{"id":29839,"date":"2023-02-26T13:40:44","date_gmt":"2023-02-26T13:40:44","guid":{"rendered":"https:\/\/holypython.com\/?p=29839"},"modified":"2023-02-26T14:45:22","modified_gmt":"2023-02-26T14:45:22","slug":"advanced-level-python-tips-tricks","status":"publish","type":"post","link":"https:\/\/holypython.com\/advanced-level-python-tips-tricks\/","title":{"rendered":"Advanced Level Python Tips & Tricks"},"content":{"rendered":"\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Python Tips & Tricks (Part III)<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Advanced Level<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

HolyPython.com<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

Here are more Python tips about relatively more complex Python concepts.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t

71) Annotated Assignment Statement: (:<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

This might not seem as impressive as some other tricks but it’s a new syntax that was introduced to Python in recent years and just good to be aware of.<\/p>

Annotated assignments allow the coder to leave type hints\u00a0<\/strong>in the code. These don’t have any enforcing power at least not yet. It’s still nice to be able to imply some type hints and definitely offers more options than only being able to comment regarding expected types of variables.<\/p>

Check out some of these examples:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t

\n\t\t\t\t
\n\t\t\t\t\t
day: str = 'Saturday'\nprint(day)\n\nlst: list = [1,2,3]\nprint(lst)\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
'Saturday'
[1,2,3]<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
The slightly less cool and older implementation would be like this:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
day= 'Saturday' #str\nprint(day)\n\nlst= [1,2,3] # list\nprint(lst)\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
You can read Python Official Documentation about Annotated Assignments here<\/a>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
72) Yield Statement: (<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
You can think of yield statement in the same category as the return<\/strong> statement. The difference is, while return statement returns a value and the function ends, yield statement can return a sequence of values, it sort of yields, hence the name.<\/p>
If you’re interested in algorithms, here is a nice demonstration of Bubble Sort Algorithm Visualization<\/a> where you can see how yield is needed and used.<\/p>
Also, here are a couple of examples with yield statement:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
def f1(a):\n    yield a\n    yield a**2\n    yield a**3\n    \nprint (f1(5))\n\nfor i in f1(5):\n    print (i)    \n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
<generator object f1 at 0x00000275EF339AC8>\n5\n25\n125<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
def f2(b):\n    for j in range(b):\n        yield j\n\nfor i in f2(5):\n    print(i)\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
0
1
2
3
4<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
73) News brought to you by: (Python Newspaper<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Another fabulous Python library newspaper3k gives a whole another meaning to newspaper access.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\t\t\t\t
Sleek businessperson reading business newspaper<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
You can install newspaper3k via pip from your Anaconda Command Prompt. If you need more instructions you can check out this article regarding how to install packages using pip with Anaconda<\/a>.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
pip install newspaper\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
After installing newspaper3k you can start using it. Here are some examples:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
import newspaper\n\npaper = newspaper.build('http:\/\/theatlantic.com')\n\nfor article in paper.articles:\n    print(article.url)\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Code above will list all the articles found in the entire newspaper.<\/p>
Check out the code below to see all the other attributes you can conveniently extract from a single article or a whole newspaper.<\/p>
Information is power, when managed well it can offer great contributions to specific tasks, projects and objectives.<\/p>
\u00a0<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
from newspaper import Article\n\nurl = 'https:\/\/www.theatlantic.com\/ideas\/archive\/2020\/06\/daca-activism\/613213\/'\narticle = Article(url)\n\narticle.download()\narticle.parse()\n\n\nprint(article.text)\nprint(article.authors)\nprint(article.publish_date)\nprint(article.images)\nprint(article.title)\nprint(article.tags)\nprint(article.summary)\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
You can see the Github repository of this cool Python library here: Newspaper 3k Github<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
