0:00

Hello and welcome to Python bytes where

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we deliver Python news and headlines directly

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to your earbuds. This is episode 368

0:06

recorded January 23rd, 2024. I'm Michael Kennedy.

0:14

And I'm Brian. I can this episode is

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and now let's let's dive right in.

0:56

Go for it, Brian. What you got?

0:59

Well, I wanted to talk about debugging a

1:01

little bit because we've got a

1:04

blog post. Actually, it's a blog

1:06

post and a really a newsletter

1:09

episode from

1:11

Eunice. It's a

1:13

site called Syntax error. And it

1:16

looks like it's a collection.

1:19

It's a newsletter about debugging, which is

1:21

kind of nice. And somehow I missed

1:23

it in the past year.

1:25

It started. It looks like February

1:27

of 2023. But we're

1:29

on episode 11 or issue 11 and

1:31

it's kind of a summary. So it's pretty

1:34

neat. It's talking about debugging Python. I really

1:36

love just the concept, the concept

1:38

of this of the newsletter, but also just

1:41

it's really good content in a small thing.

1:43

So what is he talking about? So if

1:45

you're debugging some code, you, the first thing

1:47

you got to do is you got to

1:49

get in the right mindset and then you,

1:52

then you can use some tools. So I'm

1:54

glad that he starts that with the mindset.

1:56

Just talking about mindset. Take a break. Stop.

1:59

Breathe. I'm in and come

2:01

back to it and this breaking away

2:03

from frustrated with your code to clearing

2:06

your head is really important i don't

2:08

don't skip that i think it's essential

2:10

go grab a cup of coffee or

2:12

something. I'm

2:14

using a step by step process

2:16

don't i'm just i mean it's

2:19

hard to say not to just jump to the thing that

2:21

you think might be broken and try to fix it okay

2:23

after you did that and it didn't work then come back

2:25

to this. And then do a

2:27

step by step methodical process and i

2:30

think it's very helpful. There's

2:32

a little comic here which is great of of grew

2:35

from a forget

2:38

the name of the movie. But

2:41

he says i need to debug an issue

2:43

set a break point to get started the

2:45

break point never hits the break point never

2:47

hits it's pretty funny anyway so

2:49

being methodical about it will help.

2:53

And then i'm glad he brought

2:55

this up talking about rubber ducking

2:57

or talking to ducks and this

2:59

is this is an age old and

3:02

i don't know if it ever actually

3:04

happened in my computer science classes in

3:06

our lab we had a stuffed monkey.

3:09

That if you ask the ask the

3:11

TAs or the the grad

3:14

students that were hanging out in the lab for

3:16

help they would say the ask

3:18

the monkey first. I'm into

3:21

this is just essentially getting a

3:23

description of the bug the situation

3:25

the background information in your

3:27

mind in a way that you can say it out loud will

3:30

sometimes completely solve the problem it's

3:33

incredible incredible tool. I

3:36

want to think that was interesting is

3:38

he talks about brain dump is

3:41

an alternative solution is i'm writing on

3:43

paper if you're not the kind

3:45

of person that verbalizing helps writing on paper

3:47

might help. Okay now let's get into the

3:49

tech that the tools the tools that help

3:52

with debugging and i used

3:54

to feel guilty about this all the time

3:56

but i reach for print all the time

3:58

so or. Or

4:00

some sort of like that don't you don't do

4:02

print come on. So

4:05

his technique is to start with print because

4:07

it's low friction everybody knows how to do

4:09

it plus we have strings now and

4:11

with the with the equal sign if you

4:14

do like curly braces and then the variable

4:16

name with the equal it just says it's

4:19

great it anyway. It's

4:21

really easy to debug print which is good

4:23

and it's a little friction it's easy to

4:25

add snoop is

4:28

a is a interesting cold tool kit

4:30

that he talks about for helping

4:32

to see what's going on within your code

4:34

at each step it's pretty cool tools well

4:36

i'll just quickly go through some of the

4:39

other two that's the two like

4:41

printing logging sort of things there's also ice

4:43

cream that he mentions. And

4:47

there's debuggers so talking about debuggers

4:49

this is not it's your singly

4:51

isn't mentioned like i'd use which

4:53

that's what i usually usually reach

4:55

for is like either a pie

4:57

charm or vs code debugger but.

