370-openbb.vtt

WEBVTT

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- Hello, YouTube.


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Hello, James.


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- Michael, thank you for having me.


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- Yeah, it's great to be here.


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Are you ready to kick this podcast off?


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- Let's do it.


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- All right, awesome.


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People out there watching, please throw in some questions,


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comments, feedback in the live chat.


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If you're watching later, well, there is no live chat


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'cause it's in the past, but thanks for watching anyway.


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All right, James, welcome to Talk Bythonomy.


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- Yeah, no, thank you so much for having us.


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I'm looking forward to the next hour or so.


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- Yeah, so am I.


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I ran across OpenBB not too long ago.


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I talked about it on my other podcast,


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Python Bytes, I do with Brian Okken.


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We cover like interesting projects and news and whatnot.


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I'm like, dang, this thing is,


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this thing is loaded with the Python data science stack.


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And on top of that, it's a newly,


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really successful open source project


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in the sort of business VC space as well.


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So congratulations on building a project and on that.


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And I think people are gonna be pretty fascinated


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to hear the story behind it.


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- Yeah, thank you so much.


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- Yeah, you bet.


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Before we get to the story of OpenBB,


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let's get to the story of James.


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How'd you get into programming Python?


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- So I've only been in Python for a couple years.


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My background, I'm, along with OpenBB,


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I'm a PhD student at University of Maryland Physics.


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Got into Python when I was getting bored of MATLAB.


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So started taking an interest


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in some machine learning, data science.


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Python seemed to be the way to go.


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It was super straightforward.


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A lot of similarities with MATLAB,


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especially NumPy, PyPlot.


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So it was straightforward, never looked back.


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- That's awesome.


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Yeah, the Jupyter side, data science side of Python


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is quite similar to MATLAB.


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Although it's a slightly cleaner language,


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starts with zero, not one on the indexes.


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- It does.


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And MATLAB, their attempt at Jupyter


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is not exactly where Jupyter is yet.


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- So they had a head start, right?


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I mean, MATLAB predates Jupyter by a long ways.


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- Yeah, well, their live editor is only a couple years old.


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- Okay.


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- Or at least a couple years old to me.


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- Yeah, yeah, sure.


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It probably is.


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My last experience with MATLAB was


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when I was in grad school as well,


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which has been a while.


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So it's a little bit back there.


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Awesome.


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Well, that sounds like really fun.


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I guess you started playing with Jupyter


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and the various data science tools for physics, right?


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Not for finance.


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- Correct.


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Correct.


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It was, you know, NumPy, all that fun stuff


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for doing some physics, SciPy calculations.


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- I did go right into the machine learning Kaggle


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fantastic exercise, really actually my first dive


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into Python, I love doing these NFL challenges


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that they have every year.


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So that was where I first fell in love


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with the language, if you will.


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- The NFL's challenge sounds really interesting.


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I've seen some Kaggle challenges


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and done other similar type of challenges,


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but I'm not familiar with this one, tell us about it.


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- So every year it seems like they,


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actually they have a couple as far as I know.


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they usually do like an analytics one


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where you got to present some kind of notebook


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and then a numeric one,


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think of you're watching Sunday football AWS,


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which actually if you got my bills flag in the background.


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So this particular one that I started on,


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you were looking at,


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you were given the information at a given point in time


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and you were to estimate using whatever machine learning,


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not machine learning, how far the runner would go.


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And so that was a great introduction,


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Voronoi regions and decision trees, all that fun stuff.


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- I think those kinds of challenges are really interesting


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because they don't require you to be


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developer or code enthusiasts.


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You can just be excited about football


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and it could drag you into programming


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instead of the other way around.


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- Yeah, actually the way that I did it,


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And I don't think I did, I didn't do too great on the challenge, you know, no medals or anything,


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but I actually treated it as a physics problem as a, all the players as a gas particles and


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this fun, fun stuff.


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So there really wasn't any machine learning there.


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Yeah.


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But interesting.


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And just sidebar, I gotta say the Chiefs, Bills, I'm a Chiefs fan, grew up in Kent City.


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Gotta say that was one, that's probably the best game of all last year out of all the


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games.


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That was, that's the best game of all time.


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I mean, I mean, maybe not a little painful if you're on the bill side, but wow, what


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an insane game.


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All right.


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I don't want to make it a football show, but boy, that was, that was the highlight of the


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entire year.


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I think actually, well, low light, low light on my side.


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Yeah.


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Cause for those who don't know, basically the, the chiefs came back and beat the bills


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in the last like minute and a half in some insane way, which is unfortunate, but it was


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really exciting.


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All right.


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Final, final background question.


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What kind of physics did you study?


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- So I do atomic, molecular, and optical,


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particularly cold atoms and optical lattices,


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Fouquet periodically driving, this kind of stuff.


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- Cool, that sounds awesome.


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All right, well, let's talk about this,


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the space of these things, this thing you've created here.


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So what you've created is something called OpenBB,


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which described as the most affordable,


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advanced, open, customizable investment research platform.


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And to me, from the outside,


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not having a ton of experience,


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this looks like maybe a competitor to a Bloomberg terminal,


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which I hear is required basically


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if you're a stock trader, an investor,


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that's doing sort of real-time interaction with the market.


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Yeah, yeah, so, I do have to take a step back as well and say that


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uh, the


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founder of this program, or this project didier


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Um, you know, he's the one with the real insight. I was just lucky enough to join on early


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Um to build a lot of this with him. he spent his christmas, uh coding this and you know


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from there, but but to but to talk a little bit about it, yeah, so the


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I don't like to call us a Bloomberg competitor.


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You know, Bloomberg has been in the game for quite a long time.


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They're very advanced.


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They have all the markets and whatnot.


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Sure.


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But people will say, well, do you have this one feature?


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Well, then we can't.


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You know, I guess it's not like a competitor because it has that other.


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Yeah, sure.


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But from a really high level perspective, it kind of is in that realm, right?


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Right, right, right.


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At a high level, yes.


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We're trying to achieve a lot of the same goals, right?


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Investment research.


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That's free.


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Open source.


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and available to anyone.


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We want to target the people who can't drop 25 grand a year


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for the terminal.


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- Yeah.


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Well, what's interesting to me,


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what struck me about this is it's not just,


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here's an open source version,


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or here's a free version,


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or a cheaper version that would be something of a stand-in


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for that type of thing.


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but here is something that is from the ground up


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embracing all of these data science tools


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and libraries from the Python space.


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So to me, this looks like a completely customizable,


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programmable, extendable thing


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for people who have Python skills.


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And in that way, it's massively better


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than a lot of these commercial projects, right?


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- That's exactly it, right?


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So Bloomberg is the big name in this space.


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You got your icons, your refinitives.


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There's a lot of great other tools.


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You got coinfinmoney.net terminals out there.


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But none of them provide the level of customization


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and open source that we do.


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As you said, it's super Python based.


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The reason we chose Python is that's up and coming.


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Everyone in data science seems to be learning it.


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Finance is very embedded in Excel.


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And there's some shift towards more Python learning


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in the space.


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So doing this in Python, as you said,


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is super customizable.


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You can do it the way, you know,


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you can add on very easily, fork it, add on a feature,


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add on your own datasets, and pretty user-friendly.


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- Yeah, absolutely.


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You know, just to sort of back up what you're saying,


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pre-COVID, I was hired by an investment firm


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to actually spend time with their day traders.


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And it was weird because they're like,


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well, they can't be away from their desk


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when the market is open.


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So this class has to start at 4.30 or 5 p.m.


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and then go for a little afterwards.


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So it was an interesting setup, but it was just that.


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It was a bunch of traders who were using Excel


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to try to figure out how well they were doing.


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And then a couple of people on the team were like,


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we have to learn Python, we have to get better tools.


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So I went and helped them learn Python


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so that they could stop using Excel and start using Python.


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It's absolutely where a lot of this momentum is going.


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- Yeah, and I think that they complement each other


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very well, you know, pandas.


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I don't think anyone can say enough


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about how great pandas is.


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You know, you can enter in all of your,


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whatever your trades are, whatever your research is,


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and it's right in a Jupyter notebook in one line.


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- Yeah, yeah, absolutely.


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Not to say stop using it,


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but there's a ton of stuff happening


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in the financial space around Python.


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And I do believe that Pandas actually came out


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of investment out of Wall Street.


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I'm not 100% sure, but I think that's the history.


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So let's start with open source, right?


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So we could go to the website.


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Your website is openbb.co, fan of the .co.


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We don't need that M.


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But we can go over to GitHub here and there it is.


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we can fork it, do whatever we want.


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Let's see, what is your license?


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It's MIT, which is like go crazy sort of thing, right?


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- Yeah, we're permissive.


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Feel free to do whatever you want with it.


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- Yeah, it's really nice.


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Even commercial uses the MIT license has.


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But what stood out most to me


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when I thought, oh, this is really interesting.


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And then I looked at this, I'm like,


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oh, this actually has a lot of momentum here.


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is you've got 12,000 stars and 1.3 thousand forks, right?


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That's a lot for any project.


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I mean, we're on par with some of the big web frameworks


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not long ago and stuff like that.


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You all must be really happy with the uptake


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that it's getting.


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- Yeah, the community response has been overwhelming.


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When I joined on, it was a couple thousand stars.


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Didier and I, you know, we've fired up Discord.


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We were hitting Reddit with posts weekly, monthly,


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and it took very well.


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People were very excited and we're super thankful


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for the community that's gotten us to where we are.


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- Yeah.


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I guess one thing I would maybe,


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that's not what I was hoping to happen.


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I guess one thing I maybe would like to see possibly,


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I think what would be really fun


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is maybe you could just talk us through


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what the experience of using this is,


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because it's an unusual UI.


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And I don't mean that like, oh, it's weird,


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but it's just, it's not a webpage.


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It's not a Jupyter notebook.


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It's, imagine pretty much exactly opening up iTerm


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or terminal.


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- Yeah, it's a terminal.


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- And it's weird in like, in very much the sense


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that it's as a terminal,


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it means it runs as a Tui,


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a text-based user interface type thing.


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But then as you do reports and interact with it


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through a CLI style or almost of a IPython style experience,


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it pops up windows of really beautiful interactive graphs,


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the various things you're asking for.


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Can you give people a sense of what it's like to use?


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What's the user experience there?


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Yeah, so the terminal is a command line interface tool.


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So you open it, you launch it, python terminal.py,


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and you're presented with a list of choices.


00:12:51.900 --> 00:12:53.140
So we call these contexts.


00:12:53.140 --> 00:12:57.740
That's either going to be your stocks or your crypto ETFs.


00:12:57.740 --> 00:13:01.140
We provide a lot of data.


00:13:01.140 --> 00:13:03.700
And in order to access these, you type in.


00:13:03.700 --> 00:13:05.420
It's one of these old video games


00:13:05.420 --> 00:13:07.620
where you got to type in what you want.


00:13:07.620 --> 00:13:11.160
So if you want to go into stocks, you type in stocks,


00:13:11.160 --> 00:13:13.700
and then you're presented with a new menu.


00:13:13.700 --> 00:13:20.940
So you hit it exactly how it is, that it's completely textual.


00:13:20.940 --> 00:13:24.740
All of our commands have additional options flags


00:13:24.740 --> 00:13:25.500
as well.


00:13:25.500 --> 00:13:27.780
Our documentation for some of these functions


00:13:27.780 --> 00:13:30.540
is listed on our GitHub page.


00:13:30.540 --> 00:13:33.540
We're trying to really enhance the user experience in terms


00:13:33.540 --> 00:13:35.380
of guides and documentation, since we


00:13:35.380 --> 00:13:40.820
do know that this is a very unusual user experience.


00:13:40.820 --> 00:13:42.620
As you said, it's not a website.


00:13:42.620 --> 00:13:44.620
There's nothing to click.


