How to Check if a Key Exists in a Python Dictionary

How to Check if a Key Exists in a Python Dictionary
Hostman Team
Technical writer
Python
09.01.2025
Reading time: 6 min

A dictionary (dict) in Python is an unordered data structure that uses a "key-value" format. Any value within the dictionary is accessed by explicitly referencing the key associated with the desired value. Attempting to access a non-existent key results in a program error.

To avoid such errors, it’s essential to check whether a key exists in a dictionary before trying to access its value. Python provides several built-in methods for this purpose, which we discuss in this tutorial.

In this guide, we use Python 3.10.12 running on Ubuntu 22.04.

Using the in Operator with a Dictionary

The most common way to check if a key exists in a dictionary is by using the in operator in an if/else condition:

some_dict = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...'}
some_key = 'name'

if some_key in some_dict:
    print('The key "' + some_key + '" was found.')
else:
    print('The key "' + some_key + '" was not found.')

Here, the in operator returns True if the key is found and False otherwise.

Using the in Operator with dict.keys()

You can also use the in operator with the list of dictionary keys obtained via the dict.keys() method:

some_dict = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...'}
some_key = 'name'

if some_key in some_dict.keys():
    print('The key "' + some_key + '" was found.')
else:
    print('The key "' + some_key + '" was not found.')

As you can see, the logic is identical to the previous example, except that the dict.keys() method is used instead of the dictionary instance.

At first glance, this approach might seem redundant. However, in practical applications, there may be scenarios where you specifically need to work with the list of dictionary keys rather than the dictionary itself.

Using dict.keys(), you can elegantly determine if a specified key exists in the dictionary.

Using the dict.get() Function

You can check for the presence of a key in a dictionary by attempting to retrieve its value using the built-in dict.get() method:

some_dict = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...'}
some_key = 'salary'

some_value = some_dict.get(some_key)  # Try to fetch the value for the key

# If the returned value is None, it indicates the key does not exist
if some_value is not None:
    print('The key "' + some_key + '" was found, and its value is "' + str(some_value) + '".')
else:
    print('The key "' + some_key + '" was not found.')

As shown, accessing a non-existent key with dict.get() will not raise an error (as would happen with square bracket access) but will return a None value.

However, this method has a potential drawback: the requested key might actually exist in the dictionary, but its value could still be None:

some_dict = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...', 'salary': None}
some_key = 'salary'  # The key exists, but its value is None

some_value = some_dict.get(some_key)  # Returns None

print('It is unclear if the key "' + some_key + '" exists or if it exists with a value of None.')

In such cases, whether the key does not exist or exists with a None value is ambiguous.

We can address this issue by using the ability of dict.get() to set a default value for non-existent keys:

some_dict1 = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...', 'salary': None}
some_dict2 = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...'}

some_key = 'salary'

some_value1 = some_dict1.get(some_key, "Salary not specified")
some_value2 = some_dict2.get(some_key, "Salary not specified")

print('Attempting to access the key "' + some_key + '" returned the value "' + str(some_value1) + '".')
print('Attempting to access the key "' + some_key + '" returned the value "' + str(some_value2) + '".')

Console output:

Attempting to access the key "salary" returned the value "None".
Attempting to access the key "salary" returned the value "Salary not specified".

If you attempt to retrieve the value of a non-existent key using square brackets, it will always result in an error. In the future, this error can be handled using a try/except block, thereby determining whether the key actually exists.

try/except Exception Handling

You can check if a key exists in a dictionary by handling errors with try/except—a direct, "straightforward" approach.

In this method, if accessing the key raises an error, it indicates that the key does not exist. Conversely, if no error is raised, the key exists.

To implement this, wrap the key access in a try/except block:

some_dict = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...'}
some_key = 'name'

try:
    some_value = some_dict[some_key]
    print('The key "' + some_key + '" was found, and its value is "' + some_value + '".')
except KeyError:
    print('The key "' + some_key + '" was not found.')

