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62 lines
2.1 KiB
62 lines
2.1 KiB
# -*- coding: utf-8 -*-
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import re
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import pandas as pd
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import json
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import ast # Python 的 ast.literal_eval 可以安全解析 Python 字典字符串
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def test_code_001():
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df = pd.read_csv("alpha_list.csv", nrows=5)
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# 方法1：用 ast.literal_eval（推荐，能解析 Python 字面量）
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for i, row in df.iterrows():
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regular_str = row['regular']
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if pd.notna(regular_str):
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try:
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regular_dict = ast.literal_eval(regular_str)
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code = regular_dict.get('code', '')
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print(f"Row {i}: {code[:80]}...")
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except Exception as e:
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print(f"Row {i}: 解析失败 - {e}")
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# 方法2：看看原始字符串前200个字符
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print("\n原始字符串示例:")
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print(df.iloc[0]['regular'][:200])
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def test_code_002():
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expression = "last_diff_value(ts_sum(subtract(implied_volatility_call_120, implied_volatility_put_90), 20), 5)"
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# 提取算子
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operators = set()
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for match in re.finditer(r'\b([a-z_][a-z0-9_]*)\s*\(', expression):
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op = match.group(1)
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operators.add(op)
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print(f"匹配到算子: {op}")
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print(f"\n所有算子: {operators}")
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# 提取字段
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candidates = set(re.findall(r'\b([a-z][a-z0-9_]*)\b', expression))
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print(f"\n所有候选词: {candidates}")
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# 过滤掉算子
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fields = [c for c in candidates if c not in operators and not c.isdigit() and len(c) > 2]
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print(f"\n字段: {fields}")
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def test_code_003():
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df = pd.read_csv("alpha_list.csv")
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# 检查 id 列的类型
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print(f"id 列类型: {df['id'].dtype}")
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# 检查是否有重复
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duplicates = df[df.duplicated(subset=['id'], keep=False)]
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print(f"\n重复的 id 数量: {len(duplicates)}")
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if len(duplicates) > 0:
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print("\n重复的 id 示例:")
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for aid in duplicates['id'].unique()[:5]:
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rows = df[df['id'] == aid]
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print(f" {aid}: 出现 {len(rows)} 次")
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# 打印这些行的 fitness 看是否相同
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for _, row in rows.iterrows():
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print(f" fitness: {row['is'][:100] if isinstance(row['is'], str) else row['is']}...") |