The easiest way to replace an item in a list is to use the Python indexing syntax. Indexing allows you to choose an element or range of elements in a list. With the assignment operator, you can change a value at a given position in a list.
Replace Multiple Values in a Python List. There may be many times when you want to replace not just a single item, but multiple items. This can be done quite simply using the for loop method shown earlier.
Use the translate() method to replace multiple different characters. You can create the translation table specified in translate() by the str. maketrans() . Specify a dictionary whose key is the old character and whose value is the new string in the str.
words = [w.replace('[br]', '<br />') for w in words]
These are called List Comprehensions.
You can use, for example:
words = [word.replace('[br]','<br />') for word in words]
Beside list comprehension, you can try map
>>> map(lambda x: str.replace(x, "[br]", "<br/>"), words)
['how', 'much', 'is<br/>', 'the', 'fish<br/>', 'no', 'really']
In case you're wondering about the performance of the different approaches, here are some timings:
In [1]: words = [str(i) for i in range(10000)]
In [2]: %timeit replaced = [w.replace('1', '<1>') for w in words]
100 loops, best of 3: 2.98 ms per loop
In [3]: %timeit replaced = map(lambda x: str.replace(x, '1', '<1>'), words)
100 loops, best of 3: 5.09 ms per loop
In [4]: %timeit replaced = map(lambda x: x.replace('1', '<1>'), words)
100 loops, best of 3: 4.39 ms per loop
In [5]: import re
In [6]: r = re.compile('1')
In [7]: %timeit replaced = [r.sub('<1>', w) for w in words]
100 loops, best of 3: 6.15 ms per loop
as you can see for such simple patterns the accepted list comprehension is the fastest, but look at the following:
In [8]: %timeit replaced = [w.replace('1', '<1>').replace('324', '<324>').replace('567', '<567>') for w in words]
100 loops, best of 3: 8.25 ms per loop
In [9]: r = re.compile('(1|324|567)')
In [10]: %timeit replaced = [r.sub('<\1>', w) for w in words]
100 loops, best of 3: 7.87 ms per loop
This shows that for more complicated substitutions a pre-compiled reg-exp (as in 9-10
) can be (much) faster. It really depends on your problem and the shortest part of the reg-exp.
An example with for loop (I prefer List Comprehensions).
a, b = '[br]', '<br />'
for i, v in enumerate(words):
if a in v:
words[i] = v.replace(a, b)
print(words)
# ['how', 'much', 'is<br/>', 'the', 'fish<br/>', 'no', 'really']
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