9c0050  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,728 - logic_logger - INFO
....Customer[15] {Update - Adjusting customer: balance} id: 15, name: Grace 1792465580715, balance:  [450.0000000000-->] 0E-10, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bf950  session: 0x10c9c0050  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,728 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0050)                                            - 2026-10-19 20:06:20,728 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0050)                                            - 2026-10-19 20:06:20,729 - logic_logger - INFO
..Order[12] {AfterFlush Event} id: 12, notes: None, customer_id: 15, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 450.0000000000  row: 0x10c9bded0  session: 0x10c9c0050  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,729 - logic_logger - INFO
..Order[12] {publish_kafka_message: topic='order_shipping', key={'id': 12}} id: 12, notes: None, customer_id: 15, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 450.0000000000  row: 0x10c9bded0  session: 0x10c9c0050  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,739 - logic_logger - INFO

Scenario: Unship Order Includes In Balance ✅

Scenario: Unship Order Includes In Balance
Given Customer "Heidi" with balance 0 and credit limit 1000
And Order is created for "Heidi"
And Item is created with 5 Widget
And Order is shipped
When Order is unshipped
Then Customer balance is 450

Rules exercised and logic log (4 transactions)

Rules Used in Scenario: Unship Order Includes In Balance

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Unship Order Includes In Balance (4 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c9c1480) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,748 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 16, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c9568d0  session: 0x10c9c1480  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,748 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 16, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9568d0  session: 0x10c9c1480  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,748 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c1480)                                            - 2026-10-19 20:06:20,748 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c1480)                                            - 2026-10-19 20:06:20,748 - logic_logger - INFO
..Order[13] {AfterFlush Event} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9568d0  session: 0x10c9c1480  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,748 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c16a0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,752 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 13, product_id: 2, quantity: 5, amount: None, unit_price: None  row: 0x10c9bd8d0  session: 0x10c9c16a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,752 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 13, product_id: 2, quantity: 5, amount: None, unit_price: 90.0000000000  row: 0x10c9bd8d0  session: 0x10c9c16a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,753 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 13, product_id: 2, quantity: 5, amount: 450.0000000000, unit_price: 90.0000000000  row: 0x10c9bd8d0  session: 0x10c9c16a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,753 - logic_logger - INFO
....Order[13] {Update - Adjusting order: amount_total} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9befd0  session: 0x10c9c16a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,753 - logic_logger - INFO
......Customer[16] {Update - Adjusting customer: balance} id: 16, name: Heidi 1792465580744, balance:  [0E-10-->] 450.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10ca18d50  session: 0x10c9c16a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,753 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c16a0)                                            - 2026-10-19 20:06:20,754 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c16a0)                                            - 2026-10-19 20:06:20,754 - logic_logger - INFO
....Order[13] {AfterFlush Event} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10c9befd0  session: 0x10c9c16a0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,754 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c773680) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,757 - logic_logger - INFO
..Order[13] {Update - client} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 450.0000000000  row: 0x10c9be3d0  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,757 - logic_logger - INFO
....Customer[16] {Update - Adjusting customer: balance} id: 16, name: Heidi 1792465580744, balance:  [450.0000000000-->] 0E-10, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bea50  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,758 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c773680)                                            - 2026-10-19 20:06:20,758 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c773680)                                            - 2026-10-19 20:06:20,758 - logic_logger - INFO
..Order[13] {AfterFlush Event} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 450.0000000000  row: 0x10c9be3d0  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,758 - logic_logger - INFO
..Order[13] {publish_kafka_message: topic='order_shipping', key={'id': 13}} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 450.0000000000  row: 0x10c9be3d0  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,760 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c773460) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,763 - logic_logger - INFO
..Order[13] {Update - client} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped:  [2026-01-01-->] None, amount_total: 450.0000000000  row: 0x10c9be8d0  session: 0x10c773460  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,763 - logic_logger - INFO
....Customer[16] {Update - Adjusting customer: balance} id: 16, name: Heidi 1792465580744, balance:  [0E-10-->] 450.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bde50  session: 0x10c773460  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,763 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c773460)                                            - 2026-10-19 20:06:20,763 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c773460)                                            - 2026-10-19 20:06:20,764 - logic_logger - INFO
..Order[13] {AfterFlush Event} id: 13, notes: None, customer_id: 16, CreatedOn: None, date_shipped:  [2026-01-01-->] None, amount_total: 450.0000000000  row: 0x10c9be8d0  session: 0x10c773460  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,764 - logic_logger - INFO

