Lära Introduction to Functions in Python | Python Foundations for Chemists

A function in Python is a reusable block of code that performs a specific task. You define a function once and can use it as many times as needed throughout your program. Functions help organize code, reduce repetition, and make your work easier to read and maintain.

In chemistry, you often perform repetitive calculations, such as converting units, analyzing experimental data, or processing molecular formulas. Using functions, you can:

Break complex problems into smaller, manageable pieces;
Avoid rewriting code for the same calculation or analysis;
Share and reuse useful procedures across different projects;
Make your code more readable and easier to debug.

Understanding how to write and use functions will help you build powerful, flexible Python scripts for chemical data processing and analysis.


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def greet_chemist(name):
    print(f"Hello, {name}! Welcome to the chemistry lab.")

greet_chemist("Dr. Smith")

Function Parameters and Arguments

When you define a function, you specify parameters inside the parentheses. These are variable names that act as placeholders for the values you pass to the function.

When you call a function, you provide arguments — these are the actual values assigned to the parameters.


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def calculate_molarity(moles, volume_liters):
    return moles / volume_liters

result = calculate_molarity(0.5, 1.0)
print(result)

moles and volume_liters are parameters;
0.5 and 1.0 are arguments.

Default Values for Parameters

You can set a default value for a parameter. If you do not provide an argument for that parameter, Python uses the default value.


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def greet_chemist(name, greeting="Hello"):
    return f"{greeting}, {name}!"

message = greet_chemist("Dr. Smith")  # Uses default greeting
custom_message = greet_chemist("Dr. Lee", "Welcome")
print(message)
print(custom_message)

If you call greet_chemist("Dr. Smith"), greeting is set to "Hello";
If you call greet_chemist("Dr. Lee", "Welcome"), greeting is set to "Welcome".

Return Statements

A return statement ends a function and sends a value back to where the function was called. You can return the result of a calculation, a string, or any object.


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def calculate_energy(mass, c=3.00e8):
    energy = mass * c ** 2
    return energy

energy_joules = calculate_energy(0.002)
print(energy_joules)

return energy sends the value of energy back to the caller;
If a function does not have a return statement, it returns None by default.


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def calculate_molarity(moles, volume_liters=1.0):
    """
    Calculate the molarity of a solution.
    moles: amount of solute in moles
    volume_liters: volume of solution in liters (default is 1.0 L)
    Returns molarity in mol/L
    """
    molarity = moles / volume_liters
    return molarity

# Example usage:
sodium_chloride_moles = 0.5
solution_volume = 2.0
molarity = calculate_molarity(sodium_chloride_moles, solution_volume)
print("Molarity:", molarity, "mol/L")

# Using default volume (1.0 L)
default_molarity = calculate_molarity(0.2)
print("Molarity with default volume:", default_molarity, "mol/L")

Benefits of Using Functions

Using functions in Python offers several key advantages, especially when working on chemistry calculations and data processing:

Improve code reuse;
Increase modularity;
Enhance readability.

Code Reuse

You can define a function once and use it repeatedly. This is helpful for common chemistry calculations such as converting temperatures:

def celsius_to_kelvin(celsius):
    return celsius + 273.15

# Reuse the function for multiple temperatures
kelvin_1 = celsius_to_kelvin(25)
kelvin_2 = celsius_to_kelvin(100)

Modularity

Functions break complex problems into smaller, manageable parts. For example, you can separate data loading, cleaning, and analysis steps when processing chemical experiment data:

def load_data(filename):
    import pandas as pd
    return pd.read_csv(filename)

def clean_data(df):
    return df.dropna()

def analyze_data(df):
    return df['concentration'].mean()

Readability

Named functions make code easier to understand. Anyone reading your script can quickly see what each part does, such as calculating molar mass:

def calculate_molar_mass(mass, moles):
    return mass / moles

sample_mass = 10.0  # grams
sample_moles = 0.25  # moles
molar_mass = calculate_molar_mass(sample_mass, sample_moles)

By organizing your code with functions, you make your chemistry projects easier to maintain, extend, and share with others.

1. Which option correctly calls the function defined below?

2. Which statements about function parameters, default arguments, and return values are correct

3. Complete the function definition to calculate the concentration of a solution in mol/L, given the amount of solute (in moles) and the volume of the solution (in liters).

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