Asyncio is a cool part of python. But what does it do? It is a way to write async code in Python.
This lecture shows use real world use cases, knowhows and troubleshooting methods for using asyncio in python
Transcript
1 00:00:01.740 --> 00:00:30.889 Gabor Szabo: So Hello, and welcome to the Codemavens, Meetup Group and Codemavens Channel. If you're watching it on on Youtube, my name is Gabor Sabo. I usually teach python and rust at companies and also introduce test automation and Ci, and that the area and I also think that sharing knowledge is extremely important among high tech
2 00:00:31.470 --> 00:00:56.010 Gabor Szabo: programmers and and people working in the high tech industry. So that's why I am organizing these these meetings, these presentations. As you can see it's being recorded. It's going to be on Youtube, please, like the video and follow the channel below the video, you will find a link to information about Al and and about the content of this video.
3 00:00:56.130 --> 00:01:03.549 Gabor Szabo: And I would like to welcome everyone who's who joined us in the live meeting, and especially like Eyal, giving us the presentation.
4 00:01:03.820 --> 00:01:11.349 Gabor Szabo: So now it's yours. Please introduce yourself and share the screen as you feel fit and welcome.
5 00:01:12.590 --> 00:01:30.479 Eyal Balla: Thank you. So I'll share the screen. So this is presentation about it's the it's like a take off on a presentation I did like, I think, 2 years ago, or maybe 3 years ago.
6 00:01:33.070 --> 00:01:42.467 Eyal Balla: bit about me. So I've been developing for more than 15 years and working in python like
7 00:01:43.120 --> 00:01:49.530 Eyal Balla: 5 to 10 years. And currently, I lead the data team in scenario.
8 00:01:50.390 --> 00:01:51.629 Eyal Balla: See? That's me.
9 00:01:52.994 --> 00:02:04.040 Eyal Balla: So you can find me in the links, and if you're interested we're also hiring. So you're welcome to try and join. And we're looking for people that
10 00:02:04.520 --> 00:02:08.080 Eyal Balla: working python, and that is their passion.
11 00:02:08.650 --> 00:02:13.000 Eyal Balla: So today, what I'm gonna do is I'm gonna go through
12 00:02:13.340 --> 00:02:29.884 Eyal Balla: a bit about what Asyncayo is and try to give a real world example from things that we do, and then we'll try and talk about some advanced topics regarding Asyncayo. And so that's what we're gonna do.
13 00:02:31.060 --> 00:02:36.420 Eyal Balla: I think it's important that you guys feel free to step in and ask questions if you need
14 00:02:38.620 --> 00:02:45.520 Eyal Balla: and cause there, there's gonna be a bit code and some topics, and maybe
15 00:02:45.730 --> 00:02:52.010 Eyal Balla: hopefully, it's gonna be all clear. But if somebody has any question, then feel free to jump in.
16 00:02:52.550 --> 00:03:00.030 Eyal Balla: So 1st of all, what what is Asyncaio. So Asyncaio is a style of concurrent programming in python.
17 00:03:00.340 --> 00:03:04.660 Eyal Balla: So why do we need it? So you can think of
18 00:03:04.960 --> 00:03:08.569 Eyal Balla: wanting to do multiple things in python at the same time.
19 00:03:08.770 --> 00:03:09.506 Eyal Balla: So
20 00:03:11.140 --> 00:03:19.540 Eyal Balla: a simple way to do it is using a fork right? So you can run multiple python processes at the same time.
21 00:03:20.010 --> 00:03:43.789 Eyal Balla: So the OS handles the concurrency. And you can actually use multi-cores on your machines. And the problem is that you get duplicated memory because each process has its own memory space right? And in order to communicate between the different python processes you need like OS level communications. So pipes and
22 00:03:43.950 --> 00:03:45.463 Eyal Balla: files, and
23 00:03:47.161 --> 00:03:59.079 Eyal Balla: sorry other ways of multi-process communication. So you'd say, Okay, maybe we can do it some some other way. So there's also multi-threading in python.
24 00:03:59.390 --> 00:04:02.710 Eyal Balla: So this is nice. So you can create new thread. And
25 00:04:03.242 --> 00:04:11.339 Eyal Balla: it looks like you can run multiple things at the same time. But then there's Gil. So Gil is the global interpreter lock.
26 00:04:11.878 --> 00:04:17.962 Eyal Balla: I know there's an agenda in python to try and remove it. But for now it's there
27 00:04:19.910 --> 00:04:25.750 Eyal Balla: And Gil prevents multiple commands of python running in the same process at the same time.
28 00:04:25.860 --> 00:04:34.925 Eyal Balla: So always concurrency for threading is done when you do. things like
29 00:04:35.580 --> 00:04:41.672 Eyal Balla: accessing files or network, or anytime they give access from the your
30 00:04:42.660 --> 00:04:46.390 Eyal Balla: python commands into the OS. This is done.
31 00:04:47.221 --> 00:04:59.660 Eyal Balla: There's something you don't do implicitly. You do it. You can't do it explicitly. You can only do it implicitly by accessing something or doing something that requires OS interaction.
32 00:05:00.720 --> 00:05:12.629 Eyal Balla: And there's Asyncayo. So what is Asyncaio? It's an I/O event manager. Okay? And it, helps you manage states. So you can have multiple states of your system
33 00:05:12.750 --> 00:05:24.389 Eyal Balla: on the same thread. And you can actually explicitly manage the context switching. So you can say, I want to work on multiple items. These are the multiple items. And I want to work on them.
