10 Public APIs you can use for your next project
๐ https://restcountries.com - Country data API
๐ฑ https://trefle.io - Plants data API
๐https://api.nasa.gov - Space-related API
๐ต https://developer.spotify.com - Music data API
๐ฐ https://newsapi.org - Access news articles
๐ https://sunrise-sunset.org/api - Sunrise and sunset times API
๐ฒ https://pokeapi.co - Pokรฉmon data API
๐ฅ https://omdbapi.com - Movie database API
๐ https://catfact.ninja - Cat facts API
๐ถ https://thedogapi.com - Dog picture API
๐ https://restcountries.com - Country data API
๐ฑ https://trefle.io - Plants data API
๐https://api.nasa.gov - Space-related API
๐ต https://developer.spotify.com - Music data API
๐ฐ https://newsapi.org - Access news articles
๐ https://sunrise-sunset.org/api - Sunrise and sunset times API
๐ฒ https://pokeapi.co - Pokรฉmon data API
๐ฅ https://omdbapi.com - Movie database API
๐ https://catfact.ninja - Cat facts API
๐ถ https://thedogapi.com - Dog picture API
๐7
๐ด How to MASTER a programming language using ChatGPT: ๐
1. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
2. What are some commonly asked interview questions about [lang]?
3. What are the advanced topics to learn in [lang]? Explain them to me with code examples.
4. Give me some practice questions along with solutions for [concept] in [lang].
5. What are some common mistakes that people make in [lang]?
6. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
7. How can I optimize the performance of my code in [lang]?
8. What are some coding exercises or mini-projects I can do regularly to reinforce my understanding and application of [lang] concepts?
9. Are there any specific tools or frameworks that are commonly used in [lang]? How can I learn and utilize them effectively?
10. What are the debugging techniques and tools available in [lang] to help troubleshoot and fix code issues?
11. Are there any coding conventions or style guidelines that I should follow when writing code in [lang]?
12. How can I effectively collaborate with other developers in [lang] on a project?
13. What are some common data structures and algorithms that I should be familiar with in [lang]?
How to Create Resume using ChatGPT ๐๐
https://t.iss.one/free4unow_backup/687
Master DSA ๐๐
https://t.iss.one/dsabooks/156
1. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
2. What are some commonly asked interview questions about [lang]?
3. What are the advanced topics to learn in [lang]? Explain them to me with code examples.
4. Give me some practice questions along with solutions for [concept] in [lang].
5. What are some common mistakes that people make in [lang]?
6. Can you provide some tips and best practices for writing clean and efficient code in [lang]?
7. How can I optimize the performance of my code in [lang]?
8. What are some coding exercises or mini-projects I can do regularly to reinforce my understanding and application of [lang] concepts?
9. Are there any specific tools or frameworks that are commonly used in [lang]? How can I learn and utilize them effectively?
