The escalating use of social media in recent years has made the study of opinion dynamics a crucial area for understanding societal trends. As digital communication platforms continue to shape collective consciousness, understanding the evolution, interaction, and spread of opinions has become imperative. Researchers have approached this phenomenon from a variety of perspectives, ranging from sociology to data analytics to computational simulation. To address the challenges posed by the multifaceted and multidisciplinary nature of this research, coupled with the recent scarcity of data, computational simulation has emerged as a key tool for understanding opinion dynamics in social networks. This paper presents a Python library, DOCES, designed to simulate essential features of real-world social networks. The library includes the simulation of a social network algorithm, user prioritization, and the ability to model changes in friendships.