fix(backend): supprime les vulnerabilites Sonar du Dockerfile et allege les tests d'exception
This commit is contained in:
@@ -11,13 +11,14 @@ WORKDIR /app
|
||||
RUN --mount=type=cache,target=/root/.cache/uv \
|
||||
--mount=type=bind,source=uv.lock,target=uv.lock \
|
||||
--mount=type=bind,source=pyproject.toml,target=pyproject.toml \
|
||||
uv sync --locked --no-install-project --no-dev
|
||||
uv sync --locked --no-install-project --no-dev --no-build
|
||||
|
||||
# Le projet lui-meme n'est pas installe (pas de second `uv sync`) : il tourne depuis /app, le
|
||||
# repertoire de travail, et rien ne lit ses metadonnees. L'installer imposerait de le construire
|
||||
# (backend hatchling), donc de retirer `--no-build` de l'etape ci-dessus, qui garantit que
|
||||
# l'installation des dependances n'execute aucun script de build (regle Sonar docker:S8541).
|
||||
COPY . /app
|
||||
|
||||
RUN --mount=type=cache,target=/root/.cache/uv \
|
||||
uv sync --locked --no-dev
|
||||
|
||||
|
||||
FROM python:3.14-slim AS runtime
|
||||
|
||||
|
||||
@@ -112,8 +112,10 @@ async def test_duplicate_reading_is_rejected_when_key_matches(
|
||||
)
|
||||
await data_connection.execute(statement)
|
||||
|
||||
savepoint = data_connection.begin_nested()
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
async with data_connection.begin_nested():
|
||||
async with savepoint:
|
||||
await data_connection.execute(statement)
|
||||
|
||||
|
||||
@@ -147,9 +149,12 @@ async def test_invalid_reading_is_rejected_when_constraints_fail(
|
||||
}
|
||||
values.update(changes)
|
||||
|
||||
statement = insert(Reading).values(**values)
|
||||
savepoint = data_connection.begin_nested()
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
async with data_connection.begin_nested():
|
||||
await data_connection.execute(insert(Reading).values(**values))
|
||||
async with savepoint:
|
||||
await data_connection.execute(statement)
|
||||
|
||||
|
||||
async def test_prediction_requires_period_when_energy_is_predicted(
|
||||
@@ -164,8 +169,10 @@ async def test_prediction_requires_period_when_energy_is_predicted(
|
||||
model_reference="test-model/1",
|
||||
)
|
||||
|
||||
savepoint = data_connection.begin_nested()
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
async with data_connection.begin_nested():
|
||||
async with savepoint:
|
||||
await data_connection.execute(statement)
|
||||
|
||||
|
||||
@@ -212,21 +219,22 @@ async def test_alert_rejects_prediction_when_site_differs(
|
||||
)
|
||||
).scalar_one()
|
||||
|
||||
statement = insert(Alert).values(
|
||||
source_alert_id=str(uuid4()),
|
||||
site_id=other_site,
|
||||
source="enervision",
|
||||
timestamp=MOMENT,
|
||||
type="spike",
|
||||
severity="high",
|
||||
message="Test",
|
||||
prediction_id=prediction_id,
|
||||
raw_data={},
|
||||
)
|
||||
savepoint = data_connection.begin_nested()
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
async with data_connection.begin_nested():
|
||||
await data_connection.execute(
|
||||
insert(Alert).values(
|
||||
source_alert_id=str(uuid4()),
|
||||
site_id=other_site,
|
||||
source="enervision",
|
||||
