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Conditional routing — Automation Patterns

Day 4 · ~11 min●

Yesterday: every item went the same path. Today: items branch. If value > 10, do X. Else, do Y. Same pattern as Foundations' filter, but instead of skip-or-act it's act-A-or-act-B.

python

items = [{"id": "a", "value": 5}, {"id": "b", "value": 15}]

for item in items:
    if item["value"] > 10:
        # path A
        toolset.execute_action(Action.GOOGLECALENDAR_CREATE_EVENT, {
            "calendar_id": "primary",
            "summary": f"high: {item['id']}",
            "start_datetime": "2026-12-31T10:00:00+00:00",
            "event_duration_minutes": 15,
        })
    else:
        # path B — discover task list and add a low-priority task
        lists = toolset.execute_action(Action.GOOGLETASKS_LIST_TASK_LISTS, {})
        tasklist_id = (lists.get("items") or lists.get("response_data", {}).get("items", []))[0]["id"]
        toolset.execute_action(Action.GOOGLETASKS_CREATE_TASK, {
            "tasklist_id": tasklist_id,
            "title": f"low: {item['id']}",
        })

Two destinations, one branch per item, every item gets somewhere.

And if/else is from Python Foundations?

Same if/else. The new piece isn't the syntax — it's the shape: tool A on one branch, tool B on the other. The condition is plain Python (item["value"] > 10), but the side effect is different per branch.

What about three branches?

if/elif/elif/else. For 4+ branches, you'd switch to a dispatch dict — routes = {"high": tool_a, "low": tool_b, "medium": tool_c} and routes[category](item). That pattern lives in week 4. Today: two-way branch.

Conditional routing — branching on data

The shape

python

for item in items:
    if predicate(item):
        path_a(item)
    else:
        path_b(item)

Every item exits to exactly one of path_a or path_b. No item is skipped, no item is double-processed.

Routing vs filtering vs partitioning

Three similar-looking patterns; pick the right one:

Pattern	Shape	Example
Filter	act on some, skip others	`if x > 10: send(x)` (no else)
Routing	every item → A or B	`if x > 10: send(x) else log(x)`
Partition	split into two lists, then act on each	`bigs = [x for x in xs if x > 10]; smalls = [...]`

Day 5 covers partition; today and yesterday cover the simpler shapes.

Counting per branch

In a routing loop, two counters tell you what happened:

python

a_count = 0
b_count = 0
for item in items:
    if item["value"] > 10:
        path_a(item)
        a_count += 1
    else:
        path_b(item)
        b_count += 1

print(f"path_a: {a_count}, path_b: {b_count}")

One extra line per branch; the closing report tells you the routing was sane (5 of 10 high, 5 of 10 low) without re-reading the items.

Predicate complexity

The if predicate can be as simple as item["value"] > 10 or as complex as a function:

python

def is_urgent(item):
    return item.get("priority") == "high" or item.get("due_in_hours", 999) < 24

for item in items:
    if is_urgent(item):
        ...

Extract the predicate into a function once it has 2+ conditions. The branch reads as English ("if urgent, send alert") instead of three nested and/or.

Three or more branches

python

for item in items:
    if item["value"] > 100:
        critical_path(item)
    elif item["value"] > 10:
        normal_path(item)
    else:
        low_path(item)

Readable up to ~3 branches. Beyond that, switch to a dispatch dict — covered in week 4.

Day 4 · ~11 min●

Yesterday: every item went the same path. Today: items branch. If value > 10, do X. Else, do Y. Same pattern as Foundations' filter, but instead of skip-or-act it's act-A-or-act-B.

python

items = [{"id": "a", "value": 5}, {"id": "b", "value": 15}]

for item in items:
    if item["value"] > 10:
        # path A
        toolset.execute_action(Action.GOOGLECALENDAR_CREATE_EVENT, {
            "calendar_id": "primary",
            "summary": f"high: {item['id']}",
            "start_datetime": "2026-12-31T10:00:00+00:00",
            "event_duration_minutes": 15,
        })
    else:
        # path B — discover task list and add a low-priority task
        lists = toolset.execute_action(Action.GOOGLETASKS_LIST_TASK_LISTS, {})
        tasklist_id = (lists.get("items") or lists.get("response_data", {}).get("items", []))[0]["id"]
        toolset.execute_action(Action.GOOGLETASKS_CREATE_TASK, {
            "tasklist_id": tasklist_id,
            "title": f"low: {item['id']}",
        })

Two destinations, one branch per item, every item gets somewhere.

And if/else is from Python Foundations?

What about three branches?

Conditional routing — branching on data

The shape

python

for item in items:
    if predicate(item):
        path_a(item)
    else:
        path_b(item)

Every item exits to exactly one of path_a or path_b. No item is skipped, no item is double-processed.

Routing vs filtering vs partitioning

Three similar-looking patterns; pick the right one:

Pattern	Shape	Example
Filter	act on some, skip others	`if x > 10: send(x)` (no else)
Routing	every item → A or B	`if x > 10: send(x) else log(x)`
Partition	split into two lists, then act on each	`bigs = [x for x in xs if x > 10]; smalls = [...]`

Day 5 covers partition; today and yesterday cover the simpler shapes.

Counting per branch

In a routing loop, two counters tell you what happened:

python

a_count = 0
b_count = 0
for item in items:
    if item["value"] > 10:
        path_a(item)
        a_count += 1
    else:
        path_b(item)
        b_count += 1

print(f"path_a: {a_count}, path_b: {b_count}")

One extra line per branch; the closing report tells you the routing was sane (5 of 10 high, 5 of 10 low) without re-reading the items.

Predicate complexity

The if predicate can be as simple as item["value"] > 10 or as complex as a function:

python

def is_urgent(item):
    return item.get("priority") == "high" or item.get("due_in_hours", 999) < 24

for item in items:
    if is_urgent(item):
        ...

Extract the predicate into a function once it has 2+ conditions. The branch reads as English ("if urgent, send alert") instead of three nested and/or.

Three or more branches

python

for item in items:
    if item["value"] > 100:
        critical_path(item)
    elif item["value"] > 10:
        normal_path(item)
    else:
        low_path(item)

Readable up to ~3 branches. Beyond that, switch to a dispatch dict — covered in week 4.

Conditional routing — branching on data

The shape

Routing vs filtering vs partitioning

Counting per branch

Predicate complexity

Three or more branches

Conditional routing — branching on data

The shape

Routing vs filtering vs partitioning

Counting per branch

Predicate complexity

Three or more branches

Conditional routing — branching on data

The shape

Routing vs filtering vs partitioning

Counting per branch

Predicate complexity

Three or more branches

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Conditional routing — branching on data

The shape

Routing vs filtering vs partitioning

Counting per branch

Predicate complexity

Three or more branches

Sign up to practice