MNE-Python is an open-source software package for M/EEG data analysis, providing state-of-the-art algorithms implemented in Python for preprocessing, source localization, statistical analysis, and functional connectivity estimation. It is tightly integrated with scientific Python libraries and the neuroimaging ecosystem, and is available under the new BSD license. MNE-Python offers a comprehensive analysis pipeline, including preprocessing, noise reduction, and advanced methods like ICA, decoding, and functional connectivity estimation. It supports various data formats and provides tools for data visualization and analysis. The software is designed to be flexible, efficient, and user-friendly, with a large number of features and a growing set of tools. MNE-Python is used by researchers worldwide for M/EEG analysis, and its open-source nature allows for collaboration and sharing of best practices. The software is continuously developed and improved, with a focus on accuracy, efficiency, and readability. MNE-Python is an essential tool for M/EEG research, enabling researchers to analyze and interpret complex data with high accuracy and reproducibility.MNE-Python is an open-source software package for M/EEG data analysis, providing state-of-the-art algorithms implemented in Python for preprocessing, source localization, statistical analysis, and functional connectivity estimation. It is tightly integrated with scientific Python libraries and the neuroimaging ecosystem, and is available under the new BSD license. MNE-Python offers a comprehensive analysis pipeline, including preprocessing, noise reduction, and advanced methods like ICA, decoding, and functional connectivity estimation. It supports various data formats and provides tools for data visualization and analysis. The software is designed to be flexible, efficient, and user-friendly, with a large number of features and a growing set of tools. MNE-Python is used by researchers worldwide for M/EEG analysis, and its open-source nature allows for collaboration and sharing of best practices. The software is continuously developed and improved, with a focus on accuracy, efficiency, and readability. MNE-Python is an essential tool for M/EEG research, enabling researchers to analyze and interpret complex data with high accuracy and reproducibility.