0.8.30 update (waditu#65)

viktrewang · Oct 16, 2022 · 17412af · 17412af
1 parent 05bb05a
commit 17412af
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Showing 5 changed files with 39 additions and 24 deletions.
diff --git a/czsc/__init__.py b/czsc/__init__.py
@@ -21,15 +21,16 @@
 __email__ = "zeng_bin8888@163.com"
 __date__ = "20220912"
 
-print(f"CZSC环境变量："
-      f"czsc_min_bi_len = {envs.get_min_bi_len()}; "
-      f"czsc_max_bi_num = {envs.get_max_bi_num()}; "
-      f"czsc_bi_change_th = {envs.get_bi_change_th()}")
 
 if envs.get_welcome():
     print(f"欢迎使用CZSC！当前版本标识为 {__version__}@{__date__}\n")
     aphorism.print_one()
 
+    print(f"CZSC环境变量："
+          f"czsc_min_bi_len = {envs.get_min_bi_len()}; "
+          f"czsc_max_bi_num = {envs.get_max_bi_num()}; "
+          f"czsc_bi_change_th = {envs.get_bi_change_th()}")
+
 
 if get_dir_size(home_path) > pow(1024, 3) and envs.get_verbose():
     print(f"{home_path} 目录缓存超过1GB，请适当清理。调用 czsc.empty_cache_path 可以直接清空缓存")
diff --git a/czsc/cmd.py b/czsc/cmd.py
@@ -9,17 +9,19 @@
 """
 import click
 import pandas as pd
-from czsc.aphorism import print_one
 
 
 @click.group()
 def czsc():
+    """CZSC 命令行工具"""
     pass
 
 
 @czsc.command()
 def aphorism():
     """随机输出一条缠中说禅良言警句"""
+    from czsc.aphorism import print_one
+
     print_one()
 
 
diff --git a/czsc/envs.py b/czsc/envs.py
@@ -21,7 +21,7 @@ def get_verbose(verbose=None):
 
 def get_welcome():
     """welcome - 是否输出版本标识和缠中说禅博客摘记"""
-    v = True if os.environ.get('czsc_welcome', '1') in valid_true else False
+    v = True if os.environ.get('czsc_welcome', '0') in valid_true else False
     return v
 
 

diff --git a/examples/ts_fast_backtest.py b/examples/ts_fast_backtest.py
@@ -7,9 +7,7 @@
 import os
 import pandas as pd
 from czsc.traders.ts_backtest import TsDataCache, TsStocksBacktest, freq_cn2ts
-# from czsc.strategies import trader_example1 as strategy
 from czsc.strategies import trader_strategy_a as strategy
-# from examples import tactics
 
 os.environ['czsc_verbose'] = "0"        # 是否输出详细执行信息，包括一些用于debug的信息，0 不输出，1 输出
 os.environ['czsc_min_bi_len'] = "6"     # 通过环境变量设定最小笔长度，6 对应新笔定义，7 对应老笔定义
@@ -18,8 +16,11 @@
 pd.set_option('display.max_rows', 1000)
 pd.set_option('display.max_columns', 20)
 
-data_path = r"C:\ts_data_czsc"
-dc = TsDataCache(data_path, sdt='2000-01-01', edt='2022-02-18')
+
+# data_path 是 TS_CACHE 缓存数据文件夹所在目录
+dc = TsDataCache(data_path=r"C:\ts_data_czsc", refresh=False, sdt="20120101", edt="20221001")
+
+# 获取策略的基础K线周期，回测开始时间 sdt，回测结束时间 edt，初始化K线数量init_n
 freq = freq_cn2ts[strategy('000001.SH')['base_freq']]
 sdt = '20140101'
 edt = "20211216"
@@ -35,11 +36,11 @@ def run_backtest(step_seq=('check', 'index', 'etfs', 'train', 'valid', 'stock'))
     tsb = TsStocksBacktest(dc, strategy, init_n, sdt, edt)
     for step in step_seq:
         tsb.batch_backtest(step.lower())
-        # tsb.analyze_signals(step.lower())
         tsb.analyze_results(step, 'long')
         # tsb.analyze_results(step, 'short')
         print(f"results saved into {tsb.res_path}")
 
+
 def run_more_backtest(step, ts_codes):
     """指定在某个阶段多回测一些标的，最常见的需求是在 check 阶段多检查几个标的
 
@@ -50,7 +51,6 @@ def run_more_backtest(step, ts_codes):
     tsb = TsStocksBacktest(dc, strategy, init_n, sdt, edt)
     tsb.update_step(step, ts_codes)
     tsb.batch_backtest(step.lower())
-    # tsb.analyze_signals(step.lower())
     tsb.analyze_results(step, 'long')
     # tsb.analyze_results(step, 'short')
     print(f"results saved into {tsb.res_path}")

diff --git a/examples/ts_trade_replay.py b/examples/ts_trade_replay.py
@@ -5,23 +5,35 @@
 create_dt: 2022/5/6 15:58
 describe: 请描述文件用途
 """
-from ts_fast_backtest import dc
-from czsc.data import freq_cn2ts
-from czsc.strategies import trader_strategy_a as strategy
+import pandas as pd
+from czsc.data import TsDataCache, freq_cn2ts
 from czsc.utils import BarGenerator
 from czsc.traders.utils import trade_replay
+from czsc.strategies import trader_strategy_a as strategy
+
 
-tactic = strategy("000001.SH")
+# data_path 是 TS_CACHE 缓存数据文件夹所在目录
+dc = TsDataCache(data_path=r"C:\ts_data_czsc", refresh=False, sdt="20120101", edt="20221001")
+
+# 获取单个品种的基础周期K线
+tactic = strategy("000001.SZ")
 base_freq = tactic['base_freq']
-bars = dc.pro_bar_minutes('000001.SZ', "20150101", "20220101", freq=freq_cn2ts[base_freq],
-                          asset="I", adj="hfq", raw_bar=True)
-res_path = r"C:\ts_data_czsc\trade_replay_test4"
+bars = dc.pro_bar_minutes('000001.SZ', "20150101", "20220101", freq=freq_cn2ts[base_freq], asset="E", adj="hfq")
+
+# 设置回放快照文件保存目录
+res_path = r"C:\ts_data_czsc\replay_trader_strategy_a"
+
+
+# 拆分基础周期K线，一部分用来初始化BarGenerator，随后的K线是回放区间
+start_date = pd.to_datetime("20200101")
+bg = BarGenerator(base_freq, freqs=tactic['freqs'])
+bars1 = [x for x in bars if x.dt <= start_date]
+bars2 = [x for x in bars if x.dt > start_date]
+for bar in bars1:
+    bg.update(bar)
 
 
 if __name__ == '__main__':
-    bg = BarGenerator(base_freq, freqs=tactic['freqs'])
-    bars1 = bars[:24000]
-    bars2 = bars[24000:]
-    for bar in bars1:
-        bg.update(bar)
     trade_replay(bg, bars2, strategy, res_path)
+
+