ClimaticPark is a pyhton library to simulate different environement variables of a vehicular parking lot. By means integrating different algorithms from the Deep Learning and thermodynamics fields, it is able to simulate the following parameters of a parking lot:

• The demand behavior of a PL (entry and exit hours of vehicles).
• The movement of the shadows projected by physical roofs on the PL's spaces.
• Cabin temperature of vehicles while they remain parked in the parking lot.
• The fuel consumption required by the air-conditioning system of these vehicles to cool them down based on a predefined comfort temperature

• lib: Includes the source code of the library.
• demo.ipynb: Jupyter Notebook comprising a step by step guideline to use the library.
• data: Includes the input data required for the step-by-step demo.
• figs: Includes additional figures that describe the library.
• environment.yml: dependencies of the library.

The detailed UML class diagram of the library is provided next,