34 00:05:24.920 --> 00:05:33.670 Eyal Balla: So if we look at high level at what the options are for multiprocessing. Say, we have like multiprocesses.
35 00:05:33.780 --> 00:05:47.120 Eyal Balla: so you can have concurrency, and you can use all the cpus. But you know you can't run many processes on the same machine, because each uses a full CPU, so maybe
36 00:05:47.740 --> 00:05:52.530 Eyal Balla: one to 10 cpus and processes.
37 00:05:52.800 --> 00:06:01.410 Eyal Balla: And you can use, generally, the the standard library blocking components and synchronization tools.
38 00:06:02.110 --> 00:06:16.011 Eyal Balla: And then if you need something that's maybe a bit higher on the scalability you can use threads so you can. You have a single process, and Gil is protecting you from
39 00:06:16.910 --> 00:06:22.843 Eyal Balla: doing things between threads which which ha! Which touch memory, and
40 00:06:23.670 --> 00:06:34.039 Eyal Balla: in intrusive way. And but the problem is that you let the OS think your code and you can't really
41 00:06:34.792 --> 00:06:36.720 Eyal Balla: control it manually.
42 00:06:37.070 --> 00:06:51.839 Eyal Balla: And then there's asking where you can actually handle multiple thousands of scalable small components you call them quote coroutines and but pro, and and it's in the application level.
43 00:06:51.940 --> 00:06:58.970 Eyal Balla: So this is what we're gonna look at today. And we're gonna see how it's work, how it works and how you can control it.
44 00:07:00.620 --> 00:07:03.188 Eyal Balla: So like every other
45 00:07:04.440 --> 00:07:09.849 Eyal Balla: program in the world, there's the hello world like in for asking Kaya. Right? So there's
46 00:07:12.010 --> 00:07:15.570 Eyal Balla: Let's see. Can you see my cursor, then you can.
47 00:07:16.310 --> 00:07:23.630 Eyal Balla: So there's a a regular hello world. And there's the one with asking Kyle, wait, okay, but
48 00:07:23.900 --> 00:07:29.589 Eyal Balla: this program is not really helpful, right? Because it doesn't show anything that's important for us.
49 00:07:30.210 --> 00:07:50.489 Eyal Balla: So what what do we want to do with? I think in the real world? So we want to use it for handling multiple heavy I/O processes. So like maybe database accesses or multiple web requests or file sharing or accessing many I/O components at the same time.
50 00:07:51.330 --> 00:08:10.769 Eyal Balla: And you can always use as incaio using multi processes. So you can have. maybe in a cloud application. You can have multiple pods right? And but also you can run it on multiple processes and have have the ability to use multiple cpus if needed.
51 00:08:13.430 --> 00:08:14.330 Eyal Balla: But
52 00:08:14.440 --> 00:08:28.290 Eyal Balla: the downside of Asyncago is that it's almost a different programming language. It looks like python, and it the constructs are very much like Python, and you just use like a few more keywords. But
53 00:08:28.810 --> 00:08:36.129 Eyal Balla: it's very different in concept, because each coroutine the functions that you call with the weight
54 00:08:37.038 --> 00:08:45.999 Eyal Balla: they have to be short enough to allow multiple contacts to run together. So you mustn't use
55 00:08:46.528 --> 00:08:56.480 Eyal Balla: long computations. You can't block the event. Queue. Okay, just like in iui application. You don't want the the main loop to be blocked.
56 00:08:56.890 --> 00:09:10.859 Eyal Balla: And also you can't use general purpose OS blocking commands like, create connections for socket, or select or sleep. So you have things that are, I think, ios specific
57 00:09:13.062 --> 00:09:20.630 Eyal Balla: so you even have like different libraries that you can use in Asyncaio. So
58 00:09:21.888 --> 00:09:33.809 Eyal Balla: if you usually use requests, I suggest you try use Httpx. It has a better behavior fast Api over Django and flask.
59 00:09:34.671 --> 00:09:37.929 Eyal Balla: Mpg, instead of psychopg, etcetera.
60 00:09:38.130 --> 00:09:40.760 Eyal Balla: Okay, so
61 00:09:42.130 --> 00:09:55.740 Eyal Balla: if we look at Asyncaio at the main building blocks, what we have is, we have the the main Asyncaio run command. So what it does it receives in a
62 00:09:57.490 --> 00:10:05.362 Eyal Balla: in a sync way, it received in a sync context, it receives a core routine, something that
63 00:10:05.900 --> 00:10:09.830 Eyal Balla: is run on the asicio loop and creates a loop
64 00:10:09.990 --> 00:10:16.710 Eyal Balla: and runs the core routine in it. And usually this is how you do the entry point into Asyncaya context.
65 00:10:17.300 --> 00:10:20.779 Eyal Balla: Okay? And then you have the core routines. This, these look like,
66 00:10:21.330 --> 00:10:26.570 Eyal Balla: I define Async Def and a function. And this creates a core routine.
67 00:10:26.770 --> 00:10:31.479 Eyal Balla: Okay and core routines. You can run either using domain loop
68 00:10:31.600 --> 00:10:38.720 Eyal Balla: or create a Co a context, a task using the Asyncare create task.
69 00:10:39.560 --> 00:10:40.470 Eyal Balla: Okay?
70 00:10:40.740 --> 00:10:49.319 Eyal Balla: And also when you want to wait for something to happen, and you want to release the context. So you run, await.