This method of checking for a key in a Python dictionary should generally be used as a fallback when other methods are not suitable.

This is because exception handling in Python tends to be relatively slow, which can reduce program performance. Nonetheless, checking a key via try/except is a valid approach when needed.

Using a for Loop

In programs with more complex logic, explicit key searches in a dictionary might be required—especially if the search is combined with modifying the values of the found keys.

In such cases, you can manually iterate over the dictionary using a for loop:

some_dict = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...'}
some_key = 'name'

is_found = False  # Variable to store the search status

# Iterate through the dictionary
for found_key in some_dict:
    if found_key == some_key:
        is_found = True
        some_dict[found_key] = 'Jim'  # Modify the value of the found key

if is_found:
    print('The key "' + some_key + '" was found, and its value is now "' + some_dict[some_key] + '".')
else:
    print('The key "' + some_key + '" was not found.')

In this example, all dictionary keys are sequentially iterated over, and the value of the found key is modified.

This approach allows for implementing more complex logic, combining both key searches and value modifications.

Using a while Loop

In some cases, it might be useful to use a while loop instead of a for loop:

some_dict = {'name': 'James', 'age': 35, 'occupation': 'Just a guy...'}
some_key = 'occupation'

is_found = False

some_keys = list(some_dict)  # Convert dictionary keys to a list

i = 0
while i < len(some_keys):
    if some_keys[i] == some_key:
        is_found = True
        some_dict[some_key] = 'Jim'  # Modify the value of the found key
        break
    i += 1

if is_found:
    print('The key "' + some_key + '" was found, and its value is now "' + some_dict[some_key] + '".')
else:
    print('The key "' + some_key + '" was not found.')

While the overall application logic does not change, the syntax differs from the for loop approach.

Conclusion

Before accessing a value in a dictionary, it is essential to ensure that the desired key exists in the dictionary. Otherwise, you may encounter an error, causing the program to crash.

This check can be performed using several built-in methods:

  • in operator
  • dict.get() function
  • try/except exception handling
  • for and while loops

Each specific scenario calls for a different method of checking. For the simplest cases, the in operator is typically used. When the application logic is more complex and requires additional actions, a for or while loop may be employed.

If you want to build a web service using Python, you can rent a cloud server at competitive prices with Hostman.

