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feat: merge datetime fields in DataFrame output, hide MinuteBar internal fields

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- K-line: daily+ periods output 'date' only, minute periods output 'datetime'
- Transactions (tick-by-tick): combine date param + hour/minute into 'datetime'
- XdxrRecord, HistoricalFundFlow: year/month/day merged to 'date'
- MinuteBar: rename unknown_1 to _unknown_1 (hidden from DataFrame)
- MinuteBar: add datetime column computed from bar index (A-share 240-bar pattern)
- get_minute_time_data: use history endpoint only (current-day endpoint broken in pytdx too)
- Update all examples to reflect new DataFrame column names
This commit is contained in:
Justin Gu
2026-05-22 04:19:07 +08:00
parent 0d7f7aead1
commit 00825eb24a
31 changed files with 720 additions and 663 deletions
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examples/08_fund_flow/fund_flow.py
+11 -7
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@@ -4,16 +4,20 @@
"""
import pandas as pd
from easy_tdx import TdxClient, Market
from easy_tdx import Market, TdxClient
with TdxClient.from_best_host() as c:
flow = c.get_fund_flow(Market.SH, "600519")
df = pd.DataFrame([
{"级别": "超大单", "流入(亿)": flow.super_in / 1e8, "流出(亿)": flow.super_out / 1e8},
{"级别": "大单", "流入(亿)": flow.large_in / 1e8, "流出(亿)": flow.large_out / 1e8},
{"级别": "中单", "流入(亿)": flow.medium_in / 1e8, "流出(亿)": flow.medium_out / 1e8},
{"级别": "小单", "流入(亿)": flow.small_in / 1e8, "流出(亿)": flow.small_out / 1e8},
])
# flow 是单行 DataFrame，转换为万元便于阅读
in_cols = ["super_in", "large_in", "medium_in", "small_in"]
out_cols = ["super_out", "large_out", "medium_out", "small_out"]
df = pd.DataFrame(
{
"级别": ["超大单", "大单", "中单", "小单"],
"流入(亿)": [flow[c].iloc[0] / 1e8 for c in in_cols],
"流出(亿)": [flow[c].iloc[0] / 1e8 for c in out_cols],
}
)
df["净流入(亿)"] = df["流入(亿)"] - df["流出(亿)"]
print("贵州茅台 当日资金流向:")
print(df.to_string(index=False))
examples/08_fund_flow/history_fund_flow.py
+2 -9
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@@ -1,15 +1,8 @@
"""演示：获取个股历史日线资金流向序列。"""
import pandas as pd
from easy_tdx import TdxClient, Market
from easy_tdx import Market, TdxClient
with TdxClient.from_best_host() as c:
flows = c.get_history_fund_flow(Market.SH, "600519", 0, 10)
df = pd.DataFrame([{
"日期": f"{f.year}-{f.month:02d}-{f.day:02d}",
"超大单净流入(亿)": (f.super_in - f.super_out) / 1e8,
"大单净流入(亿)": (f.large_in - f.large_out) / 1e8,
"主力净流入(亿)": f.main_net_inflow / 1e8,
} for f in flows])
df = c.get_history_fund_flow(Market.SH, "600519", 0, 10)
print(f"贵州茅台 历史资金流向，共 {len(df)} 天:")
print(df.to_string(index=False))