5:01

Sometimes you don't have access to those if you

5:03

like if you're in to something or whatever so

5:06

invoking being able to use

5:08

pdb i think he talks about pdb

5:10

which is the python debugger i i

5:12

learned how to actually had learned how

5:14

to do this mostly just to talk

5:17

about using pdb with pytast for the

5:19

book and now i use it once

5:21

in a while because sometimes it's it's

5:23

it's even more convenient especially when using

5:25

pdb with talks it's great so. Pdb

5:28

i pdb which is an interactive

5:30

repel sort of thing pudb

5:33

which is kind of like a it

5:35

got panels and stuff it's nice terminal

5:38

ui web pdb which the

5:40

same thing with the browser it's kinda nice

5:42

bird's eye is something i hadn't seen before

5:44

which is kind of cool talking about birds

5:46

eye. It has these

5:49

kind of neat diagrams with

5:51

like boxes around stuff as

5:53

things change it's a interesting

5:56

interface. Yeah yeah

5:58

i don't know if it's for. me

6:00

but if it resonates with you, it's

6:02

great. It might be worth trying on

6:04

a project. Kind of neat.

6:07

Anyway, and then a quick shout

6:09

out to some Django tools. If

6:12

you're debugging Django, there's the debug

6:14

Django tool, the Django debug toolbar

6:16

and an extension for

6:18

VS Code called colo. Anyway,

6:21

some great advice about debugging specifically

6:24

Python but really a lot

6:26

of this advice applies to

6:28

everything. So nice and kind

6:31

of nice that there's a newsletter around that. Yeah,

6:33

it is a nice newsletter. There's something kind of

6:35

good about permanency of written stuff rather than, I

6:37

mean, what we do is great and I think

6:40

it connects with a lot of people but it's

6:42

it's harder to go back to it and like

6:44

search it. Yeah and

6:46

I kind of like the idea of,

6:48

I know that a lot of newsletter

6:50

software like Substack and things like that

6:53

can keep it around for

6:55

you in medium but I like the idea

6:57

of somebody doing newsletter and putting

6:59

the newsletter things on blog posts at the

7:01

same time for people to reach

7:03

out to. So neat. I might have more to say

7:06

about that later but

7:08

I also have something to say about what

7:11

you just pointed out, what you just talked

7:13

about and I have just done

7:15

a new project. I have some things that

7:17

I've been working on and I already talked

7:19

about the Leaving the Cloud and the interview

7:21

with Mark Percentovich and how that inspired me

7:23

to kind of rethink how our infrastructure goes

7:25

and it is just paying so many dividends.

7:27

I'm going to talk about it in some

7:30

interesting ways and as part of that I've had

7:32

to write a little bit in your software and

7:34

I need some logging. I'm going to try

7:36

LogGuru. LogGuru? I know the G is combined

7:39

and wow is this a nice piece of

7:41

logging software. So what I would suggest, Brian,

7:43

if you're feeling the print coming on, if

7:45

you're like, I'm going to print this, I'm

7:47

going to print my way to this bug

7:50

solving this problem, maybe consider LogGuru-ing

7:52

your way. You just create the

7:54

LogGuru thing and you can specify,

7:56

you can say use color and

7:58

all of that. And it will

8:00

also do print statements just to sis out, right?

8:04

But you can see right here on their

8:06

homepage it says how to do color and

8:08

stuff like that. And

8:10

then if you just logger.info or

8:12

whatever, it'll print it out but way

8:14

more structured and with color. And then

8:16

if there's an exception, you're going to

8:19

say printE, or the exception.

8:21

You could just say logger.exception. And

8:24

it will create the traceback showing

8:26

the local variables at every step.

8:28

So instead of having to jump into

8:30

the debugger, you can just print your way to like, oh,

8:32

here's the entire call stack and all the values. That's pretty

8:35

cool. I super, super recommend it.

8:37

I've been using logbook. I'm a log Guru

8:39

fan. I'm resisting the urge to go and

8:41

rewrite all of my logging for all of

8:43

my things. Because it's not

8:45

that productive. But boy, is my logging not cool. All

8:49

right, that's not what I want to talk about. But

8:51

I want to talk about things that were kind

8:53

of inspired by that. So first I want to

8:56

talk about umami. And this has a Python loopback

8:59

really, really quickly here. But let's

9:01

start from the outside in.

9:04

Okay. Okay. So Brian,

9:06

I set up umami at

9:08

umami.is, which is like Google

9:11

Analytics, but not evil. That's

9:13

awesome, right? So the idea

9:15

is it's privacy preserving. It is

9:17

GDPR and CCPA compliant.

