如何直接从 Python 使用 Alpha Vantage API

How to use the Alpha Vantage API directly from Python

我一直在使用 Romel Torres 的 alpha_vantage 包,但也想直接从 python 使用 Alpha Vantage API(提供更强大的功能),如所述的包请求这里 :

import requests
import alpha_vantage

API_URL = "https://www.alphavantage.co/query"

data = {
    "function": "TIME_SERIES_DAILY",
    "symbol": "NIFTY",
    "outputsize": "compact",
    "datatype": "csv"
    "apikey": "XXX",
    }
response = requests.get(API_URL, data)
print(response.json())[/code]

但在返回的字典中收到以下错误消息:

{'Error Message': 'Invalid API call. Please retry or visit the documentation (https://www.alphavantage.co/documentation/) for TIME_SERIES_DAILY.'}

使用 requests.post() 结果是:

response = requests.post(API_URL, data)
{'detail': 'Method "POST" not allowed.'}

我已重新检查文档并遵循所有必需的 API 参数。感谢一些帮助,我可能在这里遗漏了什么,以及正确的调用是什么 and/or 任何其他替代方法。谢谢

提示在错误中。将请求的方法从 post 更改为 get:

response = requests.get(API_URL, params=data)

并使用作为 Alpha Vantage 数据存在的股票代码。 NIFTY 不是股票 - 它是指数。如果您使用 MSFT 尝试您的代码,它将起作用。

第一个

您正在使用 'csv' 数据类型。

"datatype": "csv"

但是您正在尝试以 JSON 格式打印

print(response.json())

第二

按照建议尝试使用 get 方法

import requests
import alpha_vantage
import json


API_URL = "https://www.alphavantage.co/query" 
symbols = ['QCOM',"INTC","PDD"]

for symbol in symbols:
        data = { "function": "TIME_SERIES_INTRADAY", 
        "symbol": symbol,
        "interval" : "60min",       
        "datatype": "json", 
        "apikey": "XXX" } 
        response = requests.get(API_URL, data) 
        data = response.json()
        print(symbol)
        a = (data['Time Series (60min)'])
        keys = (a.keys())
        for key in keys:
                print(a[key]['2. high'] + " " + a[key]['5. volume'])

数据中的最后一个元素之后似乎多了一个逗号 (,)。

这就是我在不使用任何包装器的情况下从 Alpha Vantage 获取每日股票时间序列的方法。接收后,我将数据转换成pandas数据框,以便进一步处理。

    import requests
    import pandas as pd

    API_URL = "https://www.alphavantage.co/query" 
    symbol = 'SMBL'

    data = { "function": "TIME_SERIES_DAILY", 
    "symbol": symbol,
    "outputsize" : "full",
    "datatype": "json", 
    "apikey": "your_api_key" } 

    response = requests.get(API_URL, data) 
    response_json = response.json() # maybe redundant

    data = pd.DataFrame.from_dict(response_json['Time Series (Daily)'], orient= 'index').sort_index(axis=1)
    data = data.rename(columns={ '1. open': 'Open', '2. high': 'High', '3. low': 'Low', '4. close': 'Close', '5. adjusted close': 'AdjClose', '6. volume': 'Volume'})
    data = data[[ 'Open', 'High', 'Low', 'Close', 'AdjClose', 'Volume']]
    data.tail() # check OK or not
import requests
import alpha_vantage

API_URL = "https://www.alphavantage.co/query"
data = {
    "function": "TIME_SERIES_DAILY",
    "symbol": "AAPL",
 "outputsize": "compact",
    "apikey": "your key"
    }

response = requests.get(API_URL, params=data)
print(response.json())

这就是我在没有任何包装的情况下的做法。您可以使用此代码轻松地从 Alpha Vantage 中提取历史股票价格。您所要做的就是插入您的符号和代币。有关提取 Alpha Vantage 数据的更多功能,请随时查看此 link:https://github.com/hklchung/StockPricePredictor/blob/master/2020/alphavantage_funcs.py

def request_stock_price_hist(symbol, token, sample = False):
    if sample == False:
        q_string = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol={}&outputsize=full&apikey={}'
    else:
        q_string = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY_ADJUSTED&symbol={}&apikey={}'

    print("Retrieving stock price data from Alpha Vantage (This may take a while)...")
    r = requests.get(q_string.format(symbol, token))
    print("Data has been successfully downloaded...")
    date = []
    colnames = list(range(0, 7))
    df = pd.DataFrame(columns = colnames)
    print("Sorting the retrieved data into a dataframe...")
    for i in tqdm(r.json()['Time Series (Daily)'].keys()):
        date.append(i)
        row = pd.DataFrame.from_dict(r.json()['Time Series (Daily)'][i], orient='index').reset_index().T[1:]
        df = pd.concat([df, row], ignore_index=True)
    df.columns = ["open", "high", "low", "close", "adjusted close", "volume", "dividend amount", "split cf"]
    df['date'] = date
    return df

以上函数的使用方法如下:

df = request_stock_price_hist('IBM', 'REPLACE_YOUR_TOKEN')
df.to_csv('output.csv')