How to use ChatGPT to be a more productive developer

Cris Pintea

Cris Pintea

As a developer, finding ways to increase productivity and efficiency is crucial. The good news is that with the advent of advanced language models like ChatGPT, you have access to an incredibly powerful tool that can help you accomplish your coding tasks more quickly and easily.

In this article, we’ll explore some tips and tricks for using ChatGPT to become a more productive developer.

Use ChatGPT to quickly look up information

As a developer, you know that you often need to look up information on various programming languages, libraries, and tools. With ChatGPT, you can do this quickly and easily by simply typing in a question or topic.

For example, if you’re working with Python and you’re not sure how to use a particular function, you can simply ask ChatGPT for help. The model will provide you with an answer or point you in the direction of relevant documentation, saving you time and effort.

Use ChatGPT for repetitive refactoring operations

You can also use ChatGPT to apply a specific refactoring operation to multiple instances of code. This is particularly useful when you have a defined refactoring operation that needs to be applied to multiple similar pieces of code.

To use ChatGPT for this purpose, you can provide the model with an initial example of the code that has already undergone the refactoring operation. You can then provide it with the other instances of code that need the same refactoring applied to them.

For instance, let’s say you have the following code snippets:

# Example 1
def calculate_total_price(items):
    total_price = 0
    for item in items:
        if item.price >= 10:
            total_price += item.price
        else:
            total_price += item.price * 2
    return total_price

# Example 2
def calculate_total_cost(items):
    total_cost = 0
    for item in items:
        if item.price >= 10:
            total_cost += item.price
        else:
            total_cost += item.price * 2
    return total_cost

# Example 3
def get_total_value(items):
    total_value = 0
    for item in items:
        if item.price >= 10:
            total_value += item.price
        else:
            total_value += item.price * 2
    return total_value

You can see that all three examples are quite similar, and they have the same for-loop structure with an if/else statement inside. Now, let’s say that you have a refactoring operation that you want to apply to all of them, such as extracting the logic inside the if/else statement into a separate function. You can provide ChatGPT with Example 1, the refactored code, and ask it to apply the same refactoring operation to Examples 2 and 3.

Here’s how you can use ChatGPT to apply the refactoring operation:

  1. Provide ChatGPT with Example 1, the refactored code, and ask it to analyze the code and identify the refactoring operation you applied.
  2. Once ChatGPT has identified the refactoring operation, provide it with Examples 2 and 3, and ask it to apply the same refactoring operation to them.
  3. Review the refactored code snippets to ensure that the refactoring operation was applied correctly.

This approach can save you time and effort in applying the same refactoring operation to multiple similar code snippets. With ChatGPT, you can streamline the process and ensure that your refactoring operations are consistent across your codebase.

Ask ChatGPT to generate code snippets

You can use ChatGPT to generate code snippets for specific tasks or challenges. By providing the model with a description of what you need the code to do, it can generate code snippets that accomplish the desired functionality. This can save you time and effort and help you to write better code.

Here’s a practical example:

ChatGPT generated Javascript code for retrieving Stripe subscriptions through the Stripe API.

Let’s take an example of a task that requires a code snippet. Suppose you need to write a function that takes in a list of numbers and returns the sum of the squares of the even numbers. You could spend time researching and writing the code yourself, but with ChatGPT, you can generate a code snippet quickly and easily.

Here’s how you can use ChatGPT to generate the code snippet:

  1. Provide ChatGPT with a description of the task. In this case, you would provide the model with a description of what the function needs to do.
  2. Ask ChatGPT to generate a code snippet that accomplishes the desired functionality. You could ask the model to generate Python code that accomplishes the task.
  3. Review the generated code snippet and make any necessary changes or improvements.

Here’s an example of a code snippet generated by ChatGPT for the task described above:

def sum_of_even_squares(numbers):
    return sum(x**2 for x in numbers if x % 2 == 0)

As you can see, the generated code snippet accomplishes the desired functionality and can save you time and effort in writing the code yourself. You can use this approach to generate code snippets for a wide range of programming challenges and tasks, from simple functions to more complex algorithms.

Use ChatGPT for code suggestions and optimization

Another powerful use of ChatGPT is to get suggestions on how to optimize your code. You can ask ChatGPT to review your code and make recommendations for how to improve it.

For instance, if you’re working on a particularly complex algorithm, you can ask ChatGPT to suggest ways to make it more efficient. The model can review your code and suggest ways to optimize it, such as by reducing the number of iterations or using more efficient data structures.

Use ChatGPT to document cryptic code

You can use the model to generate comments for your code automatically. By providing the model with your code, it can analyze it and generate comments that explain what your code does.

Let’s take an example of a piece of code that needs to be documented:

def calculate_discounted_price(price, discount):
    """
    Calculate the discounted price of an item
    """
    discounted_price = price - (price * discount)
    return discounted_price

This code calculates the discounted price of an item based on the original price and the discount percentage. While the code is relatively simple, it still needs to be documented to ensure that other developers can understand what it does.

To generate comments for this code, you can use ChatGPT as follows:

  1. Provide the code to ChatGPT and ask it to generate a comment that explains what the code does.
  2. Review the generated comment and make any necessary changes or improvements.
  3. Add the comment to the code as a documentation string.

Here’s an example of the comment generated by ChatGPT for the code above:

"""
This function takes in the original price and discount percentage of an item and calculates the discounted price. 
It then returns the discounted price as output. 
"""

As you can see, the generated comment provides a clear and concise explanation of what the code does. You can use this approach to document your code quickly and efficiently, ensuring that other developers can understand its functionality without spending extra time analyzing it.

In conclusion, using ChatGPT to generate comments for your code is a simple and effective way to improve its readability and maintainability. By providing clear and concise explanations of what your code does, you can make it easier for other developers to understand and work with your code.

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