Test for presence using the in
operator, then apply the remove
method.
if thing in some_list: some_list.remove(thing)
The remove
method will remove only the first occurrence of thing
, in order to remove all occurrences you can use while
instead of if
.
while thing in some_list: some_list.remove(thing)
This shoot-first-ask-questions-last attitude is common in Python. Instead of testing in advance if the object is suitable, just carry out the operation and catch relevant Exceptions:
try:
some_list.remove(thing)
except ValueError:
pass # or scream: thing not in some_list!
except AttributeError:
call_security("some_list not quacking like a list!")
Off course the second except clause in the example above is not only of questionable humor but totally unnecessary (the point was to illustrate duck-typing for people not familiar with the concept).
If you expect multiple occurrences of thing:
while True:
try:
some_list.remove(thing)
except ValueError:
break
However, with contextlib's suppress() contextmanager (introduced in python 3.4) the above code can be simplified to this:
with suppress(ValueError, AttributeError):
some_list.remove(thing)
Again, if you expect multiple occurrences of thing:
with suppress(ValueError):
while True:
some_list.remove(thing)
Around 1993, Python got lambda
, reduce()
, filter()
and map()
, courtesy of a Lisp hacker who missed them and submitted working patches*. You can use filter
to remove elements from the list:
is_not_thing = lambda x: x is not thing
cleaned_list = filter(is_not_thing, some_list)
There is a shortcut that may be useful for your case: if you want to filter out empty items (in fact items where bool(item) == False
, like None
, zero, empty strings or other empty collections), you can pass None as the first argument:
cleaned_list = filter(None, some_list)
filter(function, iterable)
used to be equivalent to [item for item in iterable if function(item)]
(or [item for item in iterable if item]
if the first argument is None
); in Python 3.x, it is now equivalent to (item for item in iterable if function(item))
. The subtle difference is that filter used to return a list, now it works like a generator expression - this is OK if you are only iterating over the cleaned list and discarding it, but if you really need a list, you have to enclose the filter()
call with the list()
constructor.filter
- along with companions map
and reduce
(they are not gone yet but reduce
was moved into the functools module, which is worth a look if you like high order functions).List comprehensions became the preferred style for list manipulation in Python since introduced in version 2.0 by PEP 202. The rationale behind it is that List comprehensions provide a more concise way to create lists in situations where map()
and filter()
and/or nested loops would currently be used.
cleaned_list = [ x for x in some_list if x is not thing ]
Generator expressions were introduced in version 2.4 by PEP 289. A generator expression is better for situations where you don't really need (or want) to have a full list created in memory - like when you just want to iterate over the elements one at a time. If you are only iterating over the list, you can think of a generator expression as a lazy evaluated list comprehension:
for item in (x for x in some_list if x is not thing):
do_your_thing_with(item)
!=
instead of is not
(the difference is important)