Speaker 1: Welcome to another deep dive. You know how this works.
Speaker 1: By now we take some fascinating source material and we
Speaker 1: really get into the details today. What's all about Python?
Speaker 1: Using real world Python? A Hacker's Guide to Solving Problems
Speaker 1: with code. I actually think this is a great book
Speaker 1: for anyone, even if they're not super techy.
Speaker 2: Oh, I totally agree. It's written in a way that's
Speaker 2: really engaging, even if you've never coded before in your life.
Speaker 1: So yeah, definitely a great resource.
Speaker 2: Okay, so Python, Why Python? Everyone's talking about Python? What's
Speaker 2: the big deal?
Speaker 1: Well, you know, it's interesting because Python is used in
Speaker 1: so many different fields, like you see it everywhere, machine learning,
Speaker 1: data science, web development. It's really one of the most
Speaker 1: versatile languages out there.
Speaker 2: So if someone's just starting out, is this the language
Speaker 2: to learn?
Speaker 1: I'd say so. Yeah. One of the things that makes
Speaker 1: Python so popular is that it's incredibly beginner friendly, Like
Speaker 1: the syntax is designed to be readable. You know, it's
Speaker 1: almost like reading plain English, so it's a lot easier
Speaker 1: to pick up than some of the more complex languages
Speaker 1: out there. Okay, so it's easy to learn, but is
Speaker 1: it powerful enough to actually do serious stuff?
Speaker 2: Oh? Absolutely? I mean, it's used by major companies like
Speaker 2: Google and Facebook for some really complex tasks. So yeah,
Speaker 2: you can definitely do serious stuff with it.
Speaker 1: Okay, So this book, Real World Python, it takes this
Speaker 1: approach of teaching you to think like a hacker. So
Speaker 1: what exactly do they mean by that?
Speaker 2: So when they say hacker, they don't mean like the stereotypical,
Speaker 2: you know, guy in a hoodie breaking into computer systems.
Speaker 2: It's more about using your creativity and your problem solving
Speaker 2: skills to find clever and resourceful ways to use code
Speaker 2: to solve real world problems.
Speaker 1: Okay, so give me an example. What kind of hacker
Speaker 1: projects are we talking about.
Speaker 2: So one of the projects in the book is recreating
Speaker 2: the blink comparitor that was used to discover Pluto. Whoa, yeah,
Speaker 2: it's pretty cool.
Speaker 1: That's really cool. So it's like stepping back in time
Speaker 1: and reliving that historical.
Speaker 2: Discuss exactly, and you're doing it through code.
Speaker 1: Okay, I have to admit astronomy is not really my thing.
Speaker 1: Are there other projects in the book that might appeal
Speaker 1: to I don't know, maybe someone who's more into history.
Speaker 2: Yeah, definitely. There's a project that focuses on cryptography. Specifically
Speaker 2: the Rebecca cipher that was used in World War Two.
Speaker 1: Okay, I'm listening.
Speaker 2: So the Rebecca cipher relied on a shared book between
Speaker 2: the sender and the receiver. You had to have the
Speaker 2: same book to decode the message. And in this project,
Speaker 2: you're actually using the book The Lost World as a
Speaker 2: digital one time pad.
Speaker 1: So it's like taking this historical technique, yeah, and bringing
Speaker 1: it into the digital age.
Speaker 2: Yeah, exactly. It's a great way to see how Python
Speaker 2: can bridge the gap between, you know, the past and
Speaker 2: the present.
Speaker 1: Okay, so the book mentions all these different Python libraries.
Speaker 1: Can you break that down for me? What are libraries
Speaker 1: in the context of programming?
Speaker 2: Yeah, so Python libraries are essentially collections of pre written code.
Speaker 2: They're like toolkits that give you specific functions and capabilities,
Speaker 2: so you don't have to write everything from scratch.
Speaker 1: So it's like having a toolbox full of different tools. Yeah,
Speaker 1: and you can just pick and choose the ones you
Speaker 1: need for the job.
Speaker 2: Yeah, that's a great way to think about it. You
Speaker 2: have libraries like open cv for computer vision, numb PI
Speaker 2: for working with a raise and matrices, map plot lib
Speaker 2: for creating plots and charts, and pandas for data analysis.
Speaker 1: So it's like having a whole workshop at your disposal.
Speaker 2: Exactly, and real world Python shows you how to use
Speaker 2: these tools to build some really cool projects.
Speaker 1: Okay, so give me an example a project that really
Speaker 1: showcases how these libraries can be used to solve a problem.
