o3-mini has confirmed to be OpenAI’s most superior mannequin for coding and reasoning. The o3-mini (excessive) mannequin has single-handedly outperformed different current fashions like DeepSeek-R1 and Claude 3.5 in most traditional benchmark checks. Owing to this, ChatGPT powered by o3-mini has now grow to be an on a regular basis companion for builders. It provides them an clever and environment friendly solution to sort out programming challenges—be it debugging, code era, documentation, or knowledge cleansing. This text lists 10 ChatGPT prompts that may assist you unlock the complete potential of o3-mini in your coding duties. So, let’s get began!
1. Debugging Code Errors
Suppose you might be engaged on a Python script for an internet app, and immediately, you encounter an error that you simply don’t perceive. The traceback message is lengthy and complicated, and you might be uncertain the right way to repair it. o3-mini provides a fast solution to debug the problem and perceive what went flawed.
Template Immediate: “I’ve a bit of code in [language] that’s throwing an error: [error message]. Are you able to assist me debug it? [insert code]”
Pattern Immediate:
“I’ve a bit of Python code that’s throwing an error: AttributeError: ‘NoneType’ object has no attribute ‘group’. Are you able to assist me debug it?”
import pandas as pd
# Pattern knowledge
knowledge = {
"Product": ["Laptop", "Headphones", "Smartphone", "Monitor", "Mouse"],
"Class": ["Electronics", "Electronics", "Electronics", "Accessories", "Accessories"],
"Gross sales": ["$1000", "$200", "$800", "$300", "$50"] # Gross sales values include a '$' signal
}
df = pd.DataFrame(knowledge)
# Convert Gross sales column to drift
df["Sales"] = df["Sales"].astype(float) # 🚨 This line throws a ValueError
# Calculate complete gross sales per class
total_sales = df.groupby("Class")["Sales"].sum()
print(total_sales)
Output of Code:
o3-mini’s Response:
import pandas as pd
# Pattern knowledge
knowledge = {
"Product": ["Laptop", "Headphones", "Smartphone", "Monitor", "Mouse"],
"Class": ["Electronics", "Electronics", "Electronics", "Accessories", "Accessories"],
"Gross sales": ["$1000", "$200", "$800", "$300", "$50"] # Gross sales values include a '$' signal
}
df = pd.DataFrame(knowledge)
# Convert Gross sales column to drift after stripping '$'
df["Sales"] = df["Sales"].str.change("$", "").astype(float) # ✅ Mounted: Eliminated foreign money symbols
# Calculate complete gross sales per class
total_sales = df.groupby("Class")["Sales"].sum()
print(total_sales)
Output of Code:

2. Making a Code Template
When you’ve got a brand new challenge at hand, it will possibly usually be complicated on the place to begin. There could also be totally different approaches, or a number of steps concerned, or it could require libraries you aren’t conversant in. In such instances, o3-mini will help you get began with a fundamental code template and information you thru writing the complete code.
Template Immediate: “Are you able to present a structured template and information for writing a [language] challenge that does [task]?”
Pattern Immediate:
“Are you able to present a structured template and information for establishing a Python Flask challenge that connects to a PostgreSQL database?”
o3-mini’s Response:
3. Changing Code Between Languages
Let’s say you’ve got a bit of code written in a single programming language, however your challenge requires it in one other. As a substitute of rewriting it manually, o3-mini can translate the code for you, preserving the logic and performance.
Template Immediate: “Can you change this [source language] code to [target language] whereas sustaining logic and performance?”
Pattern Immediate:
“Can you change this Python code to JavaScript (Node.js) whereas sustaining its logic and performance?”
from collections import Counter
# Pattern textual content enter
textual content = """
It is a pattern textual content. This textual content is supposed to check phrase frequency.
Some phrases seem greater than as soon as, some phrases seem solely as soon as.
"""
# Convert to lowercase and break up into phrases
phrases = textual content.decrease().break up()
# Depend phrase occurrences
word_counts = Counter(phrases)
# Print outcomes
for phrase, rely in word_counts.objects():
print(f"{phrase}: {rely}")
Output of Code:

o3-mini’s Response:
// Pattern textual content enter
let textual content = `
It is a pattern textual content. This textual content is supposed to check phrase frequency.
Some phrases seem greater than as soon as, some phrases seem solely as soon as.
`;
// Convert to lowercase and break up into phrases
let phrases = textual content.toLowerCase().change(/[^ws]/g, "").break up(/s+/);
// Depend phrase occurrences
let wordCounts = new Map();
phrases.forEach(phrase => 0) + 1);
);
// Print outcomes
wordCounts.forEach((rely, phrase) => {
console.log(`${phrase}: ${rely}`);
});
Output of Code:

