fix: 完善自定义分钟数据源配置与异常处理

- 补齐资产类型和周期参数在 API、YAML 与前端编辑器中的保存回读

- 权限判断和分时监控统一复用安全的数据源解析边界

- 增加配置往返及解析异常回归测试
This commit is contained in:
shy3130
2026-07-19 17:01:33 +08:00
parent b1b2494db9
commit 4df3062002
9 changed files with 122 additions and 14 deletions
+4 -4
View File
@@ -25,10 +25,10 @@ def _minute_allowed(capset) -> bool:
return True
from app.services import preferences
provider = preferences.get_minute_data_provider()
if provider == "tickflow":
return False
from app.data_providers import custom as custom_sources
return custom_sources.provider_has_dataset(provider, "minute")
_, fallback, error = kline_sync._resolve_minute_provider(provider)
if error is not None:
logger.warning("minute provider resolution failed while checking access: %s", error)
return not fallback
@router.get("/instruments/search")
+2 -1
View File
@@ -371,6 +371,8 @@ class DatasetConfigIn(BaseModel):
symbols_param: str = "symbols"
start_param: str = "start_time"
end_param: str = "end_time"
asset_type_param: str | None = None
freq_param: str | None = None
class AuthConfigIn(BaseModel):
@@ -1429,4 +1431,3 @@ def update_review_push(req: ReviewPushIn) -> dict:
from app.services import preferences
saved = preferences.set_review_push_channels(req.channels)
return {"review_push_channels": saved}
+6 -1
View File
@@ -296,6 +296,8 @@ def _config_to_dict(config: CustomSourceConfig) -> dict:
"symbols_param": ds.symbols_param,
"start_param": ds.start_param,
"end_param": ds.end_param,
**({"asset_type_param": ds.asset_type_param} if ds.asset_type_param else {}),
**({"freq_param": ds.freq_param} if ds.freq_param else {}),
}
return out
@@ -401,6 +403,10 @@ def _sanitize_dataset(ds_cfg: dict) -> dict:
out["start_param"] = str(ds_cfg["start_param"])
if ds_cfg.get("end_param"):
out["end_param"] = str(ds_cfg["end_param"])
if ds_cfg.get("asset_type_param"):
out["asset_type_param"] = str(ds_cfg["asset_type_param"])
if ds_cfg.get("freq_param"):
out["freq_param"] = str(ds_cfg["freq_param"])
return out
@@ -496,4 +502,3 @@ def _load_entry(entry_ref: str):
# 模块导入时即扫描一次, 保证 names()/_allowed_data_providers() 在 startup 前可用。
_load_builtin_plugins()
+8 -7
View File
@@ -733,13 +733,14 @@ def sync_minute_batch(
def intraday_monitor_support(capset: CapabilitySet | None) -> dict[str, object]:
"""返回分时信号监控可用的数据能力和单轮标的上限。"""
provider_name = preferences.get_minute_data_provider()
if provider_name != "tickflow":
from app.data_providers import custom as custom_sources
if custom_sources.provider_has_dataset(provider_name, "minute"):
return {
"available": True, "source": "custom_minute", "max_symbols": 100,
"reason": "使用已配置的分钟数据插件",
}
_, fallback, error = _resolve_minute_provider(provider_name)
if not fallback:
return {
"available": True, "source": "custom_minute", "max_symbols": 100,
"reason": "使用已配置的分钟数据插件",
}
if error is not None:
logger.warning("minute provider resolution failed while checking monitor support: %s", error)
if capset is None:
return {
"available": False, "source": None, "max_symbols": 0,
@@ -0,0 +1,29 @@
from app.api.settings import DatasetConfigIn
from app.data_providers.custom.config import CustomSourceConfig, _dataset_from_dict
from app.data_providers.custom.loader import _config_to_dict, _sanitize_for_yaml
def test_minute_request_parameter_names_survive_config_round_trip():
dataset = DatasetConfigIn(
url="https://example.test/minute",
method="GET",
asset_type_param="asset",
freq_param="period",
).model_dump()
cleaned = _sanitize_for_yaml({
"name": "test_source",
"display_name": "Test Source",
"datasets": {"minute": dataset},
})
parsed = _dataset_from_dict(cleaned["datasets"]["minute"])
exposed = _config_to_dict(CustomSourceConfig(
name="test_source",
display_name="Test Source",
datasets={"minute": parsed},
))
assert parsed.asset_type_param == "asset"
assert parsed.freq_param == "period"
assert exposed["datasets"]["minute"]["asset_type_param"] == "asset"
assert exposed["datasets"]["minute"]["freq_param"] == "period"
+41
View File
@@ -639,3 +639,44 @@ def test_resolve_minute_provider_success_returns_provider(monkeypatch):
assert provider is mock_provider
assert fallback is False
assert err is None
def test_minute_allowed_resolver_exception_returns_false(monkeypatch):
"""权限入口复用安全 resolver, 插件注册异常不再穿透为 500。"""
from app.api import kline as kline_api
from app.tickflow.capabilities import CapabilitySet
monkeypatch.setattr(
"app.services.preferences.get_minute_data_provider",
lambda: "broken",
)
def _raising(name, dataset):
raise RuntimeError("registry corrupted")
monkeypatch.setattr("app.data_providers.custom.provider_has_dataset", _raising)
assert kline_api._minute_allowed(CapabilitySet()) is False
def test_intraday_monitor_support_resolver_exception_falls_back(monkeypatch):
"""监控入口解析自定义源失败后继续按 TickFlow 能力判断。"""
from app.tickflow.capabilities import Cap, CapabilitySet
monkeypatch.setattr(
kline_sync.preferences,
"get_minute_data_provider",
lambda: "broken",
)
def _raising(name, dataset):
raise RuntimeError("registry corrupted")
monkeypatch.setattr("app.data_providers.custom.provider_has_dataset", _raising)
capset = CapabilitySet()
capset.grant(Cap.KLINE_MINUTE_BATCH)
support = kline_sync.intraday_monitor_support(capset)
assert support["available"] is True
assert support["source"] == "minute_batch"