WEBVTT 00:00.380 --> 00:01.100 Hello guys. 00:01.100 --> 00:02.960 So welcome to the Python series. 00:02.960 --> 00:07.970 Uh, now we are going to start our first session with respect to Python. 00:08.030 --> 00:13.400 Now what we are going to do in this video is that, uh, uh, and the entire code that I'm actually 00:13.400 --> 00:17.930 going to specifically write, I'm going to use the VS code ID, uh, vs code ID. 00:17.930 --> 00:24.290 I find it really amazing because here you'll be able to execute your Jupyter notebook files, your.py 00:24.320 --> 00:24.710 files. 00:24.710 --> 00:28.910 Along with that, you'll also be able to create all the environments very much easily. 00:29.090 --> 00:32.660 Uh, so it is feasible that I specifically use VS code. 00:32.660 --> 00:38.030 Along with that, you have lot of features like extensions, code assistance, and many more things. 00:38.150 --> 00:44.090 So the first step, uh, as we are starting, you know, uh, what I'm actually going to do is that 00:44.120 --> 00:50.270 over here, we are going to create our new environment, as I said, um, in this Python series, I'm 00:50.270 --> 00:53.900 going to use the newest Python version that is Python 3.12. 00:53.930 --> 01:00.080 And I am going to teach in such a way that we all, we see all the new features that have actually come 01:00.080 --> 01:05.540 from 3.10 to 3.12, so all the new features that are specifically there. 01:05.750 --> 01:09.410 We will be also discussing about them in this Python series. 01:09.800 --> 01:14.840 Uh, the first step, as you know that I'm going to create an environment and again, why you specifically 01:14.840 --> 01:15.830 require an environment. 01:15.830 --> 01:22.670 Because an environment is necessary whenever you start a new project, because in our Python project 01:22.670 --> 01:27.440 or in our data science project, we make sure that we use multiple packages, multiple libraries and. 01:27.440 --> 01:27.830 All right. 01:27.830 --> 01:33.440 And uh, every couple of months this packages or this libraries have new features and most of them are 01:33.440 --> 01:34.880 open source packages or libraries. 01:34.910 --> 01:35.090 Right. 01:35.120 --> 01:39.920 So they definitely have a lot of features that gets included every couple of months. 01:39.920 --> 01:45.620 So it is always necessary that you always maintain, uh, or try to create your entire projects in a 01:45.620 --> 01:50.990 separate, uh, with a separate environment so that there should be not any conflict, as you probably 01:50.990 --> 01:55.700 go ahead, uh, whenever a new feature is probably coming up, you know, with respect to the packages, 01:55.700 --> 01:59.570 uh, you can actually create a new project, create a new environment out there. 01:59.570 --> 02:03.950 But here, uh, the first step, what I'm actually going to do is that let's go ahead and create our 02:03.950 --> 02:04.430 environment. 02:04.430 --> 02:07.580 And for this also I will be using conda command. 02:07.580 --> 02:10.190 So first of all, I'll not go ahead and write in PowerShell. 02:10.190 --> 02:13.040 Instead, I'll go and click on Command Prompt. 02:13.040 --> 02:15.560 So quickly let's go ahead and write it down. 02:15.560 --> 02:21.860 So here I'm going to write conda create minus p v and v python uh double equal to. 02:21.890 --> 02:25.040 Let's say I want to go ahead with Python 3.12 okay. 02:25.040 --> 02:33.020 And understand one thing is that, uh over here we are using this conda create command v and v is specifically 02:33.020 --> 02:34.370 your environment name. 02:34.370 --> 02:37.160 And which Python version we are specifically using. 02:37.160 --> 02:38.090 It is 3.12. 02:38.120 --> 02:40.520 Again based on different different projects. 02:40.520 --> 02:43.370 It is not necessary that you always need to use 3.12. 02:43.400 --> 02:48.050 It depends on the kind of packages that are available, let's say open source packages. 