Scenario: Order Within Credit Limit Is Accepted ✅

Scenario: Order Within Credit Limit Is Accepted
Given Customer "Ivan" with balance 0 and credit limit 1000
And Order is created for "Ivan"
When Item is created with 10 Widget
Then Order creation succeeded
Then Customer balance is 900

Rules exercised and logic log (2 transactions)

Rules Used in Scenario: Order Within Credit Limit Is Accepted

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Order Within Credit Limit Is Accepted (2 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c9c05a0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,771 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 17, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c9557d0  session: 0x10c9c05a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,771 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 17, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9557d0  session: 0x10c9c05a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,771 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c05a0)                                            - 2026-10-19 20:06:20,772 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c05a0)                                            - 2026-10-19 20:06:20,772 - logic_logger - INFO
..Order[14] {AfterFlush Event} id: 14, notes: None, customer_id: 17, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9557d0  session: 0x10c9c05a0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,772 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c08d0) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,776 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 14, product_id: 2, quantity: 10, amount: None, unit_price: None  row: 0x10c954cd0  session: 0x10c9c08d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,776 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 14, product_id: 2, quantity: 10, amount: None, unit_price: 90.0000000000  row: 0x10c954cd0  session: 0x10c9c08d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,777 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 14, product_id: 2, quantity: 10, amount: 900.0000000000, unit_price: 90.0000000000  row: 0x10c954cd0  session: 0x10c9c08d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,777 - logic_logger - INFO
....Order[14] {Update - Adjusting order: amount_total} id: 14, notes: None, customer_id: 17, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 900.0000000000  row: 0x10c9bda50  session: 0x10c9c08d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,777 - logic_logger - INFO
......Customer[17] {Update - Adjusting customer: balance} id: 17, name: Ivan 1792465580767, balance:  [0E-10-->] 900.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10ca182d0  session: 0x10c9c08d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,777 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c08d0)                                            - 2026-10-19 20:06:20,778 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c08d0)                                            - 2026-10-19 20:06:20,778 - logic_logger - INFO
....Order[14] {AfterFlush Event} id: 14, notes: None, customer_id: 17, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 900.0000000000  row: 0x10c9bda50  session: 0x10c9c08d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,778 - logic_logger - INFO

Scenario: Order Exceeding Credit Limit Is Rejected ✅

Scenario: Order Exceeding Credit Limit Is Rejected
Given Customer "Judy" with balance 0 and credit limit 40
And Order is created for "Judy"
When Item is created with 5 Widget
Then Item creation is rejected
Then Customer balance is 0

Rules exercised and logic log (2 transactions)

Rules Used in Scenario: Order Exceeding Credit Limit Is Rejected

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
    2. Constraint Function: None  
  Order  
    3. RowEvent Order._send_order_to_kafka()  
    4. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    5. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    6. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Order Exceeding Credit Limit Is Rejected (2 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c9c0d10) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,786 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 18, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10c9551d0  session: 0x10c9c0d10  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,786 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 18, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9551d0  session: 0x10c9c0d10  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,786 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c0d10)                                            - 2026-10-19 20:06:20,786 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c0d10)                                            - 2026-10-19 20:06:20,787 - logic_logger - INFO
..Order[15] {AfterFlush Event} id: 15, notes: None, customer_id: 18, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10c9551d0  session: 0x10c9c0d10  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,787 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c9c0270) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,791 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 15, product_id: 2, quantity: 5, amount: None, unit_price: None  row: 0x10c9bf050  session: 0x10c9c0270  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,791 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 15, product_id: 2, quantity: 5, amount: None, unit_price: 90.0000000000  row: 0x10c9bf050  session: 0x10c9c0270  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,792 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 15, product_id: 2, quantity: 5, amount: 450.0000000000, unit_price: 90.0000000000  row: 0x10c9bf050  session: 0x10c9c0270  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,792 - logic_logger - INFO
....Order[15] {Update - Adjusting order: amount_total} id: 15, notes: None, customer_id: 18, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 450.0000000000  row: 0x10ca18c50  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,792 - logic_logger - INFO
......Customer[18] {Update - Adjusting customer: balance} id: 18, name: Judy 1792465580782, balance:  [0E-10-->] 450.0000000000, credit_limit: 40.0000000000, email: None, email_opt_out: None  row: 0x10ca18f50  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,792 - logic_logger - INFO
......Customer[18] {Constraint Failure: balance (450.0000000000) exceeds credit limit (40.0000000000)} id: 18, name: Judy 1792465580782, balance:  [0E-10-->] 450.0000000000, credit_limit: 40.0000000000, email: None, email_opt_out: None  row: 0x10ca18f50  session: 0x10c9c0270  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,792 - logic_logger - INFO

