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Mapping Excel shortcuts to SQL queries and Pandas syntax is standard data engineering training. 🧠
But what happens under the CPython hood when you scale these operations from a 10MB test script to a 50GB production pipeline?
Juniors blindly chain pd.merge() or df.groupby() memory automatically. In reality, Pandas creates massive underlying object overhead and explosive cache fragmentation compared to lazy, vectorized Polars execution. 💀
At scale, your syntax maps don't save you—hardware-aware architecture does. 👇
But what happens under the CPython hood when you scale these operations from a 10MB test script to a 50GB production pipeline?
Juniors blindly chain pd.merge() or df.groupby() memory automatically. In reality, Pandas creates massive underlying object overhead and explosive cache fragmentation compared to lazy, vectorized Polars execution. 💀
At scale, your syntax maps don't save you—hardware-aware architecture does. 👇
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Tracing conditional routing behavior across nested blocks is the ultimate logic checkpoint for any developer.
Take a look at this code maze and see if you can isolate the true execution path to grab the network password in under 10 seconds:
x.com/PythonDvz/stat…
Take a look at this code maze and see if you can isolate the true execution path to grab the network password in under 10 seconds:
x.com/PythonDvz/stat…
The ultimate test for your Python indentation and nested logic skills. If you think you're a true software engineer, you should be able to solve this in under 10 seconds without a compiler.
Take a close look at the values of a, b, and c, trace the conditional execution path, and ks are strictly defined by their indentation levels in Python. One wrong turn and you're locked out of the network.
What is the exact Wi-Fi password written on this board?
Drop your answer and trace logic below. Let's see who gets it right first!
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A clever nested logic test for Python beginners. Don't let the indentation levels trick your execution trace.
Can you crack the exact Wi-Fi password written on this board in under 10 seconds without a compiler? Drop your solution:
x.com/PythonDvz/stat…
Can you crack the exact Wi-Fi password written on this board in under 10 seconds without a compiler? Drop your solution:
x.com/PythonDvz/stat…
The ultimate test for your Python indentation and nested logic skills. If you think you're a true software engineer, you should be able to solve this in under 10 seconds without a compiler.
Take a close look at the values of a, b, and c, trace the conditional execution path, and ks are strictly defined by their indentation levels in Python. One wrong turn and you're locked out of the network.
What is the exact Wi-Fi password written on this board?
Drop your answer and trace logic below. Let's see who gets it right first!
0
0
1
427
Indentation isn't just for readability in Python—it strictly dictates scope constraints and logic execution blocks.
Test your mental compilation skills on this nested conditional sign board and drop your trace below:
x.com/PythonDvz/stat…
Test your mental compilation skills on this nested conditional sign board and drop your trace below:
x.com/PythonDvz/stat…
The ultimate test for your Python indentation and nested logic skills. If you think you're a true software engineer, you should be able to solve this in under 10 seconds without a compiler.
Take a close look at the values of a, b, and c, trace the conditional execution path, and ks are strictly defined by their indentation levels in Python. One wrong turn and you're locked out of the network.
What is the exact Wi-Fi password written on this board?
Drop your answer and trace logic below. Let's see who gets it right first!
0
0
2
531
The ultimate test for your Python indentation and nested logic skills. If you think you're a true software engineer, you should be able to solve this in under 10 seconds without a compiler.
Take a close look at the values of a, b, and c, trace the conditional execution path, and ks are strictly defined by their indentation levels in Python. One wrong turn and you're locked out of the network.
What is the exact Wi-Fi password written on this board?
Drop your answer and trace logic below. Let's see who gets it right first!
Take a close look at the values of a, b, and c, trace the conditional execution path, and ks are strictly defined by their indentation levels in Python. One wrong turn and you're locked out of the network.
What is the exact Wi-Fi password written on this board?
Drop your answer and trace logic below. Let's see who gets it right first!
0
0
2
772
The tech industry is treating LeetCode like a lazy HR filter, forcing developers to blindly memorize algorithms instead of learning how to evaluate real-world production constraints.
Check out the full discussion on why puzzle-solving is completely disconnected from systems engineering in the era of AI agents:
x.com/PythonDvz/stat…
Check out the full discussion on why puzzle-solving is completely disconnected from systems engineering in the era of AI agents:
x.com/PythonDvz/stat…
Stop calling API endpoints blindly without understanding how they work under the hood. Choosing the wrong API architecture is the fastest way to bottleneck your backend performance.
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
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161
Forcing frontend architects to blindly balance a B-Tree under a 45-minute interview timer is completely disconnected from real-world engineering.
