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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
| Date | Stars |
|---|---|
| 2026-07-24 | 2741 |
| 2026-07-25 | 2741 |
| 2026-07-28 | 2741 |
| 2026-07-30 | 2741 |
| 2026-08-06 | 2741 |
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Momentum
0.0
growth rate 0.00%/day
.. image:: https://raw.githubusercontent.com/mars-project/mars/master/docs/source/images/mars-logo-title.png
|PyPI version| |Docs| |Build| |Coverage| |Quality| |License|
Mars is a tensor-based unified framework for large-scale data computation
which scales numpy, pandas, scikit-learn and many other libraries.
`Documentation`_, `中文文档`_
Installation
------------
Mars is easy to install by
.. code-block:: bash
pip install pymars
Installation for Developers
```````````````````````````
When you want to contribute code to Mars, you can follow the instructions below to install Mars
for development:
.. code-block:: bash
git clone https://github.com/mars-project/mars.git
cd mars
pip install -e ".[dev]"
More details about installing Mars can be found at
`installation <https://mars-project.readthedocs.io/en/latest/installation/index.html>`_ section in
Mars document.
Architecture Overview
---------------------
.. image:: https://raw.githubusercontent.com/mars-project/mars/master/docs/source/images/architecture.png
Getting Started
---------------
Starting a new runtime locally via:
.. code-block:: python
>>> import mars
>>> mars.new_session()
Or connecting to a Mars cluster which is already initialized.
.. code-block:: python
>>> import mars
>>> mars.new_session('http://<web_ip>:<ui_port>')
Mars Tensor
-----------
Mars tensor provides a familiar interface like Numpy.
+-----------------------------------------------+-----------------------------------------------+
| **Numpy** | **Mars tensor** |
+-----------------------------------------------+-----------------------------------------------+
|.. code-block:: python |.. code-block:: python |
| | |
| import numpy as np | import mars.tensor as mt |
| N = 200_000_000 | N = 200_000_000 |
| a = np.random.uniform(-1, 1, size=(N, 2)) | a = mt.random.uniform(-1, 1, size=(N, 2)) |
| print((np.linalg.norm(a, axis=1) < 1) | print(((mt.linalg.norm(a, axis=1) < 1) |
| .sum() * 4 / N) | .sum() * 4 / N).execute()) |
| | |
+-----------------------------------------------+-----------------------------------------------+
|.. code-block:: |.. code-block:: |
| | |
| 3.14174502 | 3.14161908 |
| CPU times: user 11.6 s, sys: 8.22 s, | CPU times: user 966 ms, sys: 544 ms, |
| total: 19.9 s | total: 1.51 s |
| Wall time: 22.5 s | Wall time: 3.77 s |
| | |
+-----------------------------------------------+-----------------------------------------------+
Mars can leverage multiple cores, even on a laptop, and could be even faster for a distributed setting.
Mars DataFrame
--------------
Mars DataFrame provides a familiar interface like pandas.
+-----------------------------------------+-----------------------------------------+
| **Pandas** | **Mars DataFrame** |
+-----------------------------------------+-----------------------------------------+
|.. code-block:: python |.. code-block:: python |
| | Excerpt of 16,260 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:37b0564f04d1ef6f, topic:pytorch, topic:tensorflow
matched fp:37b0564f04d1ef6f, topic:ray