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If you build, design, write, or sell anything with AI, this is your moment.
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• Stripe verification, 5 minutes, instant approval
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• Add monthly subscriptions on top if you want
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We pay all marketing.
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The first 100 Brainlancers are onboarding right now.
In 6 months others will have founding status, recurring income, featured services on the homepage.
You'll scroll past and remember this post.
Don't.
→ brainlancer.com
Brainlancer just launched today.
Investor-backed marketplace for ALL AI freelancers. Designers, builders, copywriters, marketers, video creators, automation experts, consultants.
If you build, design, write, or sell anything with AI, this is your moment.
How it works:
• Register free at brainlancer.com
• Stripe verification, 5 minutes, instant approval
• List up to 5 services from $49 to $4,999
• Add monthly subscriptions on top if you want
• We bring the clients. You keep 80%.
The deal:
No subscription.
No bidding.
No chasing.
We pay all marketing.
Real talk: no services live yet. We just launched. Whoever joins first gets seen first.
The first 100 Brainlancers are onboarding right now.
In 6 months others will have founding status, recurring income, featured services on the homepage.
You'll scroll past and remember this post.
Don't.
→ brainlancer.com
❤2
Learn Python Coding pinned «Read this once. There won't be a second message. Brainlancer just launched today. Investor-backed marketplace for ALL AI freelancers. Designers, builders, copywriters, marketers, video creators, automation experts, consultants. If you build, design, write…»
✨ fnmatch | Python Standard Library ✨
📖 Provides tools for Unix shell-style wildcard pattern matching against filename strings.
🏷️ #Python
📖 Provides tools for Unix shell-style wildcard pattern matching against filename strings.
🏷️ #Python
✨ Quiz: Python's __all__: Packages, Modules, and Wildcard Imports ✨
📖 Test your understanding of wildcard imports, the dunder all variable, and how to control your module and package public APIs in Python.
🏷️ #intermediate #python
📖 Test your understanding of wildcard imports, the dunder all variable, and how to control your module and package public APIs in Python.
🏷️ #intermediate #python
If you need more than 3 nested loops — stop and refactor.
It's better to avoid deep nesting: such code is harder to read and maintain.
The goal is always the same — readability and maintainability.
If you catch yourself in deep nesting, stop and think about whether it can be made more understandable. Using a library will often be a better alternative.
👉 https://t.me/DataScience4
It's better to avoid deep nesting: such code is harder to read and maintain.
The goal is always the same — readability and maintainability.
If you catch yourself in deep nesting, stop and think about whether it can be made more understandable. Using a library will often be a better alternative.
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✨ ftplib | Python Standard Library ✨
📖 Provides tools for connecting to FTP servers and transferring files using the File Transfer Protocol (FTP).
🏷️ #Python
📖 Provides tools for connecting to FTP servers and transferring files using the File Transfer Protocol (FTP).
🏷️ #Python
✨ Quiz: Testing Your Code With Python's unittest ✨
📖 Test your understanding of Python unittest basics, including TestCase, assertions, fixtures, subtests, and test discovery.
🏷️ #intermediate #stdlib #testing
📖 Test your understanding of Python unittest basics, including TestCase, assertions, fixtures, subtests, and test discovery.
🏷️ #intermediate #stdlib #testing
✨ Quiz: Use Codex CLI to Enhance Your Python Projects ✨
📖 Test your understanding of how to install Codex CLI, use Plan mode, and refine features with natural language in your terminal.
🏷️ #intermediate #ai #tools
📖 Test your understanding of how to install Codex CLI, use Plan mode, and refine features with natural language in your terminal.
🏷️ #intermediate #ai #tools
✨ Quiz: ChatterBot: Build a Chatbot With Python ✨
📖 Test your understanding of the ChatterBot Python library, from training a basic bot with ListTrainer to wiring in a local LLM through Ollama.
🏷️ #intermediate #data-science #projects
📖 Test your understanding of the ChatterBot Python library, from training a basic bot with ListTrainer to wiring in a local LLM through Ollama.
🏷️ #intermediate #data-science #projects
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✨ A New Python Packaging Council and Other News for May 2026 ✨
📖 A new Python Packaging Council, PEP 803 stabilizes the free-threaded ABI, the incremental GC gets reverted, and Astral changes hands.
🏷️ #community #news
📖 A new Python Packaging Council, PEP 803 stabilizes the free-threaded ABI, the incremental GC gets reverted, and Astral changes hands.
🏷️ #community #news
Rounding dates/times in Pandas:
*
*
*
Example:
https://t.me/DataScience4
*
dt.floor — down (to the previous interval)*
dt.ceil — up (to the next interval)*
dt.round — to the nearest intervalExample:
s.dt.floor('3h') # previous 3-hour slot
s.dt.ceil('15m') # next 15-minute slot
s.dt.round('1D') # nearest dayhttps://t.me/DataScience4
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✨ getopt | Python Standard Library ✨
📖 Provides tools for parsing command line options from sys.argv following Unix getopt() conventions, with support for both short and long option styles.
🏷️ #Python
📖 Provides tools for parsing command line options from sys.argv following Unix getopt() conventions, with support for both short and long option styles.