Speaker 2: Sure, there's a project where you play the role of
Speaker 2: a coastguard search and rescue director. You're tasked with finding
Speaker 2: a missing fisherman.
Speaker 1: Okay, that sounds intense.
Speaker 2: Yeah it is. You use something called bays Rule, which
Speaker 2: is a way of updating probabilities as you get new
Speaker 2: information to guide your search efforts, and you use the
Speaker 2: OpenCV library to create a visual interface with a map
Speaker 2: of the search area, so you can actually see how
Speaker 2: the probabilities change as you make decisions.
Speaker 1: So it's not just abstract math. You're actually using data
Speaker 1: to make real time decisions in a high stakes situation.
Speaker 2: Exactly. It's a really powerful example of how Python and
Speaker 2: these libraries can be used for practical problem solving.
Speaker 1: Okay, that's really cool. Now I'm seeing how this all
Speaker 1: comes together.
Speaker 2: And that's just one example. There's another project that uses
Speaker 2: OpenCV for face recognition. You build a system that can
Speaker 2: identify individuals based on their facial features.
Speaker 1: So like how your phone unlocks with your face.
Speaker 2: Yeah, kind of like that. But in this project, you
Speaker 2: actually train the system yourself using a set of images,
Speaker 2: and then you can use it to control access to
Speaker 2: a secure area like a lab or something.
Speaker 1: Okay, that's straight out of a spy movie, I know. Right,
Speaker 1: So we're talking about real world applications here, yeah, not
Speaker 1: just theoretical stuff.
Speaker 2: Absolutely, And it gets even more interesting. There's a project
Speaker 2: that explores data visualization using core pluff maps.
Speaker 1: Core a pluff maps sounds little intimidating.
Speaker 2: They might sound complex, but they're actually pretty easy to understand.
Speaker 2: It's basically a map where different regions are shaded different
Speaker 2: colors based on some data points like population density or
Speaker 2: election results. You've probably seen them before, Okay, yeah, I
Speaker 2: think I have. Well, in this project, you use a
Speaker 2: korapleth map to visualize population density across the US. Okay,
Speaker 2: and why would I want to do that?
Speaker 1: Well, here's the twist. You're using it to plan an
Speaker 1: escape route during a zombie apocalypse.
Speaker 2: Okay, now you're speaking my language, so you're telling me
Speaker 2: I can use Python to survive a zombie apocalypse.
Speaker 1: Well, it's a fun way to learn about data visualization
Speaker 1: and how it can be used for planning and decision
Speaker 1: making even in extreme situations.
Speaker 2: I'm sold. So we've gone from discovering planets to outsmarting zombies,
Speaker 2: all with Python.
Speaker 1: And we're just getting started. There's even a project that
Speaker 1: explores the simulation hypothesis, the idea that our reality is
Speaker 1: actually a computer simulation.
Speaker 2: Whoa, Okay, we're getting into some deep philosophical territory now.
Speaker 1: Yeah, but that's one of the things I love about
Speaker 1: this book. It doesn't shy away from the big questions,
Speaker 1: and it shows you how computational thinking can help us
Speaker 1: approach these questions in new and interesting ways.
Speaker 2: Okay, my mind is officially blown. I know, right, I've
Speaker 2: covered a lot of ground already. We have, but I
Speaker 2: feel like we've only just scratched the surface.
Speaker 1: Yeah, we've only just begun to explore the possibilities of Python.
Speaker 1: So you want to dive back into that simulation idea? Yeah,
Speaker 1: I mean it's kind of freaky but also really fascinating
Speaker 1: to think that maybe our whole reality is just code.
Speaker 2: It is pretty mind bending. But you know what I
Speaker 2: like about real world Python is that it doesn't just
Speaker 2: dwell on these super abstract concepts. It brings it back
Speaker 2: down to earth with practical stuff you can actually use.
Speaker 1: Okay, good because as much as I love a good
Speaker 1: existential crisis, I also want to know how this can
Speaker 1: help me, you know, in my actual life.
Speaker 2: Right, So, like, have you ever heard of stylometries?
Speaker 1: Stylometry? Is that like some kind of fancy haircut?
Speaker 2: Haha? No, it's actually the study of linguistic style, like
Speaker 2: how you can analyze someone's writing to identify them or
Speaker 2: to figure out, you know, if they wrote something like
Speaker 2: a literary fingerprint exactly. And one of the projects in
Speaker 2: the book has using Python to compare the writing styles
Speaker 2: of different authors like Arthur Conan Doyle and HG. Well's.
Speaker 1: That's so cool. I could totally see that being used
Speaker 1: in like, yeah, historical research.
