


Is the Correspondence Between `keys()` and `values()` in Python Dictionaries Guaranteed?
Ensuring Correspondence Between Dictionary Keys and Values
In Python dictionaries, the keys() and values() methods provide access to the keys and values in the dictionary, respectively. It has been observed that the lists returned by these methods appear to maintain a one-to-one mapping, where the i-th key from keys() corresponds to the i-th value from values().
However, it is important to verify if this mapping is always guaranteed. Specifically, if a dictionary is not altered between calling keys() and values(), can we rely on the assumption that they will always yield corresponding lists?
Official Documentation
The documentation for Python dictionaries does not explicitly state whether the order of keys() and values() is preserved. However, it does provide a clue:
d = {'one':1, 'two': 2, 'three': 3}
k, v = d.keys(), d.values()
for i in range(len(k)):
print d[k[i]] == v[i]
True
True
True
This example illustrates that when no modifications are made to the dictionary between calling keys() and values(), the for-loop consistently prints True, suggesting a correspondence between the lists.
Further Observations
To confirm this observation, a more extensive search was conducted:
- The 2.x documentation states: "If items(), keys(), values(), iteritems(), iterkeys(), and itervalues() are called with no intervening modifications to the dictionary, the lists will directly correspond."
- The 3.x documentation also includes this statement.
These statements provide reassurance that the mapping between keys() and values() is indeed preserved as long as the dictionary remains unaltered.
Conclusion
Based on the official documentation and empirical observations, we can conclude that when you call keys() and values() on a Python dictionary without making any modifications to the dictionary between the calls, you can rely on a one-to-one correspondence between the lists of keys and values. This reliable mapping simplifies dictionary manipulation and ensures predictable behavior in common programming scenarios.
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