Reading from a nested Python dictionary with JSON time series data

Question

I recently acquired an API key from AlphaVantage.co to read time series data (stock). I was able to write Python code that requests and stores the JSON file into a Python dictionary,

stockinfo = requests.get(full_url).json()

but I am unable to figure out how to generate code that reads from the resulting nested Python dictionary because the names change as a function of the date of the request. Below is a truncated copy of the JSON file.

I am new to Python, but am familiar with how to read dictionaries

closing_price = stockinfo["Time Series (Daily)"]["2020-09-10"]["4. close"]

but the nested dictionary keys change are evolving dates.

Thank you for any assistance.

{
"Meta Data": {
    "1. Information": "Daily Prices (open, high, low, close) and Volumes",
    "2. Symbol": "MSFT",
    "3. Last Refreshed": "2020-09-10",
    "4. Output Size": "Full size",
    "5. Time Zone": "US/Eastern"
},
    "Time Series (Daily)": {
        "2020-09-10": {
            "1. open": "213.4000",
            "2. high": "214.7400",
            "3. low": "204.1100",
            "4. close": "205.3700",
            "5. volume": "35461514"
        },
        "2020-09-09": {
            "1. open": "207.6000",
            "2. high": "214.8399",
            "3. low": "206.7000",
            "4. close": "211.2900",
            "5. volume": "45678986"
        },
        "1999-11-02": {
            "1. open": "92.7500",
            "2. high": "94.5000",
            "3. low": "91.9400",
            "4. close": "92.5600",
            "5. volume": "23174500"
        },
        "1999-11-01": {
            "1. open": "93.2500",
            "2. high": "94.1900",
            "3. low": "92.1200",
            "4. close": "92.3700",
            "5. volume": "26630600"
        }
    }
}

Answer 1

I think you want something like this:

for day_date, day_data in closing_price['Time Series (Daily)'].items():
    print(f"Data for {day_date} is {day_data}")
    print(f"High for {day_date} is {day_data['2. high']}")