Python Gotcha: Why Your Dictionary Copy Isn't What You Think

Hey there, future coders! 👋

If you're learning Python, you've undoubtedly fallen in love with dictionaries. They're these incredibly versatile objects that let you store and manage data in a way that just makes sense. But there’s a common beginner hurdle that trips up almost everyone at least once: copying them.

You might have written code that looks like this:

python

original_dict = {"name": "Alice", "course": "Python Fundamentals"}
new_dict = original_dict

new_dict["course"] = "Advanced Algorithms"

print("New Dict:", new_dict)
print("Original Dict:", original_dict)

And then you stare at the output in disbelief:

text

New Dict: {'name': 'Alice', 'course': 'Advanced Algorithms'}
Original Dict: {'name': 'Alice', 'course': 'Advanced Algorithms'}

"Hold on," you think. "I only changed new_dict! Why did original_dict change too?"

If this has happened to you, don't worry. You haven't broken logic. You've just stumbled upon a key concept in Python (and programming in general): assignment vs. copying.

The Problem: Two Names, One Dictionary

When you write new_dict = original_dict, you are not creating a new, independent dictionary. What you're actually doing is creating a new name (new_dict) that points to the exact same dictionary object in your computer's memory.

It’s like having two remote controls for the same TV. Using either remote changes the one and only TV. original_dict and new_dict are both remotes controlling the same data.

So how do we get a second, independent TV? We need to make a true copy.

The Solutions: How to Actually Copy a Dictionary

Python provides a couple of straightforward ways to create a separate copy.

1. The copy() Method (Shallow Copy)

This is the most common and explicit way to create a clone of your dictionary.

python

original_dict = {"name": "Alice", "course": "Python Fundamentals"}
new_dict = original_dict.copy()  # This is the key!

new_dict["course"] = "Advanced Algorithms"

print("New Dict:", new_dict)
# Output: New Dict: {'name': 'Alice', 'course': 'Advanced Algorithms'}

print("Original Dict:", original_dict)
# Output: Original Dict: {'name': 'Alice', 'course': 'Python Fundamentals'} # 🎉 It's unchanged!

By using .copy(), we've created a new dictionary object, and now changes to one don't affect the other. This is called a shallow copy, and it works perfectly for most simple dictionaries.

2. The dict() Constructor

You can also create a copy by passing the original dictionary to the dict() constructor.

python

new_dict = dict(original_dict)

This works exactly the same as .copy() for our purposes here. It's a matter of personal preference which one you use.

A Word of Caution: Shallow vs. Deep Copy

Now, let's add a twist. What if your dictionary contains another mutable object, like a list?

python

import copy

original_dict = {"name": "Bob", "topics": ["Variables", "Loops"]}
shallow_copy = original_dict.copy()

# Let's change the list inside the copy
shallow_copy["topics"].append("Dictionaries")

print("Shallow Copy:", shallow_copy)
print("Original Dict:", original_dict)

Uh oh. The output might surprise you again:

text

Shallow Copy: {'name': 'Bob', 'topics': ['Variables', 'Loops', 'Dictionaries']}
Original Dict: {'name': 'Bob', 'topics': ['Variables', 'Loops', 'Dictionaries']}

The original was modified again! Why? A shallow copy only copies the references to the inner objects, not the inner objects themselves. The inner list is still the same one in memory.

To solve this, we need a deep copy.

3. The deepcopy() Method

For dictionaries containing nested lists, other dictionaries, or custom objects, you need the deepcopy() function from the copy module.

python

import copy

original_dict = {"name": "Bob", "topics": ["Variables", "Loops"]}
deep_copy = copy.deepcopy(original_dict)  # This is the key!

deep_copy["topics"].append("Dictionaries")

print("Deep Copy:", deep_copy)
# Output: Deep Copy: {'name': 'Bob', 'topics': ['Variables', 'Loops', 'Dictionaries']}

print("Original Dict:", original_dict)
# Output: Original Dict: {'name': 'Bob', 'topics': ['Variables', 'Loops']} # 🎉 Perfect!

A deep copy creates a new object and then recursively copies all objects found within the original, creating a fully independent clone.

Quick Recap

• = (Assignment): Creates a new reference to the same object. Not a copy.

• .copy() (Shallow Copy): Creates a new dictionary object but reuses the inner objects. Great for simple, one-level dictionaries.