00:13:44.620 --> 00:13:48.180
It's all textual-based, which we understand is going to be--


00:13:48.180 --> 00:13:51.260
not everyone using this product is


00:13:51.260 --> 00:13:55.740
going to be familiar with the command line interface.


00:13:55.740 --> 00:13:58.900
And our team, we actually like to call it hacker man,


00:13:58.900 --> 00:14:03.260
because you feel like you're using it.


00:14:03.260 --> 00:14:07.180
doing your financial research, you feel kind of hackery.


00:14:07.180 --> 00:14:08.020
- Yeah, absolutely.


00:14:08.020 --> 00:14:12.020
You're just, you're typing away stuff is streaming by,


00:14:12.020 --> 00:14:17.020
you know, it's so funny to have normal people


00:14:17.020 --> 00:14:20.960
who are not coders watch people doing stuff with terminals,


00:14:20.960 --> 00:14:22.420
especially if there's colors.


00:14:22.420 --> 00:14:25.460
They think something nefarious is going on


00:14:25.460 --> 00:14:26.980
or something crazy is going on.


00:14:26.980 --> 00:14:29.700
'Cause that's how it's always represented for hackers.


00:14:29.700 --> 00:14:31.760
I remember somebody asked me at a coffee shop,


00:14:31.760 --> 00:14:34.580
I had like five terminal windows all running scripts


00:14:34.580 --> 00:14:35.420
with stuff scrolling by.


00:14:35.420 --> 00:14:36.720
Like, are you trying to hack the coffee shop?


00:14:36.720 --> 00:14:37.680
Like, no, I'm just working.


00:14:37.680 --> 00:14:39.720
Don't interrupt me, please.


00:14:39.720 --> 00:14:42.180
I'm not hacking anyone, leave me alone.


00:14:42.180 --> 00:14:43.600
Yeah, it kind of has that feel, right?


00:14:43.600 --> 00:14:46.640
But it also, something that I think that speaks to


00:14:46.640 --> 00:14:49.320
is like the seriousness and the real,


00:14:49.320 --> 00:14:51.200
like this is for people who are trying to do real work.


00:14:51.200 --> 00:14:52.440
It doesn't come up and just go,


00:14:52.440 --> 00:14:54.460
like here's some buttons you can click and it's flashy.


00:14:54.460 --> 00:14:56.900
It's like, you gotta get in there,


00:14:56.900 --> 00:15:00.560
focus on the various aspects,


00:15:00.560 --> 00:15:03.160
whether you're doing stocks or whatever it is


00:15:03.160 --> 00:15:04.120
and learn the commands,


00:15:04.120 --> 00:15:06.300
but then you should be able to fly through it, right?


00:15:06.300 --> 00:15:07.880
- Yeah, and we actually,


00:15:07.880 --> 00:15:10.200
one of the things that we spent a little bit of time on


00:15:10.200 --> 00:15:12.520
earlier this year was making it


00:15:12.520 --> 00:15:14.800
so that you can actually chain commands, right?


00:15:14.800 --> 00:15:18.140
You can, if you know what your workflow is,


00:15:18.140 --> 00:15:19.800
you can either run it through a script,


00:15:19.800 --> 00:15:23.400
so you can basically go into the terminal,


00:15:23.400 --> 00:15:27.020
set up what we call an OpenBB file.


00:15:27.020 --> 00:15:28.520
You know, every morning what you do,


00:15:28.520 --> 00:15:31.320
you go, you do stocks, you look at, I don't know,


00:15:31.320 --> 00:15:33.400
the top gainers, and then you look at


00:15:33.400 --> 00:15:34.860
what Apple's volume was yesterday.


00:15:34.860 --> 00:15:36.800
You can put this all in a script, run it,


00:15:36.800 --> 00:15:38.660
go fire up your coffee, come back,


00:15:38.660 --> 00:15:40.600
and you've got all your graphs,


00:15:40.600 --> 00:15:42.320
you've got all of your tables,


00:15:42.320 --> 00:15:45.760
and really simplifying the workflow.


00:15:45.760 --> 00:15:46.820
And then when you're done with that,


00:15:46.820 --> 00:15:48.660
if you forgot something in one line,


00:15:48.660 --> 00:15:50.160
you know what it is, you can type in,


00:15:50.160 --> 00:15:52.420
you can do a backslash stocks,


00:15:52.420 --> 00:15:55.280
load in your ticker and whatever you want.


00:15:55.280 --> 00:15:57.840
So as you said, once you know the terminal,


00:15:57.840 --> 00:15:59.620
it's really easy to hop around.


00:15:59.620 --> 00:16:01.860
- Yeah, that's awesome.


00:16:01.860 --> 00:16:05.640
Now, before we talk about some of the features


00:16:05.640 --> 00:16:06.900
and some of the things you can do,


00:16:06.900 --> 00:16:09.380
because I think I'll point people


00:16:09.380 --> 00:16:10.820
to the right part on your website,


00:16:10.820 --> 00:16:13.300
but once you see what you've got here,


00:16:13.300 --> 00:16:16.260
it's like, wow, this has a bunch


00:16:16.260 --> 00:16:18.420
of great visualizations and so on.


00:16:18.420 --> 00:16:22.500
But let's just talk about some of the Python libraries


00:16:22.500 --> 00:16:23.500
that are available.


00:16:23.500 --> 00:16:25.020
It sounds like a lot of the big hitters


00:16:25.020 --> 00:16:29.660
from the data science and machine learning space are there?


00:16:29.660 --> 00:16:31.260
- Very much so, right?


00:16:31.260 --> 00:16:35.180
So the number one library we pretty much use


00:16:35.180 --> 00:16:36.940
is gonna be requests.


00:16:36.940 --> 00:16:39.220
You know, we're hitting APIs,


00:16:39.220 --> 00:16:40.940
turning those into data frames,


00:16:40.940 --> 00:16:45.300
you know, reading HTMLs, displaying.


00:16:45.300 --> 00:16:46.140
Yeah, so.


00:16:46.140 --> 00:16:47.780
- All right, before we move on from requests,


00:16:47.780 --> 00:16:51.660
because a request is a very cool library,


00:16:51.660 --> 00:16:54.180
but it also opens up the question of


00:16:54.180 --> 00:16:55.300
where does requests go?


00:16:55.300 --> 00:16:59.660
Like it looks like there's tons of real-time data here.


00:16:59.660 --> 00:17:01.740
And I know that financial data,


00:17:01.740 --> 00:17:03.140
especially in the real-time variation


00:17:03.140 --> 00:17:05.140
can be tricky to get ahold of,


00:17:05.140 --> 00:17:07.760
or maybe not tricky, but requires money.


00:17:07.760 --> 00:17:09.980
- This is a very good--


00:17:09.980 --> 00:17:12.580
- That's some variant of tricky, isn't it?


00:17:12.580 --> 00:17:15.540
- That is, and actually you do raise a very good point.


00:17:15.540 --> 00:17:20.340
So in the terminal, we do provide different endpoints


00:17:20.340 --> 00:17:23.700
for different sources.


00:17:23.700 --> 00:17:26.100
So for example, if you want to load in stocks,


00:17:26.100 --> 00:17:28.140
you can either go from Yahoo Finance,


00:17:28.140 --> 00:17:29.980
you can go from an Alpha Vantage,


00:17:29.980 --> 00:17:33.300
or you can go from Polygon or IEX Cloud.


00:17:33.300 --> 00:17:37.380
All of these require your own API key.


00:17:37.380 --> 00:17:40.880
So in order to-- part of the onboarding into the terminal


00:17:40.880 --> 00:17:43.820
is to explore all the data sources we have available.


00:17:43.820 --> 00:17:45.580
Go get your API keys.


00:17:45.580 --> 00:17:47.620
And we do have--


00:17:47.620 --> 00:17:50.300
we try to keep it free, but we are


00:17:50.300 --> 00:17:53.340
starting to incorporate some more kind of paid,


00:17:53.340 --> 00:17:56.020
you know, endpoints that can be paid.


00:17:56.020 --> 00:17:56.860
- Right, right.


00:17:56.860 --> 00:17:59.460
So if somebody already has a subscription


00:17:59.460 --> 00:18:01.840
to some data source,


00:18:01.840 --> 00:18:03.660
why not let them integrate that, right?


00:18:03.660 --> 00:18:05.380
- Exactly, that's exactly it.


00:18:05.380 --> 00:18:06.220
- Okay.


00:18:06.220 --> 00:18:07.500
- So we're not, you know,


00:18:07.500 --> 00:18:09.380
we're not distributing any of the data.


00:18:09.380 --> 00:18:11.140
We're just basically providing the tools


00:18:11.140 --> 00:18:12.240
for you to access it.


00:18:12.240 --> 00:18:14.380
- Got it.


00:18:14.380 --> 00:18:16.460
Yeah, that sounds really neat.


00:18:16.460 --> 00:18:19.980
Is there some web scraping, some beautiful soup,


00:18:19.980 --> 00:18:21.780
Or is it all APIs?


00:18:21.780 --> 00:18:26.780
- There is, so we try to keep it to APIs.


00:18:26.780 --> 00:18:28.580
- They're more stable.


00:18:28.580 --> 00:18:31.060
- Yeah, you never know what tag's gonna change.


00:18:31.060 --> 00:18:33.460
But yeah, Beautiful Soup is in there, right?


00:18:33.460 --> 00:18:35.160
Beautiful Soup's a great library.


00:18:35.160 --> 00:18:38.620
There is web scraping, yeah.


00:18:38.620 --> 00:18:40.380
- Yeah, I figured, you know, like,


00:18:40.380 --> 00:18:43.420
sometimes that's just how it works, right?


00:18:43.420 --> 00:18:44.980
Sometimes people don't have APIs,


00:18:44.980 --> 00:18:46.540
but they've got websites, which is kind of--


00:18:46.540 --> 00:18:48.220
- They do. - A cumbersome API


00:18:48.220 --> 00:18:49.660
if you go to it.


00:18:49.660 --> 00:18:51.900
I've also become a fan of pandas.


00:18:51.900 --> 00:18:54.820
Just you can, pandas will do all that for you


00:18:54.820 --> 00:18:57.260
and do the scraping for you with their read HTML


00:18:57.260 --> 00:18:58.780
if you just type in a link.


00:18:58.780 --> 00:19:00.740
- Oh, yeah.


00:19:00.740 --> 00:19:02.700
I was blown away.


00:19:02.700 --> 00:19:06.700
Chris Moffett did a course for TalkBython


00:19:06.700 --> 00:19:10.140
on replacing Excel with pandas and stuff.


00:19:10.140 --> 00:19:12.740
And some of the things you can do


00:19:12.740 --> 00:19:15.340
to get data off the internet with pandas.


00:19:15.340 --> 00:19:17.260
I'm like, why don't I just do this?


00:19:17.260 --> 00:19:18.580
This is so much better.


00:19:18.580 --> 00:19:20.380
you can put it in a webpage that might have


00:19:20.380 --> 00:19:21.780
a whole bunch of text and images


00:19:21.780 --> 00:19:23.540
and somewhere in there is a table,


00:19:23.540 --> 00:19:24.580
could be multiple tables,


00:19:24.580 --> 00:19:25.840
you can say, go to the third table


00:19:25.840 --> 00:19:28.040
and get me that as a data frame and bam.


00:19:28.040 --> 00:19:31.380
Like evil and beautiful soup,


00:19:31.380 --> 00:19:35.140
there's a lot of steps to get to a parsed data frame


00:19:35.140 --> 00:19:36.340
with header values.


00:19:36.340 --> 00:19:41.860
- Yeah, pandas is fantastic and that's a lot of requests,


00:19:41.860 --> 00:19:44.580
a lot of pandas, a lot of soup.


00:19:44.580 --> 00:19:45.420
- Yeah, awesome.


