{"id":24991,"date":"2020-01-09T12:15:08","date_gmt":"2020-01-09T10:15:08","guid":{"rendered":"https:\/\/www.webcodegeeks.com\/?p=24991"},"modified":"2020-06-23T15:00:00","modified_gmt":"2020-06-23T12:00:00","slug":"71-python-code-snippets-for-everyday-problems","status":"publish","type":"post","link":"https:\/\/www.webcodegeeks.com\/python\/71-python-code-snippets-for-everyday-problems\/","title":{"rendered":"71 Python Code Snippets for Everyday Problems"},"content":{"rendered":"\n

If you\u2019ve been following me for any amount of time, you know that I regularly publish Python code snippets for everyday problems<\/a>. Well, I figured I\u2019d finally aggregate all those responses in one massive article with links to all those resources.<\/p>\n\n\n\n

Everyday Problems<\/h2>\n\n\n\n

In this section, we\u2019ll take a look at various common scenarios that arise and how to solve them with Python code. Specifically, I\u2019ll share a brief explanation of the problem with a list of Python code solutions. Then, I\u2019ll link all the resources I have.<\/p>\n\n\n\n

Inverting a Dictionary<\/h3>\n\n\n\n

Sometimes when we have a dictionary, we want to be able to flip its keys and values. Of course, there are concerns like \u201chow do we deal with duplicate values?\u201d and \u201cwhat if the values aren\u2019t hashable?\u201d That said, in the simple case, there are a few solutions:<\/p>\n\n\n\n

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# Use to invert dictionaries that have unique values<\/code><\/div>\n
my_inverted_dict = dict(map(reversed, my_dict.items()))<\/code><\/div>\n
 <\/div>\n
# Use to invert dictionaries that have unique values<\/code><\/div>\n
my_inverted_dict = {value: key <\/code>for<\/code> key, value in my_dict.items()}<\/code><\/div>\n
 <\/div>\n
# Use to invert dictionaries that have non-unique values<\/code><\/div>\n
from collections <\/code>import<\/code> defaultdict<\/code><\/div>\n
my_inverted_dict = defaultdict(list)<\/code><\/div>\n
{my_inverted_dict[v].append(k) <\/code>for<\/code> k, v in my_dict.items()}<\/code><\/div>\n
 <\/div>\n
# Use to invert dictionaries that have non-unique values<\/code><\/div>\n
my_inverted_dict = dict()<\/code><\/div>\n
for<\/code> key, value in my_dict.items():<\/code><\/div>\n
    <\/code>my_inverted_dict.setdefault(value, list()).append(key)<\/code><\/div>\n
 <\/div>\n
# Use to invert dictionaries that have lists of values<\/code><\/div>\n
my_dict = {value: key <\/code>for<\/code> key in my_inverted_dict <\/code>for<\/code> value in my_map[key]}<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

For more explanation, check out my article titled \u201cHow to Invert a Dictionary in Python<\/a>.\u201d It includes a breakdown of each solution, their performance metrics, and when they\u2019re applicable. Likewise, I have a YouTube video<\/a> which covers the same topic.<\/p>\n\n\n\n

Summing Elements of Two Lists<\/h3>\n\n\n\n

Let\u2019s say you have two lists, and you want to merge them together into a single list by element. In other words, you want to add the first element of the first list to the first element of the second list and store the result in a new list. Well, there are several ways to do that:<\/p>\n\n\n\n

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ethernet_devices = [<\/code>1<\/code>, [<\/code>7<\/code>], [<\/code>2<\/code>], [<\/code>8374163<\/code>], [<\/code>84302738<\/code>]]<\/code><\/div>\n
usb_devices = [<\/code>1<\/code>, [<\/code>7<\/code>], [<\/code>1<\/code>], [<\/code>2314567<\/code>], [<\/code>0<\/code>]]<\/code><\/div>\n
 <\/div>\n
# The <\/code>long<\/code> way<\/code><\/div>\n
all_devices = [<\/code><\/div>\n
    <\/code>ethernet_devices[<\/code>0<\/code>] + usb_devices[<\/code>0<\/code>],<\/code><\/div>\n
    <\/code>ethernet_devices[<\/code>1<\/code>] + usb_devices[<\/code>1<\/code>],<\/code><\/div>\n
    <\/code>ethernet_devices[<\/code>2<\/code>] + usb_devices[<\/code>2<\/code>],<\/code><\/div>\n
    <\/code>ethernet_devices[<\/code>3<\/code>] + usb_devices[<\/code>3<\/code>],<\/code><\/div>\n
    <\/code>ethernet_devices[<\/code>4<\/code>] + usb_devices[<\/code>4<\/code>]<\/code><\/div>\n
]<\/code><\/div>\n
 <\/div>\n
# Some comprehension magic<\/code><\/div>\n
all_devices = [x + y <\/code>for<\/code> x, y in zip(ethernet_devices, usb_devices)]<\/code><\/div>\n
 <\/div>\n
# Let's use maps<\/code><\/div>\n
import<\/code> operator <\/code><\/div>\n
all_devices = list(map(operator.add, ethernet_devices, usb_devices))<\/code><\/div>\n
 <\/div>\n
# We can't forget our favorite computation library<\/code><\/div>\n
import<\/code> numpy as np <\/code><\/div>\n
all_devices = np.add(ethernet_devices, usb_devices)<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