74) Geopy: (Work on Open File<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Geopy is another great library that can be used for geocoding services. Converting open addresses to longitude and latitude values or converting coordinates to addresses is called geocoding. It’s a common application with almost any location related service such as media sharing, social network, navigation, transportation, streaming, gaming, websites, communication, identification, security etc.<\/p>
Here are some simple examples to demonstrate what you can quickly do with geopy library using the address of New York rooftop bar 230 Fifth.<\/strong><\/p>
Please note that you might need to change the user_agent to avoid application errors. One common error related to user_agent is InsufficientPrivilege Error.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
from geopy.geocoders import Nominatim\ngeolocator = Nominatim(user_agent=\"HiApp\")\nlocation = geolocator.geocode(\" 230 Fifth Ave, New York\")\n\nprint(location.address)\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
230, Fifth Avenue, Sheridan Meadows, Amherst Town, Erie County, New York, 14221, United States of America<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
print((location.latitude, location.longitude))\n\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
(42.983481438214326, -78.70683044449504)<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
print(location.raw)\n\n\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
{'place_id': 259174015, 'licence': 'Data \u00a9 OpenStreetMap contributors, ODbL 1.0. \nhttps:\/\/osm.org\/copyright', 'osm_type': 'way', 'osm_id': 12316939, 'boundingbox': \n['42.983431438214', '42.983531438214', '-78.706880444495', '-78.706780444495'], \n'lat': '42.983481438214326', 'lon': '-78.70683044449504', 'display_name': '230, \nFifth Avenue, Sheridan Meadows, Amherst Town, Erie County, New York, 14221, \nUnited States of America', 'class': 'place', 'type': 'house', 'importance': 0.511}<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Open Street Map’s Nominatim is a very convenient geocoding service but you should check their official documentation for any serious use case.<\/p>
Some other similar web services are\u00a0Geonames, Yandex Map API,\u00a0Bing Map API, Google Maps API V3 and Yahoo BOSS Finder. They all offer different usage benefits.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\t\t\t\t
Big Apple and Lake States Satellite View at Night<\/figcaption>\n\t\t\t\t\t\t\t\t\t\t<\/figure>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
75) sh: (Shell scripts and bash commands<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
sh is a subprocess wrapper that can be used to dynamically map system functions to Python. It facilitates writing shell scripts with bash features.<\/p>
Unfortunately latest version of sh only works for linux and Mac. If you’re using Windows you’ll need to install an old version that can be found here<\/a>.<\/p>
Let’s check out some examples of what can be done with sh:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
import sh\r\nsh.google_chrome(\"http:\/\/google.com\u201d)\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Here are some other ideas:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
import sh\r\n\r\nsh.whoami()\r\nsh.pwd()\r\nsh.mkdir('foldername')\r\nsh.touch('filename.txt')\r\nsh.echo('Hello World')\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
76) Decorators: (Augmenting functions without modifications<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Decorators are another elegant representative of Python’s expressive and minimalistic syntax.<\/p>
By using decorators you can change a function’s behavior or outcome without actually modifying it.<\/p>
In other words decorators decorate functions to make them fancier in some way.<\/p>
A decorator starts with @ <\/strong>sign in Python syntax and is placed just before the function.<\/p>
Here are some simple examples:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Let’s say we have a simple function that adds 2 numbers.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
def adder(a, b): \r\n    return a+b\r\n    \r\nprint(adder(2, 3))\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
5<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Now, without touching the original function, let’s decorate it so that it multiplies the result by 100.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
def decoten(func): \r\n    def times10(x, y): \r\n        return func(x*10, y*10) \r\n    return times10\r\n\r\n@decoten\r\ndef adder(a, b): \r\n    return a+b \r\n\r\nprint(adder(2,3))\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
50<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
77: Memory Optimization: (__slots__<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
At the advanced level Python can have<\/p>
When you start editing default Python implementations for speed and efficiency reasons you know you’re starting to get into the expert territory.<\/p>
Python classes utilize dictionaries for instant attributes by default which can take quite a space even when you’re constructing a class object.<\/p>
When this is the case you can use __slots__ magic to force Python not to have a big chunks default instance attribute dictionary and instead have a small custom list. This can save lots of memory in suitable applications.<\/p>
