Learn Python Coding

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A bit of Python basics. Day 4: Getting the current time and date The code below shows how to get the current time using the datetime module. The now() method returns a datetime object representing the current date and time according to the system clock. The strftime() method formats the time for the desired output. This code shows how to use the datetime module together with the strftime() method to get a formatted time string in the format of hours, minutes, and seconds.

from datetime import datetime

time_now = datetime.now().strftime('%H:%M:%S')
print(f'Current time: {time_now}')

Current time: 17:37:28

What if we want to return today's date? We can use date from the datetime module. Below, the today() method is used:

from datetime import date

today_date = date.today()
print(today_date)

2023-09-20

👉 https://t.me/DataScience4

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A bit of basics. Day 3: Calendar in Python There is a built-in module in Python called calendar. We can import this module to display the calendar. There are many things you can do with the calendar. Let's say we want to see the calendar for April 2022. We use the month class from the calendar module and pass the year and month as arguments. See below:

import calendar

month = calendar.month(2022, 4)
print(month)

There are many other things you can do with calendar. For example, you can use it to check whether a given year is a leap year or not. Let's check if 2022 is a leap year.

import calendar

month = calendar.isleap(2022)
print(month)

False 👉 https://t.me/DataScience4

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A bit of Python basics. Day 2: merging dictionaries If you have two dictionaries that need to be merged, this can be done in two simple ways. You can use the merge operator (|) or the operator (**). Below we have two dictionaries: first_dict and second_dict. We will use these two methods to merge the dictionaries. Here's the code: 1️⃣ Using the merge operator (|)

first_dict = {"kelly": 23,
              "Derick": 14, "John": 7}
second_dict = {"Ravi": 45, "Mpho": 67}

combined_dict = first_dict | second_dict
print(combined_dict)

Output:

{'kelly': 23, 'Derick': 14, 'John': 7, 'Ravi': 45, 'Mpho': 67}

2️⃣ Method 2: using the merge operator (**) With this operator, you need to put the dictionaries inside curly braces. In the code below, we "substitute" two dictionaries for merging using two operators *. Both dictionaries are enclosed in curly braces and separated by a comma.

first_dict = {"kelly": 23,
              "Derick": 14, "John": 7}
second_dict = {"Ravi": 45, "Mpho": 67}

combined_dict = {**first_dict, **second_dict}
print(combined_dict)

Output:

{'kelly': 23, 'Derick': 14, 'John': 7, 'Ravi': 45, 'Mpho': 67>

👉 https://t.me/DataScience4

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A channel offering free coupons for Udemy training courses https://t.me/DataScienceC

📱 Cheat Sheet for Beautiful Soup 4 Beautiful Soup — a library for extracting data from HTML and XML files, which is perfect for web scraping. 1. Installation

pip install beautifulsoup4

2. Import

from bs4 import BeautifulSoup
import requests

3. Basic parsing

html_doc = "<html><body><p class='text'>Hello, world!</p></body></html>"
soup = BeautifulSoup(html_doc, 'html.parser')  # or 'lxml', 'html5lib'
print(soup.p.text)  # Hello, world!

4. Finding elements

# First found element
first_p = soup.find('p')

# Search by class or attribute
text_elem = soup.find('p', class_='text')
text_elem = soup.find('p', {'class': 'text'})

# All elements
all_p = soup.find_all('p')
all_text_class = soup.find_all(class_='text')

5. Working with attributes and text

a_tag = soup.find('a')
print(a_tag['href&#39])    # value of the href attribute
print(a_tag.get_text()) # text inside the tag
print(a_tag.text)       # alternative

6. Navigating the tree

# Moving to parent, children, siblings
parent = soup.p.parent
children = soup.ul.children
next_sibling = soup.p.next_sibling

# Finding the previous/next element
prev_elem = soup.find_previous('p')
next_elem = soup.find_next('div')

7. Parsing a real page

response = requests.get('https://example.com')
soup = BeautifulSoup(response.text, 'html. parser')
title = soup.title.text
links = [a['href'] for a in soup.find_all('a', href=True)]

8. CSS selectors

# More powerful and concise search
items = soup.select('div.content > p.text')
first_item = soup.select_one('a.button')

tags: #cheat_sheet #useful ➡ https://t.me/DataScience4

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In Python 3.15, there will be a fully immutable dictionary. A new public immutable type, frozendict, is added to the builtins module. It is expected that frozendict will be "safe by design", because it prevents any unintended changes. This is useful not only for the CPython standard library, but also for third-party maintainers: you can rely on a reliable immutable dictionary type. Why is this needed at all: ▪️Do you want to use a map as a key in another dict or put it in a set? A regular dict is not allowed, but a frozendict is (if the values are also hashable). ▪️ @functools.lru_cache() and arguments-dictionaries: it's difficult with a dict, but normal with a frozendict. ▪️Defaults in function arguments: instead of a "mutable default", you can give frozendict(...) and not get surprises. How it looks in the API: ▪️The constructor "like a dict": frozendict(), frozendict(**kwargs), frozendict(mapping) or iterable pairs, plus you can mix with **kwargs. ▪️The order of insertion is preserved (as in a regular dict). ▪️The hash does not depend on the order of elements (logic via frozenset(items)), and the comparison is also based on the content, not on the order. ▪️There is a union via | and an "update" |= (but |= does not mutate the object, but creates a new one). ▪️.copy() in CPython essentially returns the same object (shallow), and if you need deep copying, then copy.deepcopy(). An important point: frozendict is NOT inherited from dict. This is done on purpose, so that you can't bypass the "immutability" by calling dict.__setitem__ and similar tricks. And a bonus for the stdlib: the authors have marked places where you can replace constant/public maps with frozendict (including where MappingProxyType is now used). 👉 @DataScience4

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✨ third-party libraries | Python Best Practices ✨ 📖 Guidelines and best practices for choosing and using third-party libraries in your Python code. 🏷️ #Python

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