If you want to remove leading and ending spaces, use str.strip(): >>> ” hello apple “.strip() ‘hello apple’ If you want to remove all space characters, use str.replace() (NB this only removes the “normal” ASCII space character ‘ ‘ U+0020 but not any other whitespace): >>> ” hello apple “.replace(” “, “”) ‘helloapple’ If you … Read more
Apart from tuples being immutable there is also a semantic distinction that should guide their usage. Tuples are heterogeneous data structures (i.e., their entries have different meanings), while lists are homogeneous sequences. Tuples have structure, lists have order. Using this distinction makes code more explicit and understandable. One example would be pairs of page and … Read more
I suggest ElementTree. There are other compatible implementations of the same API, such as lxml, and cElementTree in the Python standard library itself; but, in this context, what they chiefly add is even more speed — the ease of programming part depends on the API, which ElementTree defines. First build an Element instance root from … Read more
Formats Python docstrings can be written following several formats as the other posts showed. However the default Sphinx docstring format was not mentioned and is based on reStructuredText (reST). You can get some information about the main formats in this blog post. Note that the reST is recommended by the PEP 287 There follows the … Read more
To remove the first occurrence of an element, use list.remove: >>> xs = [‘a’, ‘b’, ‘c’, ‘d’] >>> xs.remove(‘b’) >>> print(xs) [‘a’, ‘c’, ‘d’] To remove all occurrences of an element, use a list comprehension: >>> xs = [‘a’, ‘b’, ‘c’, ‘d’, ‘b’, ‘b’, ‘b’, ‘b’] >>> xs = [x for x in xs if … Read more
The docs describe the attributes available on the request object (from flask import request) during a request. In most common cases request.data will be empty because it’s used as a fallback: request.data Contains the incoming request data as string in case it came with a mimetype Flask does not handle. request.args: the key/value pairs in … Read more
Enums have been added to Python 3.4 as described in PEP 435. It has also been backported to 3.3, 3.2, 3.1, 2.7, 2.6, 2.5, and 2.4 on pypi. For more advanced Enum techniques try the aenum library (2.7, 3.3+, same author as enum34. Code is not perfectly compatible between py2 and py3, e.g. you’ll need … Read more
To get elements which are in temp1 but not in temp2 : In [5]: list(set(temp1) – set(temp2)) Out[5]: [‘Four’, ‘Three’] Beware that it is asymmetric : In [5]: set([1, 2]) – set([2, 3]) Out[5]: set([1]) where you might expect/want it to equal set([1, 3]). If you do want set([1, 3]) as your answer, you can use set([1, … Read more
You can use the isin method: In [1]: df = pd.DataFrame({‘A’: [5,6,3,4], ‘B’: [1,2,3,5]}) In [2]: df Out[2]: A B 0 5 1 1 6 2 2 3 3 3 4 5 In [3]: df[df[‘A’].isin([3, 6])] Out[3]: A B 1 6 2 2 3 3 And to get the opposite use ~: In [4]: df[~df[‘A’].isin([3, … Read more
7 in a Clearest and fastest way to do it. You can also consider using a set, but constructing that set from your list may take more time than faster membership testing will save. The only way to be certain is to benchmark well. (this also depends on what operations you require)