What is Python Copy Dictionaries?

Python Copy Dictionaries is a Python Tutorial lesson that explains copy dictionary python in Python. dict2 = dict1 copies the reference. Use copy() or dict() for a shallow copy. Copy the samples and run them in the Python editor. It is written for beginners who want a clear definition and working examples.

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What is the syntax of copy dictionary python?

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Python Copy Dictionaries example for beginners

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Python Tutorial

Python Copy Dictionaries

dict2 = dict1 copies the reference. Use copy() or dict() for a shallow copy.

← Loop Dictionaries Nested Dictionaries →

copy() and dict()

Shallow copies share nested objects. Use copy.deepcopy for nested dicts you must isolate.

thisdict = {"brand": "Ford", "model": "Mustang", "year": 1964}
print(thisdict.copy())
print(dict(thisdict))

📘 Real-World Deep Dive

Most "copy" of a dict is shallow, and that bites when nested values are mutated. Knowing the safe patterns (<code>copy.deepcopy</code>, dataclass <code>replace</code>, structured cloning) keeps code safe under mutation.

Real-Life Scenario

Clone a feature-flag snapshot before a destructive operation, then run an experiment on the clone without affecting the live config.

Real-Life Example

import copy
from dataclasses import dataclass, field, replace
from typing import Iterable

@dataclass
class FeatureFlags:
    env: str = "prod"
    allow_list: list[str] = field(default_factory=list)
    rates: dict[str, float] = field(default_factory=dict)

live = FeatureFlags(
    env="prod",
    allow_list=["v1", "v2"],
    rates={"new_signup": 0.05, "search_v2": 0.50},
)

# Shallow copy: share the inner lists/dicts.
shallow = copy.copy(live)
shallow.allow_list.append("rogue")              # affects live too!
print("live.allow_list    :", live.allow_list)
print("shallow.allow_list :", shallow.allow_list)

# Deep copy: independent, safe.
deep = copy.deepcopy(live)
deep.allow_list.append("experiment")
print("deep.allow_list    :", deep.allow_list)

# Best for dataclasses: replace() preserves frozen-ness.
@dataclass(frozen=True)
class FrozenFlags:
    env: str
    allow_list: tuple[str, ...]

flags = FrozenFlags(env="prod", allow_list=("v1", "v2"))
flags2 = replace(flags, allow_list=flags.allow_list + ("v3",))
print("frozen:", flags2)

Expected Output

live.allow_list    : ['v1', 'v2', 'rogue']
shallow.allow_list : ['v1', 'v2', 'rogue']
deep.allow_list    : ['v1', 'v2', 'experiment']

Common mistakes

copy.copy on a dict copies the outer dict but aliases inner objects.
dict(other) and other.copy() are both shallow — verify before mutating nested fields.
For very deep structures, copy.deepcopy can be slow or hit recursion limits — consider reconstruction.

🚀 Performance & Best Practices

For dataclasses, dataclasses.replace is faster than copy.deepcopy.
For picklable objects, copyreg.dispatch_table can speed up deep copies with custom reducers.
Avoid blanket copy.deepcopy in tight loops — copy what you really need.

🧪 Try It Yourself

Replace deepcopy in the example with a manual rebuild for speed.
Add a test that asserts copy.copy on a nested config leaves nested state shared.
Implement a snapshot mixin that stores a deep copy and exposes restore().