71 00:10:49.480 --> 00:10:59.880 Eyal Balla: call, wait in the call routine, and then you wait for the you wait. The context itself waits until the Async context is finished
72 00:11:00.260 --> 00:11:04.519 Eyal Balla: and then returns the control to the main loop that calls this.
73 00:11:04.620 --> 00:11:05.430 Eyal Balla: Okay?
74 00:11:06.350 --> 00:11:07.370 Eyal Balla: So
75 00:11:08.022 --> 00:11:21.649 Eyal Balla: I'm gonna show you guys an example of a small program. And so what this does it. This is a synchronous program. It reads from S. 3, and then queries some database. Right?
76 00:11:22.040 --> 00:11:23.960 Eyal Balla: So we have, like a
77 00:11:24.090 --> 00:11:30.433 Eyal Balla: 2 contexts. One. This is the 1st one. This is second one, and they're not.
78 00:11:31.700 --> 00:11:48.750 Eyal Balla: they're not dependent on each other. You can see the it just gets a file, and then just runs a query. And seeing we want to try and do this together because we want to have the context returned with the content itself. But we don't have some kind of connection between the 2 contexts.
79 00:11:49.460 --> 00:11:56.740 Eyal Balla: So what you can do is you can move to Asyncayo, define this as a coroutine using the
80 00:11:57.150 --> 00:11:58.716 Eyal Balla: aio bottle.
81 00:12:00.194 --> 00:12:10.339 Eyal Balla: Async library and using Asynpg use, create, run the create a quoting from the query of the database.
82 00:12:10.660 --> 00:12:21.090 Eyal Balla: and then you can use gather to run the 2 core routines together. Okay, independently, one of each other, one from each other. So when
83 00:12:21.826 --> 00:12:30.723 Eyal Balla: the execution of the query runs the return of the items, and the body and of the file is done. This is done
84 00:12:31.300 --> 00:12:40.689 Eyal Balla: asynchronously, and while waiting for the I/O, the the context is continued to the other con. Other part.
85 00:12:41.160 --> 00:12:42.000 Eyal Balla: Okay.
86 00:12:43.430 --> 00:12:46.690 Eyal Balla: Questions great.
87 00:12:47.450 --> 00:13:16.690 Eyal Balla: So more more options. Also supports context managers. So this is very convenient because you can create. For instance, in this you can create, you look at the the bottom part here I had to connect and then close using finally. But I can also create a context manager from this and open the connection with the context manager exits close the connection. So I don't have to use
88 00:13:16.710 --> 00:13:19.260 Eyal Balla: explicit exception handling.
89 00:13:19.850 --> 00:13:21.320 Eyal Balla: And also
90 00:13:22.012 --> 00:13:33.339 Eyal Balla: I think I supports iterators so you can. use like generator way of controlling small parts of the code
91 00:13:33.848 --> 00:13:43.049 Eyal Balla: one after the other, and using Async interval. So this is these are patents very known in Python, and you can also use them in Async context.
92 00:13:45.200 --> 00:13:50.409 Eyal Balla: So now I want to show you guys, maybe a problem from our day to day work.
93 00:13:50.870 --> 00:13:56.281 Eyal Balla: I'll present the problem first.st So what we want to do is we want to do some
94 00:13:58.582 --> 00:14:21.089 Eyal Balla: in integration which reads data from an external source and then enriches it. Okay, gets information from maybe a database, and then adds to the context from the external source, and then writes the results into our database as entities. Okay? And I think the the main issue here is that maybe
95 00:14:21.659 --> 00:14:28.550 Eyal Balla: we have multiple customers. Some are small, some are large, and customers have maybe
96 00:14:29.200 --> 00:14:44.130 Eyal Balla: tens of thousands of entities. So there's a lot of reading from the external source, and also maybe a lot of writing and reading into the database. So we have a lot of I/O. And this actually fits very well the Asyncaio concepts.
97 00:14:44.460 --> 00:14:48.700 Eyal Balla: Okay, so what do we want to do?
98 00:14:49.388 --> 00:15:01.639 Eyal Balla: We wanna call something once in a while and go over each of the customers, get the information and then update with the enriched information into our database. Okay? So
99 00:15:01.810 --> 00:15:06.059 Eyal Balla: like an even nave implementation would be something like this.
100 00:15:07.620 --> 00:15:13.880 Eyal Balla: You define all the the the bootstraps
101 00:15:14.549 --> 00:15:37.869 Eyal Balla: needed, and then you get the list of customers. And then for each customer, you do the information, the enrichment. So you get the settings and you run the enricher on the information, and then you in per customer. You get the information from the integration system and enrich it and write it into your database. Right?
102 00:15:38.640 --> 00:15:40.020 Eyal Balla: So this is nice.
103 00:15:40.935 --> 00:15:41.740 Eyal Balla: But
104 00:15:42.558 --> 00:15:54.589 Eyal Balla: the problem with that when we look at this. So this runs per per customer. So that means that until one customer is done the other, the next customer doesn't start.
105 00:15:54.770 --> 00:15:59.140 Eyal Balla: Okay? So if we have small customers and large customers, then
106 00:16:00.190 --> 00:16:06.090 Eyal Balla: we have a problem that small customers are impacted by the size of large customers right?
107 00:16:06.910 --> 00:16:17.090 Eyal Balla: And also, once we have something that's bigger than the the total chrome time, then it doesn't actually
108 00:16:17.991 --> 00:16:30.509 Eyal Balla: it's not actually up to the time it's called time. So system is not up to the functionality according to the time constraints that supposed to run through.