If you\u2019d like a deeper explanation, check out my article titled \u201cHow to Sum Elements of Two Lists in Python<\/a>\u201d which even includes a fun challenge. Likewise, you might get some value out of my YouTube video on the same topic<\/a>.<\/p>\n\n\n\n

Checking if a File Exists<\/h3>\n\n\n\n

One of the amazing perks of Python is how easy it is to manage files. Unlike Java, Python has a built-in syntax for file reading and writing. As a result, checking if a file exists is a rather brief task:<\/p>\n\n\n\n

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01<\/div>\n
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# Brute force with a <\/code>try<\/code>-except block (Python <\/code>3<\/code>+)<\/code><\/div>\n
try<\/code>: <\/code><\/div>\n
    <\/code>with open(<\/code>'\/path\/to\/file'<\/code>, <\/code>'r'<\/code>) as fh:<\/code><\/div>\n
        <\/code>pass<\/code><\/div>\n
except FileNotFoundError: <\/code><\/div>\n
    <\/code>pass<\/code><\/div>\n
 <\/div>\n
# Leverage the OS <\/code>package<\/code> (possible race condition)<\/code><\/div>\n
import<\/code> os <\/code><\/div>\n
exists = os.path.isfile(<\/code>'\/path\/to\/file'<\/code>)<\/code><\/div>\n
 <\/div>\n
# Wrap the path in an object <\/code>for<\/code> enhanced functionality<\/code><\/div>\n
from pathlib <\/code>import<\/code> Path<\/code><\/div>\n
config = Path(<\/code>'\/path\/to\/file'<\/code>) <\/code><\/div>\n
if<\/code> config.is_file(): <\/code><\/div>\n
    <\/code>pass<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

As always, you can learn more about these solutions in my article titled \u201cHow to Check if a File Exists in Python<\/a>\u201d which features three solutions and performances metrics.<\/p>\n\n\n\n

Converting Two Lists Into a Dictionary<\/h3>\n\n\n\n

Previously, we talked about summing two lists in Python. As it turns out, there\u2019s a lot we can do with two lists. For example, we could try mapping one onto the other to create a dictionary.<\/p>\n\n\n\n

As with many of these problems, there are a few concerns. For instance, what if the two lists aren\u2019t the same size? Likewise, what if the keys aren\u2019t unique or hashable? That said, in the simple case, there are some straightforward solutions:<\/p>\n\n\n\n

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column_names = [<\/code>'id'<\/code>, <\/code>'color'<\/code>, <\/code>'style'<\/code>]<\/code><\/div>\n
column_values = [<\/code>1<\/code>, <\/code>'red'<\/code>, <\/code>'bold'<\/code>]<\/code><\/div>\n
 <\/div>\n
# Convert two lists into a dictionary with zip and the dict constructor<\/code><\/div>\n
name_to_value_dict = dict(zip(column_names, column_values))<\/code><\/div>\n
 <\/div>\n
# Convert two lists into a dictionary with a dictionary comprehension<\/code><\/div>\n
name_to_value_dict = {key:value <\/code>for<\/code> key, value in zip(column_names, column_values)}<\/code><\/div>\n
 <\/div>\n
# Convert two lists into a dictionary with a loop<\/code><\/div>\n
name_value_tuples = zip(column_names, column_values) <\/code><\/div>\n
name_to_value_dict = {} <\/code><\/div>\n
for<\/code> key, value in name_value_tuples: <\/code><\/div>\n
    <\/code>if<\/code> key in name_to_value_dict: <\/code><\/div>\n
        <\/code>pass # Insert logic <\/code>for<\/code> handling duplicate keys <\/code><\/div>\n
    <\/code>else<\/code>: <\/code><\/div>\n
        <\/code>name_to_value_dict[key] = value<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

Once again, you can find an explanation for each of these solutions and more in my article titled \u201cHow to Convert Two Lists Into a Dictionary in Python<\/a>.\u201d If you are a visual person, you might prefer my YouTube video which covers mapping lists to dictionaries<\/a> as well.<\/p>\n\n\n\n

