SUMMARY Muography is an imaging technique that relies on the attenuation of the muon flux traversing geological or anthropogenic structures. Several simulation frameworks help to perform muography studies by combining specialized codes: for muon generation through muon transport to muon detector performance. This methodology is precise but requires significant computational resources and time. We present an end-to-end python-based MUographY Simulation Code, which implements a muography simulation framework capable of rapidly estimating muograms of any geological structure worldwide. This framework considers the generated muon flux as the observation point; the energy loss of muons passing through the geological target; the integrated muon flux detected by the telescope and estimates the 3-D density distribution of the target using algebraic reconstruction techniques. The simulations ignore the relatively small muon flux variance caused by geomagnetic effects, solar modulation and atmospheric conditions. We validate the code performance by comparing our simulation results with data from other frameworks.