Files
ProStock/tests/test_sync.py

165 lines
5.6 KiB
Python
Raw Normal View History

"""Sync 接口测试规范与实现。
测试规范
1. 所有 sync 测试只使用 2018-01-01 2018-04-01 的数据
2. 只测试接口是否能正常返回数据不测试落库逻辑
3. 对于按股票查询的接口只测试 000001.SZ000002.SZ 两支股票
4. 使用真实 API 调用确保接口可用性
测试范围
- get_daily: 日线数据接口按股票
- sync_all_stocks: 股票基础信息接口
- sync_trade_cal_cache: 交易日历接口
- sync_namechange: 名称变更接口
- sync_bak_basic: 备用股票基础信息接口
"""
import pytest
import pandas as pd
from datetime import datetime
# 测试用常量
TEST_START_DATE = "20180101"
TEST_END_DATE = "20180401"
TEST_STOCK_CODES = ["000001.SZ", "000002.SZ"]
class TestGetDaily:
"""测试日线数据 get 接口(按股票查询)."""
def test_get_daily_single_stock(self):
"""测试 get_daily 获取单只股票数据."""
from src.data.api_wrappers.api_daily import get_daily
result = get_daily(
ts_code=TEST_STOCK_CODES[0],
start_date=TEST_START_DATE,
end_date=TEST_END_DATE,
)
# 验证返回了数据
assert isinstance(result, pd.DataFrame), "get_daily 应返回 DataFrame"
assert not result.empty, "get_daily 应返回非空数据"
def test_get_daily_has_required_columns(self):
"""测试 get_daily 返回的数据包含必要字段."""
from src.data.api_wrappers.api_daily import get_daily
result = get_daily(
ts_code=TEST_STOCK_CODES[0],
start_date=TEST_START_DATE,
end_date=TEST_END_DATE,
)
# 验证必要的列存在
required_columns = ["ts_code", "trade_date", "open", "high", "low", "close"]
for col in required_columns:
assert col in result.columns, f"get_daily 返回应包含 {col}"
def test_get_daily_multiple_stocks(self):
"""测试 get_daily 获取多只股票数据."""
from src.data.api_wrappers.api_daily import get_daily
results = {}
for code in TEST_STOCK_CODES:
result = get_daily(
ts_code=code,
start_date=TEST_START_DATE,
end_date=TEST_END_DATE,
)
results[code] = result
assert isinstance(result, pd.DataFrame), (
f"get_daily({code}) 应返回 DataFrame"
)
assert not result.empty, f"get_daily({code}) 应返回非空数据"
class TestSyncStockBasic:
"""测试股票基础信息 sync 接口."""
def test_sync_all_stocks_returns_data(self):
"""测试 sync_all_stocks 是否能正常返回数据."""
from src.data.api_wrappers.api_stock_basic import sync_all_stocks
result = sync_all_stocks()
# 验证返回了数据
assert isinstance(result, pd.DataFrame), "sync_all_stocks 应返回 DataFrame"
assert not result.empty, "sync_all_stocks 应返回非空数据"
def test_sync_all_stocks_has_required_columns(self):
"""测试 sync_all_stocks 返回的数据包含必要字段."""
from src.data.api_wrappers.api_stock_basic import sync_all_stocks
result = sync_all_stocks()
# 验证必要的列存在
required_columns = ["ts_code"]
for col in required_columns:
assert col in result.columns, f"sync_all_stocks 返回应包含 {col}"
class TestSyncTradeCal:
"""测试交易日历 sync 接口."""
def test_sync_trade_cal_cache_returns_data(self):
"""测试 sync_trade_cal_cache 是否能正常返回数据."""
from src.data.api_wrappers.api_trade_cal import sync_trade_cal_cache
result = sync_trade_cal_cache(
start_date=TEST_START_DATE,
end_date=TEST_END_DATE,
)
# 验证返回了数据
assert isinstance(result, pd.DataFrame), "sync_trade_cal_cache 应返回 DataFrame"
assert not result.empty, "sync_trade_cal_cache 应返回非空数据"
def test_sync_trade_cal_cache_has_required_columns(self):
"""测试 sync_trade_cal_cache 返回的数据包含必要字段."""
from src.data.api_wrappers.api_trade_cal import sync_trade_cal_cache
result = sync_trade_cal_cache(
start_date=TEST_START_DATE,
end_date=TEST_END_DATE,
)
# 验证必要的列存在
required_columns = ["cal_date", "is_open"]
for col in required_columns:
assert col in result.columns, f"sync_trade_cal_cache 返回应包含 {col}"
class TestSyncNamechange:
"""测试名称变更 sync 接口."""
def test_sync_namechange_returns_data(self):
"""测试 sync_namechange 是否能正常返回数据."""
from src.data.api_wrappers.api_namechange import sync_namechange
result = sync_namechange()
# 验证返回了数据(可能是空 DataFrame因为是历史变更
assert isinstance(result, pd.DataFrame), "sync_namechange 应返回 DataFrame"
class TestSyncBakBasic:
"""测试备用股票基础信息 sync 接口."""
def test_sync_bak_basic_returns_data(self):
"""测试 sync_bak_basic 是否能正常返回数据."""
from src.data.api_wrappers.api_bak_basic import sync_bak_basic
result = sync_bak_basic(
start_date=TEST_START_DATE,
end_date=TEST_END_DATE,
)
# 验证返回了数据
assert isinstance(result, pd.DataFrame), "sync_bak_basic 应返回 DataFrame"
# 注意bak_basic 可能返回空数据,这是正常的
if __name__ == "__main__":
pytest.main([__file__, "-v"])