Brief Summary
This video is a comparison between Go and Python, targeted towards intermediate programmers. It highlights the core differences in their approach to programming, their strengths in different areas like microservices (Go) vs. data science (Python), and their performance in tasks like web scraping. The video also touches upon Go's emerging role in machine learning and provides guidance on choosing the right language for specific projects, emphasizing the importance of hands-on experience and continuous learning. Finally, it looks at future trends like AI on edge devices and quantum computing, and how these languages might evolve.
- Go is like a master craftsman, procedural and efficient.
- Python is like a creative architect, object-oriented and elegant.
- Go excels in speed, concurrency, and scalability, while Python shines in readability and rapid development.
- Both languages have a role to play in future technologies like AI and quantum computing.
The video starts by setting the stage for a comparison between Go and Python, specifically aimed at intermediate programmers looking to up their game. It acknowledges Python's widespread popularity and poses the question: why even consider Go? The answer lies in their fundamentally different approaches to programming. Go is presented as a procedural language, focused on efficiency and robustness, like a master craftsman. Python, on the other hand, is described as an object-oriented language, emphasizing elegance and complexity, like a creative architect using building blocks.
Go is likened to old-school programming, emphasizing a specific order of operations. Python takes an object-oriented approach, bundling data and actions together. This difference leads to strengths in different areas. Go is preferred for building microservices and APIs where speed and efficiency are crucial. Python, with its readability and rapid development capabilities, excels in data science, scripting, and web development. Python's beginner-friendly syntax and extensive libraries contribute to its popularity, allowing developers to quickly build upon existing tools and focus on unique logic, especially in AI and machine learning.
Go is known for its blazing speed, even outperforming Java in some benchmarks. It compiles down to a single binary, simplifying deployment without the need for virtual machines or dependency management. This speed comes from its design for cloud computing, prioritizing efficiency and performance. Go's scalability is another key advantage, with goroutines (lightweight threads) enabling concurrent handling of numerous tasks. This makes Go suitable for projects that need to scale effortlessly as they grow.
In a head-to-head web scraping test, Go significantly outperformed Python, completing the task in less than half the time. This is attributed to Go's concurrency model, which allows it to spin up goroutines and handle multiple requests simultaneously. While Python can also handle concurrency, it requires more effort and isn't as efficient in resource management.
Go is starting to make inroads into the machine learning world, traditionally dominated by Python. This is driven by Go's speed, concurrency, and ease of deployment, making it suitable for certain machine learning applications, especially those dealing with massive data or real-time processing. While it's still early days, Go is finding niches where its performance advantages can be game-changers.
The choice between Go and Python depends on the project requirements. Having both tools in your toolbox is a significant advantage for intermediate programmers. If rapid prototyping is needed, Python's concise syntax and extensive libraries make it a good choice. For systems requiring massive scale and concurrency, Go's concurrency model shines. Python is like a nimble sprinter, while Go is like a marathon runner, built for endurance and handling large workloads.
Go is praised for its simplicity and straightforward syntax, with some arguing it's easier to learn than Python, especially for those with a C or C++ background. The core concepts are easy to grasp, and there's less "magic" happening behind the scenes. Go is also becoming increasingly valuable in the job market, with many companies seeking Go developers, particularly those working with cloud technologies and large-scale systems. Even if you primarily work with Python, understanding Go can make you a better Python programmer by understanding the trade-offs involved in language choices.
Looking to the future, AI and edge computing are identified as key trends. Edge computing involves running AI algorithms on devices at the edge of the network, like smartphones or self-driving cars, reducing reliance on centralized cloud servers. Go, with its efficiency and small footprint, is a strong contender for building edge-based AI applications. Python will continue to play a role in developing and training the models that run on these devices. Quantum computing is another area where both Go and Python communities are exploring potential applications.
The biggest takeaway is to never stop learning, embrace new languages and technologies, and constantly push the boundaries of what's possible. Experiment, build things, break things, and learn from it. The more you learn, the better equipped you'll be to create innovative solutions. The video encourages viewers to explore Go and Python, experiment with them, and see what they can create.
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Transcript
Full transcript of “Golang vs Python: Which Should You Choose for Your Next Project?”. Click a timestamp to open the video at that moment. Need another video? Use the YouTube transcript generator.