Speaker 2: Oh yeah, definitely, or even in like forensic science to
Speaker 2: analyze handwriting samples.
Speaker 1: Okay, So we talked about this earlier, but can we
Speaker 1: get back to text summarization because I feel like that's
Speaker 1: something that could be really useful.
Speaker 2: Well for sure, I mean we're drowning in information these days,
Speaker 2: so being able to condense large chunks of text into
Speaker 2: shorter summaries is super valuable.
Speaker 1: Right, Like, think about all the time you could save
Speaker 1: if you didn't have to wade through yeah, pages and
Speaker 1: pages of reports or articles exactly.
Speaker 2: And one of the projects in the book focuses on
Speaker 2: summarizing Martin Luther King Junior's I have a Dream speech.
Speaker 1: Okay, that's a classic.
Speaker 2: Yeah, and it breaks it down into its core message
Speaker 2: using Python.
Speaker 1: Wow.
Speaker 2: And there's another project that introduces a library called gensim,
Speaker 2: which is specifically designed for text analysis.
Speaker 1: Another library. I'm starting to see a pattern here.
Speaker 2: Yeah, Python has a library for pretty much everything.
Speaker 1: That's amazing, right.
Speaker 2: So anyway, this project uses Jensen to summarize Admiral William H.
Speaker 2: Mcraven's make your Bed speech.
Speaker 1: Oh, I've heard of that one. It's all about, you know,
Speaker 1: the importance of starting your day off. Okay, this is
Speaker 1: all super cool, But I'm a visual learner. Is there
Speaker 1: a way to make text summarization a little more visual?
Speaker 2: I'm so glad you asked that, because the book also
Speaker 2: covers word clouds.
Speaker 1: Word clouds, Yeah.
Speaker 2: They're visual representations of text where the size of each
Speaker 2: word corresponds to how frequently it appeared.
Speaker 1: So it's like a visual summary of the tex exactly.
Speaker 2: And one of the projects, yeah, has you creating a
Speaker 2: word cloud from the Sherlock Holmes story The Hound of
Speaker 2: the Basker Pills. And to make it even more fun,
Speaker 2: the word cloud is shaped like Sherlock Holmes himself.
Speaker 1: Okay, that is awesome. I know. Word clouds could be
Speaker 1: so useful analyzing social media trends or getting a quick
Speaker 1: overview of customer feedback total.
Speaker 2: And the book introduces you to the word cloud library,
Speaker 2: which makes creating these visualizations super easy.
Speaker 1: Okay, so we've gone from ancient ciphers to modern data
Speaker 1: visualization techniques. It seems like Python can do just about
Speaker 1: anything pretty much.
Speaker 2: And speaking of pushing boundaries, let's talk about astronomy.
Speaker 1: Kevin tried.
Speaker 2: So there's a project in the book that focuses on
Speaker 2: identifying exoplanets, you know, planets that orbit stars outside our
Speaker 2: solar system.
Speaker 1: WHOA how does Python help us find those?
Speaker 2: So it uses a technique called transit photometry. Imagine a
Speaker 2: firefly passing in front of a spotlight. You'd see a
Speaker 2: slight dip in the brightness of the spotlight.
Speaker 1: Right, Yeah, I think so.
Speaker 2: Well, transit photometry is kind of like that, but on
Speaker 2: a cosmic scale. When a planet passes in front of
Speaker 2: its star, it blocks a tiny bit of the star's light.
Speaker 2: And Python is used to analyze the light curves, which
Speaker 2: are graphs that show the stars brightness over time, and
Speaker 2: look for those dips.
Speaker 1: So it's like looking for a needle in a haystack, but.
Speaker 2: With code exactly. And it's amazing because Python can actually
Speaker 2: detect these incredibly tiny changes in brightness.
Speaker 1: That's insane, you know, right. So does the book actually
Speaker 1: like get into the nitty gritty of how this works?
Speaker 2: Oh yeah, it goes pretty deep. It covers concepts like
Speaker 2: limb darkening, which is where stars appear dimmer at their
Speaker 2: edges than at their centers. There's even a project on
Speaker 2: detecting an exerplanet with a moon, which would create a
Speaker 2: unique signature in the light curve.
Speaker 1: Okay, that's your next level stuff.
Speaker 2: It is, but the book breaks it down step by step.
Speaker 1: I'm seriously impressed with this book.
Speaker 2: Me too.
Speaker 1: Okay, so before we completely lose ourselves in space, I
Speaker 1: remember seeing something about a MLA map.
Speaker 2: Oh yeah, the Mars Orbiter Laser Altimeter map. It's basically
Speaker 2: a detailed topographic map of Mars. Okay, and the project
Speaker 2: in the book uses this map to help you select
Speaker 2: potential landing sites for a Martian lander.