On top of that, another benefit of __slots__ is faster access to class attributes.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Real Madrid : 5<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
class Team:\r\n    __slots__ = [\"name\", \"score\"]\r\n    def __init__(self, name, score):\r\n        self.name = name\r\n        self.score = score\r\n        \r\n\r\na=Team(\"Real Madrid\", 5)\r\nprint(a.name, a.score, sep=\" : \")\r\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
78) Time it: (Time Processes<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
timeit library is great for timing Python execution times. Just pass a function in string format to timeit.timeit()<\/b> method and it will carry out 1 million executions to report the minimum time the code takes.<\/p>
Its very useful to compare small code pieces and different functions but can be sluggish with big code.<\/p>
Check out the example below demonstrating the execution time difference between 2 very similar list comprehension methods in Python:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
import timeit\r\n\r\nlst1='''list(range(1000))'''\r\nlst2='''[i for i in range(1000)]'''\r\n\r\nx=timeit.timeit(lst1)\r\ny=timeit.timeit(lst2)\r\n\r\nprint(x, y, sep=\"------\")<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
11.646945999999843 ------- 27.643676500000083<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
timeit library is great for timing Python execution times. Just pass a function in string format to timeit.timeit() method and it will carry out 1 million executions to report the minimum time the code takes.<\/p>\n
Its very useful to compare small code pieces and different functions but can be sluggish with big code.<\/p>
Check out the example below demonstrating the execution time difference between 2 very similar list comprehension methods in Python:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
79) Virtual env: (Managing Dependencies<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Virtual Environment lets programmer create a specific environment with different versions of libraries when needed.<\/p>
When the developer needs only certain versions of modules and libraries because development requires it virtual environment can be a practical solution.<\/p>
It’s also quite straightforward with Python.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Make sure virtualenv module is installed (Installed by default in Anaconda3)<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
pip install virtualenv<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
To create a virtual environment type virtualenv followed by an environment name you’d like:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
virtualenv environment1<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
you can also activate and deactivate a virtual environment simply by typing:<\/p>
activate environment1<\/code><\/p>
deactivate<\/code><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
You’ll need to activate your specific virtual environment before installing a specific module with a specific version. Once you are done working in that environment you can deactivate it and go back to base.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
80) Groupby from itertools: (Grouping Python Data<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
If you have iterables with elements belonging to different groups, you can use itertools’ groupby method to group them and process items in groups.<\/p>
Here is an example:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
from itertools import groupby\r\n\r\nlst = [(\"car\", \"Ferrari\"), (\"car\", \"Renault\"), (\"country\", \"France\"), (\"country\", \"New Zealand\"), (\"fruit\", \"Kiwi\")]\r\n\r\nfor i, group in groupby(lst, lambda x: x[0]):\r\n    for j in group:\r\n        print (\"{} is a {}.\".format(j[1], val))\r\n    print()<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
Ferrari is a fruit.\nRenault is a fruit.\n\nFrance is a fruit.\nNew Zealand is a fruit.\n\nKiwi is a fruit.<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
81) Transposing Data: (zip method<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
This trick is simple yet genius and can be very useful sometimes.<\/p>
You can combine zip function and * unpacking <\/strong>notation for *args appropriate objects.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
mat = [[1, 2, 3], [1000, 2000, 3000]]\nzip(*mat)<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
[(1, 1000), (2, 2000), (3, 3000)]<\/pre>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
82) Working with Zipped files: (ZipFile Library<\/i>)<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
As you get more and more proficient with Python, you start experimenting more and more cases. One of these cases is encountering zip files whether it’s data science, game development, finance or scripting, zip files are a very common part of the digital world.<\/p>
Let’s check out how zipfile library can be a super convenient and quick solution for zip related tasks.<\/p>
First you can import zipfile as below:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t
from zipfile import ZipFile\n<\/code><\/pre>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t
There are many useful methods to be used with zipfile, here are some common ones:<\/p>