0:00 all right so today we are going deep on Go versus python you know specifically for those of you out there who are like me intermediate programmers we're kind of past the beginner stage right but looking to really um take things to the next level and I think this is a really fascinating comparison especially because we all know right python like it's everywhere yeah Python's been super popular for a while yeah so why even bother why are we even talking about go right like what's what's the deal well I think I think what's really interesting is approach programming in fundamentally different ways okay so that's that's interesting so like at their core how are they different okay so think of it this way go is kind of like a master Craftsman very procedural step by step you know they build something incredibly efficient and robust right python is
0:47 like a creative architect using objects right as building blocks and they can assemble elegant and complex structures go is very like uh I guess kind of like almost like old school programming way in a way yeah like very much focused on how to do things in a very specific order python is this objectoriented approach where it's more about thinking about the data and the actions kind of bundled together yeah that's interesting so I can see like how those two different mindsets would lead to strengths in different areas exactly so for example if you're thinking about you know building microsurfaces or API something that needs to be really fast really efficient you know go is often the preferred tool okay whereas python you know with its readability and it's
1:32 um its speed of development it shines in you know areas like data science scripting web development that kind of thing yeah and it's funny because I feel like um you know python like I said it's everywhere and part of that is I feel like it is so beginner friendly yeah like it really um you know it welcomes new programmers because the syntax is so clean so intuitive like there's no semicolons there's no brackets to worry about and like there's a library for like prac Bally everything you could imagine right and I think that's one of the superpowers is the fact that you can just get up and running so fast you're not Reinventing the wheel you can just tack into this huge collection of tools and really focus on the unique logic of what you're trying to build and of course you know AI machine learning like
2:17 it's the language that everyone's using yeah yeah it is a language for those fields right yeah so so those are some really um really strong points for python so now let's talk about go first second okay one of the things that I've always heard about go is that it is blazingly fast like seriously fast it is like I I've even read that it outperforms like Java in benchmarks which is crazy which is pretty impressive yeah that is wild um and then I think another thing that's really interesting about it is that it compiles down to a single binary right which means like deployment is super easy yeah you know no virtual machines or anything like that to worry about you don't have to mess with all the dependencies like where does where does that Speed come from like what is it about go that makes
3:02 it so fast I think it comes from you know it was built for the age of cloud computing right where everything has to be efficient and fast performant so you know that's why it's it's used in Technologies like Docker right which is actually written in go oh W okay um and then you know you mentioned scalability too and that's another uh you know another area where it really shines it's got these things called goroutines which are these lightweight threads that can handle like a ton of tasks concurrently so as your project grows go can scale with it uh you know pretty effortlessly that's fascinating I'm always really interested in like the underlying like architecture of these things and how they achieve these these things like how do they achieve that speed and then you know on the other side like how is
3:48 python achieving what it's achieving but yeah I mean that's super interesting so I'm wondering like in a head-to-head matchup who wins because I know I was reading about this test where um they were doing some web scraping using both go and Python and the results were kind of stunning yeah the web scraping example That's a classic yeah so in that case go absolutely crushed it by how much uh less than half the time that it took python oh wow like that's a significant difference so like what what was it about go that made it so much faster for that particular task again it's the concurrency the fact that you can spin up all these Goro tees and handle all these requests simultaneously makes it really efficient for tasks like that whereas python can do concurrency but it's often you know a little bit
4:35 more work to get it right yeah and it's not as you know um efficient and kind of doesn't manage resources quite as well okay so this last one really surprised me I was reading that go is starting to make some inroads in the machine learning world yeah which I mean come on that's been Python's domain forever so like what is driving that shift what is it about go that is making it healing for that use case yeah it's still early days but I think it's you know it goes back to that you know speed concurrency ease of deployment for certain types of machine learning applications particularly ones that are you know dealing with massive amounts of data or real-time processing you know ghost performance just really shines yeah okay so there are specific applications right
5:22 it's not necessarily taking over but it's like oh here's this this other tool right exactly interesting yeah it's really interesting to see how you know go and python are kind of shaking things up but I think what's important to remember is that you know the choice between them isn't always clearcut it really depends on the project right what are you trying to build what are the strengths of each language yeah and I think for for folks like us who are you know intermediate programmers having both of those tools in our toolbox is is probably a pretty big Advantage yeah exactly you know as an intermediate programmer you're probably facing more you know complex challenges right so you need to really think about like okay what's the the right tool for the job and and having you know even if you're not an expert in both just having that understanding can really make a difference yeah so like okay let's say
6:10 um let's say I'm working on a project and the deadline is looming right I need to get something up and running super fast right is there a clear winner there when it comes to a speed of development yeah I mean if you need to you know get a prototype up and running quickly python often has the edge there okay just because you know that concise syntax the libraries you can usually find you know pre-built Solutions or get help quickly so that can be a huge time saber so if I'm building a web app for example right and I need to get it to Market fast yeah pipon might be the smarter Choice yeah in many cases yeah I mean that's not to say you can't use go for web development but you know python just has that kind of ecosystem and emphasis on rapid development right makes sense makes sense okay okay so now
6:56 let's flip that around a little bit let's say I'm building a system that needs to handle like massive scale right like millions of users concurrently right what what are the factors that come into play there I mean that's where I think go concurrency model really shines right okay because with those gory teens it can just handle like a ton of concurrent activity without you know bogging down python can do it but it often requires you know a little more work and it might not be as efficient at that scale so python is like a like a Nimble Sprinter yeah go is like the like the marathon runner exactly built for endurance and handling those huge you know workloads over a long time right built for that robustness and you know efficiency when you're dealing with you know large scale systems resource