4. Enhancing Code Readability
Whereas writing code for work, it can be crucial that the code be readable and straightforward for all stakeholders to grasp. For this, you’ll have to write down documentation, add code feedback, or refactor the code for higher readability. In such instances, o3-mini will be of nice assist.
Template Immediate: “Are you able to generate docstrings and feedback for this [language] perform?[insert code]”
OR “Are you able to refactor this [language] code to make it extra readable?[insert code]”
Pattern Immediate:
“Are you able to add docstrings and feedback to this Python perform that processes person enter and updates a database?”
import sqlite3
def update_user_balance(user_id, quantity):
conn = sqlite3.join("database.db")
cursor = conn.cursor()
current_balance = cursor.execute("SELECT stability FROM customers WHERE id = ?", (user_id,)).fetchone()
if current_balance:
new_balance = current_balance[0] + quantity
cursor.execute("UPDATE customers SET stability = ? WHERE id = ?", (new_balance, user_id))
conn.commit()
conn.shut()
return new_balance
else:
conn.shut()
return None
o3-mini’s Response:
import sqlite3
def update_user_balance(user_id, quantity):
"""
Updates the stability of a person within the database.
Parameters:
user_id (int): The distinctive ID of the person whose stability must be up to date.
quantity (float): The quantity so as to add to (or subtract from) the person's stability.
Returns:
float: The up to date stability if the person exists.
None: If the person doesn't exist within the database.
"""
# Hook up with the SQLite database
conn = sqlite3.join("database.db")
cursor = conn.cursor()
# Fetch the present stability of the person
current_balance = cursor.execute(
"SELECT stability FROM customers WHERE id = ?", (user_id,)
).fetchone()
if current_balance:
# Calculate the brand new stability
new_balance = current_balance[0] + quantity
# Replace the person's stability within the database
cursor.execute(
"UPDATE customers SET stability = ? WHERE id = ?", (new_balance, user_id)
)
# Commit the transaction
conn.commit()
# Shut the connection
conn.shut()
return new_balance # Return the up to date stability
else:
# Shut the connection if person doesn't exist
conn.shut()
return None # Return None if person ID isn't discovered
5. Writing Code for Edge Instances and Error Dealing with
You’re making an API request in Python, however your code doesn’t deal with instances the place the request fails. It’s essential to add error dealing with to make it extra sturdy.
Template Immediate: “Are you able to add correct error dealing with to this [language] perform? [insert function]”
Pattern Immediate:
“Are you able to add correct error dealing with to this Python perform making an API request?”
import requests
response = requests.get("https://api.instance.com/knowledge")
knowledge = response.json()
o3-mini’s Response:
import requests
def fetch_api_data(url):
"""
Fetches knowledge from the given API URL with correct error dealing with.
Parameters:
url (str): The API endpoint to request knowledge from.
Returns:
dict or None: The JSON response as a dictionary if profitable, or None if an error happens.
"""
strive:
response = requests.get(url, timeout=10) # Set a timeout to keep away from hanging requests
response.raise_for_status() # Elevate an error for HTTP errors (4xx and 5xx)
return response.json() # Parse and return JSON response
besides requests.exceptions.Timeout:
print("Error: The request timed out.")
besides requests.exceptions.ConnectionError:
print("Error: Failed to connect with the server.")
besides requests.exceptions.HTTPError as err:
print(f"HTTP Error: {err}")
besides requests.exceptions.RequestException as err:
print(f"Request Error: {err}")
besides ValueError:
print("Error: Unable to decode JSON response.")
return None # Return None if any error happens