9:19

It's open source and

9:22

you can buy it as a service. I can

9:24

go over here and say pricing for nine bucks.

9:28

Some period I will get some number

9:30

of websites and it'll give me analytics

9:33

like Google Analytics for my

9:35

site. Right. That's

9:37

pretty cool. But what's better, the problem with

9:40

that is it's still third party JavaScript.

9:42

Even if they don't use cookies, but

9:44

it's still third party JavaScript. And by way of

9:46

that, it gets blocked a lot. Especially

9:49

by the developer crowd, right? And I'm not,

9:51

that's not a criticism. I'm like on the

9:53

high end of blocking, right? Like I'm like,

9:56

no, no, we're not doing this. No, you

9:58

don't need this kind of stuff. But

10:00

if you run it on your own infrastructure

10:03

under your own domain, the app is doing

10:05

nothing nefarious. It's talking to

10:07

itself for some things and it's going back and talking to itself for other

10:09

forward tracking. So this is

10:11

really, really easy to run under Docker as

10:13

a multi-tiered Docker app on your own domain,

10:16

which is what I'm doing. And so now, it

10:18

can have some really nice insights into what are

10:21

happening on Python Bytes.fm, the

10:23

courses, all that without sharing

10:25

any data with anyone ever and without

10:27

being blocked because it's

10:30

just code running on our own server, just like everything

10:32

else on the website. That's cool. Awesome, right? The problem

10:34

is, if you go over here and you're like, awesome,

10:37

okay, developers, this is me, I'm a developer, let's go,

10:39

let's take me to the docs. And

10:41

cool, look, there's an API section at the end

10:43

down here. Okay, and oh, look, there's

10:45

an API client. I don't want to write code. That's

10:47

great. NPM install API

10:50

client. Oh, crap.

10:54

The only API client for umami

10:56

is JavaScript or TypeScript. I don't

10:58

know. It doesn't matter. It runs

11:00

in JavaScript. It's not Python, right? Actually, TypeScript.

11:02

This whole app is basically TypeScript, right? That

11:04

was until this week. So

11:07

some guy down here named Michael

11:09

released this thing called umami-analytics, put

11:12

it on PyPI, go over to

11:14

the homepage. And

11:17

you can see it talks about how it works.

11:19

Basically, one of the things that's really nice

11:21

about umami over certain other systems, like

11:25

plausible.io is one that has been thrown

11:27

around in the same space and it's

11:29

similar, is that with umami, you

11:31

can send custom events that have nothing

11:34

to do with direct web actions. So

11:36

for an example, suppose somebody signs

11:40

up for an account and then opts into your newsletter.

11:42

You just talked about newsletters. And then that's a double opt-in.

11:45

So they get an email, which then goes

11:47

back to some other place where they actually

11:49

say, yes, I really, really do want to

11:52

get this. It would be cool if you

11:54

could know, okay, that happened, right? And so

11:56

the whole point of this Python

11:58

library is to add PyPI. Python-based

12:01

events to your analytics on top of just what the JavaScript

12:03

is like. You're on this page and then you went to

12:05

that page and you came from this place and you're on

12:07

this browser. It'll let you send in

12:10

things like, somebody bought a course, somebody

12:12

confirmed their email address, somebody logged in

12:14

with the mobile app for the first

12:16

time. Like all of these things that

12:18

have no straight

12:20

HTML JavaScript experience, you can just pump those

12:22

in right alongside all of your other analytics.

12:25

Still all privacy preserving, not sharing

12:27

data with anybody, no retargeting, no

12:30

cookies, none of that crap. Just I

12:32

want to view into what's happening in my app. So this

12:34

thing lets you add a custom event and

12:37

also you can register multiple sites, you can

12:39

list them out. It

12:41

has both synchronous and asynchronous programming

12:44

models based on Pydantic and HCPX

12:47

and yeah, super easy to use. Very cool.

12:49

That name? Yeah. So recommend

12:52

Umami, but one of the problems with Umami is

12:54

there's not really a great client to round that

12:56

out. So check out the one that I created.

12:59

Nice. There's going to be a theme this

13:01

week. So apparently, we

13:03

didn't plan this. Like no. Yeah. If

13:06

we did, we would have both worn blue shirts.