00:19:45.420 --> 00:19:47.780
Okay, so I sort of derailed your conversation


00:19:47.780 --> 00:19:49.900
but one of the things that first came to mind is like,


00:19:49.900 --> 00:19:51.680
okay, this is open source.


00:19:51.680 --> 00:19:54.860
Where is it getting all this interesting data from?


00:19:54.860 --> 00:19:57.780
So thanks for some of the story there.


00:19:57.780 --> 00:19:58.620
What else?


00:19:58.620 --> 00:20:00.740
What other major libraries are at play here?


00:20:00.740 --> 00:20:05.900
- So all of our plotting right now is through PyPlot.


00:20:05.900 --> 00:20:07.860
We have--


00:20:07.860 --> 00:20:08.700
- Okay.


00:20:08.700 --> 00:20:11.100
When people see those, when you're in the terminal


00:20:11.100 --> 00:20:12.980
and you ask for some kind of visualization,


00:20:12.980 --> 00:20:14.620
it pops up with that interactive window.


00:20:14.620 --> 00:20:15.940
Those are PyPlots?


00:20:15.940 --> 00:20:16.780
- Yes.


00:20:16.780 --> 00:20:17.620
- Okay. - So, PyPlots,


00:20:17.620 --> 00:20:19.460
all the styling is done in-house.


00:20:19.460 --> 00:20:22.020
We have a fantastic designer, fantastic engineer,


00:20:22.020 --> 00:20:24.220
did a great job of doing some style sheets.


00:20:24.220 --> 00:20:26.700
- Yeah.


00:20:26.700 --> 00:20:29.880
Yeah, it really does look quite strikingly nice, so.


00:20:29.880 --> 00:20:32.260
Awesome. - Yeah, and all of these


00:20:32.260 --> 00:20:35.220
are, as we like to say, it's customizable.


00:20:35.220 --> 00:20:37.260
All these style sheets are available to the end user.


00:20:37.260 --> 00:20:39.540
They're packaged right into the terminal.


00:20:39.540 --> 00:20:41.420
You can go through, if you don't like our blue,


00:20:41.420 --> 00:20:42.780
you can change that to green.


00:20:42.780 --> 00:20:45.220
- Uh-huh, okay.


00:20:45.220 --> 00:20:46.820
- Yeah, you've got machine learning,


00:20:46.820 --> 00:20:49.880
PyTorch, TensorFlow, SKLearn.


00:20:49.880 --> 00:20:53.520
- So PyTorch is a tricky subject for us


00:20:53.520 --> 00:20:57.460
because it's tough to bundle into an installer.


00:20:57.460 --> 00:21:02.460
Currently we have some Keras models built in.


00:21:02.460 --> 00:21:05.860
You do have to install that, right,


00:21:05.860 --> 00:21:08.080
'cause TensorFlow's a pretty big library.


00:21:08.080 --> 00:21:11.060
We are working on incorporating


00:21:11.060 --> 00:21:12.820
the open source in Dart's library,


00:21:12.820 --> 00:21:14.940
which is PyTorch based.


00:21:14.940 --> 00:21:18.860
And that'll also allow for, you know,


00:21:18.860 --> 00:21:22.260
flares like an example of an NLP model


00:21:22.260 --> 00:21:24.420
that's deep learning based,


00:21:24.420 --> 00:21:26.060
you know, talking about machine learning,


00:21:26.060 --> 00:21:29.280
you know, we do also have NLP models using Vader sentiment.


00:21:29.280 --> 00:21:31.500
- Oh, interesting.


00:21:31.500 --> 00:21:33.940
Because if you could say,


00:21:33.940 --> 00:21:36.540
what is the sentiment on Twitter?


00:21:36.540 --> 00:21:39.940
Or what is it on, you know, the news sites?


00:21:39.940 --> 00:21:42.500
Maybe that's going to affect.


00:21:42.500 --> 00:21:44.380
- Yeah, so that's actually something we had done.


00:21:44.380 --> 00:21:46.360
You can actually try to do some correlation


00:21:46.360 --> 00:21:48.680
with beta sentiment on news headlines


00:21:48.680 --> 00:21:49.800
from one of our data providers,


00:21:49.800 --> 00:21:52.380
and we'll actually throw that on the same chart


00:21:52.380 --> 00:21:55.860
as the price, as the stock price.


00:21:55.860 --> 00:21:57.580
- Yeah, okay.


00:21:57.580 --> 00:21:58.420
Super cool.


00:21:58.420 --> 00:22:01.860
All right, now before I was gonna ask you


00:22:01.860 --> 00:22:03.940
about how to like sort of do your,


00:22:03.940 --> 00:22:05.220
add your own extras to it,


00:22:05.220 --> 00:22:06.660
but let's actually go and just talk about


00:22:06.660 --> 00:22:08.220
some more of the visualizations


00:22:08.220 --> 00:22:09.640
and some of the pictures,


00:22:10.980 --> 00:22:12.220
on the graphs that you guys,


00:22:12.220 --> 00:22:14.140
types of questions you can answer basically.


00:22:14.140 --> 00:22:15.060
Okay. - Yeah, of course.


00:22:15.060 --> 00:22:19.820
- Yeah, so you can get it through a Windows


00:22:19.820 --> 00:22:22.220
or a macOS installer.


00:22:22.220 --> 00:22:26.320
Are you doing something like using Pi to app


00:22:26.320 --> 00:22:29.340
or Pi to EXE or Pi installer or something like that


00:22:29.340 --> 00:22:33.480
to try to bundle all up or is it just sort of a scripted--


00:22:33.480 --> 00:22:35.340
- We bundle with Pi installer.


00:22:35.340 --> 00:22:36.340
- Pi installer, okay.


00:22:36.340 --> 00:22:38.220
- Yes, so we use Pi installer,


00:22:39.500 --> 00:22:41.300
by we, I mean our engineering team.


00:22:41.300 --> 00:22:43.860
That's a little above my ability there.


00:22:43.860 --> 00:22:47.740
And yeah, so we are in the process


00:22:47.740 --> 00:22:51.140
of getting this signed through Apple


00:22:51.140 --> 00:22:52.900
and I believe Windows came through today.


00:22:52.900 --> 00:22:55.220
So at the end of the week--


00:22:55.220 --> 00:22:56.520
- You don't get the yellow,


00:22:56.520 --> 00:22:58.460
do you wanna let this happen?


00:22:58.460 --> 00:23:00.980
You get the just a regular, do you wanna let this happen?


00:23:00.980 --> 00:23:01.820
- Yes.


00:23:01.820 --> 00:23:03.100
- UAC dialogue in Windows


00:23:03.100 --> 00:23:04.900
and you'll get something similar in Mac.


00:23:04.900 --> 00:23:07.000
- Yes, and the reason we have this installer


00:23:07.000 --> 00:23:10.360
is we understand the end user is not necessarily


00:23:10.360 --> 00:23:12.000
gonna be someone that wants to go through


00:23:12.000 --> 00:23:13.660
and change all the Python.


00:23:13.660 --> 00:23:15.800
- Sure, well, it's awesome that it is Python


00:23:15.800 --> 00:23:16.720
and that people could do it,


00:23:16.720 --> 00:23:19.880
but it's certainly not intended just for Python people.


00:23:19.880 --> 00:23:22.440
It's intended for investors who may or may not be.


00:23:22.440 --> 00:23:26.640
- And we have, I don't wanna give an accurate,


00:23:26.640 --> 00:23:29.320
but we've got what, almost 200 dependencies.


00:23:29.320 --> 00:23:33.520
So, and everyone's machine acts differently.


00:23:33.520 --> 00:23:36.600
You do a GIF pull and then you run poetry install,


00:23:36.600 --> 00:23:40.640
Maybe it acts differently on everyone's machine.


00:23:40.640 --> 00:23:43.120
So we wanted to provide this option for folks


00:23:43.120 --> 00:23:46.440
to be able to just click a button and have it right there.


00:23:46.440 --> 00:23:47.520
- Well, I think it's great.


00:23:47.520 --> 00:23:51.520
And that is ideally how software should be delivered.


00:23:51.520 --> 00:23:55.520
You shouldn't have to build it and download all the pieces.


00:23:55.520 --> 00:23:57.160
You just go, here's the thing I click.


00:23:57.160 --> 00:23:58.740
I put it there and now it runs.


00:23:58.740 --> 00:24:01.760
But it's often not how it is distributed.


00:24:01.760 --> 00:24:04.500
I guess just calling out two other ways people get it.


00:24:04.500 --> 00:24:06.980
they can go to Anaconda and get it there.


00:24:06.980 --> 00:24:10.860
And you can also do a Docker type of thing, right?


00:24:10.860 --> 00:24:12.220
If you want, but.


00:24:12.220 --> 00:24:13.660
- Yeah.


00:24:13.660 --> 00:24:14.740
- Yeah, cool.


00:24:14.740 --> 00:24:16.300
- For developers, if you wanna, you know,


00:24:16.300 --> 00:24:19.500
you can do a Git pull with your content environment for Git,


00:24:19.500 --> 00:24:22.060
feel free to change it.


00:24:22.060 --> 00:24:25.420
We're always open to any pull requests.


00:24:25.420 --> 00:24:27.060
- Awesome.


00:24:27.060 --> 00:24:29.460
All right, so let's maybe talk through some of the things


00:24:29.460 --> 00:24:31.180
that I can do, and then we'll talk about


00:24:31.180 --> 00:24:32.500
some of the internals.


00:24:32.500 --> 00:24:36.140
So you mentioned that there's this whole stock section


00:24:36.140 --> 00:24:38.460
and I just totally encourage people to come over


00:24:38.460 --> 00:24:41.540
to openbb.co/products/terminal


00:24:41.540 --> 00:24:42.860
and then you sort of just scroll through here


00:24:42.860 --> 00:24:45.660
and you get a bunch of cool visualizations.


00:24:45.660 --> 00:24:47.860
You'll see why I was impressed, I think.


00:24:47.860 --> 00:24:49.780
So here's like you come up and say,


00:24:49.780 --> 00:24:53.060
I want the Qsum, I guess the cumulative sum


00:24:53.060 --> 00:24:56.500
as a sequential analysis technique


00:24:56.500 --> 00:25:00.060
that shows any sort of cumulative function


00:25:00.060 --> 00:25:03.700
applied to something like a stock price over time or whatever.


00:25:03.700 --> 00:25:05.060
- So this is just an example.


00:25:05.060 --> 00:25:08.940
So if you go into stocks and just for everyone listening,


00:25:08.940 --> 00:25:10.140
we're going through the website right now.


00:25:10.140 --> 00:25:12.780
And the first thing you'll see on our stocks,


00:25:12.780 --> 00:25:15.860
on our product, on our terminal product page under stocks,


00:25:15.860 --> 00:25:16.900
is this QSUM.


00:25:16.900 --> 00:25:19.820
And for example, you would load in whatever your ticker is,


00:25:19.820 --> 00:25:22.180
and this would be found under quantitative analysis.


00:25:22.180 --> 00:25:26.500
So stocks load in Apple, and then you'd type in QA,


00:25:26.500 --> 00:25:27.820
and then you'd have all these options.


00:25:27.820 --> 00:25:29.460
QSUM is one of them.


00:25:29.460 --> 00:25:32.340
And this is a time series, like you said there,


00:25:32.340 --> 00:25:37.340
it's a time series technique of detecting anomalies,


00:25:37.340 --> 00:25:39.500
if you will.


00:25:39.500 --> 00:25:44.420
- Yeah, you got little call outs of those events and so on.


00:25:44.420 --> 00:25:48.420
You've got 3D graphs of volatility surfaces


00:25:48.420 --> 00:25:50.300
for in this case for Apple.


00:25:50.300 --> 00:25:53.860
- Yep, volatility surface, you know, they're big,


00:25:53.860 --> 00:25:56.300
everyone loves their volatility smiles.


00:25:57.180 --> 00:26:02.180
And so, you can show the implied volatility


00:26:02.180 --> 00:26:05.880
as a function of time to expiration and strike price.