timestamp=MOMENT,
|
||||
type="spike",
|
||||
severity="high",
|
||||
message="Test",
|
||||
prediction_id=prediction_id,
|
||||
raw_data={},
|
||||
)
|
||||
)
|
||||
async with savepoint:
|
||||
await data_connection.execute(statement)
|
||||
|
||||
|
||||
async def test_recommendation_is_unique_when_alert_and_rule_match(
|
||||
@@ -256,6 +264,8 @@ async def test_recommendation_is_unique_when_alert_and_rule_match(
|
||||
)
|
||||
await data_connection.execute(statement)
|
||||
|
||||
savepoint = data_connection.begin_nested()
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
async with data_connection.begin_nested():
|
||||
async with savepoint:
|
||||
await data_connection.execute(statement)
|
||||
|
||||
@@ -1,239 +1,245 @@
|
||||
import hashlib
|
||||
import json
|
||||
|
||||
import pandas as pd
|
||||
import pytest
|
||||
|
||||
from app.etl.historical_import import (
|
||||
SOURCE_NAME,
|
||||
build_reading_batch,
|
||||
classify_quality,
|
||||
compute_sha256,
|
||||
load_metadata,
|
||||
normalize_timestamps,
|
||||
validate_source,
|
||||
)
|
||||
|
||||
|
||||
def make_metadata() -> dict:
|
||||
return {
|
||||
"total_records": 2,
|
||||
"sites": {
|
||||
"SITE001": {},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def make_dataframe() -> pd.DataFrame:
|
||||
return pd.DataFrame(
|
||||
[
|
||||
{
|
||||
"timestamp": "2023-01-01 00:00:00",
|
||||
"site_id": "SITE001",
|
||||
"site_type": "office",
|
||||
"site_name": "Site 1",
|
||||
"consumption_kwh": 10.5,
|
||||
"consumption_euros": 2.5,
|
||||
"temperature_celsius": 20.0,
|
||||
"humidity_percent": 50.0,
|
||||
"solar_irradiance_wm2": 0.0,
|
||||
"hour": 0,
|
||||
"day_of_week": 6,
|
||||
"day_name": "Sunday",
|
||||
"month": 1,
|
||||
"is_weekend": True,
|
||||
"is_working_hours": False,
|
||||
},
|
||||
{
|
||||
"timestamp": "2023-01-01 01:00:00",
|
||||
"site_id": "SITE001",
|
||||
"site_type": "office",
|
||||
"site_name": "Site 1",
|
||||
"consumption_kwh": 11.0,
|
||||
"consumption_euros": 2.7,
|
||||
"temperature_celsius": 19.5,
|
||||
"humidity_percent": 52.0,
|
||||
"solar_irradiance_wm2": 0.0,
|
||||
"hour": 1,
|
||||
"day_of_week": 6,
|
||||
"day_name": "Sunday",
|
||||
"month": 1,
|
||||
"is_weekend": True,
|
||||
"is_working_hours": False,
|
||||
},
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
def test_compute_sha256(tmp_path):
|
||||
file_path = tmp_path / "dataset.csv"
|
||||
content = b"hello-enervision"
|
||||
|
||||
file_path.write_bytes(content)
|
||||
|
||||
expected = hashlib.sha256(content).hexdigest()
|
||||
|
||||
assert compute_sha256(file_path) == expected
|
||||
|
||||
|
||||
def test_load_metadata(tmp_path):
|
||||
metadata_path = tmp_path / "metadata.json"
|
||||
|
||||
metadata = {
|
||||
"total_records": 2,
|
||||
"sites": {
|
||||
"SITE001": {},
|
||||
},
|
||||
}
|
||||
|
||||
metadata_path.write_text(
|
||||
json.dumps(metadata),
|
||||
encoding="utf-8",
|
||||
)
|
||||
|
||||
assert load_metadata(metadata_path) == metadata
|
||||
|
||||
|
||||
def test_validate_source_accepts_valid_dataset():
|
||||
frame = make_dataframe()
|
||||
|
||||
validate_source(
|
||||
frame,
|
||||
