headroom/tests/test_pricing.py
Garm efd2ac1ca4 chore: renormalize line endings to LF
`.gitattributes` declares `*.py text eol=lf` and `*.sh text eol=lf`, but
74 files (73 .py, 1 .sh) are stored in the index with CRLF line endings,
violating that contract. Every macOS/Linux clone reports these files as
"modified" on fresh checkout because git's diff engine sees the stored
bytes don't match the attribute contract, even though the working tree
and index match byte-for-byte.

Running `git add --renormalize .` rewrites each affected blob so the
stored form matches the attribute declaration. No semantic changes —
every affected file's diff is "N insertions, N deletions" with inserts
and deletes being the same lines modulo line endings.

Follow-up commit adds `.git-blame-ignore-revs` so `git blame` / GitHub
blame skip this mechanical commit.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-24 15:33:30 +02:00

130 lines
4.8 KiB
Python

from __future__ import annotations
from dataclasses import FrozenInstanceError
from datetime import date, timedelta
import pytest
import headroom.pricing as pricing
from headroom.pricing.anthropic_prices import ANTHROPIC_PRICES, get_anthropic_registry
from headroom.pricing.openai_prices import OPENAI_PRICES, get_openai_registry
from headroom.pricing.registry import ModelPricing, PricingRegistry
def test_pricing_public_exports_and_provider_registries() -> None:
assert pricing.ModelPricing is ModelPricing
assert pricing.PricingRegistry is PricingRegistry
assert "get_openai_registry" in pricing.__all__
assert "get_anthropic_registry" in pricing.__all__
assert "estimate_cost" in pricing.__all__
openai_registry = get_openai_registry()
anthropic_registry = get_anthropic_registry()
assert openai_registry.source_url == "https://openai.com/api/pricing/"
assert anthropic_registry.source_url == "https://www.anthropic.com/pricing"
assert openai_registry.prices["gpt-4o"] == OPENAI_PRICES["gpt-4o"]
assert (
anthropic_registry.prices["claude-3-5-sonnet-20241022"]
== ANTHROPIC_PRICES["claude-3-5-sonnet-20241022"]
)
openai_registry.prices.pop("gpt-4o")
anthropic_registry.prices.pop("claude-3-5-sonnet-20241022")
assert "gpt-4o" in OPENAI_PRICES
assert "claude-3-5-sonnet-20241022" in ANTHROPIC_PRICES
def test_model_pricing_is_frozen() -> None:
model = ModelPricing(model="demo", provider="test", input_per_1m=1.5, output_per_1m=2.5)
with pytest.raises(FrozenInstanceError):
model.model = "other" # type: ignore[misc]
def test_registry_staleness_and_warning() -> None:
fresh = PricingRegistry(last_updated=date.today() - timedelta(days=30))
assert fresh.is_stale() is False
assert fresh.staleness_warning() is None
stale = PricingRegistry(
last_updated=date.today() - timedelta(days=31),
source_url="https://example.test/pricing",
)
assert stale.is_stale() is True
assert stale.staleness_warning() == (
f"Pricing data is 31 days old (last updated: {stale.last_updated})."
" Please verify at: https://example.test/pricing"
)
def test_registry_estimate_cost_with_all_token_types() -> None:
registry = PricingRegistry(
last_updated=date.today() - timedelta(days=31),
prices={
"demo": ModelPricing(
model="demo",
provider="test",
input_per_1m=2.0,
output_per_1m=4.0,
cached_input_per_1m=1.0,
batch_input_per_1m=0.5,
batch_output_per_1m=0.25,
)
},
)
estimate = registry.estimate_cost(
"demo",
input_tokens=1_000_000,
output_tokens=500_000,
cached_input_tokens=250_000,
batch_input_tokens=200_000,
batch_output_tokens=100_000,
)
assert estimate.cost_usd == pytest.approx(4.375)
assert estimate.breakdown == {
"input": {"tokens": 1_000_000, "rate_per_1m": 2.0, "cost_usd": 2.0},
"output": {"tokens": 500_000, "rate_per_1m": 4.0, "cost_usd": 2.0},
"cached_input": {"tokens": 250_000, "rate_per_1m": 1.0, "cost_usd": 0.25},
"batch_input": {"tokens": 200_000, "rate_per_1m": 0.5, "cost_usd": 0.1},
"batch_output": {"tokens": 100_000, "rate_per_1m": 0.25, "cost_usd": 0.025},
}
assert estimate.pricing_date == registry.last_updated
assert estimate.is_stale is True
assert estimate.warning == (
f"Pricing data is 31 days old (last updated: {registry.last_updated})."
)
def test_registry_estimate_cost_zero_usage_returns_empty_breakdown() -> None:
registry = PricingRegistry(
last_updated=date.today(),
prices={
"demo": ModelPricing(model="demo", provider="test", input_per_1m=1.0, output_per_1m=2.0)
},
)
estimate = registry.estimate_cost("demo")
assert estimate.cost_usd == 0.0
assert estimate.breakdown == {}
assert estimate.is_stale is False
assert estimate.warning is None
@pytest.mark.parametrize(
("kwargs", "message"),
[
({}, "Model 'missing' not found in registry"),
({"cached_input_tokens": 1}, "Model 'demo' does not have cached input pricing"),
({"batch_input_tokens": 1}, "Model 'demo' does not have batch input pricing"),
({"batch_output_tokens": 1}, "Model 'demo' does not have batch output pricing"),
],
)
def test_registry_estimate_cost_error_paths(kwargs: dict[str, int], message: str) -> None:
registry = PricingRegistry(
last_updated=date.today(),
prices={
"demo": ModelPricing(model="demo", provider="test", input_per_1m=1.0, output_per_1m=2.0)
},
)
with pytest.raises(ValueError, match=message):
registry.estimate_cost("missing" if not kwargs else "demo", **kwargs)