13:08

Oh wait, we're both wearing blue shirts. We are

13:10

wearing blue shirts. Oh, my tent is off though.

13:13

All right, over to you. I had an extra

13:15

from the last one because there was a link

13:18

from Eunice about fstrings.help,

13:20

which I think I've seen before,

13:22

but I kind of forgot about,

13:24

but just looks like a Jupyter

13:26

notebook about fstrings, which

13:28

is okay. Well, I'll have a link in that in

13:31

the show notes. I

13:33

wanted to mention that, so

13:35

I did an open source

13:37

thing also. So I released a thing

13:40

called a- Oh, you did? Okay. Pytest

13:42

suite timeout. And

13:44

there's a little, I guess a

13:47

story around it. So what happened

13:49

was I recorded an episode of

13:51

Python test about repeating tests. And

13:53

I noted that Pytest repeat doesn't

13:55

have a timeout, but Pytest flake finder does have

13:58

a timeout and it'd be kind of neat. if

14:00

repeat had a timeout also. And

14:03

by timeout, I mean, like there's a, like

14:05

the entire suite. So if I want to

14:07

say like, Hey, I want to run like,

14:09

here's, I have an example. I want to

14:11

run the, my suite like a thousand times

14:14

or my test a test thousand times, cause

14:16

I'm looking for flaky behavior or something. But

14:18

I want to make sure that it only runs like 10

14:21

minutes. Um, then I want

14:23

that to be, I wanted like the entire suite,

14:25

not, not individual tests, but the entire suite to

14:27

only be like 10 minutes or an hour or

14:29

whatever, um, that's the behavior I

14:31

want. And I couldn't figure it out.

14:33

And so I wrote this

14:35

now it could have been in, in pytest

14:38

repeat, but while I was

14:40

thinking about it, I thought, well, I

14:42

have other times where like I'm, I've

14:44

got parameterized tests that are like big

14:46

lists, like 20 different waveforms or something

14:48

that I'm passing through something. Um, uh,

14:51

and sometimes I don't really know how long those are

14:53

going to take. Uh, it'd be kind of nice to

14:55

be able to say, Hey, I want to make sure

14:58

that the whole suite isn't longer than so much. So,

15:00

um, so I made it its own

15:02

plugin. So here it is, uh, pytest

15:04

suite timeout. You just pass it a

15:06

flag. It's still, I just sort

15:08

of did this a couple of days ago and, um, I think

15:11

there might be bugs in it. So, um,

15:14

I guess don't put it in production yet.

15:16

Um, that's why I know production. Yeah. It's

15:19

a little lower, uh, lower

15:21

bar for test production rather than I took

15:23

down the website. I just took down CD

15:25

CICD is possibly what you might take down,

15:28

which is still a problem. Yeah. Well,

15:30

I think I, I think I just ran

15:32

across this morning. I was playing with it

15:34

at least one use case. The word doesn't

15:36

actually time out. Um, but so that's, that's

15:39

the behavior when it fails is it won't

15:41

time out. Uh, but we'll, we'll, we'll work

15:43

with it and fix it. Um, super cool.

15:45

Uh, one of the, I announced it on,

15:47

uh, mastodon and Mike Felder, um, uh, said,

15:51

that's pretty cool. But have you tried,

15:53

uh, Python dash timeout, which yeah, there's

15:55

another one called timeout and it seems

15:58

like that should be like. what

16:00

I want. It's just the time out is the,

16:02

the PyTest timeout is per test.

16:05

It just makes sure that individual

16:07

tests themselves don't run longer than

16:09

a certain amount.

16:11

And this is kind of like, you

16:14

should know this, right? Probably about how

16:16

long your tests run. But

16:18

there's, there's, it's Python and software.

16:20

So sometimes infinite loops happen or

16:22

some use case that you never

16:24

break out of. Well,

16:27

also like just

16:29

the fact that it's taking way longer than it should

16:31

might be something

16:33

you want to trigger as an error,

16:35

right? Like if for some reason you

16:38

want to talk to a database or an API directly and

16:40

you're not stubbing it out, if those things are down, it

16:42

could take 20 seconds for them to

16:44

say, nope, every single time. And you might want

16:47

to say, if this ever takes more than five

16:49

seconds, something's wrong and just kill it. You know

16:51

what I mean? Right? Like I

16:53

think that would even be reasonable. Yeah. So that'd

16:55

be, that's the idea around PyTest timeout is if

16:57

it takes longer than a certain amount attempts to

16:59

kill it. And it does, it does

17:01

like SIG events and stuff to try

17:04

to kill the process that's going, taking

17:06

too long. So where's the new one?

