Electroretinography is a hightly informative method for diagnosing heterogeneous diseases associated with disorders of the vascular structures. This article describes the biomedical ophthalmic signal of an electroretinogram using wavelet analysis. The spectral characteristics of the signal, the time-frequency picture of the wavelet scalogram are estimated, and approaches to the automation of signal analysis using the available Python libraries are described. The description of the formation of wavelet scalograms of signals using the cwt function of the PyWT library has been formalized. The Gaussian wavelet of the 8th order is chosen as the basic function of the wavelet transform. In order to automate the analysis of wavelet scalograms, the sequence of determining the connectivity of segments using the connectedComponents function from the library of computer vision algorithms, image processing, and general-purpose numerical algorithms with open source OpenCV is described.