How to use ChatGPT for Python programming

Translator | Cui Hao​

Reviewer | Sun Shujuan

Opening Chapter

ChatGPT is an artificial intelligence language model developed by OpenAI. The model is trained on large amounts of text data, and it can produce human-like responses to natural language. This allows it to be used in a wide range of areas such as chatbots, language translation, and text generation. Of course, you can also use it to write code. ​

ChatGPT’s output effect is particularly good. Elon Musk, the founder of Tesla, said: ChatGPT’s evaluation is as follows: “ChatGPT is surprisingly good, and we are not far away from powerful artificial intelligence.”​

As a Python programmer in 2023, you can use ChatGPT for programming. For example, if you are unfamiliar with Python libraries used in data science, you can turn to ChatGPT for help. Alternatively, if you need a script that generates specific events, you can also ask ChatGPT for help. Typically, developers use Google for these tasks. But with the tool ChatGPT, it allows you to get better results. Therefore, you can use ChatGPT instead of Google. ​

How to use ChatGPT via API​

There are multiple ways to use ChatGPT . You can log in to the OpenAI website and directly use the Q&A function of ChatGPT. You can also use ChatGPT through API requests, which can make your work more efficient. You can also integrate the ChatGPT API into used in IDE. ​

If you use VScode, you can create a Python script and send the terminal question request to ChatGPT API. You just need to prepare the OpenAPI key. Below I will provide an example of a Python script that sends a request to OpenAPI:

import openai
openai.api_key = "YOUR_API_KEY" #Insert you API key here
messages = []
system_msg = input("What type of chatbot would you like to create? ")
messages.append({"role": "system", "content": system_msg})

print("Say hello to your new assistant!")
while input != "quit()": 
message = input()
messages.append({"role": "user", "content": message})
response = openai.ChatCompletion.create(
model="gpt-3.5-turbo",
messages=messages)
reply = response["choices"][0]["message"]["content"]
messages.append({"role": "assistant", "content": reply})
print("n" + reply + "n")

Assume that the above program is saved to Python help.py file and execute the script, you will get the following results: ​

By code,We can run ChatGPT as a chatbot and can also help you complete the code of preparation. In this case, we can use ChatGPT to write Python code. ​

Use Case #1: Debugging Code​

You can use ChatGPT to debug code. If you encounter an exception, you can use ChatGPT to help you generate a useful response. Note that this tool is not designed for debugging, but for general conversation. Although using it may not provide valuable information, it still provides potential solutions and ideas for you to solve the problem. ​

Use Case #2: Generate Data​

If you often process JSON data , you can use ChatGPT to generate fake data. For example, if you need to create a workplace database and want to populate it with some fake data for testing, you can ask ChatGPT to create some data based on your requirements. Look at the example below: ​

Use Case #3: Asking Questions

But the best way to use ChatGPT is to ask it questions about Python programming. For example, you want to use the Numpy library for data analysis, but you are not familiar with Numpy's methods and properties. You can read Numpy's official documentation to get the answer. A faster way is to ask ChatGPT directly, at which point ChatGPT acts like an experienced Python Numpy developer. Rather than spending time reading documentation, ask ChatGPT specific questions and it will provide you with a satisfactory answer. ​The following is an example:

​

Conclusion​

This article lists several ways to use ChatGPT in Python programming. At the same time, you can also use other features of ChatGPT for natural language processing, such as work summary or sentiment analysis.

​ Overall, ChatGPT can help with various Python programming tasks, especially those related to nature. Tasks related to language processing and data analysis. Language modeling capabilities and flexibility make ChatGPT a valuable asset for developers and data scientists.

​Translator Introduction

Cui Hao, 51CTO community editor, senior architect Teacher, has 18 years of experience in software development and architecture, and 10 years of experience in distributed architecture. ​

##Original title:

​​How to Use ChatGPT for Python Programming​​, by Michael Garbade​##

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