scrap a website ENGIE in python

Web to be scraped: [login to view URL] Tasks: 1) To scrap all the Urgent Market Messages (UMM) available on the website (as from December 2011). Total around 29000 messages 2) To create the database of power plants (part of the data included in UMM) 3) Create the program to scrap the website at the defined interval AD point 1 Website: [login to view URL] 1) Click icon POWER: 2) Chose the time when the message was published: The year: The month: 3) Click on the UMM to be scraped 4) The data from UMM should be saved in the following format (that’s an example from the other database). Type of the database to use – MongoDB or Cosmos DB { "_id" : ObjectId("5df42e7a52eb84588d3c5245"), "status" : "Inactive", "identifier" : "05470_EDF_T_00043331", "version" : 2, "name" : "PALUEL 1", "sector" : "Nuclear", "start_date" : { "$date" : 1576188000000 }, "end_date" : { "$date" : 1576274400000 }, "pub_date" : { "$date" : 1576225269000 }, "type" : "Planned", "cause" : "Complementary informations", "extra_info" : "After its restart, the plant will gradually return by various load threshold to full power. The ramp-up period will take at least 48 hours.\nFirst threshold after restart : 540MW\n-----------------------------------------------------------------------\nAprès son recouplage, la tranche remontera progressivement par palier de charge à sa pleine puissance. La remontée durera au moins 48h.\nPremier palier à atteindre : 540 MW", "max_power" : 1330, "available_power" : 0 } AD point 2 (To create the database of power plants) UMM from point 1 contain all the information we are looking for. There will be however many UMM concerning the same power plant. We need to create a database containing: “Installed Capacity (MW)” “Fuel type” “Bidding zone” “Affected asset” The Database should be in the following format: { "_id" : ObjectId("5e0488e704acf0e036fbe1f7"), "affected_asset" : "DROGENBOS 1", "installed_capacity" : 460 "fuel_type " : “fossil_gas” "bidding_zone " : “10YBE” } Last important points: a. time difference between UK and Europe (1h) b. time change (winter/summer) during spring and autumn (UK and mainland Europe) AD point 3 The scraper should be written in python.