从Yahoo获取HFT数据存为CSV遇报错，求解决方案

问题背景 #

尝试用Python从Yahoo获取高频交易（HFT）数据并保存为CSV，已安装Python和pandas，但运行代码时出现多个错误：ModuleNotFoundError（arrow模块未安装）、IndentationError（函数缩进错误）、NameError等，需要修复代码用于回归分析。

原代码：

import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol='SBIN.NS', data_range='1d', data_interval='1m'):
res = requests.get('https://query1.finance.yahoo.com/v8/finance/chart/{symbol}?range={data_range}&interval={data_interval}'.format(**locals()))
data = res.json()
body = data['chart']['result'][0]
dt = datetime.datetime
dt = pd.Series(map(lambda x: arrow.get(x).to('Asia/Calcutta').datetime.replace(tzinfo=None), body['timestamp']), name='Datetime')
df = pd.DataFrame(body['indicators']['quote'][0], index=dt)
dg = pd.DataFrame(body['timestamp'])

return df.loc[:, ('open', 'high', 'low', 'close', 'volume')]
data = get_quote_data('SBIN.NS', '5d', '1m')
data.dropna(inplace=True) #removing NaN rows
print(data)
data.to_csv('output.csv')

报错信息：

>>> import requests
>>> import pandas as pd
>>> import arrow
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ModuleNotFoundError: No module named 'arrow'
>>> import datetime
>>> 
>>> def get_quote_data(symbol='SBIN.NS', data_range='1d', data_interval='1m'):
... res = requests.get('https://query1.finance.yahoo.com/v8/finance/chart/{symbol}?range={data_range}&interval={data_interval}'.format(**locals()))
  File "<stdin>", line 2
    res = requests.get('https://query1.finance.yahoo.com/v8/finance/chart/{symbol}?range={data_range}&interval={data_interval}'.format(**locals()))
    ^
IndentationError: expected an indented block after function definition on line 1
>>> data = res.json()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'res' is not defined
>>> body = data['chart']['result'][0]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'data' is not defined
>>> dt = datetime.datetime
>>> dt = pd.Series(map(lambda x: arrow.get(x).to('Asia/Calcutta').datetime.replace(tzinfo=None), body['timestamp']), name='Datetime')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'body' is not defined
>>> df = pd.DataFrame(body['indicators']['quote'][0], index=dt)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'body' is not defined
>>> dg = pd.DataFrame(body['timestamp'])
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'body' is not defined
>>> 
>>> return df.loc[:, ('open', 'high', 'low', 'close', 'volume')]
  File "<stdin>", line 1
SyntaxError: 'return' outside function
>>> data = get_quote_data('SBIN.NS', '5d', '1m')
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'get_quote_data' is not defined
>>> data.dropna(inplace=True) #removing NaN rows
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'data' is not defined
>>> print(data)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
NameError: name 'data' is not defined
>>> data.to_csv('output.csv')

错误原因分析 #

1. 缺失依赖包：代码用到arrow和requests模块，但只安装了pandas，导致ModuleNotFoundError
2. 缩进错误：Python函数内部代码必须缩进（通常4个空格），原代码函数定义后未缩进，触发IndentationError，进而导致后续变量和函数无法识别，出现NameError
3. 无效代码：dg = pd.DataFrame(body['timestamp'])未被使用，属于冗余代码
4. 潜在异常风险：未处理API返回失败的情况（如网络问题、接口限制），可能导致后续代码崩溃

修复步骤与完整代码 #

1. 安装缺失依赖 #

打开终端/命令提示符，运行以下命令安装所需模块：

pip install requests arrow pandas

2. 修复后的完整代码 #

import requests
import pandas as pd
import arrow
import datetime

def get_quote_data(symbol='SBIN.NS', data_range='1d', data_interval='1m'):
    # 发送请求获取数据
    url = f'https://query1.finance.yahoo.com/v8/finance/chart/{symbol}?range={data_range}&interval={data_interval}'
    res = requests.get(url)
    res.raise_for_status()  # 检查请求是否成功
    data = res.json()
    
    # 解析返回的JSON数据
    chart_result = data['chart']['result']
    if not chart_result:
        raise ValueError("未获取到有效数据，请检查参数或网络连接")
    body = chart_result[0]
    
    # 处理时间戳，转换为指定时区的datetime
    timestamps = body['timestamp']
    dt_series = pd.Series(
        [arrow.get(ts).to('Asia/Calcutta').datetime.replace(tzinfo=None) for ts in timestamps],
        name='Datetime'
    )
    
    # 构建DataFrame并返回指定列
    quote_data = body['indicators']['quote'][0]
    df = pd.DataFrame(quote_data, index=dt_series)
    return df.loc[:, ['open', 'high', 'low', 'close', 'volume']]

# 调用函数获取数据并保存
try:
    data = get_quote_data('SBIN.NS', '5d', '1m')
    data.dropna(inplace=True)  # 移除含空值的行
    print(data)
    data.to_csv('hft_data.csv')  # 保存为CSV文件
    print("数据已成功保存到hft_data.csv")
except Exception as e:
    print(f"运行出错: {str(e)}")

3. 代码优化说明 #

• 用f-string替代format(**locals())，更简洁易读
• 添加res.raise_for_status()检查请求是否成功，避免后续解析失败
• 增加空结果判断，提前抛出明确错误
• 把map改成列表推导式，可读性更好
• 用try-except捕获运行时异常，方便排查问题
• 重命名输出文件为hft_data.csv，更直观

4. 运行方法 #

将修复后的代码保存为get_hft_data.py，在终端/命令提示符中运行：

python get_hft_data.py

运行成功后，当前目录会生成hft_data.csv文件，可直接用于回归分析。

内容的提问来源于stack exchange，提问作者Patrycja