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- Announcing Python-Blosc2 3.1.0 (and 3.1.1)
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- ==========================================
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+ Announcing Python-Blosc2 3.2.0
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+ ==============================
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- This is a minor release where we optimized the performance of the
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- internal compute engine, as well as indexing for NDArrays. We also
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- added new API:
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+ This is a minor release where we fixed some bugs related with the
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+ maximum type size supported by Blosc2; now, the maximum size is
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+ 512 MB (compared to 255 bytes in previous versions). We are also
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+ introducing WASM32 wheels for the first time.
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- * blosc2.evaluate: a drop-in replacement of numexpr.evaluate(). This
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- allows to evaluate expressions with combinations of NDArrays and NumPy
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- arrays. In addition, it has the next improvements:
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+ We also added new ``blosc2.matmul() `` function for computing matrix
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+ multiplication on NDArray instances.
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- - More functionality than numexpr (e.g. reductions).
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- - Follow casting rules of NumPy more closely.
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- - Use both NumPy arrays and Blosc2 NDArrays in the same expression.
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-
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- * blosc2.jit: a decorator to compile a function with a NumPy expression
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- using the compute engine of Blosc2. Useful to speed up the evaluation
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- of pure NumPy expressions at runtime.
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-
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- You can think of Python-Blosc2 3.0 as an extension of NumPy/numexpr that:
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+ You can think of Python-Blosc2 3.x as an extension of NumPy/numexpr that:
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- Can deal with ndarrays compressed using first-class codecs & filters.
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- Performs many kind of math expressions, including reductions, indexing...
@@ -26,6 +18,7 @@ You can think of Python-Blosc2 3.0 as an extension of NumPy/numexpr that:
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- Integrates with Numba and Cython via UDFs (User Defined Functions).
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- Adheres to modern NumPy casting rules way better than numexpr.
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- Computes expressions only when needed. They can also be stored for later use.
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+ - Supports linear algebra operations (like ``blosc2.matmul() ``).
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Install it with::
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