Learn Python Coding
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Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills. Admin: @HusseinSheikho || @Hussein_Sheikho
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Learn Python Coding (@pythonre) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 900 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 279-o'rinni va Hindiston mintaqasida 9 343-o'rinni egallagan.
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“Learn Python through simple, practical examples and real coding ideas. Clear explanations, useful snippets, and hands-on learning for anyone starting or improving their programming skills.
Admin: @HusseinSheikho || @Hussein_Sheikho”
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Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
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40 900
👩💻 heapq.merge(): Combining sorted data!
If you have multiple sources of data that are already sorted, you don't need to collect them into a single collection and sort them again.
heapq.merge() combines such sources into a single, ordered iterator.
In this guide:
• We will combine multiple sorted sequences;
• We will explore lazy processing of large data sources;
• We will configure comparison using the key argument;
• We will combine data sorted in reverse order.
This is especially useful when working with logs, files, and query results, where each source already provides data in the correct order.
#Python #heapq #DataProcessing #CodingTips #Programming #Algorithms
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Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
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40 900
📌 Marking Deprecated Code in Python: deprecated()
In large projects, old functions are not always immediately removed. They are often left for compatibility, but it's important to warn developers that they should no longer be used.
Previously,
warnings.warn()was often used for this purpose:
import warnings
def old_api():
warnings.warn(
"Use new_api()",
DeprecationWarning
)deprecated()decorator has been introduced:
from warnings import deprecated
@deprecated("Use new_api()")
def old_api():
return "old"@deprecated("Use NewClient")
class OldClient:
pass
40 900
Do not violate the Single Responsibility Principle 🎯
A function should do one thing, and do it well.
This function does too much:
def calculate_final_total(
price: float,
quantity: int,
discount_rate: float,
tax_rate: float
) -> float:
# Calculate the subtotal
subtotal = price * quantity
# Apply the discount
discounted_amount = subtotal * (1 - discount_rate)
# Calculate the tax
final_total = discounted_amount * (1 + tax_rate)
return final_totaldef calculate_subtotal(price: float, quantity: int) -> float:
return price * quantity
def apply_discount(subtotal: float, discount: float) -> float:
return subtotal * (1 - discount)
def calculate_tax(amount: float, tax_rate: float) -> float:
return amount * (1 + tax_rate)40 900
Here's a small fact about Python 🐍
The
:= operator is called the "walrus" because the symbols resemble the eyes and tusks of a walrus 🦭
It was introduced in Python 3.8 and allows you to assign a value to a variable and use it directly within the expression at the same time.
For example:
while (line := input("Say something: ")) != "quit":
print(f"You said: {line}")input(), and then check it.
Have you ever used the := operator in your code?
#Python #Programming #WalrusOperator #Coding #TechFacts #Python3
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Repost from Machine Learning with Python
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🧲 Your agent writes the tool. You keep the terminal closed.
You know the shape of the script before you open the editor. The hour goes to argparse, a retry wrapper, a rate limiter you have written eleven times already.
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40 900
Creating Nested Dictionary Values using `setdefault()` 🔥
When grouping data, it's often necessary to check if a key exists, create a container for it, and then add a value.
For example, distributing users by role. Without special methods, this usually involves a separate key check.
users = [
("admin", "alex"),
("user", "max"),
("admin", "kate"),
]
groups = {}
for role, name in users:
if role not in groups:
groups[role] = []
groups[role].append(name)setdefault() method allows you to perform this operation directly when accessing the dictionary. If the key exists, it returns its current value. If the key is missing, the provided value is written to the dictionary and then returned:
groups = {}
for role, name in users:
groups.setdefault(
role,
[],
).append(name)print(groups)
# {
# 'admin': ['alex', 'kate'],
# 'user': ['max']
# }setdefault() is called, even if the key already exists. Therefore, you should avoid creating expensive objects or performing functions with side effects there:
value = cache.setdefault(
key,
build_value(),
)build_value() will be called before the method itself is executed. If the value creation should only happen when the key is missing, it's better to use an explicit check or a suitable data structure, such as defaultdict.
🔥 setdefault() is well-suited for compactly initializing simple mutable containers when grouping and aggregating data. However, it's important to remember that the provided value is evaluated regardless of whether the key exists.
#Python #Coding #Dicts #Programming #CodeTips #DevLife
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