Feature: Kafka Publish Shipping Notification

Scenario: Shipping An Order Publishes To order_shipping ✅

Scenario: Shipping An Order Publishes To order_shipping
Given Customer "Echo" with balance 0 and credit limit 1000
And Order is created for "Echo"
And Item is created with 1 Widget
When Order is shipped
Then The order_shipping publish event fired
Then A message for the order is on topic order_shipping

Rules exercised and logic log (3 transactions)

Rules Used in Scenario: Shipping An Order Publishes To order_shipping

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Order  
    2. RowEvent Order._send_order_to_kafka()  
    3. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  Item  
    4. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    5. Derive Item.unit_price as Copy(product.unit_price)

Logic Log in Scenario: Shipping An Order Publishes To order_shipping (3 transactions)

Logic Phase:        ROW LOGIC       (session=0x10c9c1d00) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,804 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: None, customer_id: 19, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10ca18a50  session: 0x10c9c1d00  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,804 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: None, customer_id: 19, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10ca18a50  session: 0x10c9c1d00  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,804 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c1d00)                                            - 2026-10-19 20:06:20,805 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c1d00)                                            - 2026-10-19 20:06:20,805 - logic_logger - INFO
..Order[16] {AfterFlush Event} id: 16, notes: None, customer_id: 19, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10ca18a50  session: 0x10c9c1d00  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,805 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c772580) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,809 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: 16, product_id: 2, quantity: 1, amount: None, unit_price: None  row: 0x10ca187d0  session: 0x10c772580  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,809 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: 16, product_id: 2, quantity: 1, amount: None, unit_price: 90.0000000000  row: 0x10ca187d0  session: 0x10c772580  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,810 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: 16, product_id: 2, quantity: 1, amount: 90.0000000000, unit_price: 90.0000000000  row: 0x10ca187d0  session: 0x10c772580  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:20,810 - logic_logger - INFO
....Order[16] {Update - Adjusting order: amount_total} id: 16, notes: None, customer_id: 19, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 90.0000000000  row: 0x10c9571d0  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,810 - logic_logger - INFO
......Customer[19] {Update - Adjusting customer: balance} id: 19, name: Echo 1792465580800, balance:  [0E-10-->] 90.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bf050  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,810 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c772580)                                            - 2026-10-19 20:06:20,811 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c772580)                                            - 2026-10-19 20:06:20,811 - logic_logger - INFO
....Order[16] {AfterFlush Event} id: 16, notes: None, customer_id: 19, CreatedOn: None, date_shipped: None, amount_total:  [0E-10-->] 90.0000000000  row: 0x10c9571d0  session: 0x10c772580  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,811 - logic_logger - INFO


Logic Phase:        ROW LOGIC       (session=0x10c773680) (sqlalchemy before_flush)          - 2026-10-19 20:06:20,813 - logic_logger - INFO
..Order[16] {Update - client} id: 16, notes: None, customer_id: 19, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 90.0000000000  row: 0x10c7f3550  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,813 - logic_logger - INFO
....Customer[19] {Update - Adjusting customer: balance} id: 19, name: Echo 1792465580800, balance:  [90.0000000000-->] 0E-10, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bf1d0  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,814 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c773680)                                            - 2026-10-19 20:06:20,814 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c773680)                                            - 2026-10-19 20:06:20,814 - logic_logger - INFO
..Order[16] {AfterFlush Event} id: 16, notes: None, customer_id: 19, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 90.0000000000  row: 0x10c7f3550  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,814 - logic_logger - INFO
..Order[16] {publish_kafka_message: topic='order_shipping', key={'id': 16}} id: 16, notes: None, customer_id: 19, CreatedOn: None, date_shipped:  [None-->] 2026-01-01 00:00:00, amount_total: 90.0000000000  row: 0x10c7f3550  session: 0x10c773680  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:20,816 - logic_logger - INFO