• copy.deepcopy() (Deep Copy): Creates a new dictionary and entirely new copies of all inner objects. Essential for complex, nested dictionaries.

Understanding these concepts is crucial for writing predictable and bug-free code. It’s one of those foundational skills that separates beginners from proficient developers.

Visit codercrafter.in today to enroll and start building your future!

Unlocking Your Data: A Beginner's Guide to Looping Through Python Dictionaries

So, you've started your Python journey and you've gotten comfortable with dictionaries. You know they're amazing for storing data in key-value pairs, like a digital contact book or a mini-database. But now you have this dictionary full of information, and a question pops into your head:

"How do I actually get in there and work with all this data?"

The answer, my friend, is looping. Iterating over a dictionary is like getting a master key to every piece of data inside it. Today, we're going to walk through the three most common and useful ways to do it. Let's dive in!

Our Sample Dictionary: A Student's Profile

Let's create a dictionary we can use for all our examples. It feels more real than just dict1 or my_dict, right?

python

student_profile = {
    "name": "Anika",
    "age": 22,
    "course": "Full Stack Development",
    "skills": ["Python", "JavaScript", "HTML/CSS"],
    "graduated": False
}

Our goal is to loop through student_profile and access everything inside.

Method 1: Looping Through Keys (The Default Behavior)

This is the most straightforward method. When you loop over a dictionary directly with a for loop, Python automatically gives you the keys.

python

print("Keys in the student profile:")
for key in student_profile:
    print(f"- {key}")

# Output:
# - name
# - age
# - course
# - skills
# - graduated

Why is this useful? It's great for when you just need to check what's in the dictionary or if a specific key exists. Once you have the key, you can always access its value inside the loop.

python

for key in student_profile:
    value = student_profile[key]  # Use the key to get the value
    print(f"The key '{key}' has the value: {value}")

Method 2: Looping Through Values Directly (.values())

What if you don't care about the keys and just want to work with the values? Python has a method for that: .values().

python

print("All the values in the profile:")
for value in student_profile.values():
    print(f"- {value}")

# Output:
# - Anika
# - 22
# - Full Stack Development
# - ['Python', 'JavaScript', 'HTML/CSS']
# - False

When to use this: Imagine you want to calculate the average age from a dictionary of students or gather all the skills listed without worrying about which student they belong to. .values() is your go-to.

Method 3: The Powerhouse: Looping Through Both Keys and Values (.items())

This is, without a doubt, the most common and Pythonic way to loop through a dictionary. The .items() method returns both the key and its corresponding value simultaneously as a tuple, which we can unpack neatly into two variables.

python

print("Complete student profile:")
for key, value in student_profile.items():  # Notice the two variables!
    print(f"{key}: {value}")

# Output:
# name: Anika
# age: 22
# course: Full Stack Development
# skills: ['Python', 'JavaScript', 'HTML/CSS']
# graduated: False

See how clean that is? In one line, we get access to both pieces of information. This method is incredibly powerful and is used constantly in real-world projects for tasks like processing API responses, configuring settings, and much more.

Why .items() is a Developer's Best Friend

Let's make our example more practical. What if we want to format the output nicely?

python

for key, value in student_profile.items():
    # Let's make the key look nicer
    friendly_key = key.replace('_', ' ').title()
    print(f"{friendly_key}: {value}")

# Output:
# Name: Anika
# Age: 22
# Course: Full Stack Development
# Skills: ['Python', 'JavaScript', 'HTML/CSS']
# Graduated: False

Which Method Should You Use?

Here’s a quick cheat sheet:

• Need just the keys? Loop directly: for key in my_dict:

• Need just the values? Use .values(): for value in my_dict.values():

• Need both the key and the value? (You usually do). Use .items(): for k, v in my_dict.items():

Your Next Step

Mastering these looping techniques is a fundamental skill in Python programming. It's the first step towards manipulating data, building dynamic applications, and becoming a proficient developer.

If you enjoyed this tutorial and are serious about turning these basics into a career, this is exactly the kind of hands-on knowledge we build upon in our Full Stack Development and MERN Stack courses at CoderCrafter.

We don't just teach you syntax; we teach you how to solve problems and build real things.

Ready to write the next chapter of your story? Visit codercrafter.in to explore our courses and enroll today!