17:08

Sweet timeout is nice. It, though it

17:10

won't kill anything. Um, but it also,

17:12

it won't stop something like that, but

17:14

it'll, uh, it'll just, uh, between tests

17:16

say, Hey, this is taking kind of

17:19

too long. Let's stop now. So, okay.

17:22

Well, you might not want to, you

17:24

know, SIG kill either, because what if

17:26

it's going to put something

17:28

in a database, do some stuff and then take

17:30

it back out or make a file change and then clean up

17:32

the temporary files or, you know, whatever, right? Yeah.

17:35

Um, the, the other part of this

17:37

though is I think it's too nice

17:40

so far. It doesn't throw any exceptions

17:42

or errors or anything. It just stops

17:44

the counting. So if you normally, like

17:46

in this example, if I had a

17:48

thousand and I only get through like

17:50

150, it just stops, passes

17:53

everything, but it only ran out in 50

17:55

instead of a thousand. I'm trying to figure

17:57

out a way to like alert the user.

18:00

little bit more that there's something wrong.

18:03

Um, so we'll, we'll see. It'll grow a

18:05

little bit after, after this. Oh, oh, excellent.

18:07

Excellent. This is a crazy episode of where

18:09

it's just, we all created a bunch of

18:11

things. So let's go back to things we

18:13

created. Huh? Okay. This one

18:16

is also a thing I didn't create,

18:18

but outside in again. So I've

18:20

been using MailChimp for years. And when

18:22

I first started using MailChimp, you know,

18:24

MailChimp is I want to let you

18:26

subscribe to my newsletter and put you into groups

18:28

so that if I only want to talk to

18:31

the talk Python people, I can send that message.

18:33

If I only want to talk to the Python

18:35

bytes people, I can send that message. Right. And

18:37

the price has just been going up and up

18:40

and up like hundreds of a hundred dollars this

18:42

month, the next one, then another hundred dollars. And

18:44

like, what is going on with these people? You

18:46

know, Intuit bought it and it used to be

18:49

like kind of a cute little company. And now

18:51

it's just a accounting firm grinding its users. And

18:53

I kind of don't want anything else to do

18:55

with it. And I would much prefer to not

18:58

share all of the people, customers, people who just

19:00

want to subscribe their data with a third party

19:02

either. Right. So I went on, I think I

19:04

talked about this before. Remember I talked about the

19:07

10 different options that people had sent out of

19:09

possible newsletter places. Yeah. I wish I remember who

19:11

told me on Mastodon, but somebody said, well, there's

19:13

these five open source ones like, wait a minute.

19:15

Okay. That's interesting. And so after a bunch of

19:18

research, I decided to turn on a list monk

19:20

and list monk is written in go

19:23

and it's an open source.

19:25

There's not even a SAS version.

19:27

It's just self hosted version of

19:30

basically MailChimp, right? You can have different lists. People can

19:32

subscribe to them. You can put them into groups. You

19:34

send them emails, all that kind of stuff. Right. So

19:37

I, again, cause I have all this cool

19:39

Docker infrastructure stuff set up. Now it was

19:41

super easy to just move that over and

19:43

run that in Docker. Right. Just like you

19:45

mom, you're like, okay, how do I talk

19:47

to it? Go. There's not even an official

19:49

API client. The ones you find are like,

19:51

well, here's one for PHP. There's

19:54

actually several for Python, but they're really

19:56

bad and they don't work. I mean,

19:58

really bad. So some

20:01

of them, for example, are just, they

20:03

look at the Swagger docs, at

20:05

the open API docs and they just auto-generated.

20:07

But somehow it's like stuck in time, auto-generated

20:09

on an old version that doesn't work anymore.

20:11

I don't know, it's like even the auto-generated

20:13

one doesn't work, I'm like, ah man, I

20:15

really need this. Even more than the

20:17

umami thing, I need code to be written. So like

20:19

someone creates an account, when they buy a course and

20:22

they say, yes, I wanna be, you know, I asked

20:24

them, do you wanna be in the middle of this?

