Merge pull request #27 from jannikmi/dev version 3.0.2

.github/FUNDING.yml

@@ -1,3 +1,3 @@
 # These are supported funding model platforms
-github: [MrMinimal64]
+github: [jannikmi]
 issuehunt: mrminimal64

.github/workflows/build_test.yml

@@ -7,7 +7,6 @@ on:
   push:
     branches:
       - master
-      - dev
 
 jobs:
   test:
@@ -22,7 +21,7 @@ jobs:
           - "3.7"
           - "3.8"
           - "3.9"
-    #          - "3.10"
+          - "3.10"
     env:
       TOXENV: ${{ matrix.tox-env }}
       TOX_SKIP_MISSING_INTERPRETERS: False
@@ -45,14 +44,26 @@ jobs:
 
   tag_release:
     name: tag current release
-    if: endsWith(github.ref, '/master') == true
+    if: endsWith(github.ref, '/master')
     needs: test
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v2
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.7
+
       - name: Fetch version
         id: fetch_version
         run: echo "::set-output name=version_nr::$(cat VERSION)"
+
+      - name: Build a binary wheel and a source tarball
+        run: |
+          pip install setuptools wheel
+          python setup.py sdist bdist_wheel --python-tag py37.py38.py39.py310
+
       - name: Create Release
         id: create_release
         uses: actions/create-release@v1
@@ -65,3 +76,8 @@ jobs:
           release_name: Release ${{env.VERSION}}
           draft: false
           prerelease: false
+
+      - name: PyPI Publishing
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          password: ${{ secrets.PYPI_DEPLOYMENT_API_KEY }}

.pre-commit-config.yaml

@@ -1,6 +1,6 @@
 repos:
   - repo: https://github.com/pre-commit/pre-commit-hooks
-    rev: v4.0.1
+    rev: v4.3.0
     hooks:
       - id: check-ast  # Is it valid Python?
       - id: debug-statements # no debugging statements used
@@ -25,15 +25,15 @@ repos:
           - --filter-files
 
   - repo: https://github.com/psf/black
-    rev: 21.11b1
+    rev: 22.3.0
     hooks:
       - id: black
         language_version: python3
         args:
           - --line-length=120
 
   - repo: https://github.com/asottile/blacken-docs
-    rev: v1.12.0
+    rev: v1.12.1
     hooks:
       - id: blacken-docs
         additional_dependencies: [ black==20.8b1 ]
@@ -65,7 +65,7 @@ repos:
   #        -   id: rstcheck
 
   - repo: https://github.com/asottile/pyupgrade
-    rev: v2.29.1
+    rev: v2.34.0
     hooks:
       - id: pyupgrade
 

CHANGELOG.rst

@@ -4,7 +4,6 @@ Changelog
 
 TODOs
 
-* integrate CD PyPI upload into GHA workflow. including authentication...
 * run speed and numerical tests with the new C evaluation method!
 * Improve tests
 * compare poly.num_ops of different factorisations. tests?
@@ -55,7 +54,16 @@ idea:
     probably not worth the effort. more reasonable to just evaluate multiple polynomials in parallel
 
 
-3.0.0 (2021-12-04)
+3.0.2 (2022-06-14)
+__________________
+
+* bugfix: optional ``numba`` dependency. numba imports were not optional
+* bugfix: create __cache__ dir if not exists
+* minor documentation improvements
+* bumping dependencies
+
+
+3.0.1 (2021-12-04)
 __________________
 
 ATTENTION: major changes:

CONTRIBUTING.rst

@@ -105,4 +105,4 @@ Ready to contribute? Here's how to set up this package for local development.
 
