WEBVTT 00:01.920 --> 00:02.430 Okay. 00:02.430 --> 00:09.750 So I got a question from someone who saw my previous video about the Craigslist scraper. 00:10.380 --> 00:13.380 Um, this is from Shark Tank. 00:13.470 --> 00:16.020 Me or how you pronounce it. 00:16.320 --> 00:19.740 He asked for confessing his love to me. 00:19.740 --> 00:24.000 He asked if I could make a video about going from the array to a CSV. 00:24.600 --> 00:27.510 And of course, I will show you how to do that. 00:27.510 --> 00:29.340 It's super easy. 00:30.290 --> 00:31.730 Um, first. 00:33.120 --> 00:37.590 You need to have the scraper project as we did in the last video. 00:37.590 --> 00:47.340 If you haven't been following the video, then you need to get the project from here inside of the GitHub. 00:47.370 --> 00:54.060 I will link the GitHub in the video description or as a Udemy resource for this lecture. 00:55.140 --> 01:02.160 Um, then you get the project and you should end up with a project looking sort of like this. 01:04.200 --> 01:04.680 Okay. 01:04.680 --> 01:07.260 So we have. 01:09.100 --> 01:13.840 We have this function down here for Scrape Craigslist. 01:13.870 --> 01:20.930 And what we're going to use is something called objects to oops. 01:21.940 --> 01:23.830 Objects to CSV. 01:25.060 --> 01:33.430 So objects to CSV is basically just converting these objects, JavaScript objects to a CSV file. 01:33.910 --> 01:36.490 And of course you could build this yourself. 01:36.490 --> 01:38.700 We could build it all the way from the ground up. 01:38.710 --> 01:42.700 Basically a CSV file is not that complicated. 01:43.750 --> 01:51.490 I mean, it's just columns with a separator like a comma between them and we could do that somehow for 01:51.490 --> 01:52.510 the JavaScript. 01:52.510 --> 01:58.180 But if someone already built it, why not just use their code instead if it works for you? 01:58.600 --> 02:00.370 So that's what we're going to do. 02:02.040 --> 02:02.820 First. 02:02.820 --> 02:05.280 Let's go and get the. 02:07.270 --> 02:07.980 Package. 02:07.990 --> 02:09.820 It's called objects to CSV. 02:09.850 --> 02:13.120 So we say yarn add objects to CSV. 02:15.240 --> 02:22.590 Then let's go and check out what he's writing in here so you can create the objects to csv file here. 02:24.070 --> 02:28.240 And then we can make an async call to create the CSV file. 02:28.240 --> 02:29.140 It's super easy. 02:29.140 --> 02:31.000 You just use the data and pass it in. 02:32.740 --> 02:40.570 I'm going to link to the objects to CSV page here as well, of course, so we can follow along. 02:42.170 --> 02:49.820 So I copy paste this objects to CSV require up here in the in the top and. 02:51.300 --> 02:54.790 Well, then we will make a new async function. 02:54.810 --> 02:57.030 Everything is async these days. 02:58.530 --> 03:02.550 Create a CSV file and we pass in the data. 03:05.570 --> 03:13.550 And then let's just shamelessly copy this code we have from the page here. 03:15.680 --> 03:18.550 And so it's creating a new CC. 03:19.250 --> 03:20.720 It's basically a string. 03:20.720 --> 03:22.730 I'm guessing you're getting out of it. 03:23.180 --> 03:32.390 And from the objects to CSV that we imported up here and you put in the data, which is just this array 03:32.390 --> 03:33.470 of objects. 03:33.950 --> 03:44.120 And then we call a asynchronous function inside of CSV, which is called to Dex to disk, and we just 03:44.120 --> 03:47.770 put in our file name and we get the file. 03:47.780 --> 03:52.790 I'm, I'm not interested in having this console log here, so I'm just going to delete that. 03:52.790 --> 03:54.920 We can read the file afterwards. 