02:48.050 --> 02:51.830 When we are creating deep learning projects or any machine learning projects as such. 02:51.860 --> 02:52.070 Right. 02:52.070 --> 02:56.630 So but here, uh, since we are learning this Python series completely from basics, I'm going to go 02:56.660 --> 02:58.130 ahead and use this environment. 02:58.130 --> 02:59.750 So once I probably click this. 02:59.750 --> 03:03.320 So here you'll be able to see the installation will start taking place. 03:03.320 --> 03:09.050 And when we are creating a virtual environment, some basic libraries or packages will be automatically 03:09.050 --> 03:10.820 downloaded by this conda command. 03:10.820 --> 03:17.500 So now here you can see over here what are the basic commands, uh, basic new packages that are basically 03:17.500 --> 03:18.310 getting installed. 03:18.310 --> 03:20.110 So here are all the packages. 03:20.110 --> 03:23.320 So I'm just going to go ahead and click on, uh, press Y. 03:23.320 --> 03:27.910 And once I probably do this all the installation of the libraries will happen. 03:27.940 --> 03:28.360 Right. 03:28.360 --> 03:30.790 So it is going to take some amount of time. 03:30.790 --> 03:32.650 Again it depends on your internet speed. 03:32.650 --> 03:34.360 But let me just go ahead and show you. 03:34.360 --> 03:37.660 So here you can see a V and V environment is basically created. 03:37.660 --> 03:40.990 And these are all the default packages that you will be able to find out. 03:40.990 --> 03:43.660 Inside this right there will be a DLL folder. 03:43.690 --> 03:45.490 There will be an include folder. 03:45.520 --> 03:45.850 Right. 03:45.850 --> 03:50.890 So uh what is the basic environment that is required for any Python project. 03:50.920 --> 03:54.010 So that will be covered up inside this particular folder. 03:54.040 --> 03:54.580 Okay. 03:54.790 --> 04:00.520 Now once you go ahead and click this uh now the next thing is that let's say uh, you want to activate 04:00.520 --> 04:01.600 this environment, right. 04:01.600 --> 04:05.440 So in order to activate this environment I will go ahead and write conda activate. 04:05.440 --> 04:09.340 And we go ahead and use this v and v folder itself. 04:09.370 --> 04:09.610 Right. 04:09.640 --> 04:11.050 The same v and v folder. 04:11.050 --> 04:13.930 And here we are just going to give the location of this right. 04:13.960 --> 04:19.110 So once we press this, you'll be able to see that I have activated the venv environment. 04:19.140 --> 04:19.680 Okay. 04:19.770 --> 04:26.040 And now you can probably run any kind of.py files directly from here by using Python. 04:26.400 --> 04:31.170 Specifically, let's say I probably go ahead and create my app.py. 04:31.170 --> 04:36.510 And let's say that I am just going to write over here print one plus one right. 04:36.510 --> 04:38.040 So this is the basic command. 04:38.160 --> 04:41.340 And I'm printing this particular numerical operation one plus one. 04:41.370 --> 04:47.100 Now if I really want to run this app.py I have to make sure that I'm in the same folder location. 04:47.100 --> 04:52.260 I have activated my venv environment and now within this particular environment, we will go ahead and 04:52.260 --> 04:53.760 just execute this file. 04:53.760 --> 04:57.090 In order to execute it, you just need to write python app.py. 04:57.180 --> 05:00.960 So once you do this here, you'll be able to see that I'm able to get the response. 05:00.990 --> 05:01.530 Okay. 05:01.680 --> 05:03.810 Now let me show you one more thing. 05:03.810 --> 05:09.420 Because see as we go ahead with more lectures right I'm actually going to create a folder. 05:09.420 --> 05:13.500 Let's say this is first folder is Python Basics okay. 05:13.500 --> 05:14.670 Python basics. 05:14.670 --> 05:20.890 So inside this folder itself I will go ahead and create my Jupyter notebook file or.py file, anything 05:20.890 --> 05:21.670 that I require. 05:21.700 --> 05:25.270 Let's say I go ahead and create my Jupyter notebook file by default. 05:25.630 --> 05:28.120 Let's say this is my test dot Ipynb. 