make_metadata(),
|
||||
)
|
||||
|
||||
|
||||
def test_validate_source_rejects_missing_column():
|
||||
frame = make_dataframe().drop(columns=["consumption_kwh"])
|
||||
|
||||
with pytest.raises(
|
||||
ValueError,
|
||||
match="Colonnes obligatoires absentes",
|
||||
):
|
||||
validate_source(
|
||||
frame,
|
||||
make_metadata(),
|
||||
)
|
||||
|
||||
|
||||
def test_validate_source_rejects_duplicates():
|
||||
frame = make_dataframe()
|
||||
|
||||
frame.loc[1, "timestamp"] = frame.loc[
|
||||
0,
|
||||
"timestamp",
|
||||
]
|
||||
|
||||
with pytest.raises(
|
||||
ValueError,
|
||||
match="doublons",
|
||||
):
|
||||
validate_source(
|
||||
frame,
|
||||
make_metadata(),
|
||||
)
|
||||
|
||||
|
||||
def test_validate_source_rejects_unknown_site():
|
||||
frame = make_dataframe()
|
||||
|
||||
frame.loc[1, "site_id"] = "SITE999"
|
||||
|
||||
with pytest.raises(
|
||||
ValueError,
|
||||
match="Sites incohérents",
|
||||
):
|
||||
validate_source(
|
||||
frame,
|
||||
make_metadata(),
|
||||
)
|
||||
|
||||
|
||||
def test_normalize_timestamps_adds_timezone():
|
||||
frame = make_dataframe()
|
||||
|
||||
normalized = normalize_timestamps(
|
||||
frame,
|
||||
"UTC",
|
||||
)
|
||||
|
||||
assert normalized["timestamp"].dt.tz is not None
|
||||
|
||||
assert "_source_timestamp" in normalized.columns
|
||||
|
||||
|
||||
def test_classify_quality_good():
|
||||
row = make_dataframe().iloc[0].to_dict()
|
||||
|
||||
quality, reasons = classify_quality(row)
|
||||
|
||||
assert quality == "good"
|
||||
assert reasons == []
|
||||
|
||||
|
||||
def test_classify_quality_degraded_when_consumption_missing():
|
||||
row = make_dataframe().iloc[0].to_dict()
|
||||
row["consumption_kwh"] = None
|
||||
|
||||
quality, reasons = classify_quality(row)
|
||||
|
||||
assert quality == "degraded"
|
||||
|
||||
assert "missing:consumption_kwh" in reasons
|
||||
|
||||
|
||||
def test_build_reading_batch_respects_database_contract():
|
||||
frame = normalize_timestamps(
|
||||
make_dataframe(),
|
||||
"UTC",
|
||||
)
|
||||
|
||||
rows = build_reading_batch(
|
||||
frame.iloc[:1],
|
||||
dataset_id=3,
|
||||
)
|
||||
|
||||
assert len(rows) == 1
|
||||
|
||||
row = rows[0]
|
||||
|
||||
assert row["dataset_id"] == 3
|
||||
|
||||
# Important :
|
||||
# contrainte ck_reading_dataset_source.
|
||||
assert row["source"] == "csv"
|
||||
assert SOURCE_NAME == "csv"
|
||||
|
||||
# Important :
|
||||
# contrainte ck_reading_imputation.
|
||||
assert row["imputed_values"] is None
|
||||
assert row["imputation_method"] is None
|
||||
|
||||
assert row["data_quality"] == "good"
|
||||
assert row["null_reasons"] == []
|
||||
|
||||
|
||||
def test_build_reading_batch_keeps_missing_values():
|
||||
frame = make_dataframe()
|
||||
|
||||
frame.loc[0, "temperature_celsius"] = None
|
||||
|
||||
frame = normalize_timestamps(
|
||||
frame,
|
||||
"UTC",
|
||||
)
|
||||
|
||||
rows = build_reading_batch(
|
||||
frame.iloc[:1],
|
||||
dataset_id=3,
|
||||
)
|
||||
|
||||
row = rows[0]
|
||||
|
||||
assert row["temperature_celsius"] is None
|
||||
|
||||
assert "missing:temperature_celsius" in row["null_reasons"]