# Instance utilization
api_url = "https://api.instance.com/knowledge"
knowledge = fetch_api_data(api_url)
if knowledge:
print("API Knowledge Retrieved Efficiently!")
else:
print("Didn't retrieve API knowledge.")
6. Writing CI/CD Pipeline Configurations
Let’s suppose your workforce is deploying a Node.js software, and also you’ve been assigned the duty of establishing an automatic CI/CD pipeline. It’s essential to configure GitHub Actions to run checks and deploy the app each time modifications are pushed to the primary department. Right here’s a easy immediate you should use on o3-mini to arrange the deployment pipeline.
Template Immediate: “Are you able to generate a CI/CD pipeline configuration for a [technology stack: React, MongoDB, Node.js, etc.] challenge utilizing [CI/CD tool: GitHub Actions, Jenkins, etc.] that runs checks and deploys to [deployment environment: AWS, AKS, GKE, etc.]?”
Pattern Immediate:
“Are you able to generate a CI/CD pipeline configuration for a Node.js challenge utilizing GitHub Actions that runs checks and deploys to AWS S3 on each push to the primary department?”
o3-mini’s Response:
identify: Node.js CI/CD Pipeline
on:
push:
branches:
- predominant # Runs the workflow on pushes to the primary department
jobs:
build-and-test:
identify: Construct and Take a look at
runs-on: ubuntu-latest
steps:
- identify: Checkout repository
makes use of: actions/checkout@v3
- identify: Arrange Node.js
makes use of: actions/setup-node@v3
with:
node-version: 18
- identify: Set up dependencies
run: npm set up
- identify: Run checks
run: npm check
- identify: Construct challenge
run: npm run construct
- identify: Add construct artifacts
makes use of: actions/upload-artifact@v3
with:
identify: build-output
path: dist/
- identify: Deploy to S3
env:
AWS_ACCESS_KEY_ID: ${{ secrets and techniques.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets and techniques.AWS_SECRET_ACCESS_KEY }}
AWS_REGION: "us-east-1" # Change to your AWS area
S3_BUCKET: "your-s3-bucket-name"
run: |
aws s3 sync dist/ s3://$S3_BUCKET --delete
7. Code Optimization and Efficiency Enchancment
Have you ever ever been in conditions the place your Python perform works nice, however runs slowly on massive datasets? If this has been a roadblock in getting your job performed, right here’s how o3-mini will help you optimize your code for extra environment friendly execution.
Template Immediate: “Are you able to optimize this code for efficiency? It at present has points with [mention inefficiencies] and runs slowly for [mention scenario]. [insert code]”
Pattern Immediate:
“Are you able to optimize this Python code for efficiency? It at present has inefficiencies in checking for prime numbers and runs slowly when trying to find primes in a wide variety (e.g., 1 to 100,000).”
def is_prime(n):
if n < 2:
return False
for i in vary(2, n):
if n % i == 0:
return False
return True
def find_primes(begin, finish):
primes = []
for num in vary(begin, finish + 1):
if is_prime(num):
primes.append(num)
return primes
# Instance utilization
start_range = 1
end_range = 10000
primes = find_primes(start_range, end_range)
print(f"Discovered {len(primes)} prime numbers.")
o3-mini’s Response:
import math
def is_prime(n):
"""Test if a quantity is prime."""
if n < 2:
return False
if n == 2:
return True # 2 is the one even prime quantity
if n % 2 == 0:
return False # Eradicate even numbers > 2
# Test divisibility as much as √n
for i in vary(3, int(math.sqrt(n)) + 1, 2):
if n % i == 0:
return False
return True
def find_primes(begin, finish):
"""Discover all prime numbers in a given vary."""
primes = []
for num in vary(begin, finish + 1):
if is_prime(num):
primes.append(num)
return primes
# Instance utilization
start_range = 1
end_range = 10000
primes = find_primes(start_range, end_range)
print(f"Discovered {len(primes)} prime numbers.")