Checking if a List Is Empty<\/h3>\n\n\n\n

If you come from a statically typed language like Java or C, you might be bothered by the lack of static types in Python. Sure, not knowing the type of a variable can sometimes be frustrating, but there are perks as well. For instance, we can check if a list is empty by its type flexibility\u2014among other methods:<\/p>\n\n\n\n

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my_list = list()<\/code><\/div>\n
 <\/div>\n
# Check <\/code>if<\/code> a list is empty by its length<\/code><\/div>\n
if<\/code> len(my_list) == <\/code>0<\/code>:<\/code><\/div>\n
    <\/code>pass  # the list is empty<\/code><\/div>\n
 <\/div>\n
# Check <\/code>if<\/code> a list is empty by direct comparison (only works <\/code>for<\/code> lists)<\/code><\/div>\n
if<\/code> my_list == []:<\/code><\/div>\n
    <\/code>pass  # the list is empty<\/code><\/div>\n
 <\/div>\n
# Check <\/code>if<\/code> a list is empty by its type flexibility **preferred method**<\/code><\/div>\n
if<\/code> not my_list:<\/code><\/div>\n
    <\/code>pass  # the list is empty<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

If you\u2019d like to learn more about these three solutions, check out my article titled \u201cHow to Check if a List in Empty in Python<\/a>.\u201d If you\u2019re in a pinch, check out my YouTube video which covers the same topic<\/a>.<\/p>\n\n\n\n

Cloning a List<\/h3>\n\n\n\n

One of my favorite subjects in programming is copying data types. After all, it\u2019s never easy in this reference-based world we live, and that\u2019s true for Python as well. Luckily, if we want to copy a list, there are a few ways to do it:<\/p>\n\n\n\n

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my_list = [<\/code>27<\/code>, <\/code>13<\/code>, -<\/code>11<\/code>, <\/code>60<\/code>, <\/code>39<\/code>, <\/code>15<\/code>]<\/code><\/div>\n
 <\/div>\n
# Clone a list by brute force<\/code><\/div>\n
my_duplicate_list = [item <\/code>for<\/code> item in my_list]<\/code><\/div>\n
 <\/div>\n
# Clone a list with a slice<\/code><\/div>\n
my_duplicate_list = my_list[:]<\/code><\/div>\n
 <\/div>\n
# Clone a list with the list constructor<\/code><\/div>\n
my_duplicate_list = list(my_list) <\/code><\/div>\n
 <\/div>\n
# Clone a list with the copy function (Python <\/code>3.3<\/code>+)<\/code><\/div>\n
my_duplicate_list = my_list.copy()  # preferred method<\/code><\/div>\n
 <\/div>\n
# Clone a list with the copy <\/code>package<\/code><\/div>\n
import<\/code> copy<\/code><\/div>\n
my_duplicate_list = copy.copy(my_list)<\/code><\/div>\n
my_deep_duplicate_list = copy.deepcopy(my_list)<\/code><\/div>\n
 <\/div>\n
# Clone a list with multiplication?<\/code><\/div>\n
my_duplicate_list = my_list * <\/code>1<\/code>  # <\/code>do<\/code> not <\/code>do<\/code> this<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

When it comes to cloning, it\u2019s important to be aware of the difference between shallow and deep copies. Luckily, I have an article covering that topic<\/a>.<\/p>\n\n\n\n

Finally, you can find out more about the solutions listed above in my article titled \u201cHow to Clone a List in Python<\/a>.\u201d In addition, you might find value in my related YouTube video titled \u201c7 Ways to Copy a List in Python Featuring The Pittsburgh Penguins<\/a>.\u201d<\/p>\n\n\n\n

Retrieving the Last Item of a List<\/h3>\n\n\n\n

Since we\u2019re on the topic of lists, lets talk about getting the last item of a list. In most languages, this involves some convoluted mathematical expression involving the length of the list. What if I told you there is are several more interesting solutions in Python?<\/p>\n\n\n\n

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my_list = [<\/code>'red'<\/code>, <\/code>'blue'<\/code>, <\/code>'green'<\/code>]<\/code><\/div>\n
 <\/div>\n
# Get the last item with brute force using len<\/code><\/div>\n
last_item = my_list[len(my_list) - <\/code>1<\/code>]<\/code><\/div>\n
 <\/div>\n
# Remove the last item from the list using pop<\/code><\/div>\n
last_item = my_list.pop() <\/code><\/div>\n
 <\/div>\n
# Get the last item using negative indices *preferred & quickest method*<\/code><\/div>\n
last_item = my_list[-<\/code>1<\/code>]<\/code><\/div>\n
 <\/div>\n
# Get the last item using iterable unpacking<\/code><\/div>\n
*_, last_item = my_list<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

As always, you can learn more about these solutions from my article titled \u201cHow to Get the Last Item of a List in Python<\/a>\u201d which features a challenge, performance metrics, and a YouTube video<\/a>.<\/p>\n\n\n\n

