This program performs the following activities using 4 sub-programs of Python:
- Web scraping using
requestsand receiving data from the web - Analyzing and storing information in the database with
sqllite - Retrieving information from the database and Learning
regressionon them - Get information along with a graphical interface using
PyQt
At the beginning, we use the Spider.py program to analyze the information from the bama website.
In the next step, after analyzing the obtained information, we save it in the database using sqllite This operation is done inside the Storage.py file.
In the next step, we re-read the information from the database and by coding the categorical features into numbers and normalizing them, we prepare it for training by KNNRegression in Foreteller.py.
The Car_Spider_Ui.py file has the task of displaying the graphical interface and receiving information from the user, and after receiving the user's information, it gives it to the small program and controller Car_Price_Predict.py and displays the output in itself.
You can see the general structure of this process in the image below
The database has 9 features, Id, color, ... and final price The structure of the database is very simple and is simulated using sqlite, which easily executes sql commands on it
We use KNeighborsRegressor regression to teach information to the machine. You can read about how it works from this sklearn neighbors.
Finally, the graphic interface of our program with purple color is shown below, which is suitable for receiving sample information for Samand cars, easily by changing two lines of code, it is possible to download all cars and store them in the database, as well as determine the price of all of them, which is possible because of the index. I did not make more than 200 pages of this activity so that only the functionality of the program was tested.
If you have any questions or find a bug in the program, please contact me via email: sinaorojlo53@gmail.com.