Getting ready for release 3.0.0-beta.1

Author: FrancescAlted

ANNOUNCE.rst

@@ -1,10 +1,18 @@
-Announcing Python-Blosc2 2.6.2
-==============================
+Announcing Python-Blosc2 3.0.0-beta.1
+=====================================
 
-Updated to latest C-Blosc2 2.14.3. This was necessary to fix
-several CVEs in the C-Blosc2 library.  Also, the new version adds
-protection when platforms have just one CPU. This caused the
-internal number of threads to be 0, producing a division by zero.
+New evaluation engine (based on numexpr) for NDArray instances.
+Now, you can evaluate expressions like `a + b + 1` where `a` and `b`
+are NDArray instances.  This is a powerful feature that allows for
+efficient computations on compressed data, and supports advanced features like reductions,
+filters, user-defined functions and broadcasting (still in beta).  See this
+[example](https://github.com/Blosc/python-blosc2/blob/main/examples/ndarray/eval_expr.py).
+
+Also, we have added support for memory mapping in `SChunk` and `NDArray` instances.
+This allows to map super-chunks stored in disk and access them as if they were in memory.
+
+Last, but not least, we have added support for NumPy 2.0.0.  This means that our wheels
+are built against this version of NumPy, so you will need to use NumPy 1.23.0 or later.
 
 For more info, you can have a look at the release notes in:
 

README.rst

@@ -126,7 +126,7 @@ quite a bit of memory (but it can still be convenient for small outputs).
 It is important to note that the `NDArray` object can use memory-mapped files as well, and the
 benchmark above is actually using a memory-mapped file as the storage for the operands.
 Memory-mapped files are very useful when the operands do not fit in-memory, while keeping good
-performance.  Thanks to Jan Sellner for his implementation in Blosc2.
+performance.
 
 And here it is the performance when the operands do not fit well in-memory:
 

RELEASE_NOTES.md

@@ -1,8 +1,28 @@
 # Release notes
 
-## Changes from 2.6.2 to 2.6.3
+## Changes from 2.6.2 to 3.0.0-beta.1
 
-XXX version-specific blurb XXX
+* New evaluation engine (based on numexpr) for NDArray instances.
+  Now, you can evaluate expressions like `a + b + 1` where `a` and `b`
+  are NDArray instances.  This is a powerful feature that allows for
+  efficient computations on compressed data, and supports advanced features like reductions,
+  filters, user-defined functions and broadcasting (still in beta).  See this
+  [example](https://github.com/Blosc/python-blosc2/blob/main/examples/ndarray/eval_expr.py).
+
+* As a consequence of the above, there are many new functions to operate with, and
+  evaluate NDArray instances.  See the
+  [function section docs](https://www.blosc.org/python-blosc2/reference/operations_with_arrays.html#functions)
+  for more information.
+
+* Support for NumPy 2.0.0 is here!  Now, the wheels are built with NumPy 2.0.0.
+
+* Support for memory mapping in `SChunk` and `NDArray` instances.  This allows to map
+  super-chunks stored in disk and access them as if they were in memory.
+  If curious, see
+  [some benchmarks here](https://github.com/Blosc/python-blosc2/blob/main/examples/ndarray/eval_expr.py).
+  Thanks to @JanSellner for the excellent implementation, both in the C and the Python libraries.
+
+* Internal C-Blosc2 updated to 2.15.0.
 
 ## Changes from 2.6.1 to 2.6.2
 

VERSION

@@ -1 +1 @@
-2.6.3.dev0
+3.0.0-beta.1

pyproject.toml

@@ -5,7 +5,7 @@ requires = [
     "cython>=3",
     "cmake",
     "ninja",
-    "numpy>=2.0.0rc1",
+    "numpy>=2.0.0",
 ]
 build-backend = "setuptools.build_meta"