|
||||
|
||||
# RAW ingestion : aucune imputation.
|
||||
assert row["imputed_values"] is None
|
||||
assert row["imputation_method"] is None
|
||||
import hashlib
|
||||
import json
|
||||
|
||||
import pandas as pd
|
||||
import pytest
|
||||
|
||||
from app.etl.historical_import import (
|
||||
SOURCE_NAME,
|
||||
build_reading_batch,
|
||||
classify_quality,
|
||||
compute_sha256,
|
||||
load_metadata,
|
||||
normalize_timestamps,
|
||||
validate_source,
|
||||
)
|
||||
|
||||
|
||||
def make_metadata() -> dict:
|
||||
return {
|
||||
"total_records": 2,
|
||||
"sites": {
|
||||
"SITE001": {},
|
||||
},
|
||||
}
|
||||
|
||||
|
||||
def make_dataframe() -> pd.DataFrame:
|
||||
return pd.DataFrame(
|
||||
[
|
||||
{
|
||||
"timestamp": "2023-01-01 00:00:00",
|
||||
"site_id": "SITE001",
|
||||
"site_type": "office",
|
||||
"site_name": "Site 1",
|
||||
"consumption_kwh": 10.5,
|
||||
"consumption_euros": 2.5,
|
||||
"temperature_celsius": 20.0,
|
||||
"humidity_percent": 50.0,
|
||||
"solar_irradiance_wm2": 0.0,
|
||||
"hour": 0,
|
||||
"day_of_week": 6,
|
||||
"day_name": "Sunday",
|
||||
"month": 1,
|
||||
"is_weekend": True,
|
||||
"is_working_hours": False,
|
||||
},
|
||||
{
|
||||
"timestamp": "2023-01-01 01:00:00",
|
||||
"site_id": "SITE001",
|
||||
"site_type": "office",
|
||||
"site_name": "Site 1",
|
||||
"consumption_kwh": 11.0,
|
||||
"consumption_euros": 2.7,
|
||||
"temperature_celsius": 19.5,
|
||||
"humidity_percent": 52.0,
|
||||
"solar_irradiance_wm2": 0.0,
|
||||
"hour": 1,
|
||||
"day_of_week": 6,
|
||||
"day_name": "Sunday",
|
||||
"month": 1,
|
||||
"is_weekend": True,
|
||||
"is_working_hours": False,
|
||||
},
|
||||
]
|
||||
)
|
||||
|
||||
|
||||
def test_compute_sha256(tmp_path):
|
||||
file_path = tmp_path / "dataset.csv"
|
||||
content = b"hello-enervision"
|
||||
|
||||
file_path.write_bytes(content)
|
||||
|
||||
expected = hashlib.sha256(content).hexdigest()
|
||||
|
||||
assert compute_sha256(file_path) == expected
|
||||
|
||||
|
||||
def test_load_metadata(tmp_path):
|
||||
metadata_path = tmp_path / "metadata.json"
|
||||
|
||||
metadata = {
|
||||
"total_records": 2,
|
||||
"sites": {
|
||||
"SITE001": {},
|
||||
},
|
||||
}
|
||||
|
||||
metadata_path.write_text(
|
||||
json.dumps(metadata),
|
||||
encoding="utf-8",
|
||||
)
|
||||
|
||||
assert load_metadata(metadata_path) == metadata
|
||||
|
||||
|
||||
def test_validate_source_accepts_valid_dataset():
|
||||
frame = make_dataframe()
|
||||
|
||||
validate_source(
|
||||
frame,
|
||||
make_metadata(),
|
||||
)
|
||||
|
||||
|
||||
def test_validate_source_rejects_missing_column():
|
||||
frame = make_dataframe().drop(columns=["consumption_kwh"])
|
||||
|
||||
metadata = make_metadata()
|
||||
|
||||
with pytest.raises(
|
||||
ValueError,
|
||||
match="Colonnes obligatoires absentes",
|
||||
):
|
||||
validate_source(
|
||||
frame,
|
||||