03:55.550 --> 03:57.500 Let's try and do it. 03:58.610 --> 04:03.380 Await create CSV file jobs, fold data. 04:04.430 --> 04:04.880 Okay. 04:04.880 --> 04:13.850 So now we can say that the job is done, we can go home and let's write node index. 04:13.850 --> 04:18.390 Just index dot JS Let's see if it writes the file. 04:18.390 --> 04:20.550 It should be writing the file. 04:21.930 --> 04:22.680 Okay. 04:23.790 --> 04:24.540 Tada. 04:25.350 --> 04:34.440 So here we have the header of the csv file with the title and then there's a description and URL. 04:34.470 --> 04:36.900 There's everything that you would need. 04:37.260 --> 04:42.000 Let's try and see if Google sheets can read this. 04:46.730 --> 04:49.940 So I'm just going to upload the file. 04:52.010 --> 04:53.210 Which one is it? 04:54.840 --> 04:55.710 Let's see. 04:57.310 --> 04:58.150 It's this one. 04:59.070 --> 05:01.080 Here is the text CSV. 05:05.490 --> 05:10.740 I just want to see if Google sheets can read this file if it looks okay. 05:11.580 --> 05:14.220 So I say open with Google sheets. 05:21.850 --> 05:23.530 Yeah, it, um. 05:23.980 --> 05:25.360 It looks okay. 05:25.390 --> 05:27.400 We have the description here. 05:27.400 --> 05:30.970 It's a pretty big text, but it's okay. 05:30.970 --> 05:34.810 I think it's a interesting data to have. 05:34.930 --> 05:43.990 Then we have the title and all of the different jobs here and with the compensation address, so on. 05:45.590 --> 05:46.100 Yeah. 05:46.790 --> 05:51.680 Uh, one thing to note is it is that the date posted looks pretty odd. 05:51.860 --> 05:56.780 This is actually the epoch time of the. 05:57.560 --> 06:01.070 The date that we made before, which was a JavaScript object. 06:01.250 --> 06:07.880 So if we try and put it in here, this one is assuming that the timestamp is in milliseconds. 06:07.880 --> 06:12.240 So it's kind of a weird format that the date is in. 06:12.260 --> 06:15.410 Let's try and make it a bit more readable for the data. 06:18.720 --> 06:27.180 So if you're going index.js and instead of having this as a JavaScript date, let's try and just have 06:27.180 --> 06:33.660 it as the date time property from the page itself and let's just run it again and try and see how it 06:33.660 --> 06:35.820 looks inside Google sheets this time. 06:40.530 --> 06:42.240 Da da da da da. 06:43.750 --> 06:45.070 Let me delete this one. 06:47.350 --> 06:49.330 And I think this one is done now. 06:49.330 --> 06:50.230 It's done. 06:50.920 --> 06:53.830 I will upload the new file and check it out. 06:55.000 --> 06:56.730 Check it out now. 06:57.890 --> 06:58.780 Doot doot. 06:58.780 --> 07:00.390 Doot doot doot doot doot doot. 07:00.520 --> 07:02.920 Okay, let's see. 07:08.260 --> 07:13.840 And now we have a lot more readable format for the date, I think. 07:14.710 --> 07:15.550 So. 07:17.170 --> 07:18.100 That was it. 07:18.130 --> 07:19.030 Well, now what? 07:19.030 --> 07:20.960 What are we going to do with the rest of our time? 07:21.000 --> 07:21.760 I don't know. 07:22.390 --> 07:23.970 Uh, go home, relax. 07:23.980 --> 07:25.690 Because we already did our job now. 07:25.690 --> 07:31.180 Which is to convert the Json into an CSV file from the scrape. 07:32.200 --> 07:39.080 If you have any other things you want to know, then feel free to write me in the YouTube or on Udemy. 07:39.100 --> 07:40.750 Questions and Answers. 07:41.200 --> 07:44.800 I'm always curious to see what you would like to learn. 07:44.980 --> 07:45.820 See you.