05:28.360 --> 05:29.020 Okay. 05:29.230 --> 05:35.890 Now this Jupyter notebook file will be the similar Jupyter notebook file that we actually use in Anaconda, 05:35.890 --> 05:36.190 right? 05:36.460 --> 05:42.070 The Jupyter notebook, but in Python also sorry, in VS code you will be able to see that yes, internally 05:42.070 --> 05:46.120 you will be able to execute this text or this Jupyter notebook file also. 05:46.150 --> 05:51.760 Now initially if I go ahead and let's say over here, an option is probably coming up saying that, 05:51.790 --> 05:53.320 hey detecting kernels. 05:53.320 --> 05:59.650 So if I want to say select the same environment right V and V I can go ahead and click on Detect kernels. 05:59.650 --> 06:03.070 So here you'll get an option of selecting the Python environment. 06:03.070 --> 06:05.650 Let's say this is the environment that I have created right. 06:05.830 --> 06:08.890 Uh v and v Python 3.12.0. 06:08.890 --> 06:13.180 And these are all the other environments that I've actually created in my, uh, local system. 06:13.210 --> 06:13.510 Right. 06:13.510 --> 06:16.390 So I'm just going to go ahead and select uh, 3.12. 06:16.420 --> 06:17.320 Oh okay. 06:17.350 --> 06:19.510 Now let's go ahead and execute any code. 06:19.510 --> 06:19.720 Right. 06:19.750 --> 06:21.370 So this is my code cell okay. 06:21.400 --> 06:22.950 I can create any number of codes. 06:22.950 --> 06:25.470 Cell that I really want right now. 06:25.470 --> 06:26.310 Code cell is nothing. 06:26.310 --> 06:30.090 But here I will be writing all my Python code in order to execute it. 06:30.180 --> 06:32.400 Along with that, you also have something like markdown. 06:32.400 --> 06:36.330 So let's say that I, uh, I have this markdown cell. 06:36.330 --> 06:40.590 I can basically write comments saying like this, like let's say Python example. 06:40.590 --> 06:46.830 And if I execute it, in order to execute this cell I have to press shift enter. 06:46.860 --> 06:47.250 Okay. 06:47.280 --> 06:50.760 So if I probably press shift enter automatically this will get executed. 06:50.760 --> 06:55.170 Now the the reason we have used some markdown because I needed to write some information over here. 06:55.170 --> 06:56.160 So like title. 06:56.160 --> 06:57.750 And also I'm writing it over here. 06:57.780 --> 06:58.230 Right. 06:58.230 --> 07:02.280 So if you press shift enter then automatically this cell will get executed. 07:02.550 --> 07:07.770 Uh along with this you also have an option of run all you know, if you want to run all the cells over 07:07.770 --> 07:13.230 here, if you go ahead and, uh, see if you just go ahead and press right click, you'll be having 07:13.230 --> 07:14.550 so many different, different options. 07:14.580 --> 07:15.060 Okay. 07:15.060 --> 07:20.400 But we are just going to use shift run shift enter so that we'll be able to execute it okay. 07:20.400 --> 07:21.330 Now this is fine. 07:21.330 --> 07:24.210 Let's run our first code in Jupyter Notebook. 07:24.210 --> 07:25.830 So if I am going to write one plus one. 07:25.830 --> 07:29.910 So here you can see I'm getting an error running cell with v and v. 07:29.940 --> 07:34.710 Python 3.41 to 0 requires the ipykernel package. 07:34.740 --> 07:37.830 Okay, so this is one of the requirement that we really need to do. 07:38.040 --> 07:40.560 We need to install Ipykernel. 07:40.590 --> 07:41.040 Okay. 07:41.040 --> 07:44.340 So here I'm what I'm going to write is that pip install. 07:44.340 --> 07:49.230 If I want to install any packages I have to just go ahead and write pip install Ipykernel. 07:49.260 --> 07:49.680 Okay. 07:49.680 --> 07:55.410 So once I probably do this you'll be able to see that if I press enter you'll be seeing that hey, my 07:55.440 --> 07:57.210 Ipykernel is basically getting installed. 07:57.240 --> 07:59.130 Now what is this Ipykernel package? 07:59.160 --> 08:03.930 Ipykernel package is nothing, but it provides a kernel to this specific Jupyter notebook, which will 08:03.960 --> 08:07.020 be responsible in executing the Python code. 08:07.050 --> 08:07.560 Right. 