109 00:16:32.395 --> 00:16:36.110 Eyal Balla: So what can we do so. I think the 1st thing we can do
110 00:16:36.310 --> 00:16:48.919 Eyal Balla: is separated per customer. So we can have, some kind of injection of the customer id through a queue and have the system run only per customer. So
111 00:16:49.160 --> 00:16:54.019 Eyal Balla: it reads the information from the queue gets the customer id
112 00:16:54.380 --> 00:17:01.040 Eyal Balla: here, and then runs the same thing just for a specific customer.
113 00:17:01.160 --> 00:17:03.090 Eyal Balla: So how does this help? So
114 00:17:03.310 --> 00:17:10.749 Eyal Balla: what we can do now is we can scale out. So we can have multiple instances of this specific code run
115 00:17:12.778 --> 00:17:19.050 Eyal Balla: together each on a different customer, and assuming that they're not dependent then.
116 00:17:19.699 --> 00:17:27.270 Eyal Balla: Small customers are now not impacted by the size of large customers and the number of the the time that you wanna
117 00:17:27.829 --> 00:17:29.460 Eyal Balla: to run. This is.
118 00:17:30.045 --> 00:17:40.390 Eyal Balla: at most, the time of the biggest customer. Right? So you can scale out as much as you want, and the time that this whole process takes is the time of the biggest customer.
119 00:17:41.270 --> 00:17:42.110 Eyal Balla: Okay?
120 00:17:42.890 --> 00:17:49.890 Eyal Balla: So till now we did not touch anything. That's as Asyncare, right? So we just used like a simple
121 00:17:50.600 --> 00:17:56.219 Eyal Balla: design patterns that allow scaling out of of loops.
122 00:17:57.300 --> 00:18:02.860 Eyal Balla: So now let's try and use Asyncayo to improve the performance of this whole loop.
123 00:18:03.030 --> 00:18:05.249 Eyal Balla: So what do we do?
124 00:18:05.887 --> 00:18:09.710 Eyal Balla: We create a core routine and run it, using Asikaya run.
125 00:18:11.583 --> 00:18:17.220 Eyal Balla: This coroutine is very much similar to what we ran before.
126 00:18:19.340 --> 00:18:25.209 Eyal Balla: Except that now when we look at what happens inside the run for customer.
127 00:18:25.450 --> 00:18:27.550 Eyal Balla: this looks a bit different.
128 00:18:27.810 --> 00:18:31.698 Eyal Balla: So what do we do? First, st we create
129 00:18:33.466 --> 00:18:44.300 Eyal Balla: we run through the pages. Okay? And when we want to enrich the items, we create batches of coroutines, and then we run them together.
130 00:18:44.420 --> 00:18:59.979 Eyal Balla: Okay, so here. The coroutines are created according to the number of the integration items, and when you enrich and read the information each each batch of the
131 00:19:00.460 --> 00:19:04.559 Eyal Balla: coroutines runs together so you can wait for
132 00:19:06.570 --> 00:19:11.189 Eyal Balla: So so they happen together and wait only for the I/O for each of the items.
133 00:19:11.760 --> 00:19:12.580 Eyal Balla: Okay,
134 00:19:16.630 --> 00:19:20.870 Naty Harary: Yeah, I have a question, and just should I interrupt you? Mid sentence?
135 00:19:20.870 --> 00:19:21.420 Eyal Balla: Yeah.
136 00:19:22.394 --> 00:19:29.490 Naty Harary: So, as far as I know, in Async I/O, it is enough to mark the function itself. Async.
137 00:19:29.700 --> 00:19:34.740 Naty Harary: you just wait for it. So I'm not really familiar with the syntax like here.
138 00:19:35.258 --> 00:19:40.680 Naty Harary: So why do we need to ask Sync this as well? I'm not really sure I understand.
139 00:19:42.430 --> 00:19:48.560 Eyal Balla: What we're doing here is we wait for for each of the pages. So this is a nastic iterator, right?
140 00:19:48.940 --> 00:19:53.389 Eyal Balla: But this, this is. This is the core routine which returns an sn key iterator.
141 00:19:53.510 --> 00:19:56.173 Eyal Balla: And when when you
142 00:19:57.270 --> 00:20:06.239 Eyal Balla: what each of these pages contains items, so you want to enrich each of the items. So you create core teams for each of the items to be enriched.
143 00:20:06.390 --> 00:20:16.100 Eyal Balla: And when you run them you run them using gathers because we can when you run a weight on something. Okay, this makes the the
144 00:20:16.570 --> 00:20:24.700 Eyal Balla: higher level function. Wait till it's done. Okay, this is a way to synchronize as in context.
145 00:20:25.220 --> 00:20:29.610 Eyal Balla: Okay, so here you synchronize multiple as in context, using gather.
146 00:20:31.990 --> 00:20:41.489 Naty Harary: I see. So you just gather all the chunks that you have, and you create them with the asset iterator rather than just give a big function and just asking on that right? That's.
147 00:20:41.490 --> 00:21:00.950 Eyal Balla: Because you want to split your context into smaller processing units, each of them may be I/O bound so together the I would run together on each of the in parallel. On each of the items.
148 00:21:01.940 --> 00:21:03.429 Naty Harary: Got it. Thank you.
149 00:21:06.130 --> 00:21:07.540 Eyal Balla: Okay. So
150 00:21:08.060 --> 00:21:27.009 Eyal Balla: now, like I said before, so enrichment haps happens in parallel. And but still you can scale out. So you can have the multiple services. And so the total performance here is, not blocked. And also small customers are not impacted by the large customers.