Speaker 1: So we're not just finding exoplanets, we're also planning missions
Speaker 1: to Mars.
Speaker 2: Yep.
Speaker 1: This is too cool.
Speaker 2: It's a great example of how Python can be used
Speaker 2: for real world old mission planning. You're essentially acting as
Speaker 2: a Martian real estate agent.
Speaker 1: Ah for robots. This book is really making me rethink
Speaker 1: what's possible with coding.
Speaker 2: That's what it's all about.
Speaker 1: It's not just about writing lines of code. It's about
Speaker 1: exploring and problem solving and discovering new ways to understand
Speaker 1: the world.
Speaker 2: Couldn't just set it better myself?
Speaker 1: Okay, so remember that zombie apocalypse scenario.
Speaker 2: Oh yeah, with the core Pleth maps. Well, the book
Speaker 2: goes into a lot more detail on how you can
Speaker 2: actually use Python to plan a safe escape route. It
Speaker 2: uses US census data to map population density and guide
Speaker 2: you away from those densely populated zombie infested areas.
Speaker 1: So it's not just about surviving, it's about surviving.
Speaker 2: Strategically exactly, using data to make informed decisions. That's brilliant
Speaker 2: and The project introduces you to some cool libraries like
Speaker 2: pandas for data manipulation, Boka for plotting, and hall of
Speaker 2: Use for creating interactive visualizations.
Speaker 1: Wow, this deep dive is just the beginning. There's so
Speaker 1: much more to explore.
Speaker 2: Oh yeah, real world Python makes that very clear. And
Speaker 2: speaking of exploring further, I feel like we could talk
Speaker 2: about Python forever.
Speaker 1: Right, I mean, we've gone from discovering planets to surviving
Speaker 1: zombie apocalypses.
Speaker 2: It's crazy the range of stuff that you can do
Speaker 2: with it.
Speaker 1: It is, but you know what, I'm curious about all
Speaker 1: those everyday tasks. Can Python help with those? Two?
Speaker 2: Definitely? Like think about all the things you do on
Speaker 2: your computer that are kind of repetitive, like renaming files
Speaker 2: or converting them.
Speaker 1: Oh yeah, that stuff can be such a pain.
Speaker 2: Exactly, and Python can automate all of that.
Speaker 1: So it's like having a personal assistant.
Speaker 2: Kind of, but you're the one programming the assistant. I
Speaker 2: like that, and you can customize it to do exactly
Speaker 2: what you need.
Speaker 1: Okay, but be honest, learning a whole new programming language,
Speaker 1: yeah it sounds kind of intimidating.
Speaker 2: I get it, But that's what's so great about real
Speaker 2: world Python. It starts with the basics, like the syntax
Speaker 2: and the core concepts, and then it gradually builds up
Speaker 2: your skills through those projects we've been talking about.
Speaker 1: So it's like learning any other language exactly.
Speaker 2: You start with the alphabet, then you learn some words,
Speaker 2: and eventually you can have a conversation.
Speaker 1: That makes sense.
Speaker 2: And the key is to practice. Don't be afraid to
Speaker 2: make mistakes. That's how you learn.
Speaker 1: Yeah, the book really emphasizes that.
Speaker 2: It does. It gives you the foundation, and then it
Speaker 2: encourages you to experiment.
Speaker 1: It's like the book gives you a map.
Speaker 2: And then you get to choose your own adventure exactly.
Speaker 2: And even after you finish the book, it gives you
Speaker 2: a ton of resources.
Speaker 1: For further learning. So it's really just the beginning it is.
Speaker 2: Python is a journey, not a destination. I love that,
Speaker 2: and it's a journey that's accessible to anyone.
Speaker 1: That's what I hope people take away from this. Python
Speaker 1: isn't just for you know, computer science geniuses. It's a
Speaker 1: tool that anyone can use to solve problems, to analyze data,
Speaker 1: to be more creative. Absolutely so, if you've ever been
Speaker 1: curious about coding, but maybe felt a little intimidated. Give
Speaker 1: real world Python a try.
Speaker 2: I highly recommend it.
Speaker 1: It's a fun and engaging way to learn a really valuable.
Speaker 2: Skill, and who knows, you might just discover a passion
Speaker 2: you never knew you had.
Speaker 1: Will said, Okay, I think it's time to wrap up
Speaker 1: this deep dive into real world Python. It's been a blast,
Speaker 1: it really has. We've learned so much. You have and
Speaker 1: I hope you have to, So until next time, happy coding, everyone,