10. What are the debugging techniques and tools available in [lang] to help troubleshoot and fix code issues?
11. Are there any coding conventions or style guidelines that I should follow when writing code in [lang]?
12. How can I effectively collaborate with other developers in [lang] on a project?
13. What are some common data structures and algorithms that I should be familiar with in [lang]?
How to Create Resume using ChatGPT ๐๐
https://t.iss.one/free4unow_backup/687
Master DSA ๐๐
https://t.iss.one/dsabooks/156
๐ฅ4๐1
Python Roadmap for 2025: Complete Guide
1. Python Fundamentals
1.1 Variables, constants, and comments.
1.2 Data types: int, float, str, bool, complex.
1.3 Input and output (input(), print(), formatted strings).
1.4 Python syntax: Indentation and code structure.
2. Operators
2.1 Arithmetic: +, -, *, /, %, //, **.
2.2 Comparison: ==, !=, <, >, <=, >=.
2.3 Logical: and, or, not.
2.4 Bitwise: &, |, ^, ~, <<, >>.
2.5 Identity: is, is not.
2.6 Membership: in, not in.
3. Control Flow
3.1 Conditional statements: if, elif, else.
3.2 Loops: for, while.
3.3 Loop control: break, continue, pass.
4. Data Structures
4.1 Lists: Indexing, slicing, methods (append(), pop(), sort(), etc.).
4.2 Tuples: Immutability, packing/unpacking.
4.3 Dictionaries: Key-value pairs, methods (get(), items(), etc.).
4.4 Sets: Unique elements, set operations (union, intersection).
4.5 Strings: Immutability, methods (split(), strip(), replace()).
5. Functions
5.1 Defining functions with def.
5.2 Arguments: Positional, keyword, default, *args, **kwargs.
5.3 Anonymous functions (lambda).
5.4 Recursion.
6. Modules and Packages
6.1 Importing: import, from ... import.
6.2 Standard libraries: math, os, sys, random, datetime, time.
6.3 Installing external libraries with pip.
7. File Handling
7.1 Open and close files (open(), close()).
7.2 Read and write (read(), write(), readlines()).
7.3 Using context managers (with open(...)).
8. Object-Oriented Programming (OOP)
8.1 Classes and objects.
8.2 Methods and attributes.
8.3 Constructor (init).
8.4 Inheritance, polymorphism, encapsulation.
8.5 Special methods (str, repr, etc.).
9. Error and Exception Handling
9.1 try, except, else, finally.
9.2 Raising exceptions (raise).
9.3 Custom exceptions.
10. Comprehensions
10.1 List comprehensions.
10.2 Dictionary comprehensions.
10.3 Set comprehensions.
11. Iterators and Generators
11.1 Creating iterators using iter() and next().
11.2 Generators with yield.
11.3 Generator expressions.
12. Decorators and Closures
12.1 Functions as first-class citizens.
12.2 Nested functions.
12.3 Closures.
12.4 Creating and applying decorators.
13. Advanced Topics
13.1 Context managers (with statement).
13.2 Multithreading and multiprocessing.
13.3 Asynchronous programming with async and await.
13.4 Python's Global Interpreter Lock (GIL).
14. Python Internals
14.1 Mutable vs immutable objects.
14.2 Memory management and garbage collection.
14.3 Python's name == "main" mechanism.
15. Libraries and Frameworks
15.1 Data Science: NumPy, Pandas, Matplotlib, Seaborn.
15.2 Web Development: Flask, Django, FastAPI.
15.3 Testing: unittest, pytest.
15.4 APIs: requests, http.client.
15.5 Automation: selenium, os.
15.6 Machine Learning: scikit-learn, TensorFlow, PyTorch.
16. Tools and Best Practices
16.1 Debugging: pdb, breakpoints.
16.2 Code style: PEP 8 guidelines.
16.3 Virtual environments: venv.
16.4 Version control: Git + GitHub.
๐ Python Interview ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐
https://t.iss.one/dsabooks
๐ ๐ฃ๐ฟ๐ฒ๐บ๐ถ๐๐บ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ : https://topmate.io/coding/914624
๐ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z
Join What's app channel for jobs updates: t.iss.one/getjobss
1. Python Fundamentals
1.1 Variables, constants, and comments.
1.2 Data types: int, float, str, bool, complex.
1.3 Input and output (input(), print(), formatted strings).
1.4 Python syntax: Indentation and code structure.
2. Operators
2.1 Arithmetic: +, -, *, /, %, //, **.
2.2 Comparison: ==, !=, <, >, <=, >=.
2.3 Logical: and, or, not.
2.4 Bitwise: &, |, ^, ~, <<, >>.
2.5 Identity: is, is not.
2.6 Membership: in, not in.
3. Control Flow
3.1 Conditional statements: if, elif, else.
3.2 Loops: for, while.
3.3 Loop control: break, continue, pass.
4. Data Structures
4.1 Lists: Indexing, slicing, methods (append(), pop(), sort(), etc.).
4.2 Tuples: Immutability, packing/unpacking.
4.3 Dictionaries: Key-value pairs, methods (get(), items(), etc.).
4.4 Sets: Unique elements, set operations (union, intersection).
4.5 Strings: Immutability, methods (split(), strip(), replace()).
5. Functions
5.1 Defining functions with def.
5.2 Arguments: Positional, keyword, default, *args, **kwargs.
5.3 Anonymous functions (lambda).
5.4 Recursion.
6. Modules and Packages
6.1 Importing: import, from ... import.
6.2 Standard libraries: math, os, sys, random, datetime, time.
6.3 Installing external libraries with pip.
7. File Handling
7.1 Open and close files (open(), close()).
7.2 Read and write (read(), write(), readlines()).
7.3 Using context managers (with open(...)).
8. Object-Oriented Programming (OOP)
8.1 Classes and objects.
8.2 Methods and attributes.
8.3 Constructor (init).
8.4 Inheritance, polymorphism, encapsulation.
8.5 Special methods (str, repr, etc.).
9. Error and Exception Handling
9.1 try, except, else, finally.