151 00:21:30.120 --> 00:21:34.040 Eyal Balla: Okay. So some other things you should take into consideration.
152 00:21:34.300 --> 00:21:45.839 Eyal Balla: So I think the 1st thing is exception handling. So when you create as in context, you sometimes need to handle exception in the the top level.
153 00:21:46.000 --> 00:22:04.660 Eyal Balla: So when you do that you can register manual exception handler, so you get the the main loop and set the exception handler, and you can handle the main the errors from that are created from each of the tasks
154 00:22:06.276 --> 00:22:16.647 Eyal Balla: separately, because if you don't do that, then the the Asyncaio context would ha would behave
155 00:22:18.610 --> 00:22:27.379 Eyal Balla: it. It would exit on each of the when each when one of the sub core teams throws an exception into the main context.
156 00:22:27.760 --> 00:22:28.620 Eyal Balla: Okay?
157 00:22:28.810 --> 00:22:34.353 Eyal Balla: So sometimes you want to wait, maybe maybe for the last one, or
158 00:22:35.440 --> 00:22:41.499 Eyal Balla: perhaps some other behavior that is specific for your system. And you can do this this way
159 00:22:42.607 --> 00:22:54.359 Eyal Balla: specifically for gather you can have 2 ways to handle exceptions, so you can do it. Inside each of the core routines like we I did before, or you can
160 00:22:54.610 --> 00:23:16.869 Eyal Balla: ask the gather to collect all the exceptions from each of the core routines, and then you can handle errors together. For instance, if you want to have some retry mechanism, then this is a good way to do it. So you gather all the errors, and then you can retry all those that failed, or decide to do whatever you want to do with those that did not succeed.
161 00:23:19.144 --> 00:23:29.915 Eyal Balla: Regarding testing. So I think, if you look at this core routines what I want to test here is I want to test, maybe.
162 00:23:32.830 --> 00:23:40.820 Eyal Balla: functional response. Okay, something like a happy path and maybe an exception to test the raise for status.
163 00:23:42.300 --> 00:23:50.960 Eyal Balla: So the important part is to mark your test as pi test mark asking Kyle, so this allows you to run test in asking context.
164 00:23:51.770 --> 00:23:57.170 Eyal Balla: There's like Htpx gives Htpx mock. So you can use that.
165 00:23:57.300 --> 00:24:04.819 Eyal Balla: And and then you can inject the response. Here, for instance, and test your happy flow.
166 00:24:05.150 --> 00:24:17.508 Eyal Balla: and also you can always use pytest raises like you did before. And assuming you marked as Asyncio, you can. Test the flow of async and
167 00:24:18.130 --> 00:24:19.460 Eyal Balla: exception flow.
168 00:24:19.720 --> 00:24:20.520 Eyal Balla: Okay?
169 00:24:22.605 --> 00:24:23.380 Eyal Balla: Sorry.
170 00:24:24.240 --> 00:24:31.040 Eyal Balla: What you can also do is there's Async mock like a unit test magic mock
171 00:24:32.065 --> 00:24:40.340 Eyal Balla: you can mock coroutines. So here's an example of how you mark a coroutines and test it. So
172 00:24:40.510 --> 00:24:48.583 Eyal Balla: this is something that's nice to know, and I think it's very valuable when you're testing and mocking
173 00:24:50.250 --> 00:24:51.110 Eyal Balla: coroutines
174 00:24:51.798 --> 00:25:02.409 Eyal Balla: I think that today the default patch returns in a Async context, or a mock on a magic mark or an Async mark, according to the
175 00:25:02.938 --> 00:25:09.211 Eyal Balla: type of function that it gets. So if this is the core routine, then this would return.
176 00:25:10.050 --> 00:25:17.320 Eyal Balla: create this as an Async mark, and if not, it be a magic mark according to what is needed.
177 00:25:18.980 --> 00:25:24.740 Eyal Balla: Something else that's very important for developers is the ability to debug.
178 00:25:25.240 --> 00:25:33.950 Eyal Balla: So I think Kyle gives a debug mode when you run with the environment variable. You get
179 00:25:34.473 --> 00:25:43.669 Eyal Balla: also track, trace track trace backs on asking functions when they're not awaited. So you can find out where where this happens, and when
180 00:25:44.410 --> 00:25:57.470 Eyal Balla: and also this monitors thread safety. So when you, behave, something in your system behaves unsafe regarding the different core routines and the memory they touch.
181 00:25:57.900 --> 00:26:08.020 Eyal Balla: So you get errors in your in your logs. And also this helps debugs debug slow core routines. Because.
182 00:26:08.592 --> 00:26:10.857 Eyal Balla: I think Cayo is very
183 00:26:12.057 --> 00:26:24.449 Eyal Balla: very sensitive to having core routines and long coroutines blocking short coroutines. So this actually helps you understand better the flow of your code once you use Async I/O
184 00:26:26.425 --> 00:26:38.450 Eyal Balla: so this is how a slow log look looks like. So if I do something very slow, you'd get like a log, saying, this is this has taken too long. Okay? So you would know that
185 00:26:38.890 --> 00:26:40.749 Eyal Balla: you want to look at dysfunction.
186 00:26:42.468 --> 00:26:46.551 Eyal Balla: Also something you want you might want to consider is
187 00:26:47.599 --> 00:26:52.540 Eyal Balla: having something that solvers running in your context in your services.
188 00:26:53.396 --> 00:27:01.890 Eyal Balla: So aio debug allows you to log slow callbacks inside your production pods.
