ChatGPT is revolutionizing the way people work by providing valuable assistance and support across various job roles. Professionals from different industries, such as customer service representatives, content creators, researchers, and even healthcare providers, are benefiting from ChatGPT’s capabilities.
In the ever-evolving landscape of software development, finding tools and technologies that enhance productivity and efficiency is crucial. As a developer myself, I have experienced firsthand how ChatGPT, developed by OpenAI, can be a game-changer in my day-to-day work. In this blog, we will give 10 use cases in which ChatGPT can assist developers, streamline their workflow, and empower them to create exceptional software solutions.
Table of Contents
1. Ideation to solve a Problem
ChatGPT can be a valuable tool in helping you think through a problem by providing a fresh perspective, offering new ideas, and acting as a sounding board. As an AI language model, ChatGPT has access to a vast amount of information and can draw upon various fields of knowledge. When you present a problem to ChatGPT, it can analyze the given information, generate relevant responses, and propose potential solutions or approaches that you may not have considered before.
We gave some prompts on our problems and we received some very good suggestions.
Prompt: I want to create a system that can book tickets for movies. Can you help me in making this system? This system should be scalable enough to handle lots of traffic. Can you give me some idea of which architecture and tech stack I should use?
It gave us a lot of options to do so. But, We tried another prompt for some more specific answers.
Prompt 2: Now, I am confused as you gave so many options. can you give me some specific answers?
Now, It gave specific answers on which architecture should we use for scalability, and which tech stack, the database should we use, and it also provided information on how we can deploy this to achieve scalability.
So, Embrace the brilliance of ChatGPT as your virtual senior colleague! When you find yourself without the guidance of a senior, ChatGPT steps in seamlessly to provide invaluable assistance.
2. Generate Code
Chat GPT can be a valuable tool for generating code as it leverages its natural language processing capabilities to understand and respond to coding-related queries. By providing clear and concise instructions, you can ask Chat GPT to generate code snippets or even entire functions, saving time and effort in writing code from scratch.
We asked to write a schema for the database of the movie ticket booking system and this is what we got.
The previous response from ChatGPT states that the generated result includes Django models, which are used in the Django web framework for database management. These models represent multiple tables with appropriate field names that accurately describe the data they store. The models also ensure that the correct data types are used for each field, which is important for maintaining data integrity. The accuracy of the generated models is considered excellent, as they adhere to the requirements specified in the schema. Additionally, the response provides a detailed explanation of the entire schema, allowing for a thorough understanding of the table structures and their relationships.
3. Explain the code
As an AI language model, ChatGPT can provide explanations of code bases by utilizing its training on vast amounts of text data, including programming documentation, tutorials, and examples. When given a specific code snippet or question about code, ChatGPT can analyze the provided information and generate a response that aims to explain the code or its concepts.
class AVOneTap:
def _get_username(self, **kwargs):
username = kwargs.get("username")
if not username:
# check if the username exists or not
if "first_name" in kwargs:
username = str(kwargs["first_name"].split()[0].lower()) + str(
random.randint(1, 10000000)
)
else:
username = str(kwargs["email"].split("@")[0].lower()) + str(
random.randint(1, 10000000)
)
username = username.strip()
user = User.objects.filter(username=username).first()
if not user:
kwargs["username"] = username
self._get_username(**kwargs)
return username
def _create_user(self, **kwargs):
# creates user and calls login method
username = self._get_username(**kwargs)
user = User.objects.create_user(
username=username, password=None, email=kwargs["email"]
)
# if user.id:
# send_user_data_webengage.delay(user.id)
# else:
# logger.info('user.id does not exists _create_user')
user.first_name = kwargs.get("first_name")
user.last_name = kwargs.get("last_name") or "."
is_whatsapp_subscribed = kwargs.get('is_whatsapp_subscribed')
logger.info("whatsapp subscribed feature : %s" %str(is_whatsapp_subscribed))
if is_whatsapp_subscribed == "true":
user.is_whatsapp_subscribed = True
# storing tracking info for reporting purpose.
try:
if kwargs.get("url") and kwargs.get("source_platform"):
user.signup_source_url = kwargs.get("url")
user.signup_source_name = kwargs.get("source_platform")
except Exception as e:
logger.error(e)
# Save the user
user.save()
# save the Email Address field also
try:
existing_email, created = EmailAddress.objects.select_related(
"user"
).get_or_create(
email=user.email,
verified=True,
defaults={"user": user, "verified": True, "primary": True},
)
except Exception as e:
logger.error(e)
return user
def login(self, **kwargs):
# kwargs should contain, request, email, first_name
email = kwargs.get("email")
if not email:
return None
user = User.objects.filter(email=email).first()
logger.info("Getting user corresponding to email %s : %s" %(str(email), str(user)))
if user:
# signed In
kwargs["is_signed_up"] = False
login(
kwargs["request"],
user,
backend="allauth.account.auth_backends.AuthenticationBackend",
)
else:
# signed Up
kwargs["is_signed_up"] = True
user = self._create_user(**kwargs)
self.login(**kwargs)
kwargs["user"] = user
return kwargs
def _get_decoded_info(self, **decoded):
kwargs = {}
try:
first_name = decoded["given_name"]
except KeyError:
first_name = decoded["email"].split("@")[0]
if first_name:
kwargs["first_name"] = first_name
else:
kwargs["first_name"] = decoded.get("name").split(" ")[0]
kwargs["email"] = decoded["email"]
kwargs["last_name"] = decoded.get("family_name")
return kwargsThis is the code snippet for which we need an explanation. The result is below.