Making a Python Script Shortcut<\/h3>\n\n\n\n

Sometimes when you create a script, you want to be able to run it conveniently at the click of a button. Fortunately, there are several ways to do that.<\/p>\n\n\n\n

First, we can create a Windows shortcut with the following settings:<\/p>\n\n\n\n

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\\path\\to\\trc-image-titler.py -o \\path\\to\\output<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

Likewise, we can also create a batch file with the following code:<\/p>\n\n\n\n

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@echo<\/code> off<\/code><\/div>\n
\\path\\to\\trc-image-titler.py -o \\path\\to\\output<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

Finally, we can create a bash script with the following code:<\/p>\n\n\n\n

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#!\/bin\/sh<\/code><\/div>\n
python \/path\/to\/trc-image-titler.py -o \/path\/to\/output<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

If you\u2019re looking for more explanation, check out the article titled \u201cHow to Make a Python Script Shortcut with Arguments<\/a>.\u201d<\/p>\n\n\n\n

Sorting a List of Strings<\/h3>\n\n\n\n

Sorting is a common task that you\u2019re expected to know how to implement in Computer Science. Despite the intense focus on sorting algorithms in most curriculum, no one really tells you how complicated sorting can actually get. For instance, sorting numbers is straightforward, but what about sorting strings? How do we decide a proper ordering? Fortunately, there are a lot of options in Python:<\/p>\n\n\n\n

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my_list = [<\/code>\"leaf\"<\/code>, <\/code>\"cherry\"<\/code>, <\/code>\"fish\"<\/code>]<\/code><\/div>\n
 <\/div>\n
# Brute force method using bubble sort<\/code><\/div>\n
my_list = [<\/code>\"leaf\"<\/code>, <\/code>\"cherry\"<\/code>, <\/code>\"fish\"<\/code>]<\/code><\/div>\n
size = len(my_list)<\/code><\/div>\n
for<\/code> i in range(size):<\/code><\/div>\n
    <\/code>for<\/code> j in range(size):<\/code><\/div>\n
        <\/code>if<\/code> my_list[i] < my_list[j]:<\/code><\/div>\n
            <\/code>temp = my_list[i]<\/code><\/div>\n
            <\/code>my_list[i] = my_list[j]<\/code><\/div>\n
            <\/code>my_list[j] = temp<\/code><\/div>\n
 <\/div>\n
# Generic list sort *fastest*<\/code><\/div>\n
my_list.sort()<\/code><\/div>\n
 <\/div>\n
# Casefold list sort<\/code><\/div>\n
my_list.sort(key=str.casefold)<\/code><\/div>\n
 <\/div>\n
# Generic list sorted<\/code><\/div>\n
my_list = sorted(my_list) <\/code><\/div>\n
 <\/div>\n
# Custom list sort using casefold (>= Python <\/code>3.3<\/code>)<\/code><\/div>\n
my_list = sorted(my_list, key=str.casefold) <\/code><\/div>\n
 <\/div>\n
# Custom list sort using current locale <\/code><\/div>\n
import<\/code> locale<\/code><\/div>\n
from functools <\/code>import<\/code> cmp_to_key<\/code><\/div>\n
my_list = sorted(my_list, key=cmp_to_key(locale.strcoll)) <\/code><\/div>\n
 <\/code> <\/div>\n
# Custom reverse list sort using casefold (>= Python <\/code>3.3<\/code>)<\/code><\/div>\n
my_list = sorted(my_list, key=str.casefold, reverse=True)<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

If you\u2019re curious about how some of these solutions work, or you just want to know what some of the potential risks are, check out my article titled \u201cHow to Sort a List of Strings in Python<\/a>.\u201d<\/p>\n\n\n\n

Parsing a Spreadsheet<\/h3>\n\n\n\n

One of the more interesting use cases for Python is data science. Unfortunately, however, that means handling a lot of raw data in various formats like text files and spreadsheets. Luckily, Python has plenty of built-in utilities for reading different file formats. For example, we can parse a spreadsheet with ease:<\/p>\n\n\n\n