00:26:05.880 --> 00:26:09.940
- And I guess because these are, do you say Plotly?


00:26:09.940 --> 00:26:11.100
I'm sorry, I forgot that.


00:26:11.100 --> 00:26:13.940
- So we have some-- - Pipe lots, we said.


00:26:13.940 --> 00:26:15.660
- We use Pipe lot. - Okay.


00:26:15.660 --> 00:26:18.060
- Plotly, I think, so I've kind of,


00:26:18.060 --> 00:26:20.420
early on I did some plots in Plotly


00:26:20.420 --> 00:26:23.460
and there may be some laying around that,


00:26:23.460 --> 00:26:26.820
the interactivity of Plotly is very nice.


00:26:26.820 --> 00:26:28.740
- Right, so what I was gonna say is when these pop up


00:26:28.740 --> 00:26:33.500
with the Piplot stuff, you can basically explore the graphs


00:26:33.500 --> 00:26:36.700
just because it's like the nature of those tools, right?


00:26:36.700 --> 00:26:40.180
- Yeah, Piplot has a, what is it, plt.ion


00:26:40.180 --> 00:26:42.060
that'll allow you to use the interactive.


00:26:42.060 --> 00:26:45.860
So you'll pop up, you'll be able to zoom or pan


00:26:45.860 --> 00:26:48.180
with the usual buttons in the window.


00:26:48.180 --> 00:26:51.740
- Okay, let's, you mentioned the sentiment.


00:26:51.740 --> 00:26:53.660
So there's sentiment news.


00:26:53.660 --> 00:26:56.620
- Instantly correlating article headline sentiment


00:26:56.620 --> 00:27:01.980
through NLP models with historical price.


00:27:01.980 --> 00:27:02.820
Yeah.


00:27:02.820 --> 00:27:05.060
- Yeah, so for this example, yeah.


00:27:05.060 --> 00:27:08.020
This example, this applies a Vader sentiment, right?


00:27:08.020 --> 00:27:11.020
Which is basically just a rules mapping to certain words


00:27:11.020 --> 00:27:12.600
to give you a sentiment score.


00:27:12.600 --> 00:27:16.300
And you can see the stock price on the same chart


00:27:16.300 --> 00:27:18.760
as from the headlines from our given source.


00:27:18.760 --> 00:27:21.220
- Super cool.


00:27:21.220 --> 00:27:22.180
All right, yeah.


00:27:22.180 --> 00:27:25.820
So all these nice different visualizations and so on here,


00:27:25.820 --> 00:27:29.800
maybe talk us through what,


00:27:29.800 --> 00:27:32.320
so to get these cool things generated


00:27:32.320 --> 00:27:34.900
by the Python libraries,


00:27:34.900 --> 00:27:36.940
what is my experience as somebody sitting


00:27:36.940 --> 00:27:37.980
at the terminal CLI?


00:27:37.980 --> 00:27:40.780
Like how do I pull up, say, the sentiment news thing


00:27:40.780 --> 00:27:43.340
or the QSUM or so on?


00:27:43.340 --> 00:27:44.460
- Right.


00:27:44.460 --> 00:27:48.100
So as I mentioned, once you launch the terminal,


00:27:48.100 --> 00:27:51.820
you either use the installer, two clicks and it's up,


00:27:51.820 --> 00:27:55.620
or you run Python terminal.py


00:27:55.620 --> 00:27:57.660
and you're provided with some options.


00:27:57.660 --> 00:28:01.060
The first thing you wanna do, let's say,


00:28:01.060 --> 00:28:03.900
for example, we're doing this QSUM that's up right here.


00:28:03.900 --> 00:28:07.380
You would type into the command line interface,


00:28:07.380 --> 00:28:09.460
you would type in stocks.


00:28:09.460 --> 00:28:11.580
- Okay, yeah, and it kind of puts it into the stocks mode


00:28:11.580 --> 00:28:13.620
where different subcommands apply or something, right?


00:28:13.620 --> 00:28:15.100
- Yep, and then once you have there,


00:28:15.100 --> 00:28:16.420
you'll have a bunch of different menus.


00:28:16.420 --> 00:28:18.100
You can look at fundamental analysis,


00:28:18.100 --> 00:28:19.820
you can look at technical analysis,


00:28:19.820 --> 00:28:21.300
you can do due diligence.


00:28:21.300 --> 00:28:23.380
we've got a bunch of menus on there.


00:28:23.380 --> 00:28:25.300
So you would load in your relevant ticker.


00:28:25.300 --> 00:28:28.480
So you'd either do load Apple,


00:28:28.480 --> 00:28:31.420
or we do have some, if you have the feature flag enabled,


00:28:31.420 --> 00:28:35.620
if you just type in Apple, or A-A-P-L, it'll load in.


00:28:35.620 --> 00:28:39.140
So once you have that ticker loaded in,


00:28:39.140 --> 00:28:41.640
it does a pandas data frame in memory.


00:28:41.640 --> 00:28:47.700
So from there, we can pass it to the different functions.


00:28:48.140 --> 00:28:52.540
And for this particular one, to do the quantitative analysis,


00:28:52.540 --> 00:28:53.980
I would then type in QA.


00:28:53.980 --> 00:28:56.220
So when you're on the Stocks menu,


00:28:56.220 --> 00:28:59.340
you would-- you can type H for help,


00:28:59.340 --> 00:29:02.420
or you can do a question mark, and it'll parse that.


00:29:02.420 --> 00:29:04.580
And you'd see QA, quantitative analysis,


00:29:04.580 --> 00:29:06.940
with a couple of examples of what you can do there.


00:29:06.940 --> 00:29:09.460
And then once you go into that menu,


00:29:09.460 --> 00:29:11.980
it would pop up with different functions.


00:29:11.980 --> 00:29:14.220
And you would type in the function you want.


00:29:14.220 --> 00:29:16.340
If there's arguments, maybe there's


00:29:16.340 --> 00:29:26.740
Windows or exporting data, you would just type in -help and you'll get a pop-up of the


00:29:26.740 --> 00:29:29.660
usage and the optional arguments.


00:29:29.660 --> 00:29:33.940
And you would type in QSUM with whatever your arguments are and you would get this plot.


00:29:33.940 --> 00:29:34.940
Nice.


00:29:34.940 --> 00:29:35.940
All right.


00:29:35.940 --> 00:29:38.460
That's very cool to hear how that sort of flows through there.


00:29:38.460 --> 00:29:39.460
All right.


00:29:39.460 --> 00:29:40.460
What else?


00:29:40.460 --> 00:29:44.620
Got a bunch of stuff on crypto, like you've got Bitcoin rainbow charts, which I've never


00:29:44.620 --> 00:29:45.620
seen but...


00:29:45.620 --> 00:29:46.460
- That's fun.


00:29:46.460 --> 00:29:47.280
- Interesting.


00:29:47.280 --> 00:29:52.280
Yeah, just a bunch of open interest by exchange,


00:29:52.280 --> 00:29:56.140
different exchanges, how much traffic there is,


00:29:56.140 --> 00:29:56.980
things like that.


00:29:56.980 --> 00:29:57.800
It's pretty awesome.


00:29:57.800 --> 00:30:00.040
The ETFs, let's see.


00:30:00.040 --> 00:30:03.660
Some of these are coming up as just almost like,


00:30:03.660 --> 00:30:07.180
some of them even come up almost like a report.


00:30:07.180 --> 00:30:09.220
You've got an Excel report and you've got,


00:30:09.220 --> 00:30:11.380
- Yeah, so actually the ETFs.


00:30:11.380 --> 00:30:13.380
- It's like a train station looking,


00:30:13.380 --> 00:30:15.900
Like here's the incoming information or whatever, right?


00:30:15.900 --> 00:30:18.160
- Yeah, and actually, 'cause for example,


00:30:18.160 --> 00:30:23.160
this ETF Excel report is a third party or third,


00:30:23.160 --> 00:30:29.420
so one of our contributors has their own database.


00:30:29.420 --> 00:30:32.580
It's the author of the finance database


00:30:32.580 --> 00:30:34.440
and he has this workbook.


00:30:34.440 --> 00:30:36.420
It loads in an ETF and it basically does


00:30:36.420 --> 00:30:38.080
what you see on the screen there.


00:30:38.080 --> 00:30:41.540
And it pops up in an Excel.


00:30:41.540 --> 00:30:45.380
- Yeah, it pops this up in an Excel workbook.


00:30:45.380 --> 00:30:47.940
We do have another feature that's DCF.


00:30:47.940 --> 00:30:51.660
Someone who was working on their MBA at the time said,


00:30:51.660 --> 00:30:53.020
"Hey, you guys provide the data.


00:30:53.020 --> 00:30:57.060
"I need to do a DCF analysis."


00:30:57.060 --> 00:31:01.500
And so we coded it up, and now we have a DCF analysis tool


00:31:01.500 --> 00:31:04.460
that uses some linear regression in the terminal,


00:31:04.460 --> 00:31:06.140
and it all saves to an Excel file.


00:31:06.140 --> 00:31:07.860
- That's cool.


00:31:07.860 --> 00:31:08.940
And the fact that it goes out to Excel,


00:31:08.940 --> 00:31:10.460
that means you could hand it off to somebody


00:31:10.460 --> 00:31:15.160
who just lives in Excel and they can still use that, right?


00:31:15.160 --> 00:31:16.100
- Exactly.


00:31:16.100 --> 00:31:18.460
So, you know, we don't want to completely replace Excel


00:31:18.460 --> 00:31:22.760
because we know it's very widely used, but.


00:31:22.760 --> 00:31:25.680
- Yeah, but hook into all these different data sources,


00:31:25.680 --> 00:31:27.780
real-time data sources and pulling it together,


00:31:27.780 --> 00:31:30.220
like that's not Excel's forte.


00:31:30.220 --> 00:31:31.780
- Yeah, yeah, that's why.


00:31:31.780 --> 00:31:36.660
- That's why I should be doing it for everything.


00:31:36.660 --> 00:31:39.920
- Yeah, okay, so you've got sort of


00:31:39.920 --> 00:31:41.340
technical analysis stuff,


00:31:41.340 --> 00:31:43.520
you can compare different stocks


00:31:43.520 --> 00:31:46.880
and even check out the news over for the ETF.


00:31:46.880 --> 00:31:50.440
- Yeah, we do have over, well, I don't wanna say over,


00:31:50.440 --> 00:31:53.260
we're sitting around 700 different functionalities.


00:31:53.260 --> 00:31:56.880
So we do understand it can be slightly


00:31:56.880 --> 00:31:59.620
intimidating at first.


00:31:59.620 --> 00:32:02.080
- Yeah, that was my feeling as well


00:32:02.080 --> 00:32:04.000
when I first saw this is like, wow,


00:32:04.000 --> 00:32:06.120
this is pretty intense.


00:32:06.120 --> 00:32:07.120
There's a lot going on.


00:32:07.120 --> 00:32:10.920
You have to be an expert, which is what I was talking about at the beginning.


00:32:10.920 --> 00:32:15.880
You get into the terminal and you've got to really become an expert, but then you get


00:32:15.880 --> 00:32:18.800
this really great quick power to do it.


00:32:18.800 --> 00:32:25.720
But I would also imagine you're probably not doing stocks, crypto, ETF, economic analysis,


00:32:25.720 --> 00:32:26.720
all the same.


00:32:26.720 --> 00:32:29.800
You're probably focused on one of these areas, right?


00:32:29.800 --> 00:32:35.720
If you narrow it down, it probably gets more doable as you go.


00:32:35.720 --> 00:32:39.880
And I mean, you know, maybe you're trying, one of the things, for example, we have this


00:32:39.880 --> 00:32:46.440
econometrics menu, which, you know, one of our target audiences is kind of the academics


00:32:46.440 --> 00:32:49.680
and in your econometrics course, right?


