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We present a unique implementation of Python coding in an asynchronousobject-oriented programming (OOP) framework to fully automate the process ofcollecting data with the George Mason University (GMU) Observatory's 0.8-metertelescope. The goal of this project is to perform automated follow-upobservations for the Transiting Exoplanet Survey Satellite (TESS) mission,while still allowing for human control, monitoring, and adjustments. Prior toour implementation, the facility was computer-controlled by a human observerthrough a combination of webcams, TheSkyX, ASCOM Dome, MaxIm DL, and a weatherstation. We have automated slews and dome movements, CCD exposures, saving FITSimages and metadata, initial focusing, guiding on the target, using the ambienttemperature to adjust the focus as the telescope cools through the rest of thenight, taking calibration images (darks and flats), and monitoring localweather data. The automated weather monitor periodically checks various weatherdata from multiple sources to automate the decision to close the observatoryduring adverse conditions. We have organized the OOP code structure in such away that each hardware device or important higher-level process is categorizedas its own object class or "module" with associated attributes and methods,with inherited common methods across modules for code reusability. To allowactions to be performed simultaneously across different modules, we implementeda multithreaded approach where each module is given its own CPU thread on whichto operate concurrently with all other threads. After the initial few modules(camera, telescope, dome, data I/O) were developed, further development of thecode was carried out in tandem with testing on sky on clear nights. The code,in its current state, has been tested and used for observations on 171 nights,with more planned usage and feature additions.

An asynchronous object-oriented approach to the automation of the 0.8-meter George Mason University campus telescope in Python