How to sort a list of dictionaries by a specific field?
Answer:
This parameter passes a function that extracts the value of the desired field from each dictionary. The .sort() method modifies the list in place, while sorted() returns a new sorted list.
tags: #interview
Please open Telegram to view this post
VIEW IN TELEGRAM
❤1
Media is too big
VIEW IN TELEGRAM
Ant AI Automated Sales Robot is an intelligent robot focused on automating lead generation and sales conversion. Its core function simulates human conversation, achieving end-to-end business conversion and easily generating revenue without requiring significant time investment.
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 Commission income can be withdrawn to your account at any time, and the settlement process is transparent and open.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.
If you are interested, please join my Telegram group for more information and leave a message: https://news.1rj.ru/str/+lVKtdaI5vcQ1ZDA1
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.
If you are interested, please join my Telegram group for more information and leave a message: https://news.1rj.ru/str/+lVKtdaI5vcQ1ZDA1
❤1
How to organize a message queue via Redis?
Answer:
A more reliable approach is Redis Streams, which support groups of consumers and message processing confirmation, which helps to avoid losses. Pub/Sub is usually not used for queues, as messages are not stored and can be lost.
tags: #interview
Please open Telegram to view this post
VIEW IN TELEGRAM
❤2
This project uses YOLOv8 for object detection, OpenCV for video processing, and custom-defined security zones to detect intrusions in restricted areas. When a person enters a defined zone, the system triggers an alert sound and automatically captures snapshots for evidence.
https://youtu.be/W2T2PgVIV3A?si=6Pf_c0veplMHIvDJ
https://youtu.be/W2T2PgVIV3A?si=6Pf_c0veplMHIvDJ
YouTube
Real-Time Intrusion Detection System Using YOLOv8 & OpenCV | Python Computer Vision
Build a real-time Intrusion Detection System using Python, OpenCV, and YOLOv8.
This project demonstrates AI-powered object detection with custom security zones and alert notifications.
In this video, I show how to create an intrusion detection system using…
This project demonstrates AI-powered object detection with custom security zones and alert notifications.
In this video, I show how to create an intrusion detection system using…
❤3
What are the list methods in Python?
• append() — adds an element to the end of the list
• pop() — removes the last element of the list (or the element at a given index)
• insert() — adds an element at any position in the list by index
• remove() — removes the first found element from the list by value
• map() — applies a function to each element and returns an iterator (can be converted to a list)
• filter() — selects elements that satisfy a condition and returns an iterator
• reduce() (from the functools module) — reduces the list to a single value by processing elements sequentially
@DataScienceQ
• pop() — removes the last element of the list (or the element at a given index)
• insert() — adds an element at any position in the list by index
• remove() — removes the first found element from the list by value
• map() — applies a function to each element and returns an iterator (can be converted to a list)
• filter() — selects elements that satisfy a condition and returns an iterator
• reduce() (from the functools module) — reduces the list to a single value by processing elements sequentially
@DataScienceQ
❤4
❗️LISA HELPS EVERYONE EARN MONEY!$29,000 HE'S GIVING AWAY TODAY!
Everyone can join his channel and make money! He gives away from $200 to $5.000 every day in his channel
https://news.1rj.ru/str/+HDFF3Mo_t68zNWQy
⚡️FREE ONLY FOR THE FIRST 500 SUBSCRIBERS! FURTHER ENTRY IS PAID! 👆👇
https://news.1rj.ru/str/+HDFF3Mo_t68zNWQy
Everyone can join his channel and make money! He gives away from $200 to $5.000 every day in his channel
https://news.1rj.ru/str/+HDFF3Mo_t68zNWQy
⚡️FREE ONLY FOR THE FIRST 500 SUBSCRIBERS! FURTHER ENTRY IS PAID! 👆👇
https://news.1rj.ru/str/+HDFF3Mo_t68zNWQy
When deploying and running Python code on cloud-based clusters using Ray, one specific technical detail to focus on is the use of
When applying the
Source: https://towardsdatascience.com/ray-distributed-computing-for-all-part-2/
ray.remote decorator.When applying the
@ray.remote decorator to your Python functions, ensure that each function takes a single argument (the object being acted upon) and returns a value. This allows Ray to properly serialize and de-serialize data for distributed computing. For example:import ray
@ray.remote
def my_function(x):
# do some computation on x
return result
Source: https://towardsdatascience.com/ray-distributed-computing-for-all-part-2/
Towards Data Science
Ray: Distributed Computing For All, Part 2 | Towards Data Science
Deploying and running Python code on cloud-based clusters
❤5
Why shouldn't you compare two
float values using "=="?Answer:
tags: #interview
Please open Telegram to view this post
VIEW IN TELEGRAM
❤2👍1
Forwarded from Machine Learning with Python
Learn Python with the University of Helsinki
✓ With an official certificate
✓ From zero to advanced level
✓ 14 parts with practical tasks
All content is available → here
https://programming-25.mooc.fi/
👉 @codeprogrammer
✓ With an official certificate
✓ From zero to advanced level
✓ 14 parts with practical tasks
All content is available → here
https://programming-25.mooc.fi/
Please open Telegram to view this post
VIEW IN TELEGRAM
Forwarded from Udemy Coupons
Hands On Python Data Science - Data Science Bootcamp
Master Python for Data Science with Real-World Applications: Dive Deep into Data Analysis, Machine Learning...