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# Brute force solution<\/code><\/div>\n
csv_mapping_list = []<\/code><\/div>\n
with open(<\/code>\"\/path\/to\/data.csv\"<\/code>) as my_data:<\/code><\/div>\n
  <\/code>line_count = <\/code>0<\/code><\/div>\n
  <\/code>for<\/code> line in my_data:<\/code><\/div>\n
    <\/code>row_list = [val.strip() <\/code>for<\/code> val in line.split(<\/code>\",\"<\/code>)]<\/code><\/div>\n
    <\/code>if<\/code> line_count == <\/code>0<\/code>:<\/code><\/div>\n
      <\/code>header = row_list<\/code><\/div>\n
    <\/code>else<\/code>:<\/code><\/div>\n
      <\/code>row_dict = {key: value <\/code>for<\/code> key, value in zip(header, row_list)}<\/code><\/div>\n
      <\/code>csv_mapping_list.append(row_dict)<\/code><\/div>\n
    <\/code>line_count += <\/code>1<\/code><\/div>\n
 <\/div>\n
# CSV reader solution<\/code><\/div>\n
import<\/code> csv<\/code><\/div>\n
csv_mapping_list = []<\/code><\/div>\n
with open(<\/code>\"\/path\/to\/data.csv\"<\/code>) as my_data:<\/code><\/div>\n
    <\/code>csv_reader = csv.reader(my_data, delimiter=<\/code>\",\"<\/code>)<\/code><\/div>\n
    <\/code>line_count = <\/code>0<\/code><\/div>\n
    <\/code>for<\/code> line in csv_reader:<\/code><\/div>\n
        <\/code>if<\/code> line_count == <\/code>0<\/code>:<\/code><\/div>\n
            <\/code>header = line<\/code><\/div>\n
        <\/code>else<\/code>:<\/code><\/div>\n
            <\/code>row_dict = {key: value <\/code>for<\/code> key, value in zip(header, line)}<\/code><\/div>\n
            <\/code>csv_mapping_list.append(row_dict)<\/code><\/div>\n
        <\/code>line_count += <\/code>1<\/code><\/div>\n
 <\/div>\n
# CSV DictReader solution<\/code><\/div>\n
import<\/code> csv<\/code><\/div>\n
with open(<\/code>\"\/path\/to\/dict.csv\"<\/code>) as my_data:<\/code><\/div>\n
    <\/code>csv_mapping_list = list(csv.DictReader(my_data))<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

In this case, we try to get our output in a list of dictionaries. If you want to know more about how this works, check out the complete article titled \u201cHow to Parse a Spreadsheet in Python<\/a>.\u201d<\/p>\n\n\n\n

Sorting a List of Dictionaries<\/h3>\n\n\n\n

Once you have a list of dictionaries, you might want to organize them in some specific order. For example, if the dictionaries have a key for date, we can try sorting them in chronological order. Luckily, sorting is another relatively painless task:<\/p>\n\n\n\n

\n
\n\n\n\n
\n
01<\/div>\n
02<\/div>\n
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05<\/div>\n
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33<\/div>\n
34<\/div>\n
35<\/div>\n
36<\/div>\n
37<\/div>\n<\/td>\n
\n
\n
csv_mapping_list = [<\/code><\/div>\n
  <\/code>{<\/code><\/div>\n
    <\/code>\"Name\"<\/code>: <\/code>\"Jeremy\"<\/code>,<\/code><\/div>\n
    <\/code>\"Age\"<\/code>: <\/code>25<\/code>,<\/code><\/div>\n
    <\/code>\"Favorite Color\"<\/code>: <\/code>\"Blue\"<\/code><\/div>\n
  <\/code>},<\/code><\/div>\n
  <\/code>{<\/code><\/div>\n
     <\/code>\"Name\"<\/code>: <\/code>\"Ally\"<\/code>,<\/code><\/div>\n
     <\/code>\"Age\"<\/code>: <\/code>41<\/code>,<\/code><\/div>\n
     <\/code>\"Favorite Color\"<\/code>: <\/code>\"Magenta\"<\/code><\/div>\n
  <\/code>},<\/code><\/div>\n
  <\/code>{<\/code><\/div>\n
    <\/code>\"Name\"<\/code>: <\/code>\"Jasmine\"<\/code>,<\/code><\/div>\n
    <\/code>\"Age\"<\/code>: <\/code>29<\/code>,<\/code><\/div>\n
    <\/code>\"Favorite Color\"<\/code>: <\/code>\"Aqua\"<\/code><\/div>\n
  <\/code>}<\/code><\/div>\n
]<\/code><\/div>\n
 <\/div>\n
# Custom sorting<\/code><\/div>\n
size = len(csv_mapping_list)<\/code><\/div>\n
for<\/code> i in range(size):<\/code><\/div>\n
    <\/code>min_index = i<\/code><\/div>\n
    <\/code>for<\/code> j in range(i + <\/code>1<\/code>, size):<\/code><\/div>\n
        <\/code>if<\/code> csv_mapping_list[min_index][<\/code>\"Age\"<\/code>] > csv_mapping_list[j][<\/code>\"Age\"<\/code>]:<\/code><\/div>\n
            <\/code>min_index = j<\/code><\/div>\n
    <\/code>csv_mapping_list[i], csv_mapping_list[min_index] = csv_mapping_list[min_index], csv_mapping_list[i]<\/code><\/div>\n
 <\/div>\n
# List sorting function<\/code><\/div>\n
csv_mapping_list.sort(key=lambda item: item.get(<\/code>\"Age\"<\/code>))<\/code><\/div>\n
 <\/div>\n
# List sorting using itemgetter<\/code><\/div>\n
from operator <\/code>import<\/code> itemgetter<\/code><\/div>\n
f = itemgetter(<\/code>'Name'<\/code>)<\/code><\/div>\n
csv_mapping_list.sort(key=f)<\/code><\/div>\n
 <\/div>\n
# Iterable sorted function<\/code><\/div>\n
csv_mapping_list = sorted(csv_mapping_list, key=lambda item: item(<\/code>\"Age\"<\/code>))<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

