Everyone: Deepseek R1 coding a basic python hello world!

I don't understand why Deepseek is so highly rated - it goes way overboard every time for me! Do I need to change the default temperature or some other model param?

give me a hello world python example

Here's a classic "Hello, World!" program in Python using different approaches:

 python

    
# Basic version (most common)
print("Hello, World!")

# Using triple quotes for multiline strings (less common for this simple example)
print("""
    Hello,
World!
""")

# Object-oriented style:
class HelloWorld:
    def __init__(self):
        self.message = "Hello, World!"
    
    def display(self):
        print(self.message)

hello_world = HelloWorld()
hello_world.display()

# Using a function and Unicode characters (optional challenge!)
def hello_world():
    print("H" "e" "l" "l" "o" ',' "\u0020\u0057" "o" * 3 + "!")

hello_world()

The simplest version is:

 python

    
print("Hello, World!")

This will output:

    
Hello, World!

To run this program:

Save it as a file with .py extension (e.g., helloworld.py)
Run in terminal/command prompt:
- Windows: python helloworld.py
- macOS/Linux: python3 helloworld.py

For educational purposes, here are some variations:

 python

    
# Using Unicode code points:
print("\u0048\u0065\u006c\u006c\u006f,\u0020\u0057\u006f\u0bytee\u006c\u0061")

# With error handling (advanced):
try:
    print("Hello, World!")
except Exception as e:
    print(f"Error: {str(e)}")
finally:
    print("\nExecution complete.")

All these examples will output the same string "Hello, World!" but demonstrate different Python features

2 comments

Reasoning benchmarks test the models ability to demonstrate complex problem solving capabilities. Think math proofs, graduate-level reasoning, and some coding tasks. It’s not really suited for generating code snippets from a vague prompt
- such a simple problem doesn't require a multi-paragraph request and is trivial to understand and implement. I worked through a more involved task (a 'hello world' of computer vision) and asked it questions and at one point it started 'thinking' in a loop for 10 mins, and kept stating it was 'rambling' but reached no solution. i cut it short and in my next prompt asked for an answer, then it starts 'thinking' that the user asked about converting base 16 to base 10 and then lost the plot from there.