20:26

Yes, I wanna be there. How do I make that

20:28

happen, right? Well, Python of course. So

20:30

over the next project,

20:33

listmonkemailappapi, client for Python,

20:36

or just pip install

20:38

listmonke. Okay. So

20:40

over here, this is the next one, super

20:42

nice. You can add a subscriber, get details

20:44

about them. One of the things that's cool

20:47

in listmonke is there's a arbitrary JSON, Python

20:50

dictionary type thing associated with each user. So

20:52

whatever data you wanna put in there, you

20:54

can. And with this thing, you can manage

20:56

it. Like for example, if one

20:58

thing that's common is you have a rating or

21:00

things along those lines or actions, so you

21:03

could put that into the user as part

21:05

of their user record. So you can manage

21:07

it with that. You can search them, check

21:09

the health of your self hosted thing, segment

21:11

on your list. Obviously you gotta unsubscribe and

21:13

delete users. You can even send transactional emails.

21:16

So super, super cool stuff.

21:18

Again, one more nice open source

21:20

thing that's not some

21:23

big, super expensive, privacy

21:25

questionable SaaS service. And

21:27

instead running good over here

21:29

does take a little bit of work. Umami

21:31

is like perfect. This is

21:34

a little clunky in some little

21:36

edge cases, but it's still quite nice.

21:38

So that's the next project. Also available

21:41

on PyPI today. Nice.

21:43

That's it for our items. Cool.

21:47

Between all these things, we can help people write one,

21:49

a little bit better tests. And

21:51

to depend a little bit less

21:53

on just giving up a little

21:55

bit of privacy to trade in

21:57

convenience, like Google Analytics, for example,

21:59

or. to a lesser degree, some of these

22:01

mail platforms. Yeah. Yeah, and save some money while

22:03

you're at it. All right. Well,

22:05

normally we would jump into some

22:07

extras and I don't have

22:09

any extras this week. So do you have any

22:12

extras? I do have extras. Well, let's

22:14

see what have I got here. Yeah,

22:16

okay, so the first one is if I'm

22:18

running, self-hosting these things, I'm running them in

22:20

a Docker cluster. So it's really easy to

22:23

basically just do a Docker pull, restart,

22:26

relaunch the app, off it goes.

22:29

So that's awesome. That's one of the reasons

22:31

I'm willing to run like Umami rather than

22:33

like I have a server and all these

22:35

database things. I get a patch and whatever,

22:37

right? Just literally one command to manage

22:39

like 15 multi-tier apps, it's

22:41

awesome. But how do you know when there's a

22:44

new one? Obviously you could just

22:46

set it up to just do it continuously.

22:48

But what I realized is every GitHub repository,

22:50

this has nothing to do with Umami, just

22:52

an example, every GitHub repository, if they use

22:55

releases, right? If you

22:57

go over here and you say

22:59

like the releases, like I have

23:01

a V01.10 for my Umami thing,

23:03

there's actually two of them. If you have

23:05

that for any project, you can just go to

23:08

the GitHub URL for

23:10

the web, not the .get thing

23:12

and just do slash releases.atom and

23:15

that's an RSS feed for the releases for

23:17

any GitHub project, even if they don't have

23:20

a blog. Wow. That's cool, right? Yeah, I

23:22

can put the feed leave in. Yes,

23:24

I put it in Reader for me and now

23:27

I have Lismock and Umami and a

23:29

few other things that I'm like, if this gets changed,

23:31

I probably wanna just go take a little action on

23:33

that real quick and now it's in my RSS feed.

23:36

That's pretty cool. Yeah, so very simple. Anyone

23:38

can just watch whatever they want. Brian, we

23:40

both tried to do this one. Yeah. Kolo,

23:43

you mentioned that in your article, I ran across this,

23:45

sorry, I don't remember the last name, but I saw

23:48

one of my Mastodon

23:50

followers, Lily. She somehow

23:53

interacted with me and her profile came

23:55

by in my app and I saw

23:57

that she works on this thing called

23:59

Kolo. debugging for Django apps. I'm

24:01

like, oh, that's interesting, what is this?

24:03

So this is a thing that's in

24:05

beta, and it says, see everything happening

24:08

in your running Django app. And they

24:10

have a really nice design of their

24:13

webpage here. So, I'll be best to

24:15

see visually, says, debug your Django app

24:17

10 times faster, get instant access, et

24:19

cetera, et cetera. So this is a

24:21

plugin or extension for VS Code, and

24:23

it just has tons of information all

24:26

available to you. So it has a

24:28

tab, or whatever the thing on the

24:30

left is, you expand extension, the files, and

24:32

it plugs into that thing, a little pain,

24:34

I guess. And it shows

24:36

you the request response, like kind

24:38

of like DevTools in a web browser. So

24:41

you can see headers, HTTP

24:43

requests, responses, as kind of a

24:45

running history of the HTTP exchange

24:47

your browser is having with your

24:49

Django app. That's cool, right? Yeah.