The result is awesome. It provided us with a detailed explanation of the code snippet. What does this code do, and what are the functions in the code and more? So, When you find yourself struggling with an unfamiliar and complex old code base, don’t worry! You can rely on Chat GPT as your reliable guide to help you understand and make sense of the confusing code.
4. Refactor the Code
Chat GPT can be a valuable ally in code refactoring endeavors. By presenting your existing code and describing the desired outcome, you can seek its assistance in optimizing and improving your codebase. Chat GPT can provide suggestions and alternative approaches to enhance the code’s efficiency, readability, and maintainability. It can identify redundant or complex code snippets, propose more concise and elegant solutions, and guide you through the refactoring process step by step.
It removed redundant code and optimize the code. It also provided us with an explanation for what it did.
5. Error finding in the Code
ChatGPT is a valuable resource when it comes to identifying errors in code. With its ability to understand programming languages and concepts, it can assist developers in finding and resolving various types of errors. When faced with syntax errors, simply sharing the problematic code snippet with ChatGPT allows it to analyze the structure and pinpoint any glaring syntax mistakes.
ChatGPT gives us the error-free and optimized code for the above snippet. Here is what we got.
Say goodbye to those tiresome hours spent wrestling with bugs, and allow ChatGPT to guide you towards flawless code. With its expertise, you’ll no longer have to struggle through the painstaking process of debugging.
6. Github Readme
ChatGPT proves to be an invaluable ally when it comes to crafting comprehensive and informative README files for GitHub repositories. Leveraging its vast knowledge and language generation capabilities, ChatGPT can assist in creating READMEs that captivate and engage potential users or collaborators. By providing relevant information about the project’s purpose, features, installation instructions, and usage guidelines, ChatGPT ensures that the README communicates the essence of the project effectively.
We asked ChatGPT to write a GitHub readme for a MERN stack project and it gave the full template for that.
7. Conversion of the code from one language to another
ChatGPT offers a remarkable capability to facilitate code conversion between different programming languages, easing the burden of manual translation. Leveraging its deep understanding of multiple programming languages, ChatGPT can help developers migrate code from one language to another with relative ease. By providing the original code in the source language and specifying the target language, developers can engage in interactive conversations with ChatGPT to receive accurate translations.
We gave a code snippet of Java and ask it to convert this into Python.
So, If you don’t know any programming language and are stuck with the code of an unknown language. Don’t worry, ask ChatGPT, it will do the job.
8. Unit Testcase
ChatGPT proves to be a valuable aid in the creation of unit test cases, offering assistance to developers in this critical aspect of software development. By leveraging its extensive knowledge and understanding of programming languages, ChatGPT can provide guidance and suggestions to ensure thorough test coverage.
We asked it to write some unit test cases on an authentication system of a site. Here is what we got.
It generated 12 unit test cases for our use-case. See, How easily we can get rid of this hectic task. Although, you have to check whether the result matches your requirements. But, surely it had reduced the time and effort.
9.Documentation of the code
ChatGPT can understand the code structure and purpose, allowing it to generate accurate and detailed documentation. This documentation can include explanations of functions, methods, and classes, as well as examples of how they can be used. ChatGPT can also provide guidance on best practices and potential pitfalls to avoid. By utilizing ChatGPT’s natural language generation capabilities, developers can save time and ensure that their code is well-documented, making it easier for others to understand and maintain in the future.
Below is the code snippet of reversing a binary tree.
Documentation of above code snippet by chat GPT is below
Conclusion
In conclusion, ChatGPT, a large language model trained by OpenAI, can be a valuable tool for developers in a variety of ways. Its ability to generate natural language responses to complex questions, generate code, summarize text, and perform other language-based tasks can save developers time and effort.
ChatGPT can also be used for a wide range of applications, from developing chatbots to natural language processing and machine translation. It can help developers improve the accuracy and efficiency of their models by generating training data, testing models, and providing insights into the performance of their algorithms.
Overall, ChatGPT has the potential to revolutionize the way developers approach language-based tasks and accelerate the development of natural language-based applications. As the technology behind it continues to improve, ChatGPT will likely become an increasingly powerful tool for developers and other professionals who work with natural language data.