7:43 intensive tasks yeah that makes me think back to that web scraping example it seems like anything that involves pulling a lot of data from the web go is probably the right tool for the job yeah absolutely because web scraping often involves you know making multiple requests simultaneously right processing lots of data so go concurrency and just its overall performance makes it a good fit for that so we talked a little bit about machine learning before um and you mentioned this kind of early days but do you think go is actually starting to challenge Python's dominance there yeah I guess that's something that we should be paying attention to you know I think it is again it's it's early but I think in those in those areas where performance and scalability are really important like think about real time
8:29 image recognition or processing huge amounts of data for you know natural language processing that's where go speed and efficiency can really be game changers was finding these niches within machine learning it's like okay this is where it makes sense to use go instead of python exactly and that's why again you know as an intermediate programmer having that understanding of both is so valuable right because you can really start to see okay what are the tradeoffs right and what makes sense for you know for a particular application but I'm curious uh from a learning perspective right so you know we've talked about python being super beginner friendly how does go compare in terms of ease of learning you know a lot of people actually praise go for its Simplicity
9:17 and its you know pretty straightforward syntax some would even argue that it's easier to learn than python especially for people coming from like a c or C++ background um you know the Core Concepts are pretty easy to grasp and there's not as much kind of you know magic happening behind the scenes yeah so you know if you're an intermediate programmer looking to expand your skill set it might not be as daunting as you think yeah and the the job market I imagine is probably you know a factor here as well right like if you're if you're trying to figure out okay what am I going to invest my time in learning yeah it seems like go is is becoming increasingly valuable yeah absolutely I mean a lot of companies especially those working with you know Cloud Technologies large scale systems they're really looking for go developers yeah
10:02 yeah that makes sense and it's interesting because I was thinking you know even if you're primarily work with python right it seems like having at least a basic understanding of go can probably make you a better python programmer absolutely just because you know you can start to understand like okay what are the trade-offs that are being made right exactly and like why was python chosen for this and maybe go would have been a better choice for that right exactly yeah it's almost like being you know multilingual yeah right the more languages you know the better you can communicate with different systems absolutely and I think you know as as technology keeps evolving so rapidly just being adaptable right having that diverse skill set is is super valuable yeah for sure for sure well you know I think uh for all of our listeners out there hopefully this has
10:48 given you a good understanding of you know the key differences between go and python but you know the real learning comes when you actually start playing with these languages yourself right yeah absolutely hands on experience is key try building a small project in each language see what the differences are in the approach and and see what you like better yeah yeah I love that advice just get your hands dirty try things out and and figure out what works for you who knows you might surprise yourself okay so we've talked about how go and python like you know they're tackling today's programming challenges but I'm kind of curious like what about the future like how do you see these languages evolving what what new doors do you think they might open well that's a really good question you know technology is always changing so it's important to kind of
11:35 you know look beyond the current landscape think about you know what are the demands of tomorrow going to be yeah yeah for sure so so for intermediate programmers like me like what are some of the like trends that we should be keeping an eye on like where do you see the biggest like potential for growth for Innovation with both go and python well one area that's that's really exciting to me is this idea of you know artificial intelligence and Edge computing so this is like you know running AI algorithms on devices at the edge of the network like think about your smartphone or a sensor or even like a self-driving car right yeah instead of you know relying on these centralized Cloud servers okay so that that seems like a pretty big shift right like why is that such a big deal and how do go and python kind of fit into that yeah so
12:21 I mean moving AI to the edge it has a lot of advantages you know faster response times reduced Reliance on like you know network connectivity um enhanced privacy and security and you know guess what go with its efficiency and its small footprint it's actually like a really strong Contender for you know building those edge-based AI applications so like we might start to see go actually like powering you know these these next Generation like smart devices that are like making decisions in real time without having to constantly talk to the clout yeah exactly and then python with its You Know Rich ecosystem for AI machine learning libraries that's going to play a huge role in you know developing training those models that run on those devices interesting so it seems like we're moving towards this world where
13:08 like AI is just like baked into everything around us and and both go and python are going to be you know really important parts of making that happen absolutely and that's just one example I mean there's also you know the rise of quantum Computing which has the potential to like completely revolutionized Fields yeah you know like drug Discovery Material Science Financial modeling and it's it's still early days so it's hard to say like you know which programming languages are going to dominate in that in that Quantum realm but both go and python communities are definitely exploring that wow that's that's pretty wild so so I guess to kind of wrap things up here what what would you say are the like the key takeaways um you know that you'd want to leave our listeners with I think I think the biggest takeaway is just you know never stop learning embrace the
13:54 challenge of you know mastering new languages exploring new technologies and just you know constantly kind of push the boundaries of what's possible the more you learn the better equipped you're going to be to to create those innovative solutions yeah yeah and don't be afraid to experiment yeah like build things break things learn from it that's how you grow as a programmer that's how you figure out like what you're really capable of so we've only scratched the surface here right with go and python now it's your turn to go out there explore experiment see what you can create absolutely well hey thanks so much for joining us on this deep dive you know hopefully you learned something and you're feeling inspired to you know continue exploring the amazing world of programming thanks for having me yeah
14:40 it's great to have you and for all of you listening out there you know keep coding keep learning keep pushing the limits and we will catch you on our next Deep dive
