Flattening

Express the operation of flattening nested lists in a concise, readable Python idiom.

Data processing: flatten a list of lists for feeding into a machine learning model; Web development: convert nested menu structures into a flat list of links

Data cleaning, preparing input for algorithms that expect flat sequences, preparing data for JSON serialization, flattening nested loops results.

[item for sublist in my_list for item in sublist]

[expression for outer_iter in outer for inner_item in outer_iter]

{"item":"any expression to produce the output element","sublist":"any iterable yielding items","my_list":"list of iterables"}

• my_list matrix data rows nested

• x for row in matrix for x in row elem for sub in nested for elem in sub

Reversing loop order: [item for item in sublist for sublist in my_list] raises NameError Omitting the inner loop, leaving a nested list: [sublist for sublist in my_list] Using the same variable name for both loops causing shadowing

[item for sublist in my_list for item in sublist] vs (item for sublist in my_list for item in sublist) – generator expression [item for sublist in my_list for item in sublist] vs sum(my_list, []) – less efficient flattening

Confusing list comprehension syntax with generator expression syntax; missing the inner loop variable leads to NameError. Using the same identifier for both loops can cause unexpected variable capture.

• list comprehension idioms

The order of the for clauses matters: the outer loop variable is declared first, then the inner loop.

Conveys concise, idiomatic Python; signals familiarity with list comprehensions and functional‑style data transformation.

Think ‘for each sublist, take each item’.

Equivalent to itertools.chain.from_iterable(my_list) or sum(my_list, []), but the comprehension is usually clearer and more efficient for small‑to‑medium data.

Consider using itertools.chain.from_iterable(my_list) for better performance on large datasets.