All these solutions and more outlined in my article titled \u201cHow to Sort a List of Dictionaries in Python<\/a>.\u201d<\/p>\n\n\n\n

Writing a List Comprehension<\/h3>\n\n\n\n

One of my favorite Python topics to chat about is list comprehensions. As someone who grew up on languages like Java, C\/C++, and C#, I had never seen anything quite like a list comprehension until I played with Python. Now, I\u2019m positively obsessed with them. As a result, I put together an entire list of examples:<\/p>\n\n\n\n

\n
\n\n\n\n
\n
01<\/div>\n
02<\/div>\n
03<\/div>\n
04<\/div>\n
05<\/div>\n
06<\/div>\n
07<\/div>\n
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09<\/div>\n
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11<\/div>\n
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13<\/div>\n
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24<\/div>\n
25<\/div>\n
26<\/div>\n
27<\/div>\n
28<\/div>\n
29<\/div>\n
30<\/div>\n<\/td>\n
\n
\n
# Define a generic 1D list of constants<\/code><\/div>\n
my_list = [<\/code>2<\/code>, <\/code>5<\/code>, -<\/code>4<\/code>, <\/code>6<\/code>]<\/code><\/div>\n
 <\/div>\n
# Duplicate a 1D list of constants<\/code><\/div>\n
[item <\/code>for<\/code> item in my_list]<\/code><\/div>\n
 <\/div>\n
# Duplicate and scale a 1D list of constants<\/code><\/div>\n
[<\/code>2<\/code> * item <\/code>for<\/code> item in my_list]<\/code><\/div>\n
 <\/div>\n
# Duplicate and filter out non-negatives from 1D list of constants<\/code><\/div>\n
[item <\/code>for<\/code> item in my_list <\/code>if<\/code> item < <\/code>0<\/code>]<\/code><\/div>\n
 <\/div>\n
# Duplicate, filter, and scale a 1D list of constants<\/code><\/div>\n
[<\/code>2<\/code> * item <\/code>for<\/code> item in my_list <\/code>if<\/code> item < <\/code>0<\/code>]<\/code><\/div>\n
 <\/div>\n
# Generate all possible pairs from two lists<\/code><\/div>\n
[(a, b) <\/code>for<\/code> a in (<\/code>1<\/code>, <\/code>3<\/code>, <\/code>5<\/code>) <\/code>for<\/code> b in (<\/code>2<\/code>, <\/code>4<\/code>, <\/code>6<\/code>)]<\/code><\/div>\n
 <\/div>\n
# Redefine list of contents to be 2D<\/code><\/div>\n
my_list = [[<\/code>1<\/code>, <\/code>2<\/code>], [<\/code>3<\/code>, <\/code>4<\/code>]]<\/code><\/div>\n
 <\/div>\n
# Duplicate a 2D list<\/code><\/div>\n
[[item <\/code>for<\/code> item in sub_list] <\/code>for<\/code> sub_list in my_list]<\/code><\/div>\n
 <\/div>\n
# Duplicate an n-dimensional list<\/code><\/div>\n
def deep_copy(to_copy):<\/code><\/div>\n
    <\/code>if<\/code> type(to_copy) is list:<\/code><\/div>\n
        <\/code>return<\/code> [deep_copy(item) <\/code>for<\/code> item in to_copy]<\/code><\/div>\n
    <\/code>else<\/code>:<\/code><\/div>\n
        <\/code>return<\/code> to_copy<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

As always, you can find a more formal explanation of all this code in my article titled \u201cHow to Write a List Comprehension in Python<\/a>.\u201d As an added bonus, I have a YouTube video which shares several examples of list comprehensions<\/a>.<\/p>\n\n\n\n

Merging Two Dictionaries<\/h3>\n\n\n\n

In this collection, we talk a lot about handling data structures like lists and dictionaries. Well, this one is no different. In particular, we\u2019re looking at merging two dictionaries. Of course, combining two dictionaries comes with risks. For example, what if there are duplicate keys? Luckily, we have solutions for that:<\/p>\n\n\n\n

