README.md

Roof Analysis & Postgre Connexion_Project

🌟 Goal

Send data of buildings to database, analyze their structure,...

👷 Prerequisites

1. install the python libraries below
2. Retrieve the configuration file 'configfile.ini' to connect to the database (caution: check that the file is in the .gitignore)
3. Download and copy this folder into the ressources folder (for the images)

🗒 How it works

1. Install python libraries with pip

    pip install -r ressources/requirements.txt

2. If you need to send data to the database, check that the buildingList.json file is up-to-date

   This file should be placed in the resources folder and can be found on Teams:

   General > DATASET > buildingList.json
   

3. Put the database credentials (contained in the 'configfile.ini) in the ressources folder

   This file should be placed in the resources folder and can be found on Teams:

   General > DATASET > Base De Données - PI² > configfile.ini
   

4. How to run the program?

   One file for each use.
   Launch the one you need
   

🔨 DATASET CREATION - How to retrieve verified buildings from the database ? 📑

1. Importing the necessary modules

   # Driver library to connect and use a PostrgreSQL database
   import psycopg2 
   # Allows you to retrieve the connection parameters from the config file.ini
   import configparser
   # This library allows us to have information about the execution time of our code
   import time

2. We now need to retrieve the credentials to connect to the PostgreSQL database

   These can be found in the configfile.ini file Here is how to read this configuration file in python :

    # Read config.ini file
    config_obj = configparser.ConfigParser()
    try:
        config_obj.read("ressources/configfile.ini")
   
    except OSError as err:
        print("OS error: {0}".format(err))
        print("Unable to find file 'configfile.ini' !")
    dbparam = config_obj["postgresql"]
   
    # Postgre PARAMETERS :
    DATABASE = dbparam["database"]
    HOST = dbparam["host"]
    USER = dbparam["user"]
    PASSWORD = dbparam["password"]

3. Now that we have the prerequisites to retrieve our information, let's create the function that allows us to do this

   def read_database():
       """This function aims to save in a list all the links of the images of the buildings,
          type of roof and their ID
       """
   
       # To measure program execution time
       timer_start = time.time()
       buildings = []
   
       try:
           # Creating the connection to Postgre Database
           connexion = psycopg2.connect("host=%s dbname=%s user=%s password=%s" % (HOST, DATABASE, USER, PASSWORD))
           # Creating the SQL Query Object
           cursor = connexion.cursor()
           # We retrieve 400 verified buildings to create our dataset
           query = "SELECT id,materiau_result,lien_api FROM batiments WHERE materiau_correct='TRUE' LIMIT 400;"
           # Executing the query
           cursor.execute(query)
   
           # Iterating through the query results
           for row in cursor.fetchall():
               # We add to our list 'buildings' the tuple (ID, materiau_result, lien_api)
               buildings.append((row[0], row[1],row[2]))
   
       except (Exception, psycopg2.Error) as error:
           print("An error occurred while connecting to the Postgre database", error)
   
       finally:
           # closing database connection.
           if connexion:
               cursor.close()
               connexion.close()
               print("PostgreSQL connection closed")
               execution_time = round(time.time() - timer_start, 4)
               print(f'"batiments" table reading time :  {execution_time} ')
       return buildings

Now that you have unlocked your skills 🔓, it's up to you 👊!

Complete Python Script : main.py