Author: John Au-Yeung

Sometimes, we want to terminate a script with Python.

In this article, we’ll look at how to terminate a script with Python.

How to terminate a script with Python?

To terminate a script with Python, we can use the sys.exit method.

For instance, we write:

import sys

sys.exit()

to exit the script.

Conclusion

To terminate a script with Python, we can use the sys.exit method.

Sometimes, we want to get all subsets of a set (powerset) with Python.

In this article, we’ll look at how to get all subsets of a set (powerset) with Python.

How to get all subsets of a set (powerset) with Python?

To get all subsets of a set (powerset) with Python, we can use the chain.from_iterable and combinations functions.

For instance, we write:

from itertools import chain, combinations


def powerset(iterable):
    s = list(iterable)
    return chain.from_iterable(combinations(s, r) for r in range(len(s) + 1))


p = list(powerset("abc"))
print(p)

We define the powerset function that takes an iterable object.

In the function, we convert the iterable object to a list with list.

Then we call chain.from_iterable with the list of combinations of all the elements in s.

We get all combinatins with r going from 0 to range(len(s) + 1).

Each combination is stored in a tuple.

Therefore, p is:

[(), ('a',), ('b',), ('c',), ('a', 'b'), ('a', 'c'), ('b', 'c'), ('a', 'b', 'c')]

Conclusion

To get all subsets of a set (powerset) with Python, we can use the chain.from_iterable and combinations functions.

Sometimes, we want to sort a list of strings numerically with Python.

In this article, we’ll look at how to sort a list of strings numerically with Python.

How to sort a list of strings numerically with Python?

To sort a list of strings numerically with Python, we can use the int function to convert the number strings into integers.

Then we call sort on the integer array to sort the integers.

For instance, we write:

list1 = ["1", "10", "3", "22", "23", "4", "2", "200"]
list1 = [int(x) for x in list1]
list1.sort()
print(list1)

We convert each string to integers with [int(x) for x in list1], return that in an array, and assign it to list1.

Then we call list1.sort to sort the integer array in place.

Therefore, list1, is [1, 2, 3, 4, 10, 22, 23, 200].

Conclusion

To sort a list of strings numerically with Python, we can use the int function to convert the number strings into integers.

Then we call sort on the integer array to sort the integers.

Sometimes, we want to read specific lines from a file by line number with Python.

In this article, we’ll look at how to read specific lines from a file by line number with Python.

How to read specific lines from a file by line number with Python?

To read specific lines from a file by line number with Python, we can use the open and enumerate functions.

For instance, if we have the following text file:

foo.txt:

foo
bar
baz

Then we can read the 3rd line of the file by writing:

with open("foo.txt") as fp:
    for i, line in enumerate(fp):
        if i == 2:
            print(line)

We call open with the path to the text file.

Then we loop through each line with the index i and line returned by enumerate.

We check if i is 2 to check if it’s reading the 3rd line.

If that’s True, then we call print to print the line.

So we see ‘baz’ printed.

Conclusion

To read specific lines from a file by line number with Python, we can use the open and enumerate functions.

Sometimes, we want to convert a Python dict into a Pandas DataFrame.

In this article, we’ll look at how to convert a Python dict into a Pandas DataFrame.

How to convert a Python dict into a Pandas DataFrame?

To convert a Python dict into a Pandas DataFrame, we can use the DataFrame constructor with an iterator with the tuples of the key-value pairs.

For instance, we write:

import pandas as pd

d = {
    u'2012-06-08': 388,
    u'2012-06-09': 388,
    u'2012-06-10': 388,
    u'2012-06-11': 389,
    u'2012-06-12': 389,
    u'2012-06-13': 389
}
df = pd.DataFrame(d.items())
print(df)

to convert the d dictionary to a DataFrame.

We call d.items to return the iterator with the tuples of the key-value pairs and use that as the argument of DataFrame.

And then we assign the returned DataFrame to df.

Therefore, we get:

            0    1
0  2012-06-08  388
1  2012-06-09  388
2  2012-06-10  388
3  2012-06-11  389
4  2012-06-12  389
5  2012-06-13  389

as the value of df.

Conclusion

To convert a Python dict into a Pandas DataFrame, we can use the DataFrame constructor with an iterator with the tuples of the key-value pairs.