\n
\n\n\n\n
\n
01<\/div>\n
02<\/div>\n
03<\/div>\n
04<\/div>\n
05<\/div>\n
06<\/div>\n
07<\/div>\n
08<\/div>\n
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25<\/div>\n<\/td>\n
\n
\n
yusuke_power = {<\/code>\"Yusuke Urameshi\"<\/code>: <\/code>\"Spirit Gun\"<\/code>}<\/code><\/div>\n
hiei_power = {<\/code>\"Hiei\"<\/code>: <\/code>\"Jagan Eye\"<\/code>}<\/code><\/div>\n
powers = dict()<\/code><\/div>\n
 <\/div>\n
# Brute force<\/code><\/div>\n
for<\/code> dictionary in (yusuke_power, hiei_power):<\/code><\/div>\n
    <\/code>for<\/code> key, value in dictionary.items():<\/code><\/div>\n
        <\/code>powers[key] = value<\/code><\/div>\n
 <\/div>\n
# Dictionary Comprehension<\/code><\/div>\n
powers = {key: value <\/code>for<\/code> d in (yusuke_power, hiei_power) <\/code>for<\/code> key, value in d.items()}<\/code><\/div>\n
 <\/div>\n
# Copy and update<\/code><\/div>\n
powers = yusuke_power.copy()<\/code><\/div>\n
powers.update(hiei_power)<\/code><\/div>\n
 <\/div>\n
# Dictionary unpacking (Python <\/code>3.5<\/code>+)<\/code><\/div>\n
powers = {**yusuke_power, **hiei_power}<\/code><\/div>\n
 <\/div>\n
# Backwards compatible function <\/code>for<\/code> any number of dicts<\/code><\/div>\n
def merge_dicts(*dicts: dict):<\/code><\/div>\n
    <\/code>merged_dict = dict()<\/code><\/div>\n
    <\/code>for<\/code> dictionary in dicts:<\/code><\/div>\n
        <\/code>merge_dict.update(dictionary)<\/code><\/div>\n
    <\/code>return<\/code> merged_dict<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

If you\u2019re interested, I have an article which covers this exact topic called \u201cHow to Merge Two Dictionaries in Python<\/a>\u201d which features four solutions as well performance metrics.<\/p>\n\n\n\n

Formatting a String<\/h3>\n\n\n\n

Whether we like to admit it or not, we often find ourselves burying print statements throughout our code for quick debugging purposes. After all, a well placed print statement can save you a lot of time. Unfortunately, it\u2019s not always easy or convenient to actually display what we want. Luckily, Python has a lot of formatting options:<\/p>\n\n\n\n

\n
\n\n\n\n
\n
01<\/div>\n
02<\/div>\n
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26<\/div>\n
27<\/div>\n<\/td>\n
\n
\n
name = Jeremy<\/code><\/div>\n
age = <\/code>25<\/code><\/div>\n
 <\/div>\n
# String formatting using concatenation<\/code><\/div>\n
print(<\/code>\"My name is \"<\/code> + name + <\/code>\", and I am \"<\/code> + str(age) + <\/code>\" years old.\"<\/code>)<\/code><\/div>\n
 <\/div>\n
# String formatting using multiple prints<\/code><\/div>\n
print(<\/code>\"My name is \"<\/code>, end=<\/code>\"\"<\/code>)<\/code><\/div>\n
print(name, end=<\/code>\"\"<\/code>)<\/code><\/div>\n
print(<\/code>\", and I am \"<\/code>, end=<\/code>\"\"<\/code>)<\/code><\/div>\n
print(age, end=<\/code>\"\"<\/code>)<\/code><\/div>\n
print(<\/code>\" years old.\"<\/code>)<\/code><\/div>\n
 <\/div>\n
# String formatting using join<\/code><\/div>\n
print(<\/code>''<\/code>.join([<\/code>\"My name is \"<\/code>, name, <\/code>\", and I am \"<\/code>, str(age), <\/code>\" years old\"<\/code>]))<\/code><\/div>\n
 <\/div>\n
# String formatting using modulus operator<\/code><\/div>\n
print(<\/code>\"My name is %s, and I am %d years old.\"<\/code> % (name, age))<\/code><\/div>\n
 <\/div>\n
# String formatting using format function with ordered parameters<\/code><\/div>\n
print(<\/code>\"My name is {}, and I am {} years old\"<\/code>.format(name, age))<\/code><\/div>\n
 <\/div>\n
# String formatting using format function with named parameters<\/code><\/div>\n
print(<\/code>\"My name is {n}, and I am {a} years old\"<\/code>.format(a=age, n=name))<\/code><\/div>\n
 <\/div>\n
# String formatting using f-Strings (Python <\/code>3.6<\/code>+)<\/code><\/div>\n
print(f<\/code>\"My name is {name}, and I am {age} years old\"<\/code>)<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

Keep in mind that these solutions don\u2019t have to be used with print statements. In other words, feel free to use solutions like f-strings wherever you need them.<\/p>\n\n\n\n

