Consider this iterable:

it = (1, 2, 3, 0, 4, 5, 6, 7)

Let’s say you want to build another iterable that includes only the numbers that appear starting from the element 0. Usually, I’d do this:

# This returns (0, 4, 5, 6, 7).
from_zero = tuple(elem for idx, elem in enumerate(it) if idx >= it.index(0))

While this is quite terse and does the job, it won’t work with a generator. There’s an even more generic and terser way to do the same thing with itertools.dropwhile function. Here’s how to do it:

from itertools import dropwhile

# This returns the same thing as before (0, 4, 5, 6, 7).
from_zero = tuple(dropwhile(lambda x: x != 0, it))

Here, itertools.dropwhile is a generator function that returns elements from an iterable starting from the first element for which the predicate returns False. The predicate is a function that takes one argument and returns a boolean value.

The dropwhile function takes two arguments:

  • A function (the predicate), which takes one argument and returns a boolean value.
  • An iterable, which can be any object that can be iterated over, such as a list, tuple, string, or even another generator.

The dropwhile function starts iterating over the elements of the iterable, and drops the elements for which the predicate returns True. It then returns all the remaining elements of the iterable, regardless of whether they satisfy the condition or not.

Apart from being concise, this implementation is more generic and can be used for other purposes like skipping the header lines in a file. For example:

from itertools import dropwhile

with open("/etc/passwd") as f:
    for line in dropwhile(lambda x: x.startswith("#"), f):
        print(line)

This will print all the lines from the /etc/passwd file after the header comments:

nobody:*:-2:-2:Unprivileged User:/var/empty:/usr/bin/false
root:*:0:0:System Administrator:/var/root:/bin/sh
daemon:*:1:1:System Services:/var/root:/usr/bin/false
...

Finally, let’s see how you can skip straight to the data rows in a CSV file that contains arbitrary comments and headers like this:

# persons.csv

This is a comment
These are some other comments
The fake header starts from the next line

id,name,age,height

The real header starts from here
ID,Name,Age,Height
1,John,20,1.8
2,Jane,21,1.7
3,Jack,22,1.6
import csv
from itertools import dropwhile

with open("persons.csv", "r") as f:
    reader = csv.DictReader(f, fieldnames=("ID", "Name", "Age", "Height"))

    # Rows without comments.
    rows = dropwhile(lambda x: x["ID"] != "ID", reader)

    # Skip the header.
    next(rows)

    for row in rows:
        print(row)

Running this will give you the dicts containing the data rows only:

{'ID': '1', 'Name': 'John', 'Age': '20', 'Height': '1.8'}
{'ID': '2', 'Name': 'Jane', 'Age': '21', 'Height': '1.7'}
{'ID': '3', 'Name': 'Jack', 'Age': '22', 'Height': '1.6'}

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