all_features.sfast

"""
This code uses a lot of features of SimpleFast, including variables, lists, functions, classes, objects, machine learning, 
and asynchronous I/O. It's written in a simplified style to make it easier for a 10-year-old to understand. 
Of course, real programs would be much more complex and might not have all these features in one file.

Please note that this code won't actually run because SimpleFast, mlib, and the asynchronous I/O features don't really exist.
This is just an example to show what the syntax might look like.
"""

# This is a comment. It's like a note to yourself or to others who read your code!
# Let's start with printing Hello, World! It's like your program's first words!
print 'Hello, World!'

# Now, let's create a variable. It's like a box where you can keep things!
let my_favorite_number be 7
print 'My favorite number is: {my_favorite_number}'

# You can also create a list, which is like a row of boxes!
let my_favorite_colors be ['red', 'blue', 'green']
print 'My favorite colors are: {my_favorite_colors}'

# Let's make a function. It's like a little machine that does something for you!
define function say_hello with parameters name:
    print 'Hello, {name}!'
end function

# Now we can use our function!
say_hello 'Alice'

# We can also create a class. It's like a blueprint for creating objects!
define class Dog with parameters name, breed:
    let sound be 'woof'

    define method bark:
        print '{name} says {sound}!'
    end method
end class

# Now we can create a Dog object!
let my_dog be new Dog 'Rex', 'Golden Retriever'
my_dog.bark

# Let's do some machine learning! Imagine we have a machine learning library called mlib.
import mlib

define function train_model with parameters X, y:
    let model be new mlib.LinearRegression
    model.fit X, y
    return model
end function

# Let's pretend X and y are some data we have. Let's train a model!
let X be [[1], [2], [3], [4], [5]]
let y be [2, 4, 6, 8, 10]
let model be train_model X, y

# Now, we can use the model to predict something!
let prediction be model.predict [[6]]
print 'Prediction for input 6: {prediction}'

# Let's try to do some asynchronous I/O. This is like doing many things at the same time!
define async function fetch_data with parameters url:
    let response be await http.get url
    return response.body
end function

# Now, we can use the fetch_data function to get some data from the internet!
let data be await fetch_data 'http://example.com/data'
print 'Data: {data}'