9.2 Raising exceptions (raise).
9.3 Custom exceptions.
10. Comprehensions
10.1 List comprehensions.
10.2 Dictionary comprehensions.
10.3 Set comprehensions.
11. Iterators and Generators
11.1 Creating iterators using iter() and next().
11.2 Generators with yield.
11.3 Generator expressions.
12. Decorators and Closures
12.1 Functions as first-class citizens.
12.2 Nested functions.
12.3 Closures.
12.4 Creating and applying decorators.
13. Advanced Topics
13.1 Context managers (with statement).
13.2 Multithreading and multiprocessing.
13.3 Asynchronous programming with async and await.
13.4 Python's Global Interpreter Lock (GIL).
14. Python Internals
14.1 Mutable vs immutable objects.
14.2 Memory management and garbage collection.
14.3 Python's name == "main" mechanism.
15. Libraries and Frameworks
15.1 Data Science: NumPy, Pandas, Matplotlib, Seaborn.
15.2 Web Development: Flask, Django, FastAPI.
15.3 Testing: unittest, pytest.
15.4 APIs: requests, http.client.
15.5 Automation: selenium, os.
15.6 Machine Learning: scikit-learn, TensorFlow, PyTorch.
16. Tools and Best Practices
16.1 Debugging: pdb, breakpoints.
16.2 Code style: PEP 8 guidelines.
16.3 Virtual environments: venv.
16.4 Version control: Git + GitHub.
๐ Python Interview ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐
https://t.iss.one/dsabooks
๐ ๐ฃ๐ฟ๐ฒ๐บ๐ถ๐๐บ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ ๐๐ป๐๐ฒ๐ฟ๐๐ถ๐ฒ๐ ๐ฅ๐ฒ๐๐ผ๐๐ฟ๐ฐ๐ฒ๐ : https://topmate.io/coding/914624
๐ ๐๐ฎ๐๐ฎ ๐ฆ๐ฐ๐ถ๐ฒ๐ป๐ฐ๐ฒ: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z
Join What's app channel for jobs updates: t.iss.one/getjobss
๐4โค3
Here are some of the most popular python project ideas: ๐ก
Simple Calculator
Text-Based Adventure Game
Number Guessing Game
Password Generator
Dice Rolling Simulator
Mad Libs Generator
Currency Converter
Leap Year Checker
Word Counter
Quiz Program
Email Slicer
Rock-Paper-Scissors Game
Web Scraper (Simple)
Text Analyzer
Interest Calculator
Unit Converter
Simple Drawing Program
File Organizer
BMI Calculator
Tic-Tac-Toe Game
To-Do List Application
Inspirational Quote Generator
Task Automation Script
Simple Weather App
Automate data cleaning and analysis (EDA)
Sales analysis
Sentiment analysis
Price prediction
Customer Segmentation
Time series forecasting
Image classification
Spam email detection
Credit card fraud detection
Market basket analysis
NLP, etc
These are just starting points. Feel free to explore, combine ideas, and personalize your projects based on your interest and skills. ๐ฏ
Simple Calculator
Text-Based Adventure Game
Number Guessing Game
Password Generator
Dice Rolling Simulator
Mad Libs Generator
Currency Converter
Leap Year Checker
Word Counter
Quiz Program
Email Slicer
Rock-Paper-Scissors Game
Web Scraper (Simple)
Text Analyzer
Interest Calculator
Unit Converter
Simple Drawing Program
File Organizer
BMI Calculator
Tic-Tac-Toe Game
To-Do List Application
Inspirational Quote Generator
Task Automation Script
Simple Weather App
Automate data cleaning and analysis (EDA)
Sales analysis
Sentiment analysis
Price prediction
Customer Segmentation
Time series forecasting
Image classification
Spam email detection
Credit card fraud detection
Market basket analysis
NLP, etc
These are just starting points. Feel free to explore, combine ideas, and personalize your projects based on your interest and skills. ๐ฏ