00:32:49.680 --> 00:32:52.960
That's basically a linear regression of certain things.


00:32:52.960 --> 00:33:01.320
So maybe you want to look at the effect of a company's balance sheet on and relate that


00:33:01.320 --> 00:33:04.500
to inflation, I don't know, inflation is a hot topic.


00:33:04.500 --> 00:33:07.460
And you can actually go in into the econometrics menu,


00:33:07.460 --> 00:33:12.060
load in both of these and do your preferred


00:33:12.060 --> 00:33:15.340
regression techniques and get some insights.


00:33:15.340 --> 00:33:17.500
- Oh, that's cool.


00:33:17.500 --> 00:33:19.700
You know, thinking about education,


00:33:19.700 --> 00:33:22.340
that's a big opportunity for you all, right?


00:33:22.340 --> 00:33:23.180
- It is.


00:33:23.180 --> 00:33:28.220
- People, students are gonna be buying Bloomberg terminals


00:33:28.220 --> 00:33:31.360
and other commercial things most likely, right?


00:33:31.360 --> 00:33:33.020
Not the high-end ones anyway.


00:33:33.020 --> 00:33:33.860
- Yeah.


00:33:33.860 --> 00:33:37.140
Here's a really simple way that you could actually,


00:33:37.140 --> 00:33:40.360
if you're a teacher teaching economics


00:33:40.360 --> 00:33:42.360
or finance or investing,


00:33:42.360 --> 00:33:44.620
here's something you could bring into your class


00:33:44.620 --> 00:33:49.100
as a resource and really analyze it, right?


00:33:49.100 --> 00:33:51.340
When your projects could be, okay, pick a stock.


00:33:51.340 --> 00:33:52.600
These are the questions we have,


00:33:52.600 --> 00:33:54.300
back it up with the other data that you can find


00:33:54.300 --> 00:33:57.020
through these other areas and make predictions, right?


00:33:57.020 --> 00:33:59.060
- Exactly, that's one thing we love.


00:34:00.420 --> 00:34:06.580
some of our some of the people we talk with their experiences for their courses, they have they have


00:34:06.580 --> 00:34:10.980
assignments that they need to do use the one Bloomberg terminal that they have among 30


00:34:10.980 --> 00:34:16.500
students. So they're queued up for, you know, an hour or two, just just to get basically the same


00:34:16.500 --> 00:34:23.860
data, if you will. And, you know, we, that's one of the things we pain points we'd like to address


00:34:23.860 --> 00:34:27.780
is everyone can have this on their machine and get the data they need and do the analysis they want


00:34:27.780 --> 00:34:32.540
- Sure, I don't think it would be a very detailed thing,


00:34:32.540 --> 00:34:36.020
but it would be also interesting that the professor


00:34:36.020 --> 00:34:39.620
or the instructor could say, look here in the source code,


00:34:39.620 --> 00:34:42.540
these four lines of code, this is showing,


00:34:42.540 --> 00:34:44.780
this is where it's doing that theory


00:34:44.780 --> 00:34:45.880
we talked about last week.


00:34:45.880 --> 00:34:48.540
Like here's how it's applying this model.


00:34:48.540 --> 00:34:50.940
And I don't expect you to totally understand the code,


00:34:50.940 --> 00:34:54.140
but like you can see this is how software does it.


00:34:54.140 --> 00:34:55.780
You know, you could have a little bit more insight,


00:34:55.780 --> 00:34:57.380
whereas a lot of the commercial things,


00:34:57.380 --> 00:34:58.980
through a website for sure.


00:34:58.980 --> 00:35:01.520
But even if they're just compiled closed source,


00:35:01.520 --> 00:35:02.360
- Yeah.


00:35:02.360 --> 00:35:03.560
- You won't be able to do that.


00:35:03.560 --> 00:35:06.020
- We had a contributor reach out to us,


00:35:06.020 --> 00:35:07.420
part of the from Greece,


00:35:07.420 --> 00:35:10.820
part of their software business course


00:35:10.820 --> 00:35:13.000
was to submit a pull request somewhere.


00:35:13.000 --> 00:35:14.420
So he reached out to us,


00:35:14.420 --> 00:35:16.600
he did a nice little report.


00:35:16.600 --> 00:35:17.560
He did a pull request,


00:35:17.560 --> 00:35:19.620
added a feature to the terminal.


00:35:19.620 --> 00:35:21.700
So you know, using the theory in class there.


00:35:21.700 --> 00:35:24.460
Another professor reached out to us,


00:35:24.460 --> 00:35:27.620
he had his students write a kind of an intro guide


00:35:27.620 --> 00:35:30.420
for us that we're kind of working with


00:35:30.420 --> 00:35:32.820
and we're gonna make available.


00:35:32.820 --> 00:35:33.780
- Okay, awesome.


00:35:33.780 --> 00:35:36.260
Yeah, the intro guide for OpenBB for his students


00:35:36.260 --> 00:35:38.300
or something like that, yeah.


00:35:38.300 --> 00:35:39.140
- Yeah.


00:35:39.140 --> 00:35:40.180
- Yeah, nice.


00:35:40.180 --> 00:35:41.540
All right, let me just sort of skim through here.


00:35:41.540 --> 00:35:45.140
There's a, you said 700 people.


00:35:45.140 --> 00:35:47.060
I'm not so sure I wanna touch on all of them,


00:35:47.060 --> 00:35:49.300
but every single one of them you come to,


00:35:49.300 --> 00:35:51.220
almost like some of them are just sort of tables,


00:35:51.220 --> 00:35:56.040
But so many of them, like this portfolio optimization,


00:35:56.040 --> 00:35:59.100
you know, it's beautiful, it looks really good.


00:35:59.100 --> 00:36:00.140
And--


00:36:00.140 --> 00:36:03.540
- Thanks, we have a lot and the pipeline's really good.


00:36:03.540 --> 00:36:05.180
The rainbow chart's always a fun one.


00:36:05.180 --> 00:36:06.940
It's, you know, it's really pretty.


00:36:06.940 --> 00:36:10.540
- Yeah, I like it a lot.


00:36:10.540 --> 00:36:11.580
These are great.


00:36:11.580 --> 00:36:13.940
So I just, to me, it feels like something


00:36:13.940 --> 00:36:17.300
if I were working, doing this kind of stuff,


00:36:17.300 --> 00:36:19.380
it would be pleasing to sit down


00:36:19.380 --> 00:36:22.700
and look at these graphs and this analysis rather than,


00:36:22.700 --> 00:36:24.500
oh, well, there's just some software you look at,


00:36:24.500 --> 00:36:28.260
like it does the job, but it doesn't make you feel good


00:36:28.260 --> 00:36:29.960
using it while it's doing the job.


00:36:29.960 --> 00:36:31.740
- Yeah.


00:36:31.740 --> 00:36:33.380
- Battleship gray or I don't know, something like that.


00:36:33.380 --> 00:36:35.780
- And also, like I mentioned too,


00:36:35.780 --> 00:36:37.060
you can customize the colors,


00:36:37.060 --> 00:36:40.320
even if you wanna change the terminal colors.


00:36:40.320 --> 00:36:43.780
When you launch our terminal,


00:36:43.780 --> 00:36:46.500
you'll see some blues and reds.


00:36:46.500 --> 00:36:48.980
If you want it to be orange and green,


00:36:48.980 --> 00:36:51.620
you can go in and change it, it's fully customizable.


00:36:51.620 --> 00:36:55.900
- Cool.


00:36:55.900 --> 00:36:59.580
So there's a Jupyter section as well.


00:36:59.580 --> 00:37:00.420
- There is?


00:37:00.420 --> 00:37:01.700
- Yeah, tell us about the Jupyter section.


00:37:01.700 --> 00:37:05.180
I think that's a super big tie-in for iGN people.


00:37:05.180 --> 00:37:08.980
- Yeah, so there's two ways you can really


00:37:08.980 --> 00:37:11.160
make the most out of Jupyter.


00:37:11.160 --> 00:37:13.420
The first way is we've started kind of building


00:37:13.420 --> 00:37:17.020
an API wrapper for a lot of our functions.


00:37:17.020 --> 00:37:20.300
So one thing we haven't gone into is a little bit the architecture.


00:37:20.300 --> 00:37:24.560
And we use like an MVC model view controller


00:37:24.560 --> 00:37:27.060
where all these plots are generated in the view,


00:37:27.060 --> 00:37:30.060
and we can wrap that into an API and you can import that.


00:37:30.060 --> 00:37:36.100
So in Jupyter, if your workflow is X, Y, and Z,


00:37:36.100 --> 00:37:39.820
in the terminal, you can, from OpenBB terminal,


00:37:39.820 --> 00:37:42.940
import the API as whatever, as OpenBB.


00:37:42.940 --> 00:37:47.940
OpenBB, Vue, Vue Stock, Apple, whatever,


00:37:47.940 --> 00:37:49.240
however that works.


00:37:49.240 --> 00:37:51.380
And you can create your workflows there.


00:37:51.380 --> 00:37:52.220
One other--


00:37:52.220 --> 00:37:54.900
- You get a plot back and you just plot.show


00:37:54.900 --> 00:37:58.500
or just like empty one line and it goes on there, yeah?


00:37:58.500 --> 00:37:59.800
- Yeah, I mean, you do an inline,


00:37:59.800 --> 00:38:02.080
you can also do, you can adjust it, right?


00:38:02.080 --> 00:38:05.800
So we'll wrap, the API wraps our load function.


00:38:05.800 --> 00:38:08.540
So you can load in your stock and, you know,


00:38:08.540 --> 00:38:10.060
maybe you want to resample it


00:38:10.060 --> 00:38:12.200
or maybe you want to make your own machine learning model


00:38:12.200 --> 00:38:16.120
or whatever you want to do, you can do that with the API.


00:38:16.120 --> 00:38:19.360
Another interesting thing is that we use Paper Mill


00:38:19.360 --> 00:38:22.320
to automatically run some reports.


00:38:22.320 --> 00:38:26.840
So the example in the terminal,


00:38:26.840 --> 00:38:31.840
there's a default example called equity.ipy notebook.


00:38:31.840 --> 00:38:36.400
And if you go into the terminal,


00:38:36.400 --> 00:38:38.920
so once it launches, you go to the reports menu,


00:38:38.920 --> 00:38:40.400
just by typing reports,


00:38:40.400 --> 00:38:44.320
you type in equity, Apple, or whatever your ticker is,


00:38:44.320 --> 00:38:46.080
it'll run through paper mill,


00:38:46.080 --> 00:38:49.320
which automatically fills in your ticker,


00:38:49.320 --> 00:38:54.320
whatnot generates a predefined PDF basically


00:38:54.320 --> 00:38:56.520
with it's fully customizable.


00:38:56.520 --> 00:39:00.540
We have some fun widgets that you can play around with.


00:39:00.540 --> 00:39:02.360
And you can add KPIs.


00:39:02.360 --> 00:39:05.960
Hey, if, I don't know, if the RSI is high


00:39:05.960 --> 00:39:07.720
or if insider trading is low,


00:39:07.720 --> 00:39:09.640
I think those are some of the examples.


00:39:09.640 --> 00:39:13.280
So you can create your own custom notebooks


00:39:13.280 --> 00:39:16.920
and kind of automate your research workflow.


00:39:16.920 --> 00:39:21.480
- That's, yeah, that's super interesting.


00:39:21.480 --> 00:39:24.480
I haven't spoken about Paper Mill for a while in here,


00:39:24.480 --> 00:39:26.840
but it's a really interesting project,


00:39:26.840 --> 00:39:29.680
I think from the Netflix team, right?


00:39:29.680 --> 00:39:30.640
- I have no idea.


00:39:30.640 --> 00:39:32.700
- Yeah, I think so.


00:39:32.700 --> 00:39:34.480
Maybe tell people just a bit about


00:39:36.880 --> 00:39:40.260
about what the whole purpose of paper millage, what it is.