metadata,
|
||||
)
|
||||
|
||||
|
||||
def test_validate_source_rejects_duplicates():
|
||||
frame = make_dataframe()
|
||||
|
||||
frame.loc[1, "timestamp"] = frame.loc[
|
||||
0,
|
||||
"timestamp",
|
||||
]
|
||||
|
||||
metadata = make_metadata()
|
||||
|
||||
with pytest.raises(
|
||||
ValueError,
|
||||
match="doublons",
|
||||
):
|
||||
validate_source(
|
||||
frame,
|
||||
metadata,
|
||||
)
|
||||
|
||||
|
||||
def test_validate_source_rejects_unknown_site():
|
||||
frame = make_dataframe()
|
||||
|
||||
frame.loc[1, "site_id"] = "SITE999"
|
||||
|
||||
metadata = make_metadata()
|
||||
|
||||
with pytest.raises(
|
||||
ValueError,
|
||||
match="Sites incohérents",
|
||||
):
|
||||
validate_source(
|
||||
frame,
|
||||
metadata,
|
||||
)
|
||||
|
||||
|
||||
def test_normalize_timestamps_adds_timezone():
|
||||
frame = make_dataframe()
|
||||
|
||||
normalized = normalize_timestamps(
|
||||
frame,
|
||||
"UTC",
|
||||
)
|
||||
|
||||
assert normalized["timestamp"].dt.tz is not None
|
||||
|
||||
assert "_source_timestamp" in normalized.columns
|
||||
|
||||
|
||||
def test_classify_quality_good():
|
||||
row = make_dataframe().iloc[0].to_dict()
|
||||
|
||||
quality, reasons = classify_quality(row)
|
||||
|
||||
assert quality == "good"
|
||||
assert reasons == []
|
||||
|
||||
|
||||
def test_classify_quality_degraded_when_consumption_missing():
|
||||
row = make_dataframe().iloc[0].to_dict()
|
||||
row["consumption_kwh"] = None
|
||||
|
||||
quality, reasons = classify_quality(row)
|
||||
|
||||
assert quality == "degraded"
|
||||
|
||||
assert "missing:consumption_kwh" in reasons
|
||||
|
||||
|
||||
def test_build_reading_batch_respects_database_contract():
|
||||
frame = normalize_timestamps(
|
||||
make_dataframe(),
|
||||
"UTC",
|
||||
)
|
||||
|
||||
rows = build_reading_batch(
|
||||
frame.iloc[:1],
|
||||
dataset_id=3,
|
||||
)
|
||||
|
||||
assert len(rows) == 1
|
||||
|
||||
row = rows[0]
|
||||
|
||||
assert row["dataset_id"] == 3
|
||||
|
||||
# Important :
|
||||
# contrainte ck_reading_dataset_source.
|
||||
assert row["source"] == "csv"
|
||||
assert SOURCE_NAME == "csv"
|
||||
|
||||
# Important :
|
||||
# contrainte ck_reading_imputation.
|
||||
assert row["imputed_values"] is None
|
||||
assert row["imputation_method"] is None
|
||||
|
||||
assert row["data_quality"] == "good"
|
||||
assert row["null_reasons"] == []
|
||||
|
||||
|
||||
def test_build_reading_batch_keeps_missing_values():
|
||||
frame = make_dataframe()
|
||||
|
||||
frame.loc[0, "temperature_celsius"] = None
|
||||
|
||||
frame = normalize_timestamps(
|
||||
frame,
|
||||
"UTC",
|
||||
)
|
||||
|
||||
rows = build_reading_batch(
|
||||
frame.iloc[:1],
|
||||
dataset_id=3,
|
||||
)
|
||||
|
||||
row = rows[0]
|
||||
|
||||
assert row["temperature_celsius"] is None
|
||||
|
||||
assert "missing:temperature_celsius" in row["null_reasons"]