189 00:27:02.010 --> 00:27:08.362 Eyal Balla: And this you can enable a specific
190 00:27:09.420 --> 00:27:12.209 Eyal Balla: callbacks when this happens. And this is
191 00:27:12.340 --> 00:27:14.906 Eyal Balla: really great, because this has
192 00:27:16.144 --> 00:27:20.340 Eyal Balla: almost no performance impact on the actual services.
193 00:27:20.490 --> 00:27:26.070 Eyal Balla: And it allows you to understand better how your code behaves in production.
194 00:27:27.820 --> 00:27:28.650 Eyal Balla: Okay?
195 00:27:29.270 --> 00:27:30.080 Eyal Balla: Great
196 00:27:31.981 --> 00:27:46.289 Eyal Balla: also, something you can do is you can monitor each of the the the different tasks. There's asking Kyle, get all tasks and
197 00:27:46.770 --> 00:27:50.107 Eyal Balla: current tasks. So you can run
198 00:27:51.380 --> 00:27:56.220 Eyal Balla: a core routine once in a while to understand what is running and
199 00:27:56.340 --> 00:28:00.020 Eyal Balla: and get the stacks and understand the behavior.
200 00:28:00.690 --> 00:28:01.500 Eyal Balla: Okay.
201 00:28:03.120 --> 00:28:11.940 Eyal Balla: So this is about it. So I went over the Asynch concurrent programming framework.
202 00:28:12.702 --> 00:28:27.219 Eyal Balla: I think we saw a real world example and understood a bit how I think I behaves, and something, and why we want we'd want to use it. And also we looked at some debug testing and exceptional handling tools.
203 00:28:27.810 --> 00:28:28.950 Eyal Balla: and that's it.
204 00:28:31.170 --> 00:28:32.000 Eyal Balla: Questions.
205 00:28:36.240 --> 00:28:36.940 lapid: Can I?
206 00:28:39.040 --> 00:28:40.060 lapid: Do you hear me?
207 00:28:40.820 --> 00:28:41.869 Gabor Szabo: Yes, yes, we can hear you.
208 00:28:41.870 --> 00:28:56.800 lapid: Oh, Hi, yeah, Hi, so you touched a little bit on it. But I'm when I'm doing something that I called it like a project that develops into something a little bit bigger. I find myself sometimes I I just get lost.
209 00:28:57.150 --> 00:29:01.299 lapid: Oh, I I can't verify myself that I actually
210 00:29:02.800 --> 00:29:06.060 lapid: control all the coroutines properly, because many times
211 00:29:06.430 --> 00:29:20.690 lapid: queues that feed one another like I have some streaming, and then some queues and something like that. And so you touched a little bit on that, and how you how you monitor that! But can you expand a little bit like how do you deal with that cause. I I just
212 00:29:21.140 --> 00:29:29.730 lapid: afterwards I go back, and I just print constantly, and I check the timing, and I waste a lot of time on that, and I feel like maybe someone more experienced has a better solution.
213 00:29:31.030 --> 00:29:34.775 Eyal Balla: So I think, whe when you
214 00:29:35.460 --> 00:29:41.375 Eyal Balla: the, I think that the 1st thing is to build your software like in
215 00:29:42.340 --> 00:29:44.319 Eyal Balla: even though it's Async.
216 00:29:44.440 --> 00:29:59.850 Eyal Balla: you need to build it like a top down architecture, understanding which parts are calling what other the other parts, and making sure that when you synchronize correctly, then, once you do that, things are easier. I think.
217 00:30:01.503 --> 00:30:12.799 Eyal Balla: So you need so like other others. Other considerations in software development. You need to have a a solid design
218 00:30:13.250 --> 00:30:17.059 Eyal Balla: as a as a beginning, right? And then you can use
219 00:30:17.707 --> 00:30:21.539 Eyal Balla: something like the test monitor right here.
220 00:30:21.650 --> 00:30:26.649 Eyal Balla: So you can add this as something that you can call within your code.
221 00:30:27.310 --> 00:30:35.309 Eyal Balla: And this actually helps you understand the the different core routines that are run at the same time
222 00:30:35.530 --> 00:30:57.230 Eyal Balla: and can help, you understand, together with the slow core routines, understand the impact of each of the the different coroutines running. And when you, I think that when you say I want to understand. So you have some kind of a problem, right? You have, maybe something that doesn't get the ability to run at all.
223 00:30:57.380 --> 00:31:07.317 Eyal Balla: and you don't know why. So the reason to this is probably something is blocking the the main loop right? It's too long. So you'd get
224 00:31:08.220 --> 00:31:17.930 Eyal Balla: messages on the slow callbacks. And then you would see this in the running tests and understand the context of how it ran.
225 00:31:19.290 --> 00:31:21.089 Eyal Balla: So does this make sense.
226 00:31:21.380 --> 00:31:46.119 lapid: Yeah, some something on that on that area. It it's more so that I when the polish gets big enough, I you know, I've designed patterns for code that I know that I follow. That helps me, you know, every time again, to a code that I didn't touch for you, I know, like, okay, this is how I what I do in order to actually add a new feature. But somehow, when I when I develop with, I think.
227 00:31:46.430 --> 00:32:05.980 lapid: unless it's something the whole development many times like, if I want to change some change, something in the future, I find myself having to go very deep into the cold like, I don't mind this, or maybe I just don't know how to do a design partner. Well, and for my expense just affect the stuff that
228 00:32:06.150 --> 00:32:15.399 lapid: change in their behavior from something that's asynchronousy to asynchronically had forced me to change my code way deeper than I wanted.