Output of Code:

8. Producing Common Expressions (Regex)
o3-mini will be very useful in producing common expressions in code. Suppose you’re constructing a kind validation system for a web site and want a regex sample to validate electronic mail addresses. Simply ask o3-mini to generate a regex sample utilizing this immediate.
Template Immediate: “Are you able to generate a regex sample in [language] for [task]?”
Pattern Immediate:
“Are you able to generate a regex sample in Python for validating electronic mail addresses?”
o3-mini’s Response:
import re
# Common expression for electronic mail validation
email_pattern = r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+.[a-zA-Z0-9-.]+$"
# Operate to validate emails
def is_valid_email(electronic mail):
return re.match(email_pattern, electronic mail) isn't None
Output of Code:

9. Aiding with Knowledge Cleansing and Processing
Whereas analyzing buyer gross sales knowledge in Pandas, you usually come throughout messy datasets, lacking values, duplicate entries, and knowledge in a number of codecs. Utilizing the next immediate on o3-mini is an environment friendly solution to clear the info earlier than operating your evaluation.
Template Immediate: “Are you able to assist clear and course of a dataset with points reminiscent of [list data issues] utilizing [programming language and library]? [insert dataset]”
Pattern Immediate:
“Are you able to assist clear and course of a dataset with lacking values, duplicate rows, incorrect date codecs, and inconsistent capitalization utilizing Python and Pandas? clients.csv”
o3-mini’s Response:
import pandas as pd
# Load the dataset
df = pd.read_csv("clients.csv")
# Standardize column names (take away areas and convert to lowercase)
df.columns = df.columns.str.strip().str.decrease().str.change(" ", "_")
# Deal with lacking values
df["age"].fillna(df["age"].median(), inplace=True) # Fill lacking ages with median
df["purchase_amount"].fillna(df["purchase_amount"].imply(), inplace=True) # Fill lacking purchases with imply
# Take away duplicate rows
df = df.drop_duplicates()
# Standardize textual content knowledge (capitalize names and cities)
df["name"] = df["name"].str.title()
df["city"] = df["city"].str.title()
df["country"] = df["country"].str.higher()
# Convert dates to a constant format
df["join_date"] = pd.to_datetime(df["join_date"], errors="coerce", dayfirst=False)
# Save the cleaned dataset
df.to_csv("cleaned_customers.csv", index=False)
print("Knowledge cleansing accomplished efficiently!")
Output of Code:

10. Writing Shell Scripts for Automation
I’m certain you’ll agree with me after I say numerous our work is repetitive in nature – be it incessantly deploying functions or backing up recordsdata. As a substitute of operating these instructions manually each time, o3-mini will help you automate them by coding. It could actually write you shell scripts to automate repetitive terminal instructions primarily based in your necessities.
Template Immediate: “Are you able to write a shell script to automate [task] utilizing [specific tools or commands]?”
Pattern Immediate:
“Are you able to write a shell script to mechanically again up a listing (/house/person/paperwork) to a different location (/mnt/backup) day-after-day at midnight utilizing cron?”
o3-mini’s Response:
1️. Shell Script (backup.sh)
<pre class="wp-block-code"><code>#!/bin/bash
# Outline supply and vacation spot directories
SOURCE="/house/person/paperwork"
DESTINATION="/mnt/backup"
TIMESTAMP=$(date +"%Y-%m-%d_percentH-%M-%S")
BACKUP_DIR="$DESTINATION/backup_$TIMESTAMP"
# Create backup listing
mkdir -p "$BACKUP_DIR"
#Copy recordsdata whereas preserving attributes
rsync -av --delete "$SOURCE/" "$BACKUP_DIR/"
# Log the backup
2️. Make the Script Executable
Run the next command to provide the script execution permissions:
chmod +x /path/to/backup.sh
3️. Schedule Each day Backup at Midnight with Cron
Open the crontab editor:
crontab -e
Add this line on the finish:
0 0 * * * /path/to/backup.sh
This schedules the script to run every day at midnight (00:00).
Conclusion
As we now have on this article, o3-mini is able to dealing with every kind of coding duties from debugging advanced errors and optimizing code for higher efficiency, to writing CI/CD configurations, and changing code between languages. In a approach, o3-mini has redefined how builders method coding challenges by offering clever, environment friendly, and correct options. So go forward, check out these prompts, and let o3-mini assist you work smarter, not more durable!
Incessantly Requested Questions
A. o3-mini is OpenAI’s most superior mannequin for coding and reasoning. It outperforms fashions like DeepSeek-R1 and Claude 3.5 in benchmark checks, making it a dependable selection for builders.
A. Sure, o3-mini can analyze error messages, determine the basis trigger, and recommend fixes for varied programming languages. The above coding prompts will help you leverage o3-mini for these duties.
A. Completely! o3-mini can help with Python, JavaScript, Java, C++, Rust, Go, and lots of extra languages.
A. Sure, you possibly can ask o3-mini to generate structured templates for initiatives, together with frameworks like Flask, Django, React, and Node.js.
A. o3-mini gives extremely correct code translations whereas sustaining logic and performance, making it simpler to adapt code for various tech stacks.
A. Sure, it will possibly analyze your code and recommend optimizations to enhance pace, reminiscence utilization, and effectivity. The o3-mini immediate template given within the above article will help you with such coding duties.
A. It could actually generate docstrings, add significant feedback, and refactor messy code to make it extra readable and maintainable.
A. Sure, it will possibly generate CI/CD pipeline scripts for instruments like GitHub Actions, Jenkins, and GitLab CI/CD. You need to use the o3-mini immediate template given within the above article on ChatGPT for this.