'too many values to unpack', iterating over a dict. key=>string, value=>list
The notorious 'too many values to unpack' error surfaces when you naively try to unpack a dict with a loop. To befriend both keys and values of a dict, enlist the help of the .items()
method. It cheerfully presents pairs of keys and their corresponding lists (or cliques, as they prefer to be called) of values:
In this special friendship, key
prefers to stick with the dictionary key, and value_list
is a party-goer, hanging out with the list. No more unpacking dramas!
Deeper dive into dictionary iteration
Dictionaries in Python and their iteration methods are something we can't escape from. If you're a fan of Python 2, you've probably heard of iteritems()
, but if Python 3 is your jam, keep items()
on your speed dial since iteritems()
moved to a farm upstate living happily in Python 2 land.
Key tips for error-dodging iteration
- Remember your iteration etiquette. Use the method that suits your Python version.
- For Python 3 users,
my_dict.items()
is your night in shining armor, generating key-value pairs. - If Python 2 feels like home,
my_dict.iteritems()
is a more efficient pal, cause he doesn't like wasting memory. - Lest we forget that
items()
in Python 3 returns an iterator, not a list. Memory conservators rejoice!
Unpacking in for loops
To get the unpacking right in the loop, refer to this cheat sheet:
Just think of the structure fitting neatly into the for loop like tetris blocks, different pieces but part of the whole game.
Be aware! Pitfalls and lifelines
Let's talk about those sneaky issues that we might miss and their trusty solutions when iterating over dictionaries.
Accessing nested lists
If your dictionary's values run in packs (or lists), have an inner loop in your arsenal to iterate through each friend in the list:
Misusing dict.keys() or dict.values()
At times, all we need are keys or values. Using these incorrectly with unpacking will cause a kerfuffle. Use them when you need one component, and .items()
when both want to play.
Adapting foreign code
Looking for answers from dependable resources like Stack Overflow? Always mold the code examples to fit your Python version and target structure. Focus on accepted answers, they are community-vetted and hold the golden ticket to your solution.
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