|
||||
|
||||
# RAW ingestion : aucune imputation.
|
||||
assert row["imputed_values"] is None
|
||||
assert row["imputation_method"] is None
|
||||
|
||||
@@ -49,8 +49,10 @@ async def test_the_database_refuses_to_mutate_the_audit_log(
|
||||
) -> None:
|
||||
await une_ligne(session)
|
||||
|
||||
requete = text(instruction)
|
||||
|
||||
with pytest.raises(DBAPIError, match="ajout seul"):
|
||||
await session.execute(text(instruction))
|
||||
await session.execute(requete)
|
||||
await session.rollback()
|
||||
|
||||
|
||||
|
||||
@@ -131,11 +131,14 @@ async def test_the_database_refuses_two_tokens_sharing_a_fingerprint(
|
||||
user_agent=None,
|
||||
)
|
||||
|
||||
empreinte = fingerprint_refresh(secret)
|
||||
expiration = datetime.now(UTC) + DUREE
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
await depot.create(
|
||||
user_id=compte,
|
||||
token_hash=fingerprint_refresh(secret),
|
||||
expires_at=datetime.now(UTC) + DUREE,
|
||||
token_hash=empreinte,
|
||||
expires_at=expiration,
|
||||
client_ip=None,
|
||||
user_agent=None,
|
||||
)
|
||||
|
||||
@@ -178,12 +178,16 @@ async def test_the_database_refuses_two_tokens_sharing_a_fingerprint(
|
||||
user_agent=None,
|
||||
)
|
||||
|
||||
famille = uuid.uuid4()
|
||||
empreinte = fingerprint_refresh(secret)
|
||||
expiration = datetime.now(UTC) + DUREE
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
await depot.create(
|
||||
user_id=compte,
|
||||
family_id=uuid.uuid4(),
|
||||
token_hash=fingerprint_refresh(secret),
|
||||
expires_at=datetime.now(UTC) + DUREE,
|
||||
family_id=famille,
|
||||
token_hash=empreinte,
|
||||
expires_at=expiration,
|
||||
client_ip=None,
|
||||
user_agent=None,
|
||||
)
|
||||
|
||||
@@ -31,14 +31,12 @@ async def test_the_database_refuses_an_email_written_in_upper_case(
|
||||
) -> None:
|
||||
saisie = adresse().upper()
|
||||
|
||||
requete = text(
|
||||
"insert into app_user (email, password_hash, role) values (:e, '$argon2id$x', 'lecteur')"
|
||||
)
|
||||
|
||||
with pytest.raises(IntegrityError):
|
||||
await session.execute(
|
||||
text(
|
||||
"insert into app_user (email, password_hash, role) "
|
||||
"values (:e, '$argon2id$x', 'lecteur')"
|
||||
),
|
||||
{"e": saisie},
|
||||
)
|
||||
await session.execute(requete, {"e": saisie})
|
||||
await session.rollback()
|
||||
|
||||
|
||||
|
||||
@@ -116,13 +116,11 @@ async def test_list_history_normalizes_naive_datetimes_to_utc() -> None:
|
||||
async def test_list_history_raises_when_start_is_after_end() -> None:
|
||||
service = ReadingService(readings=FakeRepository([]))
|
||||
|
||||
debut = datetime(2026, 9, 2, tzinfo=UTC)
|
||||
fin = datetime(2026, 9, 1, tzinfo=UTC)
|
||||
|
||||
with pytest.raises(FenetreInverseeError):
|
||||
await service.list_history(
|
||||
start=datetime(2026, 9, 2, tzinfo=UTC),
|
||||
end=datetime(2026, 9, 1, tzinfo=UTC),
|
||||
limit=500,
|
||||
offset=0,
|
||||
)
|
||||
await service.list_history(start=debut, end=fin, limit=500, offset=0)
|
||||
|
||||
|
||||
async def test_list_history_raises_when_start_equals_end() -> None:
|
||||
|
||||
@@ -235,5 +235,7 @@ async def test_every_operation_refuses_an_unknown_account(action: str) -> None:
|
||||
if action == "set_active":
|
||||
arguments["is_active"] = False
|
||||
|
||||
methode = getattr(attirail.service, action)
|
||||
|
||||
with pytest.raises(UserNotFoundError):
|
||||
await getattr(attirail.service, action)(**arguments)
|
||||
await methode(**arguments)
|
||||
|
||||
@@ -19,13 +19,17 @@ def test_build_parser_reads_the_create_admin_arguments() -> None:
|
||||
|
||||
|
||||
def test_build_parser_requires_a_subcommand() -> None:
|
||||
parser = cli.build_parser()
|
||||
|
||||
with pytest.raises(SystemExit):
|
||||
cli.build_parser().parse_args([])
|
||||
parser.parse_args([])
|
||||
|
||||
|
||||
def test_build_parser_requires_an_email() -> None:
|
||||
parser = cli.build_parser()
|
||||
|
||||
with pytest.raises(SystemExit):
|
||||
cli.build_parser().parse_args(["create-admin"])
|
||||
parser.parse_args(["create-admin"])
|
||||
|
||||
|
||||
def test_read_password_generates_a_long_secret_when_asked(
|
||||
|
||||
Reference in New Issue
Block a user