00:39:40.260 --> 00:39:45.760
- So, what we use paper mill for


00:39:45.760 --> 00:39:47.960
is to basically just automatically


00:39:47.960 --> 00:39:50.000
execute a notebook template.


00:39:50.000 --> 00:39:52.600
So there's, you kind of have to go a little bit


00:39:52.600 --> 00:39:54.840
into the metadata of the Jupyter notebook


00:39:54.840 --> 00:39:58.120
and there's a cell that has like parameters


00:39:58.120 --> 00:40:02.200
and by the terminal, we can parse what the argument is.


00:40:02.200 --> 00:40:05.540
You know, for example, the ticker.


00:40:05.540 --> 00:40:10.540
And basically all the same commands will be run


00:40:10.540 --> 00:40:14.940
just replacing the ticker with whatever is executed.


00:40:14.940 --> 00:40:17.240
So paper mill is just a really nice,


00:40:17.240 --> 00:40:21.140
very, very great tool at wrapping Jupyter.


00:40:21.140 --> 00:40:23.540
- It turns notebooks almost into functions


00:40:23.540 --> 00:40:26.160
that you can call, but the output is the notebook


00:40:26.160 --> 00:40:29.300
in the form that has the results,


00:40:29.300 --> 00:40:31.220
the intermediate results and the pictures and everything,


00:40:31.220 --> 00:40:34.100
not just the answer like a function would have.


00:40:34.100 --> 00:40:35.260
- Yep, you get the whole notebook


00:40:35.260 --> 00:40:38.340
and you know you can customize it, PDF, HTML,


00:40:38.340 --> 00:40:39.860
you can send it to your buddies.


00:40:39.860 --> 00:40:42.580
- Yeah, well, you touched on the architecture a bit.


00:40:42.580 --> 00:40:45.820
Maybe we could dive into that just a little bit more.


00:40:45.820 --> 00:40:48.660
What are some of the notable things about how this is built?


00:40:48.660 --> 00:40:52.140
- Yeah, so as I kind of hinted at,


00:40:52.140 --> 00:40:53.940
actually specifically said,


00:40:53.940 --> 00:40:56.740
our code is, we use an MVC structure,


00:40:56.740 --> 00:40:58.300
so Model View Controller.


00:40:58.300 --> 00:41:03.620
So how this goes, and for example,


00:41:03.620 --> 00:41:08.060
every submenu will have a controller,


00:41:08.060 --> 00:41:10.900
and we have abstracted that,


00:41:10.900 --> 00:41:12.540
so that there's a base controller


00:41:12.540 --> 00:41:13.900
and a base docs controller


00:41:13.900 --> 00:41:15.920
that inherit all the same methods,


00:41:15.920 --> 00:41:19.140
save ourselves a little bit of redundancy.


00:41:19.140 --> 00:41:23.020
- So there's controllers like parsing and processing


00:41:23.020 --> 00:41:25.780
the commands you send in the terminal CLI.


00:41:25.780 --> 00:41:29.940
- Yes, so something I failed to mention


00:41:29.940 --> 00:41:31.700
was that we use arg parse.


00:41:31.700 --> 00:41:32.580
- Yeah.


00:41:32.580 --> 00:41:36.100
So the controller wraps in, it basically takes in,


00:41:36.100 --> 00:41:41.460
it creates an argparse object, adds the arguments,


00:41:41.460 --> 00:41:45.100
and then does the parsing, makes sure that if I type in,


00:41:45.100 --> 00:41:48.060
if I try to load a stock ticker that's four,


00:41:48.060 --> 00:41:51.220
not an actual ticker, if I try to enter a number,


00:41:51.220 --> 00:41:53.220
it'll say, "Hey, you need to be a ticker,"


00:41:53.220 --> 00:41:55.220
it does some of the logic.


00:41:55.220 --> 00:41:58.220
Our model functions get the data,


00:41:58.540 --> 00:42:02.800
transfer the data, edit the data,


00:42:02.800 --> 00:42:05.200
modify it, manipulate it in certain ways.


00:42:05.200 --> 00:42:09.960
And then the views do either tables, graphs.


00:42:09.960 --> 00:42:12.580
So, for example, if you wanted,


00:42:12.580 --> 00:42:15.840
if you look at how we do our fundamental analysis,


00:42:15.840 --> 00:42:19.480
the workflow is the controller has income


00:42:19.480 --> 00:42:23.480
and the way we do it, the function is called callIncome.


00:42:23.480 --> 00:42:25.640
We just kind of add this call underscore


00:42:25.640 --> 00:42:27.720
to whatever you type into the terminal


00:42:27.720 --> 00:42:30.720
And callIncome is a method of the controller.


00:42:30.720 --> 00:42:34.480
So that'll, you can add the arguments.


00:42:34.480 --> 00:42:38.040
And for example, the income statement has an argument


00:42:38.040 --> 00:42:41.620
that's -L, that tells you how many quarters you want to get.


00:42:41.620 --> 00:42:46.080
So the namespace, the namespace,


00:42:46.080 --> 00:42:50.360
so the parser, the argparse namespace


00:42:50.360 --> 00:42:53.260
then has the information stored.


00:42:53.260 --> 00:42:56.560
So we know, hey, we're trying to get income


00:42:56.560 --> 00:42:58.360
and we're trying to get five quarters.


00:42:58.360 --> 00:43:02.860
So that will call, it'll call the view,


00:43:02.860 --> 00:43:04.660
which will then pass in, you know,


00:43:04.660 --> 00:43:09.240
the view will say, hey, alpha vantage model,


00:43:09.240 --> 00:43:13.780
get me my five quarters of Apple income statements,


00:43:13.780 --> 00:43:15.880
and that'll return it as a data frame.


00:43:15.880 --> 00:43:17.520
And, you know, either,


00:43:17.520 --> 00:43:19.420
I guess that function doesn't have a graph,


00:43:19.420 --> 00:43:20.800
but if it's a graphing function,


00:43:20.800 --> 00:43:22.640
it would do the graph.


00:43:22.640 --> 00:43:25.140
- Call graph, pops up the window in the pipelot window.


00:43:25.140 --> 00:43:27.260
and then off it goes.


00:43:27.260 --> 00:43:28.100
That's really interesting.


00:43:28.100 --> 00:43:30.660
I have never really thought about


00:43:30.660 --> 00:43:35.660
how you might do the processing of CLI commands,


00:43:35.660 --> 00:43:37.340
but within an application.


00:43:37.340 --> 00:43:39.740
When I think arg pars, I think startup.


00:43:39.740 --> 00:43:42.780
Like what commands are passed to my application


00:43:42.780 --> 00:43:44.100
during startup to figure it out?


00:43:44.100 --> 00:43:48.220
But of course, as you continue to issue commands,


00:43:48.220 --> 00:43:50.140
if that's text on a line,


00:43:50.140 --> 00:43:53.100
it makes sense to sort of treat it the same, right?


00:43:53.100 --> 00:43:55.380
- Yeah, and while we actually do on startup


00:43:55.380 --> 00:43:56.820
actually do have our parts.


00:43:56.820 --> 00:44:01.820
So you can, for example, my favorite flag


00:44:01.820 --> 00:44:04.540
that we have for the terminal is debug.


00:44:04.540 --> 00:44:05.900
That way you can actually get a full


00:44:05.900 --> 00:44:07.880
instead of catching all the errors, right?


00:44:07.880 --> 00:44:09.660
'Cause if we're not catching all the errors


00:44:09.660 --> 00:44:12.180
in the terminal, it would crash every time


00:44:12.180 --> 00:44:13.980
you had an exception or whatnot.


00:44:13.980 --> 00:44:15.700
But with this debug flag,


00:44:15.700 --> 00:44:18.500
it'll actually show you the full stack trace


00:44:18.500 --> 00:44:20.720
and just instead of just the exception.


00:44:20.720 --> 00:44:23.520
So we actually do wrap around the startup and whatnot.


00:44:23.520 --> 00:44:27.680
And we also do like, we have a reset command


00:44:27.680 --> 00:44:30.800
that if you're in the terminal, you type in reset,


00:44:30.800 --> 00:44:33.680
maybe you changed an API key or you're developing


00:44:33.680 --> 00:44:36.200
and you change your function, you need to reload it.


00:44:36.200 --> 00:44:39.480
You hit reset, it'll relaunch the terminal,


00:44:39.480 --> 00:44:40.560
exit then relaunch.


00:44:40.560 --> 00:44:44.480
So that's the general workflow.


00:44:44.480 --> 00:44:47.560
- Yeah, does the terminal run in whatever terminal


00:44:47.560 --> 00:44:49.040
of your OS?


00:44:49.040 --> 00:44:52.000
Like if I have iTerm set up on my Mac,


00:44:52.000 --> 00:44:52.840
it'll run there.


00:44:52.840 --> 00:44:54.240
If I have Windows Terminal and PowerShell,


00:44:54.240 --> 00:44:55.440
it'll run over there.


00:44:55.440 --> 00:44:58.800
- Yeah, just make sure you're in the right directory.


00:44:58.800 --> 00:45:00.580
- Yeah, okay, fantastic.


00:45:00.580 --> 00:45:04.600
Yeah, super, super interesting.


00:45:04.600 --> 00:45:06.600
Let's see, what did I wanna ask you about here?


00:45:06.600 --> 00:45:08.620
One other thing I'm trying to remember.


00:45:08.620 --> 00:45:12.160
It's gone, it's lost.


00:45:12.160 --> 00:45:14.200
I wanted to follow up with something, but that's okay.


00:45:14.200 --> 00:45:17.680
- Well, I can also, I can even add a statement


00:45:17.680 --> 00:45:22.440
that doing this MVC allows us to have different views.


00:45:22.440 --> 00:45:24.120
I know one thing you'll probably ask me about


00:45:24.120 --> 00:45:29.120
is that we have these bots on our website and the ideas.


00:45:29.120 --> 00:45:31.480
- Yeah, I did notice over here that you have a products,


00:45:31.480 --> 00:45:33.120
you got a terminal and then documentation


00:45:33.120 --> 00:45:35.280
and then you have bots.


00:45:35.280 --> 00:45:36.320
Yeah, coming soon bots.


00:45:36.320 --> 00:45:37.960
I do remember now what I would ask you,


00:45:37.960 --> 00:45:39.520
but let's talk bots for a second.


00:45:39.520 --> 00:45:40.880
- Yeah. - Come back to it.


00:45:40.880 --> 00:45:45.220
- So bots, I don't wanna give away,


00:45:45.220 --> 00:45:48.600
we do have some exciting announcement coming soon.


00:45:48.600 --> 00:45:50.640
And I would like to take this opportunity


00:45:50.640 --> 00:45:52.840
to apologize to anyone that's trying to get this,


00:45:52.840 --> 00:45:54.520
get the Discord bot in our server


00:45:54.520 --> 00:45:58.200
as we're currently limited to the maximum 100 servers


00:45:58.200 --> 00:46:00.360
we can be in without the verification


00:46:00.360 --> 00:46:01.440
that we're working on.


00:46:01.440 --> 00:46:03.520
- Got it.


00:46:03.520 --> 00:46:04.960
So under the listing here,


00:46:04.960 --> 00:46:08.760
you have bots coming for Discord, Telegram, Slack, and more.


00:46:08.760 --> 00:46:11.280
And yeah, I guess news is coming, huh?


00:46:11.280 --> 00:46:12.800
- Yeah, and all of this,


00:46:12.800 --> 00:46:17.440
one of the kind of using MVC, we're able to extract,


00:46:17.440 --> 00:46:21.680
extract, abstract all of our methods


00:46:21.680 --> 00:46:24.200
and then we can just, we do all the processing


00:46:24.200 --> 00:46:25.560
on the same model function


00:46:25.560 --> 00:46:27.320
and then we can pass it to different views


00:46:27.320 --> 00:46:29.560
for Discord or Telegram or Slack.