🏷 Category: development
🌍 Language: English (US)
👥 Students: 29,499 students
⭐️ Rating: 4.4/5.0 (392 reviews)
🏃♂️ Enrollments Left: 1,000
⏳ Expires In: 3D:23H:15M
💰 Price:$20.63 => FREE
🆔 Coupon: 4439248302A1B82C38D3
⚠️ Please note: A verification layer has been added to prevent bad actors and bots from claiming the courses, so it is important for genuine users to enroll manually to not lose this free opportunity.
💎 By: https://news.1rj.ru/str/DataScienceC
Master Python for Data Science with Real-World Applications: Dive Deep into Data Analysis, Machine Learning...
🏷 Category: development
🌍 Language: English (US)
👥 Students: 29,499 students
⭐️ Rating: 4.4/5.0 (392 reviews)
🏃♂️ Enrollments Left: 1,000
⏳ Expires In: 3D:23H:15M
💰 Price:
🆔 Coupon: 4439248302A1B82C38D3
⚠️ Please note: A verification layer has been added to prevent bad actors and bots from claiming the courses, so it is important for genuine users to enroll manually to not lose this free opportunity.
💎 By: https://news.1rj.ru/str/DataScienceC
❤3
🔬 Optimizing Python Code for Scalability📈
As your data grows, ensuring the performance of your Python code becomes crucial. Automated tests can help you catch degraded performance issues before they impact your application's reliability.
To create optimized code, focus on:
• Efficient data structures (e.g., NumPy arrays)
• Parallel processing using libraries like Pandas and joblib
• Caching mechanisms to reduce redundant computations
Check out the latest updates in pandas 3.0, including new features for data manipulation and analysis. Christopher Trudeau's latest episode is now available!
As your data grows, ensuring the performance of your Python code becomes crucial. Automated tests can help you catch degraded performance issues before they impact your application's reliability.
To create optimized code, focus on:
• Efficient data structures (e.g., NumPy arrays)
• Parallel processing using libraries like Pandas and joblib
• Caching mechanisms to reduce redundant computations
Check out the latest updates in pandas 3.0, including new features for data manipulation and analysis. Christopher Trudeau's latest episode is now available!
📚 How Long Does It Take to Learn Python?
How long does it really take to learn Python?
Most beginners can learn core Python fundamentals in about 2-6 months with consistent practice. However, writing a tiny noscript in days or weeks is just the beginning - real confidence comes from projects and feedback.
Key Takeaways:
• Learn core Python fundamentals in 2-6 months.
• Write a tiny noscript in days or weeks, but build confidence through projects and feedback.
• Becoming job-ready takes 6-12 months, depending on background and target role.
How long does it really take to learn Python?
Most beginners can learn core Python fundamentals in about 2-6 months with consistent practice. However, writing a tiny noscript in days or weeks is just the beginning - real confidence comes from projects and feedback.
Key Takeaways:
• Learn core Python fundamentals in 2-6 months.
• Write a tiny noscript in days or weeks, but build confidence through projects and feedback.
• Becoming job-ready takes 6-12 months, depending on background and target role.
📚 Create Callable Instances With Python's .call()
Do you know how to create custom classes in Python that can be called like functions? 🤔
A callable instance is an object that can be executed using parentheses with optional arguments. Examples include functions, methods, and even custom classes! 🌟 To create a callable instance, you need to add the
By understanding how to create and use callable instances, you'll become a more powerful Python developer. Tutorial
Do you know how to create custom classes in Python that can be called like functions? 🤔
A callable instance is an object that can be executed using parentheses with optional arguments. Examples include functions, methods, and even custom classes! 🌟 To create a callable instance, you need to add the
.__call__() special method to your class. It's like adding a magic button that lets you call your class like a function. By understanding how to create and use callable instances, you'll become a more powerful Python developer. Tutorial
YouTube
Python Classes in 1 Minute!
⭐ Join my Patreon: https://www.patreon.com/b001io
💬 Discord: https://discord.gg/jA8SShU8zJ
🐦 Follow me on Twitter: https://twitter.com/b001io
🔗 More links: https://linktr.ee/b001io
💬 Discord: https://discord.gg/jA8SShU8zJ
🐦 Follow me on Twitter: https://twitter.com/b001io
🔗 More links: https://linktr.ee/b001io
🔍 🖥 The Terminal: First Steps and Useful Commands for Python Developers 📚
--------------------------------------------------------
Learn how to navigate and manage your file system like a pro with the terminal, the command-line interface that's faster and more flexible than graphical interfaces for many development tasks.
