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使用Python保存下载的CSV文件

[英]Saving a downloaded CSV file using Python

I want to download a csv file from a link with request and save it as MSFT.csv . 我想从带有请求的链接下载一个csv文件,并将其保存为MSFT.csv However, my code return error 但是,我的代码返回错误

File "< stdin >", line 1, in _csv.Error: new-line character seen in unquoted field - do you need to open the file in universal-newline mode? 文件“<stdin>”,第1行,在_csv.Error中:在未引用字段中看到的新行字符 - 您是否需要以通用换行模式打开文件?

import requests
import csv

data=requests.get('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'
cr = csv.reader(data)

for row in cr:
    print row

How can I save it with MSFT.csv ? 如何使用MSFT.csv保存它?

If you're trying to write this data to a CSV file, you can first download it using requests.get , then save each line to a CSV file. 如果您尝试将此数据写入CSV文件,可以先使用requests.get下载,然后将每行保存为CSV文件。

import csv
import requests

url = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'
response = requests.get(url)        

with open('out.csv', 'w') as f:
    writer = csv.writer(f)
    for line in response.iter_lines():
        writer.writerow(line.decode('utf-8').split(','))

Alternatively, if you have pandas installed ( pip install --user pandas ), you can load data by passing a URL directly. 或者,如果您安装了pandas( pip install --user pandas ),则可以通过直接传递URL来加载数据。

import pandas as pd

df = pd.read_csv(url)   
df.head()

    timestamp    open    high     low   close  adjusted_close    volume  dividend_amount  split_coefficient
0  2019-06-19  135.00  135.93  133.81  135.69          135.69  17946556              0.0                1.0
1  2019-06-18  134.19  135.24  133.57  135.16          135.16  25908534              0.0                1.0
2  2019-06-17  132.63  133.73  132.53  132.85          132.85  14517785              0.0                1.0
3  2019-06-14  132.26  133.79  131.64  132.45          132.45  17821703              0.0                1.0
4  2019-06-13  131.98  132.67  131.56  132.32          132.32  17200848              0.0                1.0

df.to_csv('out.csv')

You can achieve it via requests as 你可以通过请求来实现它

import os
import requests

def download_file(url, filename):
    ''' Downloads file from the url and save it as filename '''
    # check if file already exists
    if not os.path.isfile(filename):
        print('Downloading File')
        response = requests.get(url)
        # Check if the response is ok (200)
        if response.status_code == 200:
            # Open file and write the content
            with open(filename, 'wb') as file:
                # A chunk of 128 bytes
                for chunk in response:
                    file.write(chunk)
    else:
        print('File exists')

You can call the function with your url and filename that you want. 您可以使用所需的URL和文件名调用该函数。 In your case it would be: 在你的情况下,它将是:

url = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'
filename = 'MSFT.csv'
download_file(url, filename)

Hope this helps. 希望这可以帮助。

There is a simpler way for you. 有一种更简单的方法。

import urllib.request

csv_url = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv'

urllib.request.urlretrieve(csv_url, 'MSFT.csv')

Here you go 干得好

import requests, csv

download = requests.get('https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol=MSFT&apikey=demo&datatype=csv')

with open('MSFT.csv', 'w') as temp_file:
    temp_file.writelines(download.content)

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