๐5
Want to get started with System design interview preparation, start with these ๐
1. Learn to understand requirements
2. Learn the difference between horizontal and vertical scaling.
3. Study latency and throughput trade-offs and optimization techniques.
4. Understand the CAP Theorem (Consistency, Availability, Partition Tolerance).
5. Learn HTTP/HTTPS protocols, request-response lifecycle, and headers.
6. Understand DNS and how domain resolution works.
7. Study load balancers, their types (Layer 4 and Layer 7), and algorithms.
8. Learn about CDNs, their use cases, and caching strategies.
9. Understand SQL databases (ACID properties, normalization) and NoSQL types (keyโvalue, document, graph).
10. Study caching tools (Redis, Memcached) and strategies (write-through, write-back, eviction policies).
11. Learn about blob storage systems like S3 or Google Cloud Storage.
12. Study sharding and horizontal partitioning of databases.
13. Understand replication (leaderโfollower, multi-leader) and consistency models.
14. Learn failover mechanisms like active-passive and active-active setups.
15. Study message queues like RabbitMQ, Kafka, and SQS.
16. Understand consensus algorithms such as Paxos and Raft.
17. Learn event-driven architectures, Pub/Sub models, and event sourcing.
18. Study distributed transactions (two-phase commit, sagas).
19. Learn rate-limiting techniques (token bucket, leaky bucket algorithms).
20. Study API design principles for REST, GraphQL, and gRPC.
21. Understand microservices architecture, communication, and trade-offs with monoliths.
22. Learn authentication and authorization methods (OAuth, JWT, SSO).
23. Study metrics collection tools like Prometheus or Datadog.
24. Understand logging systems (e.g., ELK stack) and tracing tools (OpenTelemetry, Jaeger).
25.Learn about encryption (data at rest and in transit) and rate-limiting for security.
26. And then practise the most commonly asked questions like URL shorteners, chat systems, ride-sharing apps, search engines, video streaming, and e-commerce websites
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
1. Learn to understand requirements
2. Learn the difference between horizontal and vertical scaling.
3. Study latency and throughput trade-offs and optimization techniques.
4. Understand the CAP Theorem (Consistency, Availability, Partition Tolerance).
5. Learn HTTP/HTTPS protocols, request-response lifecycle, and headers.
6. Understand DNS and how domain resolution works.
7. Study load balancers, their types (Layer 4 and Layer 7), and algorithms.
8. Learn about CDNs, their use cases, and caching strategies.
9. Understand SQL databases (ACID properties, normalization) and NoSQL types (keyโvalue, document, graph).
10. Study caching tools (Redis, Memcached) and strategies (write-through, write-back, eviction policies).
11. Learn about blob storage systems like S3 or Google Cloud Storage.
12. Study sharding and horizontal partitioning of databases.
13. Understand replication (leaderโfollower, multi-leader) and consistency models.
14. Learn failover mechanisms like active-passive and active-active setups.
15. Study message queues like RabbitMQ, Kafka, and SQS.
16. Understand consensus algorithms such as Paxos and Raft.
17. Learn event-driven architectures, Pub/Sub models, and event sourcing.
18. Study distributed transactions (two-phase commit, sagas).
19. Learn rate-limiting techniques (token bucket, leaky bucket algorithms).
20. Study API design principles for REST, GraphQL, and gRPC.
21. Understand microservices architecture, communication, and trade-offs with monoliths.
22. Learn authentication and authorization methods (OAuth, JWT, SSO).
23. Study metrics collection tools like Prometheus or Datadog.
24. Understand logging systems (e.g., ELK stack) and tracing tools (OpenTelemetry, Jaeger).
25.Learn about encryption (data at rest and in transit) and rate-limiting for security.
26. And then practise the most commonly asked questions like URL shorteners, chat systems, ride-sharing apps, search engines, video streaming, and e-commerce websites
Coding Interview Resources: https://whatsapp.com/channel/0029VammZijATRSlLxywEC3X
๐5โค2
International studentsโ๏ธ are having a tough time securing a full time job in Tech. ๐ค
Reasons
1. Market has limited opportunities for entry level junior data/software engineers.
2. People having 0-3 years of workex are competing against job seekers having 8+ years of seasoned experience.
3. Lot of companies have their operations in off-shore, as companies grow the headcount of offshore>>onshore.
Solution :
Build up relevant skillsets, latch on to the newer technologies that will bring you at par with experienced candidates.
Build apps/ai models/data pipelines/dashboards that tracks live data.
People who have secured job has everything to lose and their routine is restricted and have limitied time to be dedicated to learning. You on the other hand have nothing to lose and everything to gain.
Request for that coffee chat.
Take that certification exam.
Attend that quarterly event.
Success is sweeter when its delayed.
Reasons
1. Market has limited opportunities for entry level junior data/software engineers.
2. People having 0-3 years of workex are competing against job seekers having 8+ years of seasoned experience.
3. Lot of companies have their operations in off-shore, as companies grow the headcount of offshore>>onshore.
Solution :
Build up relevant skillsets, latch on to the newer technologies that will bring you at par with experienced candidates.
Build apps/ai models/data pipelines/dashboards that tracks live data.
People who have secured job has everything to lose and their routine is restricted and have limitied time to be dedicated to learning. You on the other hand have nothing to lose and everything to gain.
Request for that coffee chat.
Take that certification exam.
Attend that quarterly event.
Success is sweeter when its delayed.
๐ฅ4