An AI agent can implement standard data structures instantly. What actually breaks production web apps at scale isn't an unoptimized sort; it's a memory leak, rigid component state management, or broken proxy handoffs. Full discussion:
x.com/PythonDvz/stat…
An AI agent can implement standard data structures instantly. What actually breaks production web apps at scale isn't an unoptimized sort; it's a memory leak, rigid component state management, or broken proxy handoffs. Full discussion:
x.com/PythonDvz/stat…
Stop calling API endpoints blindly without understanding how they work under the hood. Choosing the wrong API architecture is the fastest way to bottleneck your backend performance.
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
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0
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667
Grinding LeetCode serves as a lazy corporate filter, forcing full-stack developers to memorize data structures instead of learning how to manage real production state and async event loops.
In the era of AI coding agents, syntax and basic algorithms are fully commoditized. Full breakdown on why the technical hiring pipeline is broken:
x.com/PythonDvz/stat…
In the era of AI coding agents, syntax and basic algorithms are fully commoditized. Full breakdown on why the technical hiring pipeline is broken:
x.com/PythonDvz/stat…
Stop calling API endpoints blindly without understanding how they work under the hood. Choosing the wrong API architecture is the fastest way to bottleneck your backend performance.
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
0
0
1
565
In the era of AI coding tools, syntax typing and basic data structure configuration are fully commoditized. A developer with an MCP-capable agent can implement standard sorting algorithms instantly.
Why the tech hiring pipeline needs to move from LeetCode grind to real code debugging and live architecture reviews:
x.com/PythonDvz/stat…
Why the tech hiring pipeline needs to move from LeetCode grind to real code debugging and live architecture reviews:
x.com/PythonDvz/stat…
Stop calling API endpoints blindly without understanding how they work under the hood. Choosing the wrong API architecture is the fastest way to bottleneck your backend performance.
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
0
1
1
621
The tech industry is treating LeetCode like a lazy HR filter, forcing developers to blindly memorize algorithms instead of learning how to evaluate real-world production constraints.
Check out the full discussion on why puzzle-solving is completely disconnected from systems engineering in the era of AI agents:
x.com/PythonDvz/stat…
Check out the full discussion on why puzzle-solving is completely disconnected from systems engineering in the era of AI agents:
x.com/PythonDvz/stat…
Stop calling API endpoints blindly without understanding how they work under the hood. Choosing the wrong API architecture is the fastest way to bottleneck your backend performance.
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
0
0
1
566
What actually breaks enterprise systems under heavy load isn't an unoptimized sorting algorithm—it's a broken race condition, bad database indexing, loose state boundaries, or misconfigured network timeouts.
Grinding algorithmic puzzles doesn't teach you how to build fault-tolerant production architecture. Full breakdown:
x.com/PythonDvz/stat…
Grinding algorithmic puzzles doesn't teach you how to build fault-tolerant production architecture. Full breakdown:
x.com/PythonDvz/stat…
Stop calling API endpoints blindly without understanding how they work under the hood. Choosing the wrong API architecture is the fastest way to bottleneck your backend performance.
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
0
0
3
586
Stop calling API endpoints blindly without understanding how they work under the hood. Choosing the wrong API architecture is the fastest way to bottleneck your backend performance.
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
Here is the real-world breakdown every developer needs to know:
1. REST API:
The undisputed king ndard HTTP methods (GET, POST, PUT, DELETE) and JSON. Super simple and stateless, but easily suffers from over-fetching or under-fetching data on complex screens.
2. GraphQL API:
Lets the client ask for the exact data fields they need in a single query—nothing more, nothing less. Saves mobile bandwidth, but shifts heavy parsing and caching complexity straight to your backend server.
3. WebSocket API:
Kills the request-response waiting game by opening a persistent, two-way real-time connection. Essential when building live chat apps, financial tickers, or streaming AI agent responses.
4. gRPC API:
Replaces bulky JSON with binary Protocol Buffers over HTTP/2. It is blazingly fast with ultra-low latency, making it the gold standard for internal microservice-to-microservice communication.
5. SOAP API:
The strict, XML-based veteran. Heavy and verbose, but still dominates legacy banking, payment gateways, and enterprise systems where rigid security compliance is mandatory.
Check the comparison matrix in the 4th image and save this cheat sheet for your next system design interview!
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Since X only allows 4 images per post, I could only include the visual diagram for REST API above.
I still have the visual architecture diagrams for the other 5: GraphQL, WebSocket, gRPC, SOAP, and Open API.
Which one are you currently learning or struggling with the most? Drop the name below and I will reply directly with its visual diagram and how it works!
I still have the visual architecture diagrams for the other 5: GraphQL, WebSocket, gRPC, SOAP, and Open API.
Which one are you currently learning or struggling with the most? Drop the name below and I will reply directly with its visual diagram and how it works!
