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Repair Windows errors before they cause bigger problemsFix Now →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →A Python dictionary stores values under unique keys. Use d[key] to look up or assign an entry, key in d to test whether a key exists, and d.items() to loop through keys and values. The examples below cover the core operations and the behaviors that matter when keys are missing or entries change.
What a Python dictionary is
A dictionary is a mutable mapping: each key identifies one value, and keys are unique within the dictionary. In this example, name and language are keys, while Ada and Python are their values:
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person = {"name": "Ada", "language": "Python"}If you assign a value to a key that is already present, the dictionary replaces that key’s value rather than creating a duplicate key.
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Use {} for an empty dictionary, a literal for known entries, or dict() when building one from keyword arguments or key-value pairs:
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empty = {}
person = {"name": "Ada", "language": "Python"}
settings = dict(theme="dark", notifications=True)
from_pairs = dict([("name", "Ada"), ("language", "Python")])A dictionary comprehension creates entries from an iterable. This one maps each number to its square:
squares = {n: n * n for n in range(4)}
# {0: 0, 1: 1, 2: 4, 3: 9}How to retrieve, add, and change values
Use square brackets with a key to retrieve its value. Assign through the same syntax to add a new key or replace the value for an existing one:
person = {"name": "Ada"}
print(person["name"]) # Ada
person["language"] = "Python" # add an entry
person["name"] = "Grace" # replace the existing valueBracket lookup is appropriate when the key is expected to exist. If it does not, Python raises a KeyError; choose a default-returning lookup or check membership when absence is normal.
How to handle a missing key
Use get() when a missing key should produce a fallback instead of an exception. With no second argument, d.get(key) returns None when the key is absent; with a second argument, it returns that supplied default:
person = {"name": "Ada"}
print(person.get("language")) # None
print(person.get("language", "unknown")) # unknownIf None might itself be a stored value, get() alone cannot tell you whether the key was absent or present with a value of None. Test membership first:
if "language" in person:
print(person["language"])
else:
print("No language entry")The expression key in d checks dictionary keys, not values. To check whether a value appears, use value in d.values().
How to test for a key and remove an entry
Use in to test whether a key exists, and del to delete an entry by key:
person = {"name": "Ada", "language": "Python"}
if "language" in person:
del person["language"]Deleting a key that is not present raises KeyError, so a membership check is useful if absence is possible. del d[key] removes the entry; it does not return its value.
How to iterate through a dictionary
A for loop over a dictionary yields its keys. Use items() when each loop needs both the key and its value:
person = {"name": "Ada", "language": "Python"}
for key in person:
print(key)
for key, value in person.items():
print(key, value)The methods keys(), values(), and items() provide views of the dictionary’s keys, values, and key-value pairs. These views reflect the dictionary’s contents, so they are useful for inspecting entries without making a separate list.
Which values can be dictionary keys?
Keys must have stable hash behavior while they are in the dictionary. Strings and numbers are common choices. A tuple can be a key if all of its contents are themselves suitable; a tuple containing a list, for example, is not suitable.
Lists and dictionaries cannot be keys because they are mutable. A value-based hash for an object that can change would not reliably identify its stored entry. Values do not have this restriction: a dictionary can store mutable values such as lists.
groups = {"admins": ["Ada", "Grace"]}How to update or merge entries
Call update() to add entries from another mapping or an iterable of key-value pairs. When an incoming key already exists, its value replaces the current value:
profile = {"name": "Ada", "language": "Python"}
profile.update({"language": "English", "city": "London"})
# {"name": "Ada", "language": "English", "city": "London"}What dictionary order means
Dictionary insertion order is a language guarantee in Python 3.7 and later. The official Python data model describes keys as being produced in the order they were added sequentially: Python data model reference. Python 3.6 preserved order in CPython as an implementation detail, but it was not yet a language guarantee.
Replacing the value for an existing key does not change its position. Deleting a key and adding it again places it at the end. If code depends on ordering, target Python 3.7 or later rather than relying on older implementation-specific behavior.
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Example: count values with a dictionary
A dictionary is useful when each item needs to be associated with a running count. This example counts how often each word appears:
words = ["apple", "pear", "apple", "plum", "pear", "apple"]
counts = {}
for word in words:
counts[word] = counts.get(word, 0) + 1
print(counts)
# {"apple": 3, "pear": 2, "plum": 1}The get(word, 0) call supplies a starting count for a word not yet seen; each pass then stores the incremented count under that word’s key.
Official Python documentation
The Python 3.14.7 tutorial explains dictionary creation and common operations in its dictionaries section. The built-in types reference documents dictionary methods and behavior.
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