Python
09.01.2025
Reading time: 6 min

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For example, we can exclude specific elements from the resulting dictionary: objects = ['human', 'cat', 'alien', 'car'] states = ['walking', 'purring', 'hiding', 'driving'] objects_states = {obj: state for obj, state in zip(objects, states) if obj != 'alien'} # Protect Earth from unknown extraterrestrial influence print(objects_states) Console output: {'human': 'walking', 'cat': 'purring', 'car': 'driving'} We can refine the selection criteria further by introducing multiple conditions: objects = ['human', 'cat', 'alien', 'car'] states = ['walking', 'purring', 'hiding', 'driving'] objects_states = {obj: state for obj, state in zip(objects, states) if obj != 'alien' if obj != 'cat'} # Exclude the alien and the cat—who might be a disguised visitor from another galaxy print(objects_states) Console output: {'human': 'walking', 'car': 'driving'} When using multiple if statements in a dictionary comprehension, they behave as if connected by a logical and operator. You can make dictionary generation even more flexible by combining if and else operators: objects = ['human', 'cat', 'alien', 'car'] states = ['walking', 'purring', 'hiding', 'driving'] # In this example, all string elements in the first list are longer than those in the second list, except for 'cat' objects_states = { obj: ('[SUSPICIOUS]' if len(obj) < len(state) else 'calmly ' + state) for obj, state in zip(objects, states) } # Mark the suspicious 'cat' appropriately and slightly modify other values print(objects_states) Console output: {'human': 'calmly walking', 'cat': '[SUSPICIOUS]', 'alien': 'calmly hiding', 'car': 'calmly driving'} Creating a Complex Dictionary from a Single List In the earlier examples, we created dictionaries from two separate lists. But what if the keys and values needed for the new dictionary are contained within a single list? In such cases, the logic of the dictionary comprehension needs to be adjusted: objects_and_states = [ 'human', 'walking', 'cat', 'purring', 'alien', 'hiding', 'car', 'driving' ] # Keys and values are stored sequentially in one list objects_states = { objects_and_states[i]: objects_and_states[i + 1] for i in range(0, len(objects_and_states), 2) } # The `range` function specifies the start, end, and step for iteration: range(START, STOP, STEP) print(objects_states) Console output: {'human': 'walking', 'cat': 'purring', 'alien': 'hiding', 'car': 'driving'} Sometimes, a list might contain nested dictionaries as elements. The values of these nested dictionaries can also be used to create a new dictionary. Here’s how the logic changes in such cases: objects = [ {'name': 'human', 'state': 'walking', 'location': 'street'}, {'name': 'cat', 'state': 'purring', 'location': 'windowsill'}, {'name': 'alien', 'state': 'hiding', 'location': 'spaceship'}, {'name': 'car', 'state': 'driving', 'location': 'highway'} ] objects_states = { obj['name']: obj['state'] for obj in objects } # Extract 'name' as key and 'state' as value print(objects_states) Console output: {'human': 'walking', 'cat': 'purring', 'alien': 'hiding', 'car': 'driving'} This approach enables handling more complex data structures, such as lists of dictionaries, by targeting specific key-value pairs from each nested dictionary. Converting a Dictionary to a List Converting a dictionary into a list in Python is a straightforward task, often better described as extracting data. From a single dictionary, you can derive several types of lists: A list of keys A list of values A list of key-value pairs Here’s how it can be done: objects_states = { 'human': 'walking', 'cat': 'purring', 'alien': 'hiding', 'car': 'driving' } # Convert dictionary components to lists using the `list()` function objects_keys = list(objects_states.keys()) # List of keys objects_values = list(objects_states.values()) # List of values objects_items = list(objects_states.items()) # List of key-value pairs print(objects_keys) print(objects_values) print(objects_items) Console output: ['human', 'cat', 'alien', 'car'] ['walking', 'purring', 'hiding', 'driving'] [('human', 'walking'), ('cat', 'purring'), ('alien', 'hiding'), ('car', 'driving')] Conclusion Lists and dictionaries are fundamental data structures in Python, each offering distinct ways of storing and accessing data. Dictionaries are more informative than lists, storing data as key-value pairs, whereas lists store values that are accessed by index. Converting a dictionary into a list is straightforward, requiring no additional data since you’re simply extracting keys, values, or their pairs. Converting a list into a dictionary, on the other hand, requires additional data or rules to map the list elements to dictionary keys and values. There are a few methods to convert a List to Dictionary Tool Key Values Syntax dict.fromkeys() Common new_dict = dict.fromkeys(old_list) Dictionary Comprehension Common new_dict = {new_key: 'any value' for new_key in old_list} Dict Comp + zip() Unique new_dict = {new_key: old_val for new_key, old_val in zip(list1, list2)} Dict Comp + zip() + if Unique new_dict = {new_key: old_val for new_key, old_val in zip(list1, list2) if ...} Dict Comp + zip() + if-else Unique new_dict = {new_key: (... if ... else ...) for new_key, old_val in zip(list1, list2)} Complex lists may require more intricate dictionary comprehension syntax. Techniques shown in this guide, such as using zip() and range() for iterations, help handle such cases. Converting a dictionary to a list is also possible in several ways, but it is much simpler. Tool Extracts Syntax list.keys() Keys list(old_dict.keys()) list.values() Values list(old_dict.values()) list.items() Key-Value Pairs list(old_dict.items()) Python offers flexible and efficient ways to convert structured data types between lists and dictionaries, enabling powerful manipulation and access.
13 January 2025 · 11 min to read

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