229 00:32:15.650 --> 00:32:22.590 lapid: So this is what actually, I'm I'm curious about this is like, this is the pendate I experienced.
230 00:32:23.800 --> 00:32:28.240 lapid: did it? Didn't like next like, Are you? Are you?
231 00:32:28.430 --> 00:32:40.939 lapid: The the something changing in the future. I want to add something, and this thing now is let's say I. I have some. I'm scraping some information, and I'm leaving it, and I want to do it in parallel.
232 00:32:41.100 --> 00:32:44.689 lapid: But and I have an existing project that was not
233 00:32:44.840 --> 00:32:54.990 lapid: so so far didn't assume anything that has to be in parallel cause. Cause I I had a different data source that I used before, and it was way, way, way faster. So now.
234 00:32:54.990 --> 00:32:55.840 lapid: so.
235 00:32:56.690 --> 00:33:02.479 Eyal Balla: So I I think what you would do is you would add, maybe an Asyncare context to
236 00:33:02.620 --> 00:33:06.920 Eyal Balla: part of the code right, and then
237 00:33:07.310 --> 00:33:14.299 Eyal Balla: run it, maybe, with Asynchaire run, and the rest would remain synchronous.
238 00:33:14.780 --> 00:33:20.479 Eyal Balla: So you can limit the the extent of what you're looking to.
239 00:33:21.090 --> 00:33:27.019 Eyal Balla: and also, as always be sure to test the specific part
240 00:33:27.350 --> 00:33:32.620 Eyal Balla: as a as as a different, like a different library, that you're calling
241 00:33:33.050 --> 00:33:35.920 Eyal Balla: and and treat it like one
242 00:33:36.190 --> 00:33:44.869 Eyal Balla: so like a different code component, a different part of the code and put it somewhere. That's self-contained
243 00:33:46.018 --> 00:33:48.710 Eyal Balla: and maybe that can help.
244 00:33:49.990 --> 00:34:00.119 lapid: Yeah. So so what you're describing is how I solved it. But I didn't. I was not. Actually. I was asking myself like if I had to go over the project again.
245 00:34:00.440 --> 00:34:06.849 lapid: saying, Oh, maybe in the future some I will have some asynchronic way, some asynchronic part.
246 00:34:07.720 --> 00:34:13.109 lapid: I want to actually prepare my code for the possibility of something as running in Async in the future.
247 00:34:13.980 --> 00:34:17.570 Eyal Balla: So I can tell you that we had.
248 00:34:18.586 --> 00:34:23.349 Eyal Balla: we needed to move from synchronous code to Async code in our company.
249 00:34:23.860 --> 00:34:25.130 Eyal Balla: And this is a
250 00:34:25.620 --> 00:34:31.530 Eyal Balla: this is, quite a big migration, because, as I, as I described in the beginning of the talk.
251 00:34:31.690 --> 00:34:39.639 Eyal Balla: using Asyncahyo is like something very different than the design of a synchronous program.
252 00:34:40.050 --> 00:34:43.910 Eyal Balla: So I don't think I have like a
253 00:34:44.429 --> 00:34:56.759 Eyal Balla: anything that I can say. Well, if you write a synchronous problem, and you want to prepare, do this and that because I think that you need to look at it in a very different way. Writing Async code and sync code.
254 00:34:57.500 --> 00:35:01.580 lapid: Okay. So it sounds like you went through the same problems I had. So.
255 00:35:02.470 --> 00:35:02.940 Eyal Balla: Yeah.
256 00:35:02.940 --> 00:35:04.480 lapid: At least we suffer together.
257 00:35:06.480 --> 00:35:08.990 Eyal Balla: Suffering. Sharing is always good.
258 00:35:08.990 --> 00:35:11.800 lapid: Yeah, yeah, thank you.
259 00:35:12.560 --> 00:35:13.260 Eyal Balla: You're welcome.
260 00:35:15.480 --> 00:35:16.050 Eyal Balla: Anything else.
261 00:35:16.050 --> 00:35:21.090 Naty Harary: Yeah. Yeah, I have a question. I'm using a lot of 3rd party.
262 00:35:21.766 --> 00:35:39.670 Naty Harary: Libraries. Test Api sequel. Alchemy like that. And they sometimes hide the implementation of I think I/O, and I always wondered, because I just believe it works well. Is there any way to worry the event loop. So I know.
263 00:35:39.910 --> 00:35:43.440 Naty Harary: like, what's running right now.
264 00:35:43.810 --> 00:35:48.510 Naty Harary: Is it even possible? Is that something that python hides from us completely?
265 00:35:48.690 --> 00:35:56.280 Eyal Balla: So so this is like a way to query all the tasks that are running in Asyncayo.
266 00:35:56.680 --> 00:35:57.110 Naty Harary: All right.
267 00:35:58.330 --> 00:36:06.459 Eyal Balla: And also there's a library I did not talk about here, and it's called Aio Monitor. So you can look into that, too.
268 00:36:07.030 --> 00:36:08.999 Eyal Balla: And it's very nice.
269 00:36:09.965 --> 00:36:11.860 Eyal Balla: So you can try that, too.
270 00:36:12.550 --> 00:36:15.994 Naty Harary: Alright cool cause you talked about the timing, so I didn't know if
271 00:36:16.470 --> 00:36:19.789 Naty Harary: if there are the concerns but a or mine, too. That's cool.
272 00:36:19.930 --> 00:36:20.890 Naty Harary: We'll check it.
