Understanding Loop Logic with Requests and Pandas in Python

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In this article, we will explore why using .request in a while loop does not work as expected. We’ll delve into the world of asynchronous programming and how it relates to requests and pandas dataframes.

Introduction

Python’s requests library is used to send HTTP requests and returns server responses. The pandas library provides high-performance, easy-to-use data structures and data analysis tools. When working with APIs like Alpha Vantage, we often need to make multiple requests to fetch data. However, if the loop logic is not implemented correctly, it can lead to unexpected behavior.

Problem Statement

The problem statement provided in the Stack Overflow post asks why using .request in a while loop does not work as expected. The goal is to fetch data from an API and use another input after the first while loop is executed.

Background Information

Asynchronous Programming

Asynchronous programming allows your program to execute multiple tasks concurrently, improving overall performance and responsiveness. However, it can be challenging to implement correctly, especially when working with I/O-bound operations like HTTP requests.

In Python, we use coroutines and event loops to achieve asynchronous behavior. The asyncio library provides a high-level interface for writing single-threaded concurrent code using coroutines, multiplexing I/O access over sockets and other resources, and implementing network clients and servers.

Requests Library

The requests library is a popular Python library used for making HTTP requests. It provides an easy-to-use interface for sending HTTP requests and returns server responses.

Pandas Dataframes

Pandas dataframes are two-dimensional labeled data structures with columns of potentially different types. They are the primary data structure in pandas, which is built on top of NumPy arrays and offers data analysis tools.

Solution Explanation

The provided solution explains why using .request in a while loop does not work as expected. Let’s break down the key points:

Corrected Loop Logic

import requests
while True:
    # get user input, expects a ticker symbol (e.g. ibm)
    stock = input("Please enter a ticker symbol: ")
    print('checking stock:', stock)
    # if user pressed enter (empty string), then finish
    if not stock:
        break # this breaks out of the while loop
    # craft URL, request the webpage and create the dataframe from the JSON data
    url = f"https://www.alphavantage.co/query?function=EMA&amp;symbol={stock}&amp;interval=weekly&amp;time_" \
          f"period=10&amp;series_type=open&amp;apikey=MyAPI"
    request = requests.get(url)
    data = request.json()
    df = pd.DataFrame(data)
    # if there is data, df.size will be greater than 0
    if df.size: # this is equivalent to df.size > 0
        print(df)
    else:
        print('no data')
# we are out of the loop
print('end')

The key changes include:

Moving the while loop outside the input statement. This allows the program to continue executing even if the user presses enter without entering a ticker symbol.
Breaking out of the while loop when an empty string is entered as the input.

Explanation

Using .request in a while loop can lead to unexpected behavior because it blocks the execution of the next iteration until the request completes. By moving the while loop outside the input statement and breaking out of the loop when an empty string is entered, we ensure that the program continues executing even if the user presses enter without entering a ticker symbol.

Additional Considerations

Validation

While not necessary in this case, adding validation to handle potential errors or invalid inputs can improve the robustness of the program. This can be achieved by wrapping the request in a try-except block.

import requests
while True:
    # get user input, expects a ticker symbol (e.g. ibm)
    stock = input("Please enter a ticker symbol: ")
    print('checking stock:', stock)
    # if user pressed enter (empty string), then finish
    if not stock:
        break # this breaks out of the while loop
    try:
        # craft URL, request the webpage and create the dataframe from the JSON data
        url = f"https://www.alphavantage.co/query?function=EMA&amp;symbol={stock}&amp;interval=weekly&amp;time_" \
              f"period=10&amp;series_type=open&amp;apikey=MyAPI"
        request = requests.get(url)
        request.raise_for_status()
        data = request.json()
        df = pd.DataFrame(data)
        # if there is data, df.size will be greater than 0
        if df.size: 
            print(df)
        else:
            print('no data')
    except requests.RequestException as e:
        print(f"Request Error: {e}")
# we are out of the loop
print('end')

By adding a try-except block, we can catch any exceptions raised during the request and handle them accordingly.

Conclusion

Using .request in a while loop can lead to unexpected behavior if not implemented correctly. By moving the while loop outside the input statement and breaking out of the loop when an empty string is entered, we ensure that the program continues executing even if the user presses enter without entering a ticker symbol. Additionally, adding validation to handle potential errors or invalid inputs can improve the robustness of the program.

Last modified on 2023-07-16