Scenario: Inbound Order Message Creates The Order And Items ✅

Scenario: Inbound Order Message Creates The Order And Items
Given Customer "Delta" with balance 0 and credit limit 1000
When Inbound order message is consumed for "Delta" with 2 Widget and 1 Gadget
Then Order is persisted from the message
Then Order has 2 items
Then Order amount_total is 330
Then Customer balance is 330
Then Message blob is marked processed

Rules exercised and logic log (1 transaction)

Rules Used in Scenario: Inbound Order Message Creates The Order And Items

  Customer  
    1. Derive Customer.balance as Sum(Order.amount_total Where lambda row: row.date_shipped is None))  
  Item  
    2. Derive Item.amount as Formula (1): as_expression=lambda row: row.quantity * row.unit [...]  
    3. Derive Item.unit_price as Copy(product.unit_price)  
  Order  
    4. RowEvent Order._send_order_to_kafka()  
    5. Derive Order.amount_total as Sum(Item.amount Where  - None)  
  OrderB2bMessage  
    6. RowEvent OrderB2bMessage._publish_order_b2b()

Logic Log in Scenario: Inbound Order Message Creates The Order And Items (1 transaction)

Logic Phase:        ROW LOGIC       (session=0x10c9c19d0) (sqlalchemy before_flush)          - 2026-10-19 20:06:24,046 - logic_logger - INFO
..Order[None] {Insert - client} id: None, notes: behave kafka test, customer_id: 20, CreatedOn: None, date_shipped: None, amount_total: None  row: 0x10ca183d0  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,046 - logic_logger - INFO
..Order[None] {server aggregate_defaults: amount_total } id: None, notes: behave kafka test, customer_id: 20, CreatedOn: None, date_shipped: None, amount_total: 0  row: 0x10ca183d0  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,047 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: None, product_id: 2, quantity: 2, amount: None, unit_price: None  row: 0x10ca18c50  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,047 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: None, product_id: 2, quantity: 2, amount: None, unit_price: 90.0000000000  row: 0x10ca18c50  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,048 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: None, product_id: 2, quantity: 2, amount: 180.0000000000, unit_price: 90.0000000000  row: 0x10ca18c50  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,048 - logic_logger - INFO
....Order[None] {Update - Adjusting order: amount_total} id: None, notes: behave kafka test, customer_id: 20, CreatedOn: None, date_shipped: None, amount_total:  [0-->] 180.0000000000  row: 0x10ca183d0  session: 0x10c9c19d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:24,048 - logic_logger - INFO
......Customer[20] {Update - Adjusting customer: balance} id: 20, name: Delta 1792465584034, balance:  [0E-10-->] 180.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bc9d0  session: 0x10c9c19d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:24,048 - logic_logger - INFO
..Item[None] {Insert - client} id: None, order_id: None, product_id: 1, quantity: 1, amount: None, unit_price: None  row: 0x10c957150  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,048 - logic_logger - INFO
..Item[None] {copy_rules for role: product - unit_price} id: None, order_id: None, product_id: 1, quantity: 1, amount: None, unit_price: 150.0000000000  row: 0x10c957150  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,049 - logic_logger - INFO
..Item[None] {Formula amount} id: None, order_id: None, product_id: 1, quantity: 1, amount: 150.0000000000, unit_price: 150.0000000000  row: 0x10c957150  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,049 - logic_logger - INFO
....Order[None] {Update - Adjusting order: amount_total} id: None, notes: behave kafka test, customer_id: 20, CreatedOn: None, date_shipped: None, amount_total:  [180.0000000000-->] 330.0000000000  row: 0x10ca183d0  session: 0x10c9c19d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:24,049 - logic_logger - INFO
......Customer[20] {Update - Adjusting customer: balance} id: 20, name: Delta 1792465584034, balance:  [180.0000000000-->] 330.0000000000, credit_limit: 1000.0000000000, email: None, email_opt_out: None  row: 0x10c9bc9d0  session: 0x10c9c19d0  ins_upd_dlt: upd, initial: upd - 2026-10-19 20:06:24,049 - logic_logger - INFO
..OrderB2bMessage[None] {Insert - client} id: None, received_at: None, payload: {"Account": "Delta 1792465584034", "Notes": "behave kafka test", "Items": [{"Name": "Widget", "QuantityOrdered": 2}, {"Name": "Gadget", "QuantityOrdered": 1}]}, is_processed: True, error_text: None  row: 0x10c75d2b0  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,049 - logic_logger - INFO
..OrderB2bMessage[None] {server_defaults: received_at } id: None, received_at: 2026-10-19, payload: {"Account": "Delta 1792465584034", "Notes": "behave kafka test", "Items": [{"Name": "Widget", "QuantityOrdered": 2}, {"Name": "Gadget", "QuantityOrdered": 1}]}, is_processed: True, error_text: None  row: 0x10c75d2b0  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,049 - logic_logger - INFO
Logic Phase:        COMMIT LOGIC        (session=0x10c9c19d0)                                            - 2026-10-19 20:06:24,050 - logic_logger - INFO
Logic Phase:        AFTER_FLUSH LOGIC   (session=0x10c9c19d0)                                            - 2026-10-19 20:06:24,051 - logic_logger - INFO
..Order[17] {AfterFlush Event} id: 17, notes: behave kafka test, customer_id: 20, CreatedOn: None, date_shipped: None, amount_total: 330.0000000000  row: 0x10ca183d0  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,051 - logic_logger - INFO
..OrderB2bMessage[1] {AfterFlush Event} id: 1, received_at: 2026-10-19, payload: {"Account": "Delta 1792465584034", "Notes": "behave kafka test", "Items": [{"Name": "Widget", "QuantityOrdered": 2}, {"Name": "Gadget", "QuantityOrdered": 1}]}, is_processed: True, error_text: None  row: 0x10c75d2b0  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,051 - logic_logger - INFO
..OrderB2bMessage[1] {_publish_order_b2b: skipping re-publish — blob.id=1 already is_processed=True (debug path)} id: 1, received_at: 2026-10-19, payload: {"Account": "Delta 1792465584034", "Notes": "behave kafka test", "Items": [{"Name": "Widget", "QuantityOrdered": 2}, {"Name": "Gadget", "QuantityOrdered": 1}]}, is_processed: True, error_text: None  row: 0x10c75d2b0  session: 0x10c9c19d0  ins_upd_dlt: ins, initial: ins - 2026-10-19 20:06:24,051 - logic_logger - INFO