As always, you can find an explanation of all these solutions and more in my article titled \u201cHow to Format a String in Python<\/a>.\u201d If you\u2019d rather see these snippets in action, check out my YouTube video titled \u201c6 Ways to Format a String in Python Featuring My Cat<\/a>.\u201d<\/p>\n\n\n\n

Printing on the Same Line<\/h3>\n\n\n\n

Along a similar line as formatting strings, sometimes you just need to print on the same line in Python. As the print<\/code> command is currently designed, it automatically applies a newline to the end of your string. Luckily, there are a few ways around that:<\/p>\n\n\n\n

\n
\n\n\n\n
\n
1<\/div>\n
2<\/div>\n
3<\/div>\n
4<\/div>\n
5<\/div>\n
6<\/div>\n
7<\/div>\n
8<\/div>\n
9<\/div>\n<\/td>\n
\n
\n
# Python <\/code>2<\/code> only<\/code><\/div>\n
print <\/code>\"Live PD\"<\/code>,<\/code><\/div>\n
 <\/div>\n
# Backwards compatible (also fastest)<\/code><\/div>\n
import<\/code> sys<\/code><\/div>\n
sys.stdout.write(<\/code>\"Breaking Bad\"<\/code>)<\/code><\/div>\n
 <\/div>\n
# Python <\/code>3<\/code> only<\/code><\/div>\n
print(<\/code>\"Mob Psycho 100\"<\/code>, end=<\/code>\"\"<\/code>)<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

As always, if you plan to use any of these solutions, check out the article titled \u201cHow to Print on the Same Line in Python<\/a>\u201d for additional use cases and caveats.<\/p>\n\n\n\n

Testing Performance<\/h3>\n\n\n\n

Finally, sometimes you just want to compare a couple chunks of code. Luckily, Python has a few straightforward options:<\/p>\n\n\n\n

\n
\n\n\n\n
\n
01<\/div>\n
02<\/div>\n
03<\/div>\n
04<\/div>\n
05<\/div>\n
06<\/div>\n
07<\/div>\n
08<\/div>\n
09<\/div>\n
10<\/div>\n
11<\/div>\n
12<\/div>\n
13<\/div>\n
14<\/div>\n<\/td>\n
\n
\n
# Brute force solution<\/code><\/div>\n
import<\/code> datetime<\/code><\/div>\n
start_time = datetime.datetime.now()<\/code><\/div>\n
[(a, b) <\/code>for<\/code> a in (<\/code>1<\/code>, <\/code>3<\/code>, <\/code>5<\/code>) <\/code>for<\/code> b in (<\/code>2<\/code>, <\/code>4<\/code>, <\/code>6<\/code>)] # example snippet<\/code><\/div>\n
end_time = datetime.datetime.now()<\/code><\/div>\n
print end_time - start_time<\/code><\/div>\n
 <\/div>\n
# timeit solution<\/code><\/div>\n
import<\/code> timeit<\/code><\/div>\n
min(timeit.repeat(<\/code>\"[(a, b) for a in (1, 3, 5) for b in (2, 4, 6)]\"<\/code>))<\/code><\/div>\n
 <\/div>\n
# cProfile solution<\/code><\/div>\n
import<\/code> cProfile<\/code><\/div>\n
cProfile.run(<\/code>\"[(a, b) for a in (1, 3, 5) for b in (2, 4, 6)]\"<\/code>)<\/code><\/div>\n<\/div>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n\n\n\n

Again, if you want more details, check the article titled \u201cHow to Performance Test Python Code<\/a>.\u201d<\/p>\n\n\n\n

Share Your Own Problems<\/h2>\n\n\n\n

As you can see, this article and its associated series is already quite large. That said, I\u2019d love to continue growing them. As a result, you should consider sharing some of your own problems. After all, there has be something you Google regularly. Why not share it with us?<\/p>\n\n\n\n

\n\n\n\n
\n

Published on Web Code Geeks with permission by Jeremy Grifski, partner at our WCG program<\/a>. See the original article here: 71 Python Code Snippets for Everyday Problems<\/a><\/p>\n

Opinions expressed by Web Code Geeks contributors are their own.<\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

If you\u2019ve been following me for any amount of time, you know that I regularly publish Python code snippets for everyday problems. Well, I figured I\u2019d finally aggregate all those responses in one massive article with links to all those resources. Everyday Problems In this section, we\u2019ll take a look at various common scenarios that …<\/p>\n","protected":false},"author":14722,"featured_media":1651,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[53],"tags":[],"class_list":["post-24991","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-python"],"yoast_head":"\n71 Python Code Snippets for Everyday Problems - Web Code Geeks - 2026<\/title>\n<meta name=\"description\" content=\"Interested to learn about Python Code Snippets? 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