 
 
-.. _Github Issues: https://github.com/MrMinimal64/multivar_horner/issues
+.. _Github Issues: https://github.com/jannikmi/multivar_horner/issues

README.rst

@@ -64,7 +64,7 @@ Simple example:
 .. code-block:: python
 
     import numpy as np
-    from multivar_horner.multivar_horner import HornerMultivarPolynomial
+    from multivar_horner import HornerMultivarPolynomial
 
     # input parameters defining the polynomial
     #   p(x) = 5.0 + 1.0 x_1^3 x_2^1 + 2.0 x_1^2 x_3^1 + 3.0 x_1^1 x_2^1 x_3^1

VERSION

@@ -1 +1 @@
-3.0.1
+3.0.2

docs/0_getting_started.rst

@@ -57,7 +57,7 @@ and evaluating :math:`p` at a point :math:`x`:
 .. code-block:: python
 
     import numpy as np
-    from multivar_horner.multivar_horner import HornerMultivarPolynomial
+    from multivar_horner import HornerMultivarPolynomial
 
     coefficients = np.array([[5.0], [1.0], [2.0], [3.0]], dtype=np.float64)  # shape: (M,1)
     exponents = np.array(

docs/1_usage.rst

@@ -6,7 +6,7 @@ Usage
 
 .. note::
 
-   Also check out the :ref:`API documentation <api>` or the `code <https://github.com/MrMinimal64/multivar_horner>`__.
+   Also check out the :ref:`API documentation <api>` or the `code <https://github.com/jannikmi/multivar_horner>`__.
 
 
 Let's look at the example multivariate polynomial:
@@ -61,7 +61,7 @@ to create a representation of the multivariate polynomial :math:`p` in Horner fa
 
 .. code-block:: python
 
-    from multivar_horner.multivar_horner import HornerMultivarPolynomial
+    from multivar_horner import HornerMultivarPolynomial
 
     horner_polynomial = HornerMultivarPolynomial(coefficients, exponents)
 
@@ -108,7 +108,7 @@ it is possible to represent the polynomial without any factorisation (refered to
 
 .. code-block:: python
 
-    from multivar_horner.multivar_horner import MultivarPolynomial
+    from multivar_horner import MultivarPolynomial
 
     polynomial = MultivarPolynomial(coefficients, exponents)
 

multivar_horner/_numba_replacements.py

@@ -0,0 +1,48 @@
+""" 'transparent' numba functionality replacements
+
+njit decorator
+data types
+
+dtype_2int_tuple = typeof((1, 1))
+@njit(b1(i4, i4, i4[:, :]), cache=True)
+@njit(dtype_2int_tuple(f8, f8), cache=True)
+"""
+
+
+def njit(*args, **kwargs):
+    def wrapper(f):
+        return f
+
+    return wrapper
+
+
+class SubscriptAndCallable(object):
+    def __init__(self, *args, **kwargs):
+        pass
+
+    def __class_getitem__(cls, item):
+        return None
+
+
+# DTYPES
+# @njit(b1(i4, i4, i4[:, :]), cache=True)
+
+
+class b1(SubscriptAndCallable):
+    pass
+
+
+class f8(SubscriptAndCallable):
+    pass
+
+
+class i8(SubscriptAndCallable):
+    pass
+
+
+class u4(SubscriptAndCallable):
+    pass
+
+
+class void(SubscriptAndCallable):
+    pass

multivar_horner/classes/horner_poly.py

@@ -14,12 +14,10 @@
     OptimalFactorisationRoot,
 )
 from multivar_horner.classes.helpers import FactorContainer
-from multivar_horner.global_settings import BOOL_DTYPE, FLOAT_DTYPE, TYPE_1D_FLOAT, UINT_DTYPE
+from multivar_horner.global_settings import BOOL_DTYPE, FLOAT_DTYPE, PATH2CACHE, TYPE_1D_FLOAT, UINT_DTYPE
 from multivar_horner.helper_fcts import rectify_query_point, validate_query_point
 from multivar_horner.helpers_fcts_numba import eval_recipe
 
-PATH2CACHE = Path(__file__).parent.parent / "__pycache__"
-
 
 class HornerMultivarPolynