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import math
import sqlite3
import pytest
from server.reward import (
_bin_progress,
_cardinality_score,
_layer1_operational,
_layer2_progress,
_numeric_range_score,
_value_overlap_score,
compute_step_reward,
)
from sql_env.models import EpisodeContext, QuestionRecord
def _build_question_record() -> QuestionRecord:
return QuestionRecord(
question_id="q-episode-context",
question_text="How many students are there?",
database_name="student_assessment",
gold_sql="SELECT COUNT(*) FROM students",
gold_answer="0",
answer_type="integer",
difficulty="easy",
tables_involved=["students"],
)
def _build_episode_context(**kwargs: object) -> EpisodeContext:
return EpisodeContext(
episode_id="ep-episode-context",
db_connection=sqlite3.connect(":memory:"),
question_record=_build_question_record(),
**kwargs,
)
class TestLayer1Operational:
def test_layer1_successful_query(self) -> None:
context = _build_episode_context()
try:
reward = _layer1_operational(
context,
action_type="QUERY",
sql="SELECT 1",
rows=[(1,)],
error=None,
)
assert reward == 0.025
finally:
context.db_connection.close()
def test_layer1_successful_describe(self) -> None:
context = _build_episode_context()
try:
reward = _layer1_operational(
context,
action_type="DESCRIBE",
sql="DESCRIBE students",
rows=[("id", "INTEGER")],
error=None,
)
assert reward == 0.015
finally:
context.db_connection.close()
def test_layer1_successful_sample(self) -> None:
context = _build_episode_context()
try:
reward = _layer1_operational(
context,
action_type="SAMPLE",
sql="SELECT * FROM students LIMIT 5",
rows=[(1,)],
error=None,
)
assert reward == 0.015
finally:
context.db_connection.close()
def test_layer1_error_query(self) -> None:
context = _build_episode_context()
try:
reward = _layer1_operational(
context,
action_type="QUERY",
sql="SELECT missing FROM students",
rows=None,
error="no such column",
)
assert reward == -0.005
finally:
context.db_connection.close()
def test_layer1_new_info_no_cap(self) -> None:
"""New info is awarded per unique query with no cumulative cap."""
context = _build_episode_context()
try:
total = 0.0
for idx in range(15):
r = _layer1_operational(
context,
action_type="QUERY",
sql=f"SELECT {idx}",
rows=[(idx,)],
error=None,
)
total += r
# 15 unique queries: exec_ok(0.02) + new_info(0.01) - cost(0.005)
assert total == pytest.approx(15 * 0.025)
finally:
context.db_connection.close()
def test_layer1_repeat_penalty(self) -> None:
context = _build_episode_context()
try:
_layer1_operational(
context,
action_type="QUERY",
sql="SELECT 1",
rows=[(1,)],
error=None,
)
reward = _layer1_operational(
context,
action_type="QUERY",
sql="SELECT 1",
rows=[(1,)],
error=None,
)
assert reward == -0.015
finally:
context.db_connection.close()
def test_layer1_repeat_no_exec_ok(self) -> None:
context = _build_episode_context()
try:
_layer1_operational(
context,
action_type="QUERY",
sql="SELECT 2",
rows=[(2,)],
error=None,
)
reward = _layer1_operational(
context,
action_type="QUERY",
sql="SELECT 2",
rows=[(2,)],
error=None,
)
assert reward <= -0.005
assert reward == -0.015
finally:
context.db_connection.close()
def test_layer1_step_cost_always_applied(self) -> None:
context = _build_episode_context()
try:
reward_success = _layer1_operational(
context,
action_type="SAMPLE",
sql="SELECT * FROM students LIMIT 1",
rows=[(1,)],
error=None,
)
reward_error = _layer1_operational(
context,
action_type="QUERY",
sql="SELECT bad",
rows=None,
error="bad query",
)
assert reward_success < 0.02
assert reward_error == -0.005
finally:
context.db_connection.close()
class TestCardinalityScore:
def test_cardinality_exact_match(self) -> None:
assert _cardinality_score([(1,), (2,)], [(3,), (4,)]) == 1.0
def test_cardinality_zero_pred(self) -> None:
assert _cardinality_score([], [(1,)]) == 0.0
def test_cardinality_zero_gold(self) -> None:
assert _cardinality_score([(1,)], []) == 0.0
def test_cardinality_both_empty(self) -> None:
assert _cardinality_score([], []) == 1.0
def test_cardinality_pred_larger(self) -> None:
pred_rows = [(idx,) for idx in range(10)]
assert _cardinality_score(pred_rows, [(1,)]) == pytest.approx(0.1)
def test_cardinality_gold_larger(self) -> None:
gold_rows = [(idx,) for idx in range(4)]
assert _cardinality_score([(1,)], gold_rows) == 0.25
def test_cardinality_returns_float_in_range(self) -> None:
score = _cardinality_score([(1,), (2,)], [(1,)])
assert 0.0 <= score <= 1.0
class TestValueOverlapScore:
def test_value_overlap_identical(self) -> None:
assert _value_overlap_score([(1, "a")], [(1, "a")]) == 1.0
def test_value_overlap_disjoint(self) -> None:
assert _value_overlap_score([(1, "x")], [(2, "y")]) == 0.0
def test_value_overlap_partial(self) -> None:
score = _value_overlap_score([(1, "a"), (2, "b")], [(1, "a"), (3, "c")])
assert score == pytest.approx(2 / 6)
def test_value_overlap_empty_pred(self) -> None:
assert _value_overlap_score([], [(1,)]) == 0.0
def test_value_overlap_empty_gold(self) -> None:
assert _value_overlap_score([(1,)], []) == 0.0
def test_value_overlap_both_empty(self) -> None:
assert _value_overlap_score([], []) == 0.0
def test_value_overlap_stringifies_values(self) -> None:
score = _value_overlap_score([(1, 2.5, None)], [(1, 2.5, None)])
assert score == 1.0
def test_value_overlap_returns_float_in_range(self) -> None:
score = _value_overlap_score([(1, "a")], [(1, "b")])
assert 0.0 <= score <= 1.0
class TestNumericRangeScore:
def test_numeric_range_identical(self) -> None:
assert _numeric_range_score([(10,)], [(10,)]) == 1.0
def test_numeric_range_no_numerics_in_gold(self) -> None:
assert _numeric_range_score([("a",)], [("b",)]) == 1.0
def test_numeric_range_close_values(self) -> None:
score = _numeric_range_score([(11,)], [(10,)])
assert score > 0.5
assert score < 1.0
def test_numeric_range_far_values(self) -> None:
score = _numeric_range_score([(1000000,)], [(1,)])
assert score < 0.1
def test_numeric_range_zero_distance(self) -> None:
assert _numeric_range_score([(0,)], [(0,)]) == 1.0
def test_numeric_range_negative_numbers(self) -> None:
expected = 1.0 / (1.0 + math.log1p(10.0))
score = _numeric_range_score([(-5,)], [(5,)])
assert score == expected
def test_numeric_range_mixed_types(self) -> None:
assert _numeric_range_score([(10, "a")], [(10, "b")]) == 1.0
def test_numeric_range_empty_pred(self) -> None:
assert _numeric_range_score([], [(1,)]) == 0.0
def test_numeric_range_returns_float_in_range(self) -> None:
score = _numeric_range_score([(5,), (10,)], [(7,)])
assert 0.0 <= score <= 1.0
class TestBinProgress:
def test_bin_progress_zero(self) -> None:
assert _bin_progress(0.0) == 0.0
def test_bin_progress_low(self) -> None:
assert _bin_progress(0.124) == 0.0
def test_bin_progress_boundary_0125(self) -> None:
assert _bin_progress(0.125) == 0.25
def test_bin_progress_mid_low(self) -> None:
assert _bin_progress(0.3) == 0.25
def test_bin_progress_boundary_0375(self) -> None:
assert _bin_progress(0.375) == 0.5
def test_bin_progress_mid(self) -> None:
assert _bin_progress(0.5) == 0.5
def test_bin_progress_boundary_0625(self) -> None:
assert _bin_progress(0.625) == 0.75
def test_bin_progress_mid_high(self) -> None:
assert _bin_progress(0.7) == 0.75
def test_bin_progress_boundary_0875(self) -> None:
assert _bin_progress(0.875) == 1.0
def test_bin_progress_one(self) -> None:
assert _bin_progress(1.0) == 1.0
class TestLayer2Progress:
def test_layer2_perfect_match(self) -> None:
context = _build_episode_context(gold_rows=[(1, "a", 10)])
try:
reward = _layer2_progress(context, rows=[(1, "a", 10)])
assert reward == pytest.approx(0.15)
assert context.previous_progress == 1.0
finally:
context.db_connection.close()
def test_layer2_no_change(self) -> None:
context = _build_episode_context(gold_rows=[(1, "a", 10)])
try:
_layer2_progress(context, rows=[(1, "a", 10)])
reward = _layer2_progress(context, rows=[(1, "a", 10)])
assert reward == 0.0
assert context.previous_progress == 1.0
finally:
context.db_connection.close()
def test_layer2_improvement(self) -> None:
context = _build_episode_context(gold_rows=[(1,), (2,), (3,), (4,)])
try:
first_reward = _layer2_progress(context, rows=[(1,)])
assert first_reward == pytest.approx(0.0375)
assert context.previous_progress == 0.25
second_reward = _layer2_progress(context, rows=[(1,), (2,), (3,), (4,)])
assert second_reward == pytest.approx(0.1125)
assert context.previous_progress == 1.0
finally:
context.db_connection.close()
def test_layer2_regression_penalized(self) -> None:
"""Delta-based: regression yields negative reward."""
context = _build_episode_context(gold_rows=[(1, "a", 10)])
try:
_layer2_progress(context, rows=[(1, "a", 10)])
assert context.previous_progress == 1.0
reward = _layer2_progress(context, rows=[])
assert reward < 0.0
assert context.previous_progress == 0.0
finally:
context.db_connection.close()
def test_layer2_recovery_rewarded(self) -> None:
"""Delta-based: recovery after regression IS rewarded."""
context = _build_episode_context(gold_rows=[(1, "a", 10)])
try:
_layer2_progress(context, rows=[(1, "a", 10)]) # -> 1.0
_layer2_progress(context, rows=[]) # -> 0.0 (regression)
reward = _layer2_progress(context, rows=[(1, "a", 10)]) # -> 1.0 (recovery)
assert reward == pytest.approx(0.15)
assert context.previous_progress == 1.0
finally:
context.db_connection.close()
def test_layer2_empty_gold_rows(self) -> None:
context = _build_episode_context(gold_rows=[])
try:
reward = _layer2_progress(context, rows=[(1,)])
assert reward == 0.0
assert context.previous_progress == 0.0
finally:
context.db_connection.close()
def test_layer2_weighted_average(self) -> None:
context = _build_episode_context(gold_rows=[(10,), (20,)])
try:
reward = _layer2_progress(context, rows=[(10,), (1000,)])
assert reward == pytest.approx(0.075)
assert context.previous_progress == 0.5
finally:
context.db_connection.close()
def test_layer2_updates_previous_progress(self) -> None:
context = _build_episode_context(gold_rows=[(1,), (2,), (3,), (4,)])
try:
assert context.previous_progress == 0.0
_layer2_progress(context, rows=[(1,), (2,), (3,), (4,)])
assert context.previous_progress == 1.0
finally:
context.db_connection.close()
class TestComputeStepReward:
def test_compute_reward_query_success(self) -> None:
context = _build_episode_context(gold_rows=[(10,), (20,)])
try:
reward = compute_step_reward(
context,
action_type="QUERY",
sql="SELECT value FROM t",
rows=[(10,), (1000,)],
error=None,
)
assert reward == pytest.approx(0.1)
finally:
context.db_connection.close()
def test_compute_reward_query_error(self) -> None:
context = _build_episode_context(gold_rows=[(1,)])
try:
reward = compute_step_reward(
context,
action_type="QUERY",
sql="SELECT missing",
rows=None,
error="no such column",
)
assert reward == -0.005
finally:
context.db_connection.close()
def test_compute_reward_describe(self) -> None:
context = _build_episode_context(gold_rows=[(1,)])
try:
reward = compute_step_reward(
context,
action_type="DESCRIBE",
sql="DESCRIBE students",
rows=[("id", "INTEGER")],
error=None,
)
assert reward == 0.015
assert context.previous_progress == 0.0
finally:
context.db_connection.close()
def test_compute_reward_sample(self) -> None:
context = _build_episode_context(gold_rows=[(1,)])
try:
reward = compute_step_reward(
context,
action_type="SAMPLE",
sql="SELECT * FROM students LIMIT 1",
rows=[(1,)],
error=None,
)
assert reward == 0.015
assert context.previous_progress == 0.0
finally:
context.db_connection.close()
def test_compute_reward_per_step_cap(self) -> None:
"""Per-step clipping caps at 0.15."""
context = _build_episode_context(gold_rows=[(1, "a", 10)])
try:
reward = compute_step_reward(
context,
action_type="QUERY",
sql="SELECT 1, 'a', 10",
rows=[(1, "a", 10)],
error=None,
)
assert reward <= 0.15
finally:
context.db_connection.close()
def test_compute_reward_per_step_floor(self) -> None:
"""Per-step clipping floors at -0.05."""
context = _build_episode_context(gold_rows=[(1, "a", 10)])
try:
# First get to high progress
compute_step_reward(
context,
action_type="QUERY",
sql="SELECT 1, 'a', 10",
rows=[(1, "a", 10)],
error=None,
)
# Then regress badly (repeat + regression)
reward = compute_step_reward(
context,
action_type="QUERY",
sql="SELECT 1, 'a', 10",
rows=[(1, "a", 10)],
error=None,
)
assert reward >= -0.05
finally:
context.db_connection.close()
def test_compute_reward_no_cumulative_tracking(self) -> None:
"""Each step is independent — no cumulative state."""
context = _build_episode_context(gold_rows=[(1,)])
try:
assert not hasattr(context, "cumulative_step_reward")
finally:
context.db_connection.close()
def test_compute_reward_layer2_skipped_for_describe(self) -> None:
context = _build_episode_context(gold_rows=[(1,), (2,)])
try:
compute_step_reward(
context,
action_type="DESCRIBE",
sql="DESCRIBE students",
rows=[("id", "INTEGER")],
error=None,
)
assert context.previous_progress == 0.0
finally:
context.db_connection.close()
def test_compute_reward_layer2_skipped_when_rows_none(self) -> None:
context = _build_episode_context(gold_rows=[(1,), (2,)])
try:
compute_step_reward(
context,
action_type="QUERY",
sql="SELECT missing",
rows=None,
error="no such column",
)
assert context.previous_progress == 0.0
finally:
context.db_connection.close()
def test_compute_reward_layer2_skipped_empty_gold(self) -> None:
context = _build_episode_context(gold_rows=[])
try:
reward = compute_step_reward(
context,
action_type="QUERY",
sql="SELECT 1",
rows=[(1,)],
error=None,
)
assert reward == 0.025
assert context.previous_progress == 0.0
finally:
context.db_connection.close()
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