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Repair common Windows errors and clear accumulated junk for a smoother, more stable PC - no reinstall needed.Free scan · no reinstallUse {} to create an empty dictionary, a dictionary literal for known key-value pairs, and a comprehension or dict.fromkeys() to initialize a set of keys. For separate mutable values such as lists, use a comprehension. If you only need a fallback when reading a possibly absent key, use get()—it does not add the key to the dictionary.
Start with an empty dictionary or known values
In Python 3.14, {} creates an empty dictionary. To start with entries, put comma-separated key: value pairs inside braces:
settings = {}
user = {"name": "Ada", "active": True}Use a literal when the keys and values are known and you want the mapping to be easy to read at a glance. The official Python data structures tutorial documents dictionary literals and creation patterns.
Braces alone create a dictionary, not an empty set. To create an empty set, write set().
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Build a dictionary with dict()
The dict() constructor can make an empty dictionary or build one from a mapping, an iterable of key-value pairs, or keyword arguments. Use it when your input already has one of those forms:
empty = dict()
scores = dict([("Ada", 10), ("Lin", 12)])
options = dict(theme="dark", compact=True)If construction supplies the same key more than once, the later value replaces the earlier one. For example, dict([("Ada", 10), ("Ada", 11)]) produces {"Ada": 11}. The constructor’s accepted inputs and duplicate-key behavior are covered in the Python 3.14 built-in types reference.
Initialize keys with zero or another shared value
For a range of generated integer keys, use a dictionary comprehension. For an existing iterable of keys that should all start with the same immutable value, dict.fromkeys() is concise.
Generate keys with a comprehension
zeros = {i: 0 for i in range(5)}This creates keys 0 through 4, each associated with the integer 0. Change the expression after the colon to produce a different initial value for each key.
Use dict.fromkeys() for one common value
flags = dict.fromkeys(["draft", "review", "published"], False)Each key receives the same value reference. This is suitable for immutable values such as integers, booleans, or strings. The behavior of fromkeys() is specified in the Python built-in types reference.
Create distinct mutable defaults for each key
Do not use dict.fromkeys(keys, []) when each key needs its own list. Every entry would refer to the same list, so appending through one key would also appear through the others. Create a new value for each key with a comprehension instead:
buckets = {name: [] for name in ["red", "blue", "green"]}
buckets["red"].append("apple")
# Only the red bucket contains "apple".The same rule applies to other mutable values, such as dictionaries or sets: construct a fresh object inside the comprehension for each key. Python’s built-in types reference describes dict.fromkeys() as assigning the same value to each key.
Choose the initializer that fits the data
| Situation | Use | Example |
|---|---|---|
| No entries yet | Empty literal or constructor | {} or dict() |
| Small, fixed set of known pairs | Dictionary literal | {"name": "Ada"} |
| Input is a mapping or key-value pairs | dict() |
dict([("Ada", 10)]) |
| Keys or values come from an expression | Dictionary comprehension | {i: 0 for i in range(5)} |
| Every key needs the same immutable value | dict.fromkeys() |
dict.fromkeys(keys, 0) |
| Every key needs a separate mutable value | Dictionary comprehension | {key: [] for key in keys} |
Use get() to read with a fallback, not to initialize
When a key may be absent and you only need a fallback for that lookup, call d.get(key, default). If the key is missing and no default is supplied, get() returns None; with a default, it returns that value instead of raising KeyError.
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mode = settings.get("mode", "standard")
# settings is still empty; "mode" was not inserted.Use assignment, such as settings["mode"] = "standard", if the key should actually be stored. The Python data structures tutorial and built-in types reference distinguish lookup with get() from adding an entry.
Quick Recap
Check key and ordering behavior
- Dictionary keys must be hashable. A list is mutable and unhashable, so it cannot be used as a key.
- Assigning a value to a key that is already present replaces that key’s previous value.
- Python dictionaries preserve insertion order, as documented in the Python 3.14 built-in types reference.
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