08:07.560 --> 08:10.830 It is pretty much necessary and compulsory in Anaconda. 08:10.860 --> 08:14.910 The default Jupyter notebook has Ipykernel already integrated to it. 08:14.940 --> 08:17.610 Okay, so this is the first thing that you really need to do. 08:17.610 --> 08:22.890 Whenever you want to run the Jupyter notebook, you just go ahead and write pip install Ipykernel. 08:22.920 --> 08:27.150 One more thing that you can actually do is that here what I will do, I will go ahead and create one 08:27.150 --> 08:32.950 requirements.txt TXT because this requirements txt you know later on whatever packages I want. 08:32.980 --> 08:35.410 Let's say the first package I want is Ipykernel. 08:35.440 --> 08:40.630 I'll keep a note of this over here and any number of packages I will be requiring let's say in the future 08:40.630 --> 08:44.260 classes you'll be seeing pandas numpy different different packages. 08:44.260 --> 08:46.570 So we will try to install it from here itself. 08:46.570 --> 08:50.920 We'll write over here and we'll run this requirement dot txt which will be responsible in installing 08:50.920 --> 08:51.820 all the packages. 08:51.820 --> 08:55.480 Now you can see that the Ipykernel has got successfully executed. 08:55.480 --> 08:57.910 Now let me just go ahead and run the same code. 08:57.910 --> 09:00.340 So here you'll be able to see if I run the same code. 09:00.340 --> 09:01.990 Now it is just going to execute. 09:01.990 --> 09:03.640 It is saying that connecting to kernel. 09:03.640 --> 09:06.280 And here I am having my output right. 09:06.280 --> 09:09.640 So now I can probably go ahead and write any type of code that I want. 09:09.670 --> 09:11.590 Let's say I want to go ahead and write print. 09:11.620 --> 09:14.350 Hello hello world. 09:14.350 --> 09:14.680 Okay. 09:14.710 --> 09:15.610 Something like this. 09:15.610 --> 09:19.630 So here you'll be able to see that it is executing right for.py file. 09:19.630 --> 09:25.540 I don't want any type of kernel because in the terminal in the terminal automatically that particular 09:25.540 --> 09:28.600 terminal has this environment set up right. 09:28.600 --> 09:33.440 So in order to execute it I have to go ahead and write Python app dot Pi, right? 09:33.620 --> 09:35.030 Or whatever is the file name. 09:35.030 --> 09:40.850 In this case, if I want to execute any cell, I have to just press that particular cell and press shift 09:40.850 --> 09:41.420 enter. 09:41.450 --> 09:41.990 Okay. 09:42.200 --> 09:46.970 So in this video we have discussed about how you can go ahead and create your environment. 09:46.970 --> 09:51.830 Because going forward, any session that is probably going to come up in this course, I'm going to 09:51.860 --> 09:53.990 probably create a folder wise like this. 09:53.990 --> 09:59.600 For the first class I will probably create Python basics, create my Jupyter notebook file or.py file, 09:59.600 --> 10:03.890 execute all the code in front of you, write all the code in front of you and continue right. 10:03.890 --> 10:08.360 So for right now, I will just go ahead and delete this folder because I don't require it. 10:08.360 --> 10:11.180 Because at the end of the day, I will do one thing. 10:11.210 --> 10:12.200 Okay, just a second. 10:12.230 --> 10:13.850 I will just close this okay. 10:14.360 --> 10:14.780 Yeah. 10:14.810 --> 10:16.670 Now let me just go ahead and delete it. 10:16.670 --> 10:22.100 Because in the next session I will go ahead and create everything from scratch requirement dot txt I 10:22.100 --> 10:24.860 will keep it so that I keep on updating my packages. 10:24.860 --> 10:27.470 So yes, this was it from my side. 10:27.470 --> 10:33.320 I hope you like this video and in the next video we will start our Python basics. 10:33.320 --> 10:34.970 So yes, this was it. 10:34.970 --> 10:35.420 Thank you. 10:35.450 --> 10:35.900 Take care. 10:35.930 --> 10:36.560 Bye bye.