1 00:00:00,300 --> 00:00:04,980 All right, so hopefully you would have found the solution, if not the solution is super simple. 2 00:00:04,980 --> 00:00:09,510 Guys, are we going to do is we're going to make use of a bit of JavaScript concept over here? 3 00:00:09,780 --> 00:00:14,490 That's the reason I really wanted to show this kind of scenario over here so that you can understand, 4 00:00:14,490 --> 00:00:18,940 like what else we can do with the playwright and the power of JavaScript. 5 00:00:19,320 --> 00:00:27,060 So in order to grab all the details from a table, all we're going to do is be defined or find the whole 6 00:00:27,060 --> 00:00:28,320 table like how are we going to do so? 7 00:00:28,320 --> 00:00:34,230 If you remember in our earlier section, we talked about how we can get that data right from a text 8 00:00:34,230 --> 00:00:36,420 box or a text, something like that. 9 00:00:36,540 --> 00:00:38,580 But that was a very, very basic thing that we discussed. 10 00:00:38,700 --> 00:00:44,730 But this time we're going to talk about a bit more advanced concept here, like how we can get the details 11 00:00:44,730 --> 00:00:47,350 from a from a table. 12 00:00:47,670 --> 00:00:55,470 So for doing that, I'm just going to do a const and I'm just going to add to the table result or something 13 00:00:55,470 --> 00:00:59,570 like that, which is going to hold all the whole great table itself. 14 00:00:59,580 --> 00:01:04,770 So I'm going to do something like Badler and the for the first time, I'm going to show you how we can 15 00:01:04,770 --> 00:01:07,850 use a dollar to evaluate this done that. 16 00:01:07,860 --> 00:01:14,580 Our eval is very, very interesting because it's going to evaluate, evaluate the whole dom and you 17 00:01:14,580 --> 00:01:21,930 can tell what you need to really require to search for within your table on your dom. 18 00:01:21,960 --> 00:01:28,200 So in this place, I really required a table off the table roll and then I'm going to get all the rows 19 00:01:28,200 --> 00:01:29,840 from this particular table. 20 00:01:30,450 --> 00:01:37,860 And once I get that, I'm also going to create an array or a two dimensional array for this particular 21 00:01:37,860 --> 00:01:38,220 table. 22 00:01:38,280 --> 00:01:45,810 So you can see that I'm going to use an array dot from method, which is going to have all my rows. 23 00:01:45,810 --> 00:01:51,440 And within that I'm going to hold all the row of the particular table itself. 24 00:01:51,840 --> 00:01:55,610 So within the rows will have columns as well as you know. 25 00:01:55,830 --> 00:02:02,130 So I'm just going to get all the columns that I'm going to grab all the columns off that particular 26 00:02:02,130 --> 00:02:02,450 row. 27 00:02:02,640 --> 00:02:09,930 So for doing that, I really require what is called as a query selector, all method not selected, 28 00:02:09,930 --> 00:02:12,840 because if I've got this right now, it's considered only one column. 29 00:02:14,010 --> 00:02:20,820 All is going to select all the columns, which has a tag of two to basically the column data is going 30 00:02:20,820 --> 00:02:30,270 to be sitting on the TD for us and then I'm going to return the array dart from of all the columns which 31 00:02:30,270 --> 00:02:32,040 we have over here. 32 00:02:32,430 --> 00:02:38,870 And then I'm going to get a specific data from that particular column, which is nothing but not the 33 00:02:38,880 --> 00:02:43,110 columns column, which is going to be the column. 34 00:02:44,780 --> 00:02:51,680 Docked in text so you can get an extra Hesterman or whatever that you want, I can grab those details 35 00:02:51,680 --> 00:02:57,880 right from there and once you have all these details, you have all the details required for your great 36 00:02:57,980 --> 00:02:58,870 table results. 37 00:02:59,150 --> 00:03:00,740 So this is really, really cool. 38 00:03:00,740 --> 00:03:03,050 You can grab all those details right from here. 39 00:03:03,560 --> 00:03:09,980 And once you have all these table information, basically this guy is now a two dimensional array of 40 00:03:10,220 --> 00:03:13,010 data and it has an array of array of data, basically. 