✨ local variable | Python Glossary ✨
📖 A variable that you bind inside a function or method body.
🏷️ #Python
📖 A variable that you bind inside a function or method body.
🏷️ #Python
✨ Quiz: How to Integrate ChatGPT's API With Python Projects ✨
📖 Test your knowledge of the ChatGPT API in Python. Practice sending prompts with openai and handling text and code responses in this quick quiz.
🏷️ #intermediate #ai #api
📖 Test your knowledge of the ChatGPT API in Python. Practice sending prompts with openai and handling text and code responses in this quick quiz.
🏷️ #intermediate #ai #api
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How to correctly terminate Python scripts
In production, it's important to clearly signal the result of the program's work. For this,
• 0 — success
• a non-zero value — error
This approach helps CI/CD, Docker or cron to correctly respond to failures. It's mandatory for CLI utilities and automation, so that the execution is predictable
https://t.me/DataScience4
In production, it's important to clearly signal the result of the program's work. For this,
sys.exit(<code>) is used:• 0 — success
• a non-zero value — error
This approach helps CI/CD, Docker or cron to correctly respond to failures. It's mandatory for CLI utilities and automation, so that the execution is predictable
https://t.me/DataScience4
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✨ Anaconda Navigator | Python Tools ✨
📖 A desktop graphical interface included with the Anaconda Distribution.
🏷️ #Python
📖 A desktop graphical interface included with the Anaconda Distribution.
🏷️ #Python
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✨ unpacking | Python Glossary ✨
📖 Passing multiple values at once by expanding an iterable.
🏷️ #Python
📖 Passing multiple values at once by expanding an iterable.
🏷️ #Python
✨ Quiz: How to Integrate Local LLMs With Ollama and Python ✨
📖 Check your understanding of using Ollama with Python to run local LLMs, generate text, chat, and call tools for private, offline apps.
🏷️ #intermediate #ai #tools
📖 Check your understanding of using Ollama with Python to run local LLMs, generate text, chat, and call tools for private, offline apps.
🏷️ #intermediate #ai #tools
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Working with f-strings: more possibilities than it seems!
f-strings often replace
f-strings are convenient for aligning columns without additional tools. This makes the output readable in the CLI and logs:
Debug expressions (Python 3.8+):
Specifiers
Specifiers support width and padding, for example 08d for zeros. This is convenient for reports and IDs:
You can access dictionaries and immediately calculate metrics, for example
🔥 f-strings are a cool tool for formatting, logging, and debugging, if you apply them taking into account the version of Python and the context of the output.
🚪 @DataScience4
f-strings often replace
.format() in everyday code, but their capabilities are not always fully utilized. They support formatting, function calls, working with data structures, and convenient debugging (from 3.8+).f-strings are convenient for aligning columns without additional tools. This makes the output readable in the CLI and logs:
rows = [
("id", "name", "role"),
(1, "Ivan", "admin"),
(2, "Olga", "editor"),
]
for r in rows:
print(f"{r[0]:<5} {r[1]:<10} {r[2]:<10}")
Debug expressions (Python 3.8+):
{x=> displays the name and value of the variable, which speeds up debugging. Supports formatting of calculations:x = 12
y = 7
print(f"{x=} {y=} {x*y=} x/y={x/y:.3f}")
Specifiers
!r, !a: !r - repr(), !a - ascii() for unambiguous logs. Eliminates ambiguities in the output of objects:path = "/var/data/config.yaml"
print(f"{path!r} {path!a}") # repr and ascii()
Specifiers support width and padding, for example 08d for zeros. This is convenient for reports and IDs:
n = 42
print(f"{n:08d}") # → #00000042
You can access dictionaries and immediately calculate metrics, for example
len():data = {"user": "Ivan", "items": [1, 2, 3]}
print(f"{data['user']}=», items={data['items']}")
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Forwarded from Tech Jobs Hub
Python Clean Code: Stop Writing Bad Code — Lessons from Uncle Bob
Are you tired of writing messy and unorganized code that leads to frustration and bugs? You can transform your code from a confusing mess into something crystal clear with a few simple changes. In this article, we'll explore key principles from the book "Clean Code" by Robert C. Martin, also known as Uncle Bob, and apply them to Python. Whether you're a web developer, software engineer, data analyst, or data scientist, these principles will help you write clean, readable, and maintainable Python code.
Read: https://habr.com/en/articles/841820/
https://t.me/CodeProgrammer🧠
Are you tired of writing messy and unorganized code that leads to frustration and bugs? You can transform your code from a confusing mess into something crystal clear with a few simple changes. In this article, we'll explore key principles from the book "Clean Code" by Robert C. Martin, also known as Uncle Bob, and apply them to Python. Whether you're a web developer, software engineer, data analyst, or data scientist, these principles will help you write clean, readable, and maintainable Python code.
Read: https://habr.com/en/articles/841820/
https://t.me/CodeProgrammer
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✨ 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
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3️⃣ Data Visualization
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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.
Low Initial Investment Risk. Bot development and testing incur significant costs. While rental fees are required, in the early stages of the project, the company prioritizes market expansion and brand awareness over short-term profits.
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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
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Programmer
23%
Researcher
33%
Engineer