00:46:29.560 --> 00:46:32.640
- Nice, yeah, I'm sure, or comment as much as you can,


00:46:32.640 --> 00:46:36.800
but you can build a Slack bot in Flask, for example,


00:46:36.800 --> 00:46:37.840
or something like that, right,


00:46:37.840 --> 00:46:39.880
where it kind of uses a web communication


00:46:39.880 --> 00:46:41.760
to talk to your bot.


00:46:41.760 --> 00:46:44.020
And so I guess you could do things like go into Slack


00:46:44.020 --> 00:46:46.700
and say, "Hey, OpenBB bot,


00:46:46.700 --> 00:46:51.500
"tell me about important events in stock


00:46:51.500 --> 00:46:52.980
"or I've been watching this thing.


00:46:52.980 --> 00:46:54.420
"If it crosses the threshold,


00:46:54.420 --> 00:46:56.020
"just yell at me about it, right?


00:46:56.020 --> 00:46:56.860
"Let me know."


00:46:56.860 --> 00:46:57.680
Something like that.


00:46:57.680 --> 00:46:58.860
Is that kind of the flow?


00:46:58.860 --> 00:46:59.840
- Pretty much.


00:46:59.840 --> 00:47:01.860
Yeah, just some async stuff.


00:47:01.860 --> 00:47:03.660
It's running on a server somewhere


00:47:03.660 --> 00:47:06.360
and it waits to read in the command.


00:47:06.360 --> 00:47:08.940
So. - Cool.


00:47:08.940 --> 00:47:10.780
One other question I wanted to ask you


00:47:10.780 --> 00:47:15.460
Is what I've seen so far looks like really cool ways to,


00:47:15.460 --> 00:47:19.480
all of it's static, so you can only read so much into it,


00:47:19.480 --> 00:47:22.260
but it looks like, let me answer a question


00:47:22.260 --> 00:47:25.020
about this information, either historical


00:47:25.020 --> 00:47:27.580
or sort of up to now about some stock


00:47:27.580 --> 00:47:29.260
or the economy or whatever.


00:47:29.260 --> 00:47:31.660
Is there a way to have like a dashboard


00:47:31.660 --> 00:47:32.700
where I can put different things up


00:47:32.700 --> 00:47:35.940
and they're just constantly churning with real data?


00:47:39.100 --> 00:47:40.980
- That is possible, yes.


00:47:40.980 --> 00:47:48.120
- Not to make a case, but possible.


00:47:48.120 --> 00:47:53.140
- I mean, it is possible and I'll leave it at that,


00:47:53.140 --> 00:47:54.460
that it is possible.


00:47:54.460 --> 00:47:55.660
- All right, sounds good.


00:47:55.660 --> 00:47:58.580
That was the one I was asking about.


00:47:58.580 --> 00:48:02.740
All right, now one thing I wanna touch on here


00:48:02.740 --> 00:48:06.140
before we get too far away with time


00:48:07.300 --> 00:48:10.220
is two things stood out to me when I went


00:48:10.220 --> 00:48:12.100
and sort of clicked around your site.


00:48:12.100 --> 00:48:13.060
Now that's pretty interesting.


00:48:13.060 --> 00:48:15.540
I can't remember, you know, some news article


00:48:15.540 --> 00:48:18.300
that talked about OpenBB that I thought


00:48:18.300 --> 00:48:19.140
was pretty interesting.


00:48:19.140 --> 00:48:20.900
I come over here, okay, wow, this is really pretty.


00:48:20.900 --> 00:48:21.740
It's pretty cool.


00:48:21.740 --> 00:48:23.660
It's open source and so on.


00:48:23.660 --> 00:48:25.140
The other one is like right across the top,


00:48:25.140 --> 00:48:30.100
it says announcing our $8.5 million seed fund funding


00:48:30.100 --> 00:48:31.280
and public launch.


00:48:31.280 --> 00:48:36.580
And that sounds like a non-trivial deal.


00:48:36.580 --> 00:48:38.520
- That's awesome, congratulations.


00:48:38.520 --> 00:48:39.580
- Yeah, thank you so much.


00:48:39.580 --> 00:48:43.560
I mean, yeah, that's a pretty big deal for us.


00:48:43.560 --> 00:48:45.540
- I would think.


00:48:45.540 --> 00:48:50.540
- So yeah, I mean, actually fun fact about this was that,


00:48:50.540 --> 00:48:57.020
so Didier and I were just doing this for fun on the side,


00:48:57.020 --> 00:49:00.140
you know, and then my wife and I,


00:49:00.140 --> 00:49:03.020
we got married in 20, about a year ago,


00:49:03.020 --> 00:49:06.060
actually a year ago in 11 days.


00:49:06.060 --> 00:49:07.060
- Oh cool, great.


00:49:07.060 --> 00:49:11.580
- So we're on our honeymoon in Napa Valley,


00:49:11.580 --> 00:49:13.540
good old land of the VC.


00:49:13.540 --> 00:49:15.140
And on our last night there,


00:49:15.140 --> 00:49:18.540
last night there, you know,


00:49:18.540 --> 00:49:21.340
fun day of wine touring and whatnot,


00:49:21.340 --> 00:49:24.420
I get a LinkedIn message from someone saying,


00:49:24.420 --> 00:49:27.700
"Hey, we're interested in investing in you."


00:49:27.700 --> 00:49:31.020
And needless to say, that turned into


00:49:33.740 --> 00:49:40.860
meeting up with meeting up with him on quick 20 minute chat the day of driving through


00:49:40.860 --> 00:49:47.100
San Francisco before actually trying to get out to Alcatraz because we had that scheduled.


00:49:47.100 --> 00:49:52.260
Wow. What funny timing on one hand, it's like terrible timing on other it's perfect. You're


00:49:52.260 --> 00:49:57.900
right there. Yeah, I mean, I was like, Hey, I'm in Napa. And so I'll give a shout out


00:49:57.900 --> 00:50:05.160
to JJ over at OSS Capital. He's been fantastic working with us. JJ was like, I will meet


00:50:05.160 --> 00:50:09.240
you wherever you are right now. And I'm like, man, I am not in any state to be talking to


00:50:09.240 --> 00:50:18.520
anyone right now. So yeah, no, it was a great opportunity to reach out with him. They led


00:50:18.520 --> 00:50:24.920
the round. We have a great group of angels on board as well.


00:50:24.920 --> 00:50:30.040
So yeah, well I guess there's a couple other call outs I want to make real quick.


00:50:30.040 --> 00:50:34.200
One Travis Oliphant is an advisor to you all, which is pretty awesome.


00:50:34.200 --> 00:50:38.240
People surely know him as one of the founders of Anaconda.


00:50:38.240 --> 00:50:39.240
Yep.


00:50:39.240 --> 00:50:40.960
Travis is on board as an advisor for us.


00:50:40.960 --> 00:50:44.360
It's been fantastic working with him, getting to know him a little bit.


00:50:44.360 --> 00:50:45.360
That's super cool.


00:50:45.360 --> 00:50:53.920
Then also Naval Rivacant is one of the investors and I know him from this Twitter storm thing


00:50:53.920 --> 00:50:56.120
turned into a discussion called how to get rich.


00:50:56.120 --> 00:50:57.880
Have you listened to this?


00:50:57.880 --> 00:50:59.120
- Parts.


00:50:59.120 --> 00:51:01.560
- Yeah, it's pretty interesting, pretty fascinating.


00:51:01.560 --> 00:51:06.440
So he's involved as well, which is pretty cool.


00:51:06.440 --> 00:51:08.560
Awesome, I think that's really neat.


00:51:08.560 --> 00:51:10.080
Like I said, congratulations to you guys.


00:51:10.080 --> 00:51:11.800
Keep good, gonna keep working on this.


00:51:11.800 --> 00:51:16.700
But open source projects often struggle to get support,


00:51:16.700 --> 00:51:19.220
even when it blows my mind that they do.


00:51:20.600 --> 00:51:25.600
see projects like requests or flask or something like that.


00:51:25.600 --> 00:51:31.160
And so much of the world and the tech world in particular,


00:51:31.160 --> 00:51:33.260
where there's tons of extra money


00:51:33.260 --> 00:51:36.820
and there's not very much support, right?


00:51:36.820 --> 00:51:39.160
You know, as far as I know,


00:51:39.160 --> 00:51:41.720
David Lord isn't just mostly on his yacht


00:51:41.720 --> 00:51:44.240
and periodically accepting PRs, right?


00:51:44.240 --> 00:51:47.980
Like, but if you think of how foundational


00:51:47.980 --> 00:51:52.580
some of these projects are for so many companies.


00:51:52.580 --> 00:51:56.360
It seems almost like David should be on a yacht.


00:51:56.360 --> 00:51:57.200
You know what I mean?


00:51:57.200 --> 00:52:00.060
Like it should be easier for them


00:52:00.060 --> 00:52:01.620
to get really strong support.


00:52:01.620 --> 00:52:04.340
And here's an example of a company


00:52:04.340 --> 00:52:05.740
getting really good support,


00:52:05.740 --> 00:52:08.480
giving away to some degree.


00:52:08.480 --> 00:52:11.500
Can you talk about what the business model is


00:52:11.500 --> 00:52:13.940
or is it just growth and-


00:52:13.940 --> 00:52:15.620
- Right now we primarily,


00:52:15.620 --> 00:52:17.460
primarily we wanna focus on growth


00:52:17.460 --> 00:52:21.660
and really hammering home the user experience, right?


00:52:21.660 --> 00:52:23.400
One of the things you talked about is,


00:52:23.400 --> 00:52:25.180
maybe when someone fires this up,


00:52:25.180 --> 00:52:29.780
they're not used to seeing a textual type thing


00:52:29.780 --> 00:52:33.180
where I need to type in all the commands there.


00:52:33.180 --> 00:52:37.260
Everyone's just used to buttons, fancy web apps.


00:52:37.260 --> 00:52:40.500
So right now we really wanna hammer home


00:52:40.500 --> 00:52:44.060
the user experience, make it as fluid as possible.


00:52:44.060 --> 00:52:46.980
We're working on documentation, we're working on guides.


00:52:46.980 --> 00:52:52.020
Yeah, it seems like something that would lend itself really well to a bunch of small video


00:52:52.020 --> 00:52:57.420
videos on like you could just say help this goes, would you like to watch a video on how


00:52:57.420 --> 00:52:58.420
to do this?


00:52:58.420 --> 00:52:59.420
Two minutes?


00:52:59.420 --> 00:53:00.420
Yes.


00:53:00.420 --> 00:53:01.420
All right, I'll watch the video.


00:53:01.420 --> 00:53:02.420
Just like pop that up or something.


00:53:02.420 --> 00:53:03.420
Yeah, yeah, no, that's it.


00:53:03.420 --> 00:53:05.420
And you know, some series of those.


00:53:05.420 --> 00:53:06.420
Yeah.


00:53:06.420 --> 00:53:09.500
Because for example, you know, fundamental analysis or technical analysis are buried


00:53:09.500 --> 00:53:10.500
three or four menus down.


00:53:10.500 --> 00:53:16.020
And if you're downloading the tool to do that, you know, maybe you're going to be intimidated


00:53:16.020 --> 00:53:17.620
at first, 'cause you don't know where it is.


00:53:17.620 --> 00:53:18.460
- Right, right.


00:53:18.460 --> 00:53:20.660
I tried, I couldn't find it or whatever, yeah.


00:53:20.660 --> 00:53:23.300
- Yeah, so right now we wanna focus on the community


00:53:23.300 --> 00:53:25.900
and we wanna focus on the user experience.


00:53:25.900 --> 00:53:27.300
- Cool.


00:53:27.300 --> 00:53:30.020
All right, well, you've definitely got a little runway there


00:53:30.020 --> 00:53:31.420
so that's great.


