✨ relative import | Python Glossary ✨
📖 Import modules from the same package or parent packages using leading dots.
🏷️ #Python
📖 Import modules from the same package or parent packages using leading dots.
🏷️ #Python
✨ GeoPandas Basics: Maps, Projections, and Spatial Joins ✨
📖 Dive into GeoPandas with this tutorial covering data loading, mapping, CRS concepts, projections, and spatial joins for intuitive analysis.
🏷️ #intermediate #data-science
📖 Dive into GeoPandas with this tutorial covering data loading, mapping, CRS concepts, projections, and spatial joins for intuitive analysis.
🏷️ #intermediate #data-science
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
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✨ wildcard import | Python Glossary ✨
📖 An import uses the star syntax to pull many names into your current namespace at once.
🏷️ #Python
📖 An import uses the star syntax to pull many names into your current namespace at once.
🏷️ #Python
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I. Core Functions: Fully Automated "Lead Generation - Interaction - Conversion"
Precise Lead Generation and Human-like Communication: Ant AI is trained on over 20 million real social chat records, enabling it to autonomously identify target customers and build trust through natural conversation, requiring no human intervention.
High Conversion Rate Across Multiple Scenarios: Ant AI intelligently recommends high-conversion-rate products based on chat content, guiding customers to complete purchases through platforms such as iFood, Shopee, and Amazon. It also supports other transaction scenarios such as movie ticket purchases and utility bill payments.
24/7 Operation: Ant AI continuously searches for customers and recommends products. You only need to monitor progress via your mobile phone, requiring no additional management time.
II. Your Profit Guarantee: Low Risk, High Transparency, Zero Inventory Pressure, Stable Commission Sharing
We have established partnerships with platforms such as Shopee and Amazon, which directly provide abundant product sourcing. You don't need to worry about inventory or logistics. After each successful order, the company will charge the merchant a commission and share all profits with you. Earnings are predictable and withdrawals are convenient. Member data shows that each bot can generate $30 to $100 in profit per day. Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open.
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✨ cProfile | Python Standard Library ✨
📖 Provides a way to measure where time is being spent in your application.
🏷️ #Python
📖 Provides a way to measure where time is being spent in your application.
🏷️ #Python
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✨ Quiz: GeoPandas Basics: Maps, Projections, and Spatial Joins ✨
📖 Test GeoPandas basics for reading, mapping, projecting, and spatial joins to handle geospatial data confidently.
🏷️ #intermediate #data-science
📖 Test GeoPandas basics for reading, mapping, projecting, and spatial joins to handle geospatial data confidently.
🏷️ #intermediate #data-science
Forwarded from Machine Learning with Python
Do you see yourself as a programmer, researcher, or engineer?
Anonymous Poll
45%
Programmer
22%
Researcher
33%
Engineer
Do you hate writing monotonous
__init__, __repr__ and __eq__ for each class? Dataclasses do it for you.class Point:
def __init__(self, x, y):
self.x = x
self.y = y
def __repr__(self):
return f"Point(x={self.x}, y={self.y})"
def __eq__(self, other):
return self.x == other.x and self.y == other.y
class User:
def __init__(self, name, age):
self.name = name
self.age = age
def __repr__(self):
return f"User(name={self.name}, age={self.age})"
def __eq__(self, other):
return self.name == other.name and self.age == other.age
Problem:
This is crap. Tons of boilerplate code that's easy to break or forget to update.
from dataclasses import dataclass
@dataclass
class Point:
x: int
y: int
@dataclass
class User:
name: str
age: int
p1 = Point(10, 20)
p2 = Point(10, 20)
u = User("Ivan", 30)
print(p1) # Point(x=10, y=20)
print(p1 == p2) # True
print(u) # User(name='Ivan', age=30)
How it works:
The decorator @dataclass automatically generates methods based on type annotations.
Customizing a dataclass:
from dataclasses import dataclass, fieldinits generated by default?:
@dataclass(order=True, frozen=True)
class Product:
name: str
price: float = 0.0
tags: list[str] = field(default_factory=list, compare=False)
def expensive(self):
return self.price > 1000
p1 = Product("Laptop", 1500.0)
p2 = Product("Mouse", 50.0)
print(p1 > p2) # True (price comparison due to order=True)
p1.tags.append("tech")
# p1.name = "PC" # Error! frozen=True makes the object immutable
are not a replacement for regular classes. Use them for data structures where standard methods are needed.🔵 __initreprtializer with parameters🔵 __repr_eqetty string representation🔵 __eq__ - comparison acltllles
gth geTrue: __lt__, __le__, __gt__, __ge__
Important:
Dataclasses
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Creating Barcodes in Python!
Barcode generation can be easily automated using the
First, install the library itself and the dependency for image generation:
The
Import the main module and
Let's create an
Save it to disk:
As a result, the
Generating several barcodes: a common scenario is generating a series of barcodes, for example for a list of products or database records:
Here, it's also important to comply with the format requirement: 12 digits for
If you need to encode arbitrary strings (order numbers, documents), it's more convenient to use
This format is not limited to numbers and is widely used in logistics and document management.
In practice, generation is often outsourced to a function - for reuse in services or
🔥 This approach is convenient to scale and supplement with logic (validation, writer settings, saving paths in the database, etc.).
👉 @DataScience4
Barcode generation can be easily automated using the
python-barcode library.First, install the library itself and the dependency for image generation:
pip install python-barcode pillow
The
Pillow library is used to save in PNG format via ImageWriter.Import the main module and
writer for working with images:import barcode
from barcode.writer import ImageWriter
Let's create an
EAN-13 barcode. Important: exactly 12 digits are passed, and the check digit is automatically calculated and added.ean = barcode.get(
"ean13",
"590123412345",
writer=ImageWriter()
)
Save it to disk:
filename = ean.save("product_barcode")
print(filename)As a result, the
product_barcode.png file will be created in the current directory.Generating several barcodes: a common scenario is generating a series of barcodes, for example for a list of products or database records:
codes = [
"123456789012",
"987654321098",
"111222333444"
]
for value in codes:
code_obj = barcode.get(
"ean13",
value,
writer=ImageWriter()
)
code_obj.save(f"barcode_{value}")
Here, it's also important to comply with the format requirement: 12 digits for
EAN-13, otherwise the library will throw an exception.If you need to encode arbitrary strings (order numbers, documents), it's more convenient to use
Code128:code128 = barcode.get(
"code128",
"ORDER-2025-001",
writer=ImageWriter()
)
code128.save("order_barcode")
This format is not limited to numbers and is widely used in logistics and document management.
In practice, generation is often outsourced to a function - for reuse in services or
APIs:def generate_barcode(value, filename):
code = barcode.get(
"code128",
value,
writer=ImageWriter()
)
return code.save(filename)
generate_barcode("INVOICE-4587", "invoice_4587")
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