Skip to main content

Python - .strip(), .capitalize(), .title(), .spit()

🐍 .strip() removes certain characters from both ends of the string. .capitalize() capitalizes the first letter of the string and sets the rest of the string to lower case. .title() capitalizes first letter of every word in the string.

Example

Run the following code in Jupyter notebook and you will see how each of the above functions work.

a = "   john SNOW   "
b = "0000CAEsy0james00"
print(a.strip().capitalize()+" loves "+b.strip('0').title())

.strip()

.strip() removes all spaces from the front and back of a string. Not the spaces in between. .strip() has default argument as space, i.e. ' '. But if you pass another character, it will look for that character in front and back of the string and remove it.

For example, if you run print('0000James0Cameron000'.strip('0')), it will remove all 0s from front and back and print 'James0Cameron'. Note that the 0 in between remains as it is.

You can pass a string too. Example, print('agentJamesagentCameronagent'.strip('agent')) will return 'JamesagentCameron'.

.capitalize()

It capitalizes first letter of the string. and sets the rest of the characyers to lowercase.

Example, print('jAmEs CaMeRoN'.capitalize()) returns James cameron

.title()

It capitalizes the first letter of all words separated by space.

Example, print('jAmEs CaMeRoN'.title()) returns James Cameron

.split()

It separates words in a sentence by a character. The default character it uses to separate is space.

Example, print("hello world".split()) will return ['hello', 'world']
Example, print("mississippi".split('i')) will return ['m', 'ss', 'ss', 'pp']

Comments

Popular posts from this blog

Python - List - Append, Count, Extend, Index, Insert, Pop, Remove, Reverse, Sort

🐍 Advance List List is widely used and it's functionalities are heavily useful. Append Adds one element at the end of the list. Syntax list1.append(value) Input l1 = [1, 2, 3] l1.append(4) l1 Output [1, 2, 3, 4] append can be used to add any datatype in a list. It can even add list inside list. Caution: Append does not return anything. It just appends the list. Count .count(value) counts the number of occurrences of an element in the list. Syntax list1.count(value) Input l1 = [1, 2, 3, 4, 3] l1.count(3) Output 2 It returns 0 if the value is not found in the list. Extend .count(value) counts the number of occurrences of an element in the list. Syntax list1.extend(list) Input l1 = [1, 2, 3] l1.extend([4, 5]) Output [1, 2, 3, 4, 5] If we use append, entire list will be added to the first list like one element. Extend, i nstead of considering a list as one element, it joins the two lists one after other. Append works in the following way. Input l1 = [1, 2, 3] l1.append([4, 5]) Output...

Difference between .exec() and .execPopulate() in Mongoose?

Here I answer what is the difference between .exec() and .execPopulate() in Mongoose? .exec() is used with a query while .execPopulate() is used with a document Syntax for .exec() is as follows: Model.query() . populate ( 'field' ) . exec () // returns promise . then ( function ( document ) { console . log ( document ); }); Syntax for .execPopulate() is as follows: fetchedDocument . populate ( 'field' ) . execPopulate () // returns promise . then ( function ( document ) { console . log ( document ); }); When working with individual document use .execPopulate(), for model query use .exec(). Both returns a promise. One can do without .exec() or .execPopulate() but then has to pass a callback in populate.

683 K Empty Slots

  Approach #1: Insert Into Sorted Structure [Accepted] Intuition Let's add flowers in the order they bloom. When each flower blooms, we check it's neighbors to see if they can satisfy the condition with the current flower. Algorithm We'll maintain  active , a sorted data structure containing every flower that has currently bloomed. When we add a flower to  active , we should check it's lower and higher neighbors. If some neighbor satisfies the condition, we know the condition occurred first on this day. Complexity Analysis Time Complexity (Java):  O(N \log N) O ( N lo g N ) , where  N N  is the length of  flowers . Every insertion and search is  O(\log N) O ( lo g N ) . Time Complexity (Python):  O(N^2) O ( N 2 ) . As above, except  list.insert  is  O(N) O ( N ) . Space Complexity:  O(N) O ( N ) , the size of  active . Approach #2: Min Queue [Accepted] Intuition For each contiguous block ("window") of  k  po...