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In the era of AI coding tools, syntax typing and basic algorithm generation are fully commoditized. A developer with an MCP-capable agent can implement standard data structures instantly.
Why the tech hiring pipeline needs to move from LeetCode grind to real code debugging and architecture reviews:
x.com/PythonDvz/stat…
Why the tech hiring pipeline needs to move from LeetCode grind to real code debugging and architecture reviews:
x.com/PythonDvz/stat…
The tech industry is still stuck in a massive cognitive dissonance loop. Forcing software engineers to blindly memorize how to balance a B-Tree or invert a binary tree on a whiteboard under a 45-minute timer is completely disconnected from real-world systems architecture.
In the era of AI coding agents, syntax typing and low-level algorithmic brute-forcing are fully commoditized. A junior developer with an MCP-capable agent can split a string or implement a sorting algorithm instantly. What actually breaks production engineering isn't a suboptimal sorting algorithm; it's a broken race condition, bad database indexing, loose state boundaries, or misconfigured network timeouts under heavy load.
Grinding LeetCode teaches developers how to pass a broken corporate filter, not how to ship production-ready, maintainable, and fault-tolerant software architectures. It is time to replace competitive puzzle-solving with real system design reviews and code debugging pipelines.
Are people still paying these platforms just to memorize patterns for interviews, or do you think algorithmic puzzles still build actual engineering depth? Let's talk below!
1
0
6
1,921
The tech industry is treating LeetCode like a lazy HR filter, forcing developers to blindly memorize algorithms instead of learning how to evaluate real-world production constraints.
Check out the full discussion on why puzzle-solving is completely disconnected from systems engineering in the era of AI agents:
x.com/PythonDvz/stat…
Check out the full discussion on why puzzle-solving is completely disconnected from systems engineering in the era of AI agents:
x.com/PythonDvz/stat…
The tech industry is still stuck in a massive cognitive dissonance loop. Forcing software engineers to blindly memorize how to balance a B-Tree or invert a binary tree on a whiteboard under a 45-minute timer is completely disconnected from real-world systems architecture.
In the era of AI coding agents, syntax typing and low-level algorithmic brute-forcing are fully commoditized. A junior developer with an MCP-capable agent can split a string or implement a sorting algorithm instantly. What actually breaks production engineering isn't a suboptimal sorting algorithm; it's a broken race condition, bad database indexing, loose state boundaries, or misconfigured network timeouts under heavy load.
Grinding LeetCode teaches developers how to pass a broken corporate filter, not how to ship production-ready, maintainable, and fault-tolerant software architectures. It is time to replace competitive puzzle-solving with real system design reviews and code debugging pipelines.
Are people still paying these platforms just to memorize patterns for interviews, or do you think algorithmic puzzles still build actual engineering depth? Let's talk below!
0
1
3
1,947
What actually breaks enterprise systems under heavy load isn't an unoptimized sorting algorithm—it's a broken race condition, bad database indexing, loose state boundaries, or misconfigured network timeouts.
Grinding algorithmic puzzles doesn't teach you how to build fault-tolerant production architecture. Full breakdown:
x.com/PythonDvz/stat…
Grinding algorithmic puzzles doesn't teach you how to build fault-tolerant production architecture. Full breakdown:
x.com/PythonDvz/stat…
The tech industry is still stuck in a massive cognitive dissonance loop. Forcing software engineers to blindly memorize how to balance a B-Tree or invert a binary tree on a whiteboard under a 45-minute timer is completely disconnected from real-world systems architecture.
In the era of AI coding agents, syntax typing and low-level algorithmic brute-forcing are fully commoditized. A junior developer with an MCP-capable agent can split a string or implement a sorting algorithm instantly. What actually breaks production engineering isn't a suboptimal sorting algorithm; it's a broken race condition, bad database indexing, loose state boundaries, or misconfigured network timeouts under heavy load.
Grinding LeetCode teaches developers how to pass a broken corporate filter, not how to ship production-ready, maintainable, and fault-tolerant software architectures. It is time to replace competitive puzzle-solving with real system design reviews and code debugging pipelines.
Are people still paying these platforms just to memorize patterns for interviews, or do you think algorithmic puzzles still build actual engineering depth? Let's talk below!
0
0
3
1,396
The tech industry is still stuck in a massive cognitive dissonance loop. Forcing software engineers to blindly memorize how to balance a B-Tree or invert a binary tree on a whiteboard under a 45-minute timer is completely disconnected from real-world systems architecture.