24:51

And I think it's showing you,

24:53

not entirely sure, but I think

24:55

it might be showing you even

24:57

Python code, not just web things,

24:59

right? It has local variables, arguments,

25:02

and it has even like this

25:04

tree thing for visualizing code execution

25:06

paths. So, yeah. Yeah,

25:09

so you click on the, sorry, you click on

25:11

the request, it shows you the code, and then

25:13

it actually shows you the local variables that were

25:15

passed around as well. It's pretty neat. Yeah, I

25:17

don't know that the tree, the

25:19

visual thing is super pretty, but I don't know

25:21

how it is, but I haven't played with it

25:23

yet. It's awesome, wouldn't

25:25

use it. Yeah,

25:30

you can do, what is it? Inspect

25:32

all the outbound HTTP requests made. That's kind

25:35

of neat. And SQL

25:37

queries, it'll track all

25:39

the SQL queries that were made. Really

25:41

good for understanding what's happening. What's up,

25:43

Brian? Good. No, it's just really nice because

25:45

you never know when your queries get out

25:47

of hand and you're making way more than you need

25:49

to. Exactly, especially in

25:52

the ORM space, because

25:54

it's so easy to do lazy loading and say,

25:56

give me all the customers. For each customer, get

25:58

me this thing. them and that's

26:00

a relationship. So every time do

26:03

the loop, it's another database query, the

26:05

so-called n plus one form

26:07

is problem, right? And you would just see like,

26:09

whoa, the SQL thing is full. I thought they

26:11

were like two or three requests and now it's

26:13

just full. What is happening here, right? So that's

26:15

great. Yeah. Anyway, ooh, background

26:17

jobs. Yeah. Even contract your salary background tasks.

26:20

So right now it's in beta. I'm pretty

26:22

sure this is a thing that costs money

26:24

at some point. Yeah.

26:26

So if you VS code, check this

26:28

out. It's kind of interesting. Yeah, definitely

26:31

neat. All right. Another thing that's cool is

26:33

I've talked about warp

26:36

before and I've been using warp at the terminal

26:38

a lot. One of the drawbacks of warp for

26:40

all of its beauty and cool

26:42

features is that it doesn't,

26:44

it only works on Mac for now,

26:46

which is a limitation. Let's call it.

26:49

Not for me. For other people, not

26:52

for me, but for a good chunk.

26:54

Now I say he's only somewhat of

26:56

a limitation. So like on my Mac,

26:58

if I SSH into my Docker cluster

27:00

thing that I've been talking about,

27:03

warp will like inject the warp

27:05

behaviors into the Linux shell

27:07

over there. So I get like end

27:09

to end warp as a Mac user.

27:11

But if I was actually a Linux

27:13

user, I couldn't use warp because it's

27:15

a Mac app until pretty much now.

27:17

Right? So coming soon is warp on

27:20

Linux. So people want to sign up

27:22

for that. I put a link for

27:24

in the Linux terminal signup page to

27:26

get on the wait list and warp

27:28

is just a super neat way to work

27:30

with your terminals. More like an

27:32

editor. It's got AI built in, which most

27:34

AI built in things I hate. They're really

27:37

bad, but you can say things like just

27:39

say hash. And then you'll say something like,

27:41

you know, search this directory for all files

27:43

with this pattern, except that directory. And then

27:45

it'll go, here's the command that you type.

27:48

You know, like that kind of, it's because it's that kind of

27:50

stuff that I'm like, what's the parameter to this? How

27:53

do I grab that again? I don't have no idea. So

27:56

anyway, it's pretty cool. I wonder if it's

27:58

set up. I'm just curious if it. since

28:00

they're doing different platforms, if they've got

28:02

a UI layer and then a warp

28:05

core. Oh my God, they probably

28:07

do have a warp core. And if they didn't name it that,

28:09

they've really lost a chance here,

28:12

right? Yeah, hopefully. So I talked

28:14

about this before. I realized through

28:16

search about two and a half

28:18

years ago, something called B-PY-TOP.