/Users/val/dev/ApiLogicServer/ApiLogicServer-dev/build_and_test/genai-logic/samples/basic_demo_eai/test/api_logic_server_behave/behave_run.py completed at October 19, 2026 20:06:24

Behave Logic Report

Behave Logic Report

Contents

Requirements Traceability To Rules

Coverage summary

Traceability matrix

Rule coverage by tests

Requirements in detail

§1 Business Logic — Check Credit

§2 B2B API — Accept orders from external partners

§3 Kafka Subscribe — Inbound orders from sales channel

§4 Kafka Publish — Notify shipping on dispatch

§5 Security

Rules not traced to a requirement

Data Model

Derived columns

Security (RBAC)

Roles and CRUD (DefaultRolePermission)

Row-level grants (Grant)

Messages and APIs

Tests and Results

Feature: B2B Order Integration

Scenario: Partner Order Is Accepted And Rules Derive The Totals ✅

Scenario: Partner Order For An Unknown Customer Is Rejected ✅

Scenario: Partner Order Exceeding Credit Limit Is Rejected ✅

Feature: Check Credit

Scenario: Create Order Rolls Up To Customer Balance ✅

Scenario: Update Item Quantity Recalculates Amounts ✅

Scenario: Update Item Product Recopies Unit Price ✅

Scenario: Delete Item Reduces Order And Balance ✅

Scenario: Change Order Customer Adjusts Both Balances ✅

Scenario: Ship Order Excludes From Balance ✅

Scenario: Unship Order Includes In Balance ✅

Scenario: Order Within Credit Limit Is Accepted ✅

Scenario: Order Exceeding Credit Limit Is Rejected ✅

Feature: Kafka Publish Shipping Notification

Scenario: Shipping An Order Publishes To order_shipping ✅

Feature: Kafka Subscribe Order Integration

Scenario: Inbound Order Message Creates The Order And Items ✅