🏷️ #Python
✨ Quiz: Using Python for Data Analysis ✨
📖 Test your understanding of a data analysis workflow in Python, from cleansing raw data with pandas to spotting insights with regression.
🏷️ #intermediate #best-practices #data-science #python
📖 Test your understanding of a data analysis workflow in Python, from cleansing raw data with pandas to spotting insights with regression.
🏷️ #intermediate #best-practices #data-science #python
✨ How to Use OpenCode for AI-Assisted Python Coding ✨
📖 Learn how to use OpenCode, an open-source AI coding assistant, with a free Gemini API key to analyze and refactor Python code in your terminal.
🏷️ #intermediate #ai #python #tools
📖 Learn how to use OpenCode, an open-source AI coding assistant, with a free Gemini API key to analyze and refactor Python code in your terminal.
🏷️ #intermediate #ai #python #tools
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Forwarded from Machine Learning with Python
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Areas covered: #Python #AI #Cisco #PMP #Fortinet #AWS #Azure #Excel #CompTIA #ITIL #Cloud + more
🔗 Download each free resource here:
• Free Courses (Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS)
👉https://bit.ly/4ejSFbz
• IT Certs E-book
👉 https://bit.ly/42y8owh
• IT Exams Skill Test
👉 https://bit.ly/42kp7Dv
• Free AI Materials & Support Tools
👉 https://bit.ly/3QEfWek
• Free Cloud Study Guide
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📲 Need exam help? Contact admin: wa.link/40f942
💬 Join our study group (free tips & support): https://chat.whatsapp.com/K3n7OYEXgT1CHGylN6fM5a
❤1
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
✅ https://t.me/Codeprogrammer
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✨ netrc | Python Standard Library ✨
📖 Provides tools for parsing .netrc credentials files and looking up logins, accounts, and passwords by host.
🏷️ #Python
📖 Provides tools for parsing .netrc credentials files and looking up logins, accounts, and passwords by host.
🏷️ #Python
✨ Quiz: The Factory Method Pattern and Its Implementation in Python ✨
📖 Check your grasp of the Factory Method pattern in Python: when to use it, the roles involved, and how to implement a flexible object factory.
🏷️ #intermediate #best-practices
📖 Check your grasp of the Factory Method pattern in Python: when to use it, the roles involved, and how to implement a flexible object factory.
🏷️ #intermediate #best-practices
What is a Lambda Function?
A lambda function is a small anonymous function defined using the lambda keyword. It's often used for short, throwaway functions that are only needed temporarily.
Basic Syntax- The syntax of a lambda function is:
"lambda arguments: expression"
-arguments: A comma-separated list of parameters.
-expression: An expression that is evaluated and returned.
Examples
1️⃣ Basic Lambda Function:
Here, lambda x, y: x + y is a lambda function that adds two numbers.
2️⃣ Lambda with map():
map() applies the lambda function to each item in the numbers list.
3️⃣ Lambda with filter():
filter() uses the lambda function to filter out only the even numbers.
4️⃣ Lambda with reduce():
reduce() applies the lambda function cumulatively to the items in the list.
Pros and Cons-
Pros:
-> Concise and readable.
-> Useful for small, simple functions.
-> Handy for functional programming (e.g., map, filter, reduce).
Cons:
-> Limited to single expressions.
-> Can be less readable if overused.
-> Lack of function name can make debugging harder.
Lambda functions are an excellent tool for any Python developer to have in their toolkit. They can help streamline your code and make your functions more elegant and efficient.
A lambda function is a small anonymous function defined using the lambda keyword. It's often used for short, throwaway functions that are only needed temporarily.
Basic Syntax- The syntax of a lambda function is:
"lambda arguments: expression"
-arguments: A comma-separated list of parameters.
-expression: An expression that is evaluated and returned.
Examples
1️⃣ Basic Lambda Function:
add = lambda x, y: x + y
print(add(2, 3)) # Output: 5
Here, lambda x, y: x + y is a lambda function that adds two numbers.
2️⃣ Lambda with map():
numbers = [1, 2, 3, 4, 5]
squared = list(map(lambda x: x ** 2, numbers))
print(squared) # Output: [1, 4, 9, 16, 25]
map() applies the lambda function to each item in the numbers list.
3️⃣ Lambda with filter():
numbers = [1, 2, 3, 4, 5]
even = list(filter(lambda x: x % 2 == 0, numbers))
print(even) # Output: [2, 4]
filter() uses the lambda function to filter out only the even numbers.
4️⃣ Lambda with reduce():
from functools import reduce
numbers = [1, 2, 3, 4, 5]
product = reduce(lambda x, y: x * y, numbers)
print(product) # Output: 120
reduce() applies the lambda function cumulatively to the items in the list.
Pros and Cons-
Pros:
-> Concise and readable.
-> Useful for small, simple functions.
-> Handy for functional programming (e.g., map, filter, reduce).
Cons:
-> Limited to single expressions.
-> Can be less readable if overused.
-> Lack of function name can make debugging harder.
Lambda functions are an excellent tool for any Python developer to have in their toolkit. They can help streamline your code and make your functions more elegant and efficient.
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