There are three most significant changes related to dictionaries in Python 3.

Removed dict.has_key()

  • Fixer: python-modernize -wnf lib2to3.fixes.fix_has_key (See caveat below)
  • Prevalence: Common

The dict.has_key() method, long deprecated in favor of the in operator, is no longer available in Python 3.

Instead of:


you should use:

'keyname' in dictionary

Note that the recommended fixer replaces all calls to any has_key method; it does not check that its object is actually a dictionary.

If you use a third-party dict-like class, it should implement in already. If not, complain to its author: it should have been added as part of adding Python 3 support.

If your own codebase contains a custom dict-like class, add a __contains__() method to it to implement the in operator. If possible, mark the has_key method as deprecated. Then run the fixer, and review the output. Typically, the fixer’s changes will need to be reverted in tests for the has_key method itself.

If you are using objects with unrelated semantics for the attribute has_key, you’ll need to review the fixer’s output and revert its changes for such objects.

Changed Key Order

  • Fixer: None
  • Prevalence: Uncommon

The Python language specification has never guaranteed order of keys in a dictionary, and mentioned that applications shouldn’t rely on it. In practice, however, the order of elements in a dict was usually remained consistent between successive executions of Python 2.

Suppose we have a simple script with the following content:

$ cat order.py
dictionary = {'a': 1, 'b': 2, 'c': 3, 'd': 4, 'e': 5}

With python2, the result contained elements of dict in the same order for every execution:

$ python2 order.py
[('a', 1), ('c', 3), ('b', 2), ('e', 5), ('d', 4)]

$ python2 order.py
[('a', 1), ('c', 3), ('b', 2), ('e', 5), ('d', 4)]

$ python2 order.py
[('a', 1), ('c', 3), ('b', 2), ('e', 5), ('d', 4)]

The predictable ordering is a side effect of predictable hashing. Unfortunately, in some cases malicious users could take advantage of the predictability to cause denial of service attacks. (See CVE-2012-1150 for more details.) To counter this vulnerability, Python 2.6.8+ and 2.7.3+ allowed randomizing the hash function, and thus dictionary order, on each invocation of the interpreter. This is done by setting the environment variable $PYTHONHASHSEED to random:

$ PYTHONHASHSEED=random python2 order.py
[('b', 2), ('c', 3), ('a', 1), ('d', 4), ('e', 5)]

$ PYTHONHASHSEED=random python2 order.py
[('e', 5), ('d', 4), ('a', 1), ('c', 3), ('b', 2)]

In Python 3.3+, this setting is the default:

$ python3 order.py
[('a', 1), ('d', 4), ('e', 5), ('c', 3), ('b', 2)]

$ python3 order.py
[('c', 3), ('e', 5), ('d', 4), ('a', 1), ('b', 2)]

Additionally, CPython 3.6+ uses a new implementation of dictionaries, which makes them appear sorted by insertion order (though you can only rely on this behavior in Python 3.7+):

$ python3 order.py
[('a', 1), ('b', 2), ('c', 3), ('d', 4), ('e', 5)]

Unfortunately, an automated fixer for removing dependencies on dict order is not available. However, the issue can be detected by running the code under Python 2 with PYTHONHASHSEED=random. Do that, and investigate and fix any failures.

Dict Views and Iterators

  • Fixer: python-modernize -wnf libmodernize.fixes.fix_dict_six (See caveat below)
  • Prevalence: Common

The methods dict.keys(), dict.items() and dict.values() now return views instead of lists.

The following are the most important differences:

  • Unlike lists, a view does not hold copy the data. Updates to the underlying dict are reflected in the view.
  • The items in a view are not accessible by indexing. If you need that you’ll need to convert the view to a list (e.g. list(d.values())).
  • Key and value views support set operations, such as intersection and union.

The following common operations work the same between views and lists, as long as the underlying dict is not modified:

  • Iteration (e.g. for x in d.values())
  • Member testing (e.g. if x in d.values())
  • Length testing (e.g. len(d.values()))

The methods dict.iterkeys(), dict.iteritems() and dict.itervalues(), and the less-used dict.viewkeys(), dict.viewitems() and dict.viewvalues(), are no longer available.

Cross-Version Iteration and Views

To get iterators in both Python 2 and Python 3, calls to iterkeys(), itervalues() and iteritems() can be replaced by calls to functions from the Compatibility library: six library:


Similarly, viewkeys(), viewvalues() and viewitems() have compatibility wrappers in Compatibility library: six:


In Python 3, both iter* and view* functions correspond to keys(), items(), and values().

However, we recommend avoiding the six wrappers whenever it’s sensible. For example, one often sees iter* functions in Python 2 code:

for v in dictionary.itervalues():

To be compatible with Python 3, this code can be changed to use six:

for v in six.itervalues(dictionary):

… or a “native” method:

for v in dictionary.values():

The latter is more readable. However, it can be argued that the former is more memory-efficient in Python 2, as a new list is not created.

In most real-world use cases, the memory difference is entirely negligible: the extra list is a fraction of the size of a dictionary, and tiny compared to the data itself. Any speed difference is almost always negligible. So, we suggest using the more readable variant unless either:

  • not all items are processed (for example, a break ends the loop early), or
  • special optimizations are needed (for example, if the dictionary could contain millions of items or more).

Fixer caveats

The recommended fixer rewrites the usage of dict methods, but very often its changes are not ideal. We recommend treating its output as “markers” that indicate code that needs to change, but addressing each such place individually by hand.

For example, the fixer will change:

key_list = dictionary.keys()
for key in key_list:


key_list = list(dictionary.keys())
for key in key_list:

This change is entirely unnecessary. The new version is less performant (in both Python 2 and Python 3), and less readable. However, the fixer cannot detect that the list is only used for iteration, so it emits overly defensive code.

In this case, both speed and readability can be improved by iterating over the dict itself:

for key in dictionary:

Also, the fixer will not change instances code that modifies a dictionary while iterating over it. The following is valid in Python 2, where an extra copy of keys is iterated over:

for key in dictionary.keys():
    del dictionary[key]

In Python 3, this will raise RuntimeError: dictionary changed size during iteration.

In this particular case, dictionary.clear() can replace the loop. More generally, this kind of issue may be solved by creating a list explicitly:

for key in list(dictionary.keys()):
    del dictionary[key]

The fixer will not change code like this. However, the RuntimeError makes the issue easy to detect.