28:20

So B-PY-TOP is an awesome, over, it

28:23

gets too small, it thinks it's gonna

28:25

hide all of its graphics, way to

28:27

look at how your server is going.

28:30

And it is so neat,

28:32

the way that this app works. I

28:34

definitely, let me just, I'll put it

28:37

up. Here's the live running version of

28:40

the one that I've been messing with lately. And

28:43

Brian, you can see you've got your memory. There's

28:45

not a whole lot of action going on right now. So it's

28:47

kind of flat graphs, but like if the memory jumped up, you

28:50

would see it go up. It shows you how much memory is

28:52

free, how much is being

28:54

used, how much of that is being

28:56

cached, disk activity. You can see the

28:59

network traffic, the multiple, it has

29:01

four CPUs and it shows you

29:04

graphs for all four CPUs as

29:06

well as like the combined. And

29:08

I'm not gonna show the processes because they

29:10

might show command arguments that

29:12

I just don't wanna share. But it seems

29:15

like it probably somehow could be a bad idea that I'm

29:17

not aware of, but we'll learn later in a hard way.

29:20

But isn't that an amazing way to

29:22

just, this is over an SSH session.

29:24

Oh, that's pretty cool. That's amazing. Yeah,

29:27

and watch this. So if I

29:30

just hit escape, you get even,

29:32

it's like an old video game

29:34

options with mouse support and everything.

29:36

Oh, that's pretty cool. Yeah, so

29:39

another thing to sort of announce

29:41

here is there's B-PY top, which

29:43

you can pip X install, but they've

29:45

also as part of this released a

29:47

B top rewritten and I think it

29:49

must be C++. So

29:52

anyway, that's cool, right? People

29:54

can, I think that's supposed to be a little bit more

29:56

high performance, although to me they kind

29:58

of seem like the same type of thing. Anyway,

30:00

really cool if you've been using like

30:02

top or something like this, you

30:04

know, there's a really much better way and Glances

30:08

is good, but B top is the new the

30:10

new winner of my world here And

30:12

you know those sort of graphs even if you

30:14

don't need them You can have a second monitor

30:16

and have one of those running everybody in your

30:18

life I'll think you do something cooler than you

30:20

actually do. Oh, you're a hacker aren't you? That's

30:22

a terminal Yeah,

30:25

I am okay. Yeah, don't cross me cross.

30:28

All right Right,

30:31

I think that's our extras Do

30:34

it is Chris Tyler just real quick has a

30:36

recommendation Switch to bottom BTM

30:38

which is similar but written in rust

30:40

and a little more performant also cross-platform

30:43

like be I top Okay.

30:45

Well, maybe maybe that needs

30:47

to be checked out as well. Maybe my time

30:50

with B top was short I'll be over to

30:52

bottom before I know it top and bottom. That's

30:54

just terrible. Yeah, these are funny Thanks

30:57

Christopher. All right. I think I'm ready

30:59

for a joke. Yeah, I got something You know,

31:01

I've been talking about Consolidating

31:03

all these servers and running different things.

31:06

We just talked about the monitor in

31:08

your server and Soccer so

31:10

I thought it might be fun to

31:12

share this Post on info

31:14

sec exchange mastodon from Jeff Hall and

31:16

I've got this you described this for

31:18

us Brian It's just a mess of

31:20

cables coming out of with a back

31:23

of what a bunch of I don't

31:25

know Network equipment. Yeah

31:27

It's just like the world you couldn't imagine a

31:30

worse set of tangled wires and

31:32

they're dirty too, right? It's not just like They're

31:36

covered in those all these routers and

31:38

others They're white,

31:40

but they're most they're significantly brown as well.

31:42

Looks like a whole bunch of hubs hanging

31:44

in between and stuff Yeah, yeah, a lot

31:46

of these pieces are just suspended by the

31:48

wires and it just says the cloud Yeah

31:54

Yeah, very nice. I love it. Yeah,

31:56

that's very cool. So indeed funny. All

31:58

right. Well, that's it for the show, I

32:00

suppose. And we don't normally have

32:03

a final call to action, but go

32:05

check out your new PyTest thing, your

32:07

timeout, and check out some

32:10

of these other self-hosted things. Yeah, it's really

32:12

cool. A lot

32:14

of stuff people can adopt in. Yeah, well, thanks for

32:16

being here. And chat with you all later.