•
•
•
--------------------------------------------------------
Learn how to navigate and manage your file system like a pro with the terminal, the command-line interface that's faster and more flexible than graphical interfaces for many development tasks.
•
cd: Change directories, navigate your file system 💻•
ls: List files and directories in your current directory 📁•
mkdir: Create new directories for projects or organize existing ones...🔍 Python News: Tier List and Wiki for Beginners 📚
----------------------------------------------------------
For those new to Python programming, staying up-to-date with the latest news and trends can be overwhelming. Here's a concise summary of recent Python news:
- HighGuard Wiki provides tier lists, wardens, and weapons for beginners.
- Check out Harvard's publicly available ML textbook on their GitHub repository 📊.
- Learn complex regular expressions in readable Python code using Pregex 💻.
- Stay informed with the latest Python updates and trends 👏.
----------------------------------------------------------
For those new to Python programming, staying up-to-date with the latest news and trends can be overwhelming. Here's a concise summary of recent Python news:
- HighGuard Wiki provides tier lists, wardens, and weapons for beginners.
- Check out Harvard's publicly available ML textbook on their GitHub repository 📊.
- Learn complex regular expressions in readable Python code using Pregex 💻.
- Stay informed with the latest Python updates and trends 👏.
🔬 Python State Machine Simulator and Visualizer: A Powerful Tool for Complex Systems 🤖
Learn how to create a state machine simulator in Python that visualizes complex systems, automating testing and analysis.
• Create a custom state machine using Python classes and objects.
• Use visualization libraries like Matplotlib or Seaborn to display the state machine's behavior.
• Test and optimize your state machine with automated code reviews.
Check out this example code: 📝
Save it as
Learn how to create a state machine simulator in Python that visualizes complex systems, automating testing and analysis.
• Create a custom state machine using Python classes and objects.
• Use visualization libraries like Matplotlib or Seaborn to display the state machine's behavior.
• Test and optimize your state machine with automated code reviews.
Check out this example code: 📝
import matplotlib.pyplot as plt
class StateMachine:
def __init__(self):
self.states = {}
def add_state(self, name, function):
self.states[name] = function
def update(self, current_state, input_value):
if current_state in self.states:
output_function = self.states[current_state](input_value)
print(f"{current_state} -> {output_function}")
Save it as
smac.py and run it to see the visualization: 📈❤3
Enjoy our content? Advertise on this channel and reach a highly engaged audience! 👉🏻
It's easy with Telega.io. As the leading platform for native ads and integrations on Telegram, it provides user-friendly and efficient tools for quick and automated ad launches.
⚡️ Place your ad here in three simple steps:
1 Sign up
2 Top up the balance in a convenient way
3 Create your advertising post
If your ad aligns with our content, we’ll gladly publish it.
Start your promotion journey now!
It's easy with Telega.io. As the leading platform for native ads and integrations on Telegram, it provides user-friendly and efficient tools for quick and automated ad launches.
⚡️ Place your ad here in three simple steps:
1 Sign up
2 Top up the balance in a convenient way
3 Create your advertising post
If your ad aligns with our content, we’ll gladly publish it.
Start your promotion journey now!
❤2
Singleton via new: One object rules all👑
When you have five loggers, three configurations, and two connections to the same database in your code - this is not architecture, but a communal apartment. Singleton solves: one object, no copies.
1️⃣ What's the point
Singleton guarantees that the class will have only one instance. All "new" calls simply return the already existing instance.
2️⃣ Practice
3️⃣ Why it's important
4️⃣ Nuances
🧠 Tip: implement Singleton as a metaclass or via a decorator - it'll be prettier and more flexible.
Useful?
❤️ - Yes
👍 - I already use it
👩💻 @DataScienceQ
When you have five loggers, three configurations, and two connections to the same database in your code - this is not architecture, but a communal apartment. Singleton solves: one object, no copies.
Singleton guarantees that the class will have only one instance. All "new" calls simply return the already existing instance.
class Singleton:
_instance = None
def __new__(cls, *args, **kwargs):
if not cls._instance:
print("Creating the first and last instance 🧱")
cls._instance = super().__new__(cls)
return cls._instance
# Check it out
a = Singleton()
b = Singleton()
print(a is b) # True
💠 Common access to resources (DB, logger, config)💠 Control of the system state💠 Minimum overhead
➡️ Thread safety - add locking if there's multithreading➡️ Don't overdo it - too many singletons = hidden dependencies➡️ Sometimes it's better to use DI (dependency injection)
Useful?
Please open Telegram to view this post
VIEW IN TELEGRAM
❤2