00:53:31.420 --> 00:53:33.660
How many people are working on it now?


00:53:33.660 --> 00:53:38.140
- So our team is, so our team,


00:53:38.140 --> 00:53:40.460
first off, shout out to everyone


00:53:40.460 --> 00:53:42.400
bothering me on Slack during this.


00:53:44.300 --> 00:53:46.820
- I'm ignoring you because I'm talking about you, okay.


00:53:46.820 --> 00:53:47.660
- Pretty much.


00:53:47.660 --> 00:53:52.220
So shout out, we're at 15 right now.


00:53:52.220 --> 00:53:54.340
- Awesome.


00:53:54.340 --> 00:53:59.020
- I'll take this opportunity to mention


00:53:59.020 --> 00:54:00.820
that we do have some open job postings


00:54:00.820 --> 00:54:03.900
on our website as well at the moment.


00:54:03.900 --> 00:54:04.860
- Oh really, okay.


00:54:04.860 --> 00:54:11.180
- So yeah, just throwing that out there on our website,


00:54:12.140 --> 00:54:14.900
Openbb.co/company/careers.


00:54:14.900 --> 00:54:20.980
- Yeah, so I'm guessing some of these are Python-related ones?


00:54:20.980 --> 00:54:23.740
- Yep, yep.


00:54:23.740 --> 00:54:29.780
Or currently, currently we're looking for DevOps


00:54:29.780 --> 00:54:33.420
and we're also looking for some social media managers


00:54:33.420 --> 00:54:35.040
at the time. - Sure, cool.


00:54:35.040 --> 00:54:39.860
Remote, remote an option?


00:54:39.860 --> 00:54:41.340
- 100%.


00:54:41.340 --> 00:54:42.740
- Yeah.


00:54:42.740 --> 00:54:46.020
- Yeah, 100% remote, flexible hours.


00:54:46.020 --> 00:54:48.620
- Cool, very cool.


00:54:48.620 --> 00:54:51.100
Yeah, I know a lot of people are interested


00:54:51.100 --> 00:54:52.020
in finding new jobs.


00:54:52.020 --> 00:54:55.100
On one hand, if you're a software developer,


00:54:55.100 --> 00:54:59.540
you can kind of find jobs pretty easily these days


00:54:59.540 --> 00:55:00.860
because there's such a demand,


00:55:00.860 --> 00:55:02.960
but on the other, it's like, well, you can have this job,


00:55:02.960 --> 00:55:05.960
but all right, you've got to move to this city


00:55:05.960 --> 00:55:07.100
that you don't already live in,


00:55:07.100 --> 00:55:08.020
or you don't wanna move to,


00:55:08.020 --> 00:55:10.460
or you wanna change countries or whatever, right?


00:55:10.460 --> 00:55:12.500
So I think remote's pretty awesome.


00:55:12.500 --> 00:55:16.980
- Yeah, and we're spread out all over the globe.


00:55:16.980 --> 00:55:19.460
So it's a good time.


00:55:19.460 --> 00:55:20.420
- Yeah, absolutely.


00:55:20.420 --> 00:55:23.380
That's the way it should be, beautiful.


00:55:23.380 --> 00:55:27.740
Okay, well, I think that's about all I had to ask


00:55:27.740 --> 00:55:30.820
about all the things I wanted to make sure we covered,


00:55:30.820 --> 00:55:34.740
but yeah, it's something really cool you all built


00:55:34.740 --> 00:55:36.620
with Python and the data science stack


00:55:36.620 --> 00:55:39.660
and the open source growth is cool


00:55:39.660 --> 00:55:43.600
and the funding is, looks real positive, so awesome.


00:55:43.600 --> 00:55:47.540
I guess, you know, sounds like you accept PRs,


00:55:47.540 --> 00:55:49.180
people wanna contribute.


00:55:49.180 --> 00:55:50.020
- Yeah.


00:55:50.020 --> 00:55:51.860
- It seems like one of those projects that is very easy,


00:55:51.860 --> 00:55:54.100
not easy, but very open to contributions


00:55:54.100 --> 00:55:56.860
'cause it has so many sort of standalone little features,


00:55:56.860 --> 00:55:58.460
like, oh, I wanna add this new algorithm


00:55:58.460 --> 00:56:01.700
or this new picture to this part of it, right?


00:56:01.700 --> 00:56:03.900
You don't have to understand the whole system massively


00:56:03.900 --> 00:56:05.420
in order to do that, right?


00:56:05.420 --> 00:56:08.060
- Yeah, this was actually the first open source project


00:56:08.060 --> 00:56:09.740
that I myself worked on.


00:56:09.740 --> 00:56:12.280
I picked a good one to start on.


00:56:12.280 --> 00:56:17.280
No PR is too small, no issue.


00:56:17.280 --> 00:56:20.700
We are on Discord.


00:56:20.700 --> 00:56:23.340
I know a lot of people aren't huge fans of,


00:56:23.340 --> 00:56:25.900
you know, are putting the support there,


00:56:25.900 --> 00:56:27.300
saying, "Hey, come on Discord."


00:56:27.300 --> 00:56:29.940
But we're there if anyone has questions on how to install


00:56:29.940 --> 00:56:34.940
and how to submit a PR, any ideas, we're around to talk.


00:56:34.940 --> 00:56:36.240
- Yeah.


00:56:37.060 --> 00:56:37.900
- Awesome.


00:56:37.900 --> 00:56:40.380
All right, James, before you get out of here, though,


00:56:40.380 --> 00:56:43.140
I've got to ask you the final two questions.


00:56:43.140 --> 00:56:43.980
- Shoot.


00:56:43.980 --> 00:56:45.720
- All right, so if you're gonna work on this,


00:56:45.720 --> 00:56:46.660
write some Python code,


00:56:46.660 --> 00:56:49.420
what editor do you open up these days?


00:56:49.420 --> 00:56:54.420
- Oh, man, so I'm gonna get a lot of bad feedback


00:56:54.420 --> 00:56:57.260
from my team on this one,


00:56:57.260 --> 00:56:59.780
but I am a PyCharm person.


00:56:59.780 --> 00:57:04.220
Git scares me, and the fact that I can open up


00:57:04.220 --> 00:57:09.220
a GUI window makes my life a lot easier.


00:57:09.220 --> 00:57:12.940
Everyone else uses VS Code,


00:57:12.940 --> 00:57:15.060
so there's always a constant debate,


00:57:15.060 --> 00:57:16.360
but I'm a PyCharm.


00:57:16.360 --> 00:57:20.460
- Well, you won't get any negative feedback from me.


00:57:20.460 --> 00:57:21.700
I think PyCharm's awesome.


00:57:21.700 --> 00:57:25.740
I use it as well, and all the PR features


00:57:25.740 --> 00:57:28.660
and get features built into it are pretty excellent.


00:57:28.660 --> 00:57:30.340
- Yeah, VS Code's also great.


00:57:30.340 --> 00:57:33.340
Love to those guys as well.


00:57:33.340 --> 00:57:34.300
- Yeah, I think, you know,


00:57:34.300 --> 00:57:35.940
when I started asking this question,


00:57:35.940 --> 00:57:38.140
six, seven years ago, whatever it was,


00:57:38.140 --> 00:57:40.500
it was like, I don't know what this person,


00:57:40.500 --> 00:57:43.260
like, I really don't know what this person is gonna say.


00:57:43.260 --> 00:57:44.340
It could be anything.


00:57:44.340 --> 00:57:45.740
It could be something like random thing


00:57:45.740 --> 00:57:46.580
I haven't even heard of.


00:57:46.580 --> 00:57:47.400
Like, that's an editor?


00:57:47.400 --> 00:57:49.040
Okay, let me research that.


00:57:49.040 --> 00:57:50.340
These days, it's really down,


00:57:50.340 --> 00:57:53.400
it's down to two contenders, pretty much,


00:57:53.400 --> 00:57:56.340
unless you get the Vim, Emacs, Engel,


00:57:56.340 --> 00:57:58.660
which is not as popular, but yeah,


00:57:58.660 --> 00:58:00.140
it's down to those two pretty much.


00:58:00.140 --> 00:58:00.980
Awesome. - Yeah.


00:58:02.580 --> 00:58:03.820
- Notepad.


00:58:03.820 --> 00:58:04.660
- Yeah.


00:58:04.660 --> 00:58:06.820
You just gotta read something.


00:58:06.820 --> 00:58:07.920
All right, and then,


00:58:07.920 --> 00:58:10.580
notable PyPI package,


00:58:10.580 --> 00:58:12.180
something you wanna give a shout out to?


00:58:12.180 --> 00:58:14.140
- Oh man, we have so many, as I said,


00:58:14.140 --> 00:58:17.900
you know, 200-ish.


00:58:17.900 --> 00:58:20.320
One of the ones that's been really great,


00:58:20.320 --> 00:58:22.900
another open source project, the rich package.


00:58:22.900 --> 00:58:27.900
That's what we use to add all the colorful text interfaces,


00:58:27.900 --> 00:58:30.060
as well as the prompt toolkit,


00:58:30.060 --> 00:58:31.500
another great open source package


00:58:31.500 --> 00:58:34.860
that's what does our auto-completes and whatnot


00:58:34.860 --> 00:58:36.740
to try to make it a little bit easier


00:58:36.740 --> 00:58:38.220
on the user experience.


00:58:38.220 --> 00:58:39.900
- That's fantastic, okay.


00:58:39.900 --> 00:58:40.740
- So there's two.


00:58:40.740 --> 00:58:42.460
- Yeah, I like Prompt Toolkit as well,


00:58:42.460 --> 00:58:44.700
and of course Rich.


00:58:44.700 --> 00:58:47.380
And you know, speaking of--


00:58:47.380 --> 00:58:50.540
- Textual. - Oh, I/O, right.


00:58:50.540 --> 00:58:52.760
Speaking of open source projects,


00:58:52.760 --> 00:58:54.180
that is not the right one.


00:58:54.180 --> 00:58:59.220
But it's really cool that


00:59:00.400 --> 00:59:05.400
Will McGugan has got textualize.io


00:59:05.400 --> 00:59:07.120
is what I was looking for.


00:59:07.120 --> 00:59:11.440
Has really found a place building great TUIs,


00:59:11.440 --> 00:59:13.960
text user interfaces with Rich,


00:59:13.960 --> 00:59:15.720
and there's just so many things based on it.


00:59:15.720 --> 00:59:20.200
And he also has some funding as well to keep going there,


00:59:20.200 --> 00:59:24.080
which is, I think, another one of the bright,


00:59:24.080 --> 00:59:26.500
awesome pieces of news around sort of, you know,


00:59:26.500 --> 00:59:28.940
vibrant open source in Python.


00:59:28.940 --> 00:59:32.180
- Yeah, I mean, the rich package is fantastic.


00:59:32.180 --> 00:59:37.020
Yeah, it's all we use now.


00:59:37.020 --> 00:59:37.860
- That's awesome.


00:59:37.860 --> 00:59:39.980
It's like got some crazy new feature every week.


00:59:39.980 --> 00:59:41.380
It's all-- - Pretty much.


00:59:41.380 --> 00:59:42.900
- Never sitting still.


00:59:42.900 --> 00:59:46.140
All right, well, James,


00:59:46.140 --> 00:59:47.820
it's been great to have you on the show.


00:59:47.820 --> 00:59:49.580
Thank you so much for coming on


00:59:49.580 --> 00:59:51.820
and sharing a look with your project.


00:59:51.820 --> 00:59:54.120
- Yeah, no, thank you so much for having me.


00:59:54.120 --> 00:59:56.740
It's really great.


00:59:56.740 --> 00:59:58.380
- Yeah, you bet.


00:59:58.380 --> 00:59:59.220
See you later.


00:59:59.220 --> 01:00:00.380
- All right, take care.


01:00:00.380 --> 01:00:01.380
- Bye. - Go Bills.