In the era of AI coding agents, syntax typing and low-level algorithmic brute-forcing are fully commoditized. A junior developer with an MCP-capable agent can split a string or implement a sorting algorithm instantly. What actually breaks production engineering isn't a suboptimal sorting algorithm; it's a broken race condition, bad database indexing, loose state boundaries, or misconfigured network timeouts under heavy load.
Grinding LeetCode teaches developers how to pass a broken corporate filter, not how to ship production-ready, maintainable, and fault-tolerant software architectures. It is time to replace competitive puzzle-solving with real system design reviews and code debugging pipelines.
Are people still paying these platforms just to memorize patterns for interviews, or do you think algorithmic puzzles still build actual engineering depth? Let's talk below!
In the era of AI coding agents, syntax typing and low-level algorithmic brute-forcing are fully commoditized. A junior developer with an MCP-capable agent can split a string or implement a sorting algorithm instantly. What actually breaks production engineering isn't a suboptimal sorting algorithm; it's a broken race condition, bad database indexing, loose state boundaries, or misconfigured network timeouts under heavy load.
Grinding LeetCode teaches developers how to pass a broken corporate filter, not how to ship production-ready, maintainable, and fault-tolerant software architectures. It is time to replace competitive puzzle-solving with real system design reviews and code debugging pipelines.
Are people still paying these platforms just to memorize patterns for interviews, or do you think algorithmic puzzles still build actual engineering depth? Let's talk below!
Genuine question: what's up with LeetCode, HackerRank, and all of those services?
Are people still paying them to learn how to sort a B-Tree for a coding interview?
1
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3,770
LeetCode serves as a lazy HR proxy filter because standardizing real systems engineering evaluation is too hard for big tech corporations.
Drop your raw thoughts or interview horror stories below—I am ready to look at how we fix this broken hiring pipeline together!
Drop your raw thoughts or interview horror stories below—I am ready to look at how we fix this broken hiring pipeline together!
0
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347
Why C++ developers secretly look down on Python, and why Python developers just don't care.
Writing "Hello World" in C++ requires memory inclusion, namespace declaration, stack initialization, and standard output streams before execution. Python just calls print().
But here is nt() function is actually written in C. Under the hood, CPython has to parse the string, handle PyObject allocation, look up the sys.stdout object, and invoke the underlying C standard library's write() system call.
Python gives you the speed to ship products, but C++ gives you the power to build Python. Choose your weapon wisely.
Writing "Hello World" in C++ requires memory inclusion, namespace declaration, stack initialization, and standard output streams before execution. Python just calls print().
But here is nt() function is actually written in C. Under the hood, CPython has to parse the string, handle PyObject allocation, look up the sys.stdout object, and invoke the underlying C standard library's write() system call.
Python gives you the speed to ship products, but C++ gives you the power to build Python. Choose your weapon wisely.
1
0
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4,389
If you want to build high-performance data pipelines or AI models, you will end up writing Python on top and C++ or Rust extensions at the core anyway.
Which language did you learn first, and which one do you actually enjoy writing more today? Drop your choice below!
Which language did you learn first, and which one do you actually enjoy writing more today? Drop your choice below!
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Every single line of high-level Python still triggers PyObject memory allocation and C system calls at the OS level.
Understanding this abstraction layer is key to debugging performance bottlenecks in production:
x.com/PythonDvz/stat…
Understanding this abstraction layer is key to debugging performance bottlenecks in production:
x.com/PythonDvz/stat…
Why C++ developers secretly look down on Python, and why Python developers just don't care.
Writing "Hello World" in C++ requires memory inclusion, namespace declaration, stack initialization, and standard output streams before execution. Python just calls print().
But here is nt() function is actually written in C. Under the hood, CPython has to parse the string, handle PyObject allocation, look up the sys.stdout object, and invoke the underlying C standard library's write() system call.
Python gives you the speed to ship products, but C++ gives you the power to build Python. Choose your weapon wisely.
0
0
7
1,552
Developer velocity vs raw hardware execution is the ultimate engineering trade-off. Python lets you ship AI products fast, while C++ powers the underlying runtime and core libraries.
Check out this quick breakdown of how Python's simplicity relies on C under the hood:
x.com/PythonDvz/stat…
Check out this quick breakdown of how Python's simplicity relies on C under the hood:
x.com/PythonDvz/stat…
Why C++ developers secretly look down on Python, and why Python developers just don't care.
Writing "Hello World" in C++ requires memory inclusion, namespace declaration, stack initialization, and standard output streams before execution. Python just calls print().
But here is nt() function is actually written in C. Under the hood, CPython has to parse the string, handle PyObject allocation, look up the sys.stdout object, and invoke the underlying C standard library's write() system call.
Python gives you the speed to ship products, but C++ gives you the power to build Python. Choose your weapon wisely.
0
0
7
1,327