273 00:36:22.530 --> 00:36:23.380 Naty Harary: Thank you.
274 00:36:27.600 --> 00:36:29.680 Eyal Balla: Okay, so I think we're done.
275 00:36:30.493 --> 00:36:46.420 Eyal Balla: Thank you guys for listening. And you can reach me this email or Linkedin. And also there's a Github project with this presentation and all the code samples together.
276 00:36:47.370 --> 00:36:51.650 Eyal Balla: I can. I think I sent it to Gabor last time, but I can send it again.
277 00:36:51.880 --> 00:36:53.749 Eyal Balla: and he can spread it out.
278 00:36:53.970 --> 00:36:58.322 Gabor Szabo: Yes, that would be a good idea. I think I'm going to include it in in the there is this
279 00:36:58.740 --> 00:37:09.540 Gabor Szabo: web page about the the presentation which will be linked from the video. And and then on that page you'll see also, I include these these links as well.
280 00:37:09.810 --> 00:37:12.380 Gabor Szabo: Oh, so your your Linkedin, and your
281 00:37:12.870 --> 00:37:15.660 Gabor Szabo: and the link to your that Github page.
282 00:37:15.950 --> 00:37:16.730 Gabor Szabo: We'll get to.
283 00:37:16.730 --> 00:37:17.390 Eyal Balla: Okay. Great.
284 00:37:17.390 --> 00:37:18.530 Gabor Szabo: Repository.
285 00:37:18.820 --> 00:37:19.959 lapid: It's a nice, clear.
286 00:37:19.960 --> 00:37:22.739 Gabor Szabo: No more questions. Then. Thank you very much.
287 00:37:23.530 --> 00:37:27.019 Gabor Szabo: Yeah, thank you. Everyone for participating. And.
288 00:37:27.020 --> 00:37:28.569 Eyal Balla: I think there's 1 more question.
289 00:37:28.570 --> 00:37:31.890 lapid: Oh, I if I can ask chitchat questions.
290 00:37:32.120 --> 00:37:32.950 Gabor Szabo: You're good. Go ahead.
291 00:37:32.950 --> 00:37:37.289 lapid: So you said you you have a company like what your company does, and
292 00:37:37.430 --> 00:37:39.700 lapid: can you elaborate a little bit for more.
293 00:37:40.840 --> 00:37:43.977 Eyal Balla: Sure. So scenario, we do.
294 00:37:45.833 --> 00:37:55.216 Eyal Balla: we do security for health for healthcare. So we give hospitals tools to understand security posture and
295 00:37:56.927 --> 00:38:03.010 Eyal Balla: and attack detection. So we detect, malicious content and attacks on hospitals.
296 00:38:04.950 --> 00:38:06.262 Eyal Balla: And I think,
297 00:38:07.670 --> 00:38:16.929 Eyal Balla: because hospitals are very sensitive. So we need to handle like a very high scale, we do with with passive network inspection.
298 00:38:17.150 --> 00:38:19.275 Eyal Balla: And so we handle like,
299 00:38:20.770 --> 00:38:30.910 Eyal Balla: quite a lot of information in our cloud. So we need to use tools and also using asyncaio helps us
300 00:38:31.040 --> 00:38:34.540 Eyal Balla: scale out and handle things as we need.
301 00:38:35.900 --> 00:38:37.260 Eyal Balla: I hope that.
302 00:38:38.536 --> 00:38:39.730 lapid: Get answered.
303 00:38:40.010 --> 00:38:46.181 lapid: Yeah, no, I'm just curious, like, it's very. It's very far from my my expertise. I'm a i'm a data scientist. And
304 00:38:46.960 --> 00:38:54.960 lapid: MI came across a sync when some of my project needed some boost.
305 00:38:55.770 --> 00:39:01.929 lapid: And you're looking also for data scientist. I'm not available now. But in about a month or 2.
306 00:39:03.532 --> 00:39:14.997 Eyal Balla: So I think data scientist is not something that we're currently looking for. But you, you could actually look at the company career page. There are several positions, and
307 00:39:16.130 --> 00:39:19.450 Eyal Balla: we're expanding, and it's it's a good time, I think.
308 00:39:20.570 --> 00:39:22.509 Eyal Balla: Alright. Then brush.
309 00:39:24.170 --> 00:39:24.860 lapid: Alright. Thank you.
310 00:39:26.120 --> 00:39:32.120 Gabor Szabo: So. So thank you. Thank you very much. Thank you, Al, for the presentation, and for all the questions people
311 00:39:32.430 --> 00:39:38.840 Gabor Szabo: and everyone who was watching, please again, like the video, as I told you, and follow the Channel.
312 00:39:38.980 --> 00:39:46.519 Gabor Szabo: And if you would like to present at one of our meetings, then please get in touch with me.
313 00:39:46.790 --> 00:39:53.759 Gabor Szabo: I would be happy to to provide the the place for people to to share their their knowledge.
314 00:39:54.540 --> 00:39:55.679 Gabor Szabo: Thank you very much.
315 00:39:56.000 --> 00:39:56.850 Gabor Szabo: Goodbye.
316 00:39:56.850 --> 00:39:57.250 Eyal Balla: Bye-bye.
317 00:39:57.250 --> 00:39:57.590 Dmitry Morgovsky: Sure.
318 00:39:57.590 --> 00:39:58.919 lapid: Bye-bye. Thank you.
319 00:39:59.980 --> 00:40:01.209 Shalaka Deshan: Thank you, anyway.
