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Hello and welcome to this lecture, where we are going to create a new project in bicarb to connect

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our genetic algorithm to the database we created using my scale so we can click New Project in Dubai

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Sha idea.

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We can define it the name of the project, for example, genetic.

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And here you can specify the folder you were going to save it.

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We are going to use the goal in that environment.

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So when we created the project, a new environment will be created in Anaconda that we installed before.

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Let's click Create.

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We can delete this file that was automatically generated.

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Let's create a new by file how will call genetic algorithm.

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And now we can import some libraries from random in part, random in part.

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Mads Lots lib dots by plot s VLT.

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This is a library to visualize graphs by them and also lets you boards by my L to contact our Python

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file through the database.

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When we try to run this code, see, that's when it was returns because there is no module named Matt

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blot the Lib, so it means we need to install this package.

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We can click through, you know, here and let's type B install Matt Blot Lib.

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This is a Python Colman's to install libraries.

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Run this code.

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We can see that the downloads process has already started.

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After that, we can see that the package was installed.

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Now we need to install by my --.

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Well, let's type people install by my ask.

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You'll run this code.

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We can see the message successfully installed.

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Now we can try to run this code again.

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See, that's no air or was returned.

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So it means that the libraries were installed correctly.

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We will.

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We use the same code we implemented as before.

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So we'll just based the code.

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Here it is this same.

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We implemented step by step in Google CoLab.

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Glass products, glass in the video glass genetic algorithm.

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And now we need to generate the list of products because we are not going to use up by phone list as

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we did before.

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The idea is to connect to the database in order to do that.

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We can create a main function here in by Shaam.

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If Maine equals Maine, we can see here these arul.

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It means that every time we run these codes, the flow of the program will start executing all the codes,

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which is inside this block.

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We can create our products list and an empty list, and now we can connect to our database.

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So I will create this new variable connection.

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Let's call the new library dots connect and we need to specify so parameters.

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The first one host local hosts.

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It means that we are connecting to our local machine.

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If you are using another database which starts in the internet, you can just put the IP number, the

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next parameter user ID.

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The phone user in this database is roads and the order parameter.

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The passwords.

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Now you'll need to specify here that passwords you choose when you install the library.

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In this case, here I use this best word here.

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One two three four, five, six, seven and eight and the last parameter.

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The database, which defines the name as products.

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As we can see here in work bank, let's create another variable cursor, equal connection dots cursor.

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It means that we are connecting to the database.

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Now we can execute some queries.

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Cursor.

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But is it cute and we can type ASCII L code?

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For example, this code here just selects all the columns so we can type here the name of the columns.

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For example, we want to get product name space price quantity from products.

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We can just copy these codes and go back to the workbench.

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When we run this code, we will select all Carlos products, the names, base price and quantity.

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We can type that code here, select and run.

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See that we are specifying only the columns we want to get product name, space, price and quantity.

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Now we can go through these results for products.

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This is a new variable and great email in cursor, and let's pourrions the product.

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Now we can run this code, see that we are going through each one of the rows of our data sets.

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We are going through these stable here.

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We can see that we have positioned zero position one and position two.

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If we type here, position zero, we will get only the names.

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We can.

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Also type products was the position number one.

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We can see this basis and in position number two, we will see the prices of the products now that we

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have the information we need.

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We can access products list, but up bands.

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We will create a new object product and let's sans the parameters.

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The first one, as we can see, is the name of the product.

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This second one, this base was issue one and the third one, the price was issue number.

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Sure, we can put these quotes in comments, and after executing the aquaria in the database, we can

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close the cursor.

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And also we can close the connection to release the memory.

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After that, we can print products lists.

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Let's run these codes and we can see that we have one object in each one of the positions.

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We can also implement a for loop just to see the results for product in product list for its product.

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Let's run this code.

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We can see the objects and just see the names we can just type product that name.

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Run this code and we have the names of each one of the products.

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But there's something additional in this code, which is the quantity column.

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For example, there are five cell phones on the start and that are two TV 55.

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So we need to create five cell phone objects and to be these 55 objects.

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And regarding order products, we can see that that are then ventilators.

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So we need to create than objects regarding this product should do that is quite simple.

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We can just implement another far loop here.

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For I in range product imposition number three, we can see that position zero is the name World Space

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Shoe is the price and position three is the quantity and odds each one of the products in the list.

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We can just run this code again, and now it's easy to see the results.

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There is only one refrigerator a.

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And there are five cell phones.

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We can see that there are three 550 for the VFR de Q and so one we can also bring two here product list.

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Let's check the length.

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Run this code.

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See that before there were 14 products and now that are 47 products.

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Basically, this is the only change we need to perform to run the genetic algorithm connected to my

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scale.

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We just need to access the product stable.

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Now we can put all these screens in commands and then we'll just base this same code we had implemented

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before.

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We can see here that we are creating this basis prices and names variables.

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We are going through each one of the products for these seven products, then limits population size,

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mutation, number of four generations.

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We are creating here the genetic algorithm.

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And after that, we are calling this solve methods.

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We can run this set of codes.

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And now we can see the results, for example, in generation number zero.

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The total prize was won.

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It means that this space occupied by all the products exceeded the maximum capacity of the truck as

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we saw earlier, and the chromosome is different that are more products are here because before there

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were only 14 products and now that are four, these seven products because we are considering the quantity

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we can see here that we have bad results.

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Total price is equal to one for all generations, and it may have been because now there are more products

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and we have the limits only three.

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So we need to increase the size of the limits to work with more products.

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Let's change should then run this code again.

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And now we can take a look at this solution.

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For example, generation zero four thousands.

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And this base is equal to zero point zero nine in generation one.

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The total prize equals one because as we can see here than point six, the six is greater than the capacity

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of the truck.

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We can see all the results considering all the generations.

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And finally, we can see that the best solution was found one generation for this seven, and the total

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price is fifty five thousand.

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And this space equals 9.10.

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And here we can see the products that we are going to load on the truck.

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Something very interesting about this new implementation, considering the quantity of the products,

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is that there are five cell phones and all of them are going to be loaded on the truck.

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On the order of hands that are banned, ventilators and only five of them were loaded.

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And it happens because this space occupied by this cell phone is less then this space occupied by the

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ventilator.

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And the price of the ventilator is only one hundred and ninety nine, and the price of the cell phone

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is two thousand one hundred and ninety nine.

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So the genetic algorithm will adapt to this kind of situation.

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It's very interesting because the genetic algorithm knows that when loading more cell phones, the profits

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will be bad.

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We can try to run this code again.

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As I said before, a good way to test the algorithm is to run it for a couple of times and see the results.

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See, that's now.

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The best solution was found on generation number 59.

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And the total price is a little lower than the last is a crucial.

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And we can see that's only for cell phones were loaded on the truck.

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And regarding the ventilator.

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Only three of band were is on that trip.

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And finally, we can see the graph with the results here.

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So we'll put this quote here.

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BLT Dot plots the healthy dots by, though we are using the matte blot label library to see the results.

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Let's run again.

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And then we can follow their results, considering each one of the generations something very similar.

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We implemented using Google CoLab and we can see the results 50 Q, and then you can take a look at

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the products that will be loaded on the truck for cell phones.

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Now we are loading Refrigerator A..

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And in this solution, we are going to load one two three four five six ventilators.

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And just a reminder, if you are also fans of a company, you need to sand's.

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This list of products should be manager of the company, and in the next section of the course, you

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are going to learn how to work with genetic algorithm libraries.

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See you there!