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Data Theft Repackaged: A Case Study in Malicious Wrapper Packages on npm
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
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|MNE|
MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more.
Documentation ^^^^^^^^^^^^^
Documentation
_ for MNE-Python encompasses installation instructions, tutorials,
and examples for a wide variety of topics, contributing guidelines, and an API
reference.
Forum ^^^^^^
The user forum
_ is the best place to ask questions about MNE-Python usage or
the contribution process. The forum also features job opportunities and other
announcements.
If you find a bug or have an idea for a new feature that should be added to
MNE-Python, please use the
issue tracker <https://github.com/mne-tools/mne-python/issues/new/choose>
__ of
our GitHub repository.
Installation ^^^^^^^^^^^^
To install the latest stable version of MNE-Python with minimal dependencies only, use pip_ in a terminal:
.. code-block:: console
$ pip install --upgrade mne
The current MNE-Python release requires Python 3.9 or higher. MNE-Python 0.17 was the last release to support Python 2.7.
For more complete instructions, including our standalone installers and more
advanced installation methods, please refer to the installation guide
_.
Get the development version ^^^^^^^^^^^^^^^^^^^^^^^^^^^
To install the latest development version of MNE-Python using pip_, open a terminal and type:
.. code-block:: console
$ pip install --upgrade https://github.com/mne-tools/mne-python/archive/refs/heads/main.zip
To clone the repository with git <https://git-scm.com/>
__, open a terminal
and type:
.. code-block:: console
$ git clone https://github.com/mne-tools/mne-python.git
Dependencies ^^^^^^^^^^^^
The minimum required dependencies to run MNE-Python are:
Python <https://www.python.org>
__ ≥ 3.9NumPy <https://numpy.org>
__ ≥ 1.23SciPy <https://scipy.org>
__ ≥ 1.9Matplotlib <https://matplotlib.org>
__ ≥ 3.6Pooch <https://www.fatiando.org/pooch/latest/>
__ ≥ 1.5tqdm <https://tqdm.github.io>
__Jinja2 <https://palletsprojects.com/p/jinja/>
__decorator <https://github.com/micheles/decorator>
__lazy_loader <https://pypi.org/project/lazy_loader/>
__For full functionality, some functions require:
scikit-learn <https://scikit-learn.org/stable/>
__ ≥ 1.1
Joblib <https://joblib.readthedocs.io/en/latest/index.html>
__ ≥ 0.15 (for parallelization)
mne-qt-browser <https://github.com/mne-tools/mne-qt-browser>
__ ≥ 0.5 (for fast raw data visualization)
Qt <https://www.qt.io>
__ ≥ 5.15 via one of the following bindings (for fast raw data visualization and interactive 3D visualization):
PySide6 <https://doc.qt.io/qtforpython-6/>
__ ≥ 6.0PyQt6 <https://www.riverbankcomputing.com/software/pyqt/>
__ ≥ 6.0PyQt5 <https://www.riverbankcomputing.com/software/pyqt/>
__ ≥ 5.15Numba <https://numba.pydata.org>
__ ≥ 0.54.0
NiBabel <https://nipy.org/nibabel/>
__ ≥ 3.2.1
OpenMEEG <https://openmeeg.github.io>
__ ≥ 2.5.6
pandas <https://pandas.pydata.org>
__ ≥ 1.3.2
Picard <https://pierreablin.github.io/picard/>
__ ≥ 0.3
CuPy <https://cupy.dev>
__ ≥ 9.0.0 (for NVIDIA CUDA acceleration)
DIPY <https://dipy.org>
__ ≥ 1.4.0
imageio <https://imageio.readthedocs.io/en/stable/>
__ ≥ 2.8.0
PyVista <https://pyvista.org>
__ ≥ 0.32 (for 3D visualization)
PyVistaQt <https://qtdocs.pyvista.org>
__ ≥ 0.4 (for 3D visualization)
mffpy <https://github.com/BEL-Public/mffpy>
__ ≥ 0.5.7
h5py <https://www.h5py.org>
__
h5io <https://github.com/h5io/h5io>
__
pymatreader <https://pymatreader.readthedocs.io/en/latest/>
__
Contributing ^^^^^^^^^^^^
Please see the contributing guidelines <https://mne.tools/dev/development/contributing.html>
__ on our documentation website.
About ^^^^^
+---------+------------+----------------+ | CI | |Codecov| | |Bandit| | +---------+------------+----------------+ | Package | |PyPI| | |conda-forge| | +---------+------------+----------------+ | Docs | |Docs| | |Discourse| | +---------+------------+----------------+ | Meta | |Zenodo| | |OpenSSF| | +---------+------------+----------------+
License ^^^^^^^
MNE-Python is licensed under the BSD-3-Clause license.
.. _Documentation: https://mne.tools/dev/ .. _user forum: https://mne.discourse.group .. _installation guide: https://mne.tools/dev/install/index.html .. _pip: https://pip.pypa.io/en/stable/
.. |PyPI| image:: https://img.shields.io/pypi/dm/mne.svg?label=PyPI :target: https://pypi.org/project/mne/
.. |conda-forge| image:: https://img.shields.io/conda/dn/conda-forge/mne.svg?label=Conda :target: https://anaconda.org/conda-forge/mne
.. |Docs| image:: https://img.shields.io/badge/Docs-online-green?label=Documentation :target: https://mne.tools/dev/
.. |Zenodo| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.592483.svg :target: https://doi.org/10.5281/zenodo.592483
.. |Discourse| image:: https://img.shields.io/discourse/status?label=Forum&server=https%3A%2F%2Fmne.discourse.group%2F :target: https://mne.discourse.group/
.. |Codecov| image:: https://img.shields.io/codecov/c/github/mne-tools/mne-python?label=Coverage :target: https://codecov.io/gh/mne-tools/mne-python
.. |Bandit| image:: https://img.shields.io/badge/Security-Bandit-yellow.svg :target: https://github.com/PyCQA/bandit
.. |OpenSSF| image:: https://www.bestpractices.dev/projects/7783/badge :target: https://www.bestpractices.dev/projects/7783
.. |MNE| image:: https://mne.tools/dev/_static/mne_logo_gray.svg :target: https://mne.tools/dev/
FAQs
MNE-Python project for MEG and EEG data analysis.
We found that mne demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 3 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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