41 00:03:13,520 --> 00:03:22,490 And once you have all these details, you can now use our powerful efforts to grab the details and write 42 00:03:22,490 --> 00:03:24,040 on the filesystems. 43 00:03:24,040 --> 00:03:26,150 So I'm just going to use the file system. 44 00:03:26,240 --> 00:03:28,370 Remember, we have been using this a lot as well. 45 00:03:29,480 --> 00:03:35,870 And then I'm going to go all the way down over here and then I'm just going to write consed off. 46 00:03:37,280 --> 00:03:49,520 Maybe a grid data is equal to jasen dot string if I mean, I'm using this a lot as well in this call 47 00:03:49,520 --> 00:03:50,000 so far. 48 00:03:50,450 --> 00:03:53,480 So I'm going to grab the great table result. 49 00:03:53,870 --> 00:04:02,000 I'm going to get all the details and once I have this I can then write file, think of that particular 50 00:04:02,540 --> 00:04:02,940 data. 51 00:04:02,960 --> 00:04:12,800 So I'm going to write something like a great, great table data dard Jasen, which is going to be coming 52 00:04:12,800 --> 00:04:13,970 from that great 53 00:04:16,640 --> 00:04:17,050 data. 54 00:04:17,510 --> 00:04:17,960 That's it. 55 00:04:18,530 --> 00:04:21,840 So once I have all these details, I could be able to write that on the table. 56 00:04:21,860 --> 00:04:32,480 So on the days on file, so right on the JS on file, uh, and you could see the particular result coming 57 00:04:32,480 --> 00:04:34,010 in in this particular folder. 58 00:04:34,070 --> 00:04:34,960 So we'll quickly see you. 59 00:04:35,030 --> 00:04:35,930 How does it really work? 60 00:04:35,930 --> 00:04:38,990 So I'm just going to run this guy data driven technologies once again. 61 00:04:44,580 --> 00:04:49,290 So you can actually see that everything has happened behind the scene, so if you go to the great day 62 00:04:49,330 --> 00:04:52,890 where they are jasen, the data is already there for us. 63 00:04:52,890 --> 00:04:55,590 Guys, you can see that everything is actually coming. 64 00:04:55,590 --> 00:04:57,270 So you can see that is an array of arrays. 65 00:04:57,570 --> 00:05:04,110 I can probably show you in a better view, something like a jasen format or something like that. 66 00:05:04,800 --> 00:05:09,870 And if I just paste this guy, process it, you can see that the data comes in. 67 00:05:10,200 --> 00:05:11,280 So this is the data, right? 68 00:05:11,280 --> 00:05:17,580 Cultic four thousand twenty four one is your automation, catechetical automation, dotcom, the benefits. 69 00:05:17,580 --> 00:05:22,810 Edit and delete some Prashanth Ramish, Jon Tester, the user. 70 00:05:22,830 --> 00:05:25,680 So this is before the delete operation that we are doing. 71 00:05:25,680 --> 00:05:25,950 Right. 72 00:05:26,640 --> 00:05:34,110 So once we perform a lead operation, that particular data that it does, the user will not be there 73 00:05:34,110 --> 00:05:35,290 and that it will be different. 74 00:05:35,730 --> 00:05:36,330 So that's it. 75 00:05:36,390 --> 00:05:43,410 So this way we could see that we could be able to grab data right from the table and we can show that 76 00:05:43,410 --> 00:05:43,740 as well. 77 00:05:43,770 --> 00:05:49,180 So this is another way that we can grab the details and we can export it to adjacent files and stuff. 78 00:05:49,200 --> 00:05:54,510 I mean, the imagination is the only limited I mean, we can keep doing a lot of things on this particular 79 00:05:54,780 --> 00:05:55,440 lab. 80 00:05:55,720 --> 00:05:57,810 But again, your imagination is going to be the limit. 81 00:05:57,810 --> 00:06:00,900 Once again, as I told you, can keep doing whatever that you want to do. 82 00:06:01,290 --> 00:06:03,600 And playwrite is highly, highly extendable. 83 00:06:03,750 --> 00:06:09,660 So this way we could complete that data driven testing and how we can able to manage that data and how 84 00:06:09,660 --> 00:06:15,420 we can even export the data right from the already inserted data, like exploding a great table and 85 00:06:15,420 --> 00:06:16,800 verify that if you want to.