This paper presents a new method that combines computer vision skills, like optical character recognition (OCR) technology, with a method for showing Braille characters on a screen. This approach transmutes source codification in Python into the Braille language. The process of mechanically converting text source codes into Braille source codes improves accessibility for individuals with potentially damaged optical systems. The computer system performs preprocessing on stimulation images to heighten the visibility and clarity of text before extracting it using innovative OCR technology. This text is then translated into Braille using a predefined mapping that retains Python syntax. The correctness of this approach is validated by comparing the output with the actual Braille transcription. In addition, people provide novel mathematical techniques to assess the correctness of conversions and analyze the performance of systems. These algorithms assess the accuracy of Braille translation and character recognition to pinpoint areas that need improvement. The findings demonstrate substantial improvements compared to earlier methods, indicating that this methodology has the potential to enhance the productivity and autonomy of visually impaired programmers. By using state-of-the-art OCR and image processing technology, the ongoing efforts enhance the accessibility of programming and elevate computer science education for those with visual impairments.