The One Prompt to Generate Them All: The Ultimate ChatGPT Tool for Developers, Say Goodbye to Language Barriers.
The world of programming languages is vast and diverse, with each language having its strengths and weaknesses. As a developer, it can be daunting to learn and master multiple languages, especially when working on complex projects that require multiple programming languages. However, what if there was a tool that could generate code in any programming language, using a simple pseudo-code formatted as a YAML file? This is where the ultimate ChatGPT prompt comes in.
ChatGPT is a large language model developed by OpenAI, based on the GPT-3.5 architecture. It is a powerful tool that can generate natural language text, including code, based on prompts provided to it. With the ultimate ChatGPT prompt, you can ask ChatGPT to generate code in any programming language it knows using a simple YAML file.
YAML is a human-readable data serialization language that is commonly used for configuration files and data exchange between languages. It is simple and easy to read, making it a great format for the ultimate ChatGPT prompt. The YAML file contains the instructions and variables that ChatGPT needs to generate the code.
To use the ultimate ChatGPT prompt, you simply need to create a YAML file with the necessary information. The YAML file should contain a list of instructions and variables that ChatGPT will use to generate the code. For example, if you want to generate a function that calculates the area of a rectangle, your YAML file might look like this:
The Ultimate Prompt
Using the provided yaml, please create the [INSERT LANGUAGE HERE] code [DESCRIBE BRIEFLY THE FUNCTIONS YOU EXPECT].
[YAML CODE]
Example: “Using the provided yaml, please create a ReactJs code that grabs the Variables in a form and posts them to SQL”
Variables:
- name: text
- age: integer
- email: email
- ticket: textarea
- status: bool
SQL:
- server: Oracle
- tablename: clients
Columns:
- name: varchar2(50)
- age: integer(2)
- email: varchar2(50)
- ticket: varchar2(255)
- status: bool
Actions:
- Submit
- ResetOnce you have created the YAML file, you can submit it to ChatGPT, which will generate the code in the specified programming language. ChatGPT will use natural language processing to understand the instructions and variables in the YAML file and generate the corresponding code.
Here are some example outputs of the prompt:
ReactJS
<form onSubmit={handleSubmit} onReset={handleReset}>
<label>
Name:
<input
type="text"
name="name"
value={formData.name}
onChange={handleInputChange}
/>
</label>
<label>
Age:
<input
type="number"
name="age"
value={formData.age}
onChange={handleInputChange}
/>
</label>
<label>
Email:
<input
type="email"
name="email"
value={formData.email}
onChange={handleInputChange}
/>
</label>
<label>
Ticket:
<textarea
name="ticket"
value={formData.ticket}
onChange={handleInputChange}
/>
</label>
<label>
Status:
<input
type="checkbox"
name="status"
checked={formData.status}
onChange={handleInputChange}
/>
</label>
<button type="submit">Submit</button>
<button type="reset">Reset</button>
</form>
<script>
const [formData, setFormData] = useState({
name: "",
age: 0,
email: "",
ticket: "",
status: false
});
const handleInputChange = (event) => {
const { name, value } = event.target;
setFormData({ ...formData, [name]: value });
};
const handleSubmit = (event) => {
event.preventDefault();
const data = JSON.stringify(formData);
fetch("https://example.com/api/clients", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: data
})
.then((response) => response.json())
.then((data) => console.log(data))
.catch((error) => console.error(error));
};
const handleSubmit = (event) => {
event.preventDefault();
const data = JSON.stringify(formData);
fetch("https://example.com/api/clients", {
method: "POST",
headers: { "Content-Type": "application/json" },
body: data
})
.then((response) => response.json())
.then((data) => console.log(data))
.catch((error) => console.error(error));
};
const handleReset = () => {
setFormData({
name: "",
age: 0,
email: "",
ticket: "",
status: false
});
};
</script>Next, you can ask ChatGPT to translate the code to any language you want like Python for instance.
Python
import cx_Oracle
# Define the Oracle database connection details
dsn_tns = cx_Oracle.makedsn('host', 'port', service_name='service_name')
conn = cx_Oracle.connect(user='username', password='password', dsn=dsn_tns)
# Define the SQL statement to insert data into the clients table
insert_sql = "INSERT INTO clients (name, age, email, ticket, status) VALUES (:name, :age, :email, :ticket, :status)"
# Define the function to handle form submission
def handle_submit(data):
# Execute the SQL statement to insert data into the clients table
cursor = conn.cursor()
cursor.execute(insert_sql, data)
cursor.close()
conn.commit()
conn.close()
# Define the function to handle form reset
def handle_reset():
pass # Do nothing for now
# Define the form data as a dictionary
formData = {
'name': 'John Smith',
'age': 30,
'email': 'john.smith@example.com',
'ticket': 'Lorem ipsum dolor sit amet, consectetur adipiscing elit.',
'status': True
}
# Call the handle_submit function with the form data
handle_submit(formData)Just for fun I also tried C#…
C#
using Oracle.ManagedDataAccess.Client;
using System;
using System.Collections.Generic;
class Program
{
// Define the Oracle database connection details
private const string connectionString = "Data Source=host:port/service_name;User Id=username;Password=password;";
// Define the SQL statement to insert data into the clients table
private const string insertSql = "INSERT INTO clients (name, age, email, ticket, status) VALUES (:name, :age, :email, :ticket, :status)";
static void Main()
{
// Define the form data as a dictionary
var formData = new Dictionary<string, object>
{
{ "name", "John Smith" },
{ "age", 30 },
{ "email", "john.smith@example.com" },
{ "ticket", "Lorem ipsum dolor sit amet, consectetur adipiscing elit." },
{ "status", true }
};
// Call the HandleSubmit function with the form data
HandleSubmit(formData);
}
// Define the function to handle form submission
private static void HandleSubmit(Dictionary<string, object> data)
{
// Connect to the Oracle database
using (var conn = new OracleConnection(connectionString))
{
conn.Open();
// Create a command object with the SQL statement and parameters
using (var cmd = new OracleCommand(insertSql, conn))
{
cmd.Parameters.Add("name", OracleDbType.Varchar2).Value = data["name"];
cmd.Parameters.Add("age", OracleDbType.Int32).Value = data["age"];
cmd.Parameters.Add("email", OracleDbType.Varchar2).Value = data["email"];
cmd.Parameters.Add("ticket", OracleDbType.Varchar2).Value = data["ticket"];
cmd.Parameters.Add("status", OracleDbType.Boolean).Value = data["status"];
// Execute the command to insert data into the clients table
cmd.ExecuteNonQuery();
}
// Disconnect from the Oracle database
conn.Close();
}
}
// Define the function to handle form reset
private static void HandleReset()
{
// Do nothing for now
}
}The ultimate ChatGPT prompt is a powerful tool that can save developers time and effort when working with multiple programming languages. It can also help beginners learn new programming languages by generating code in a familiar language that they already know.
However, it is important to note that while ChatGPT is a powerful tool, it is not perfect. The generated code may not always be optimal, and it is still important for developers to have a good understanding of the programming language they are working with. Additionally, the ultimate ChatGPT prompt may not support all programming languages, so it is important to check the list of supported languages before using it.
So in conclusion, the ultimate ChatGPT prompt is a powerful tool that can generate code in any programming language it knows using a simple YAML file. It can save developers time and effort when working with multiple programming languages, and help beginners learn new programming languages. However, it is important to use it wisely and understand its limitations.
Disclaimer:
The code examples provided earlier are for illustrative purposes only and have not been fully tested. We strongly advise against running the code unless you have a solid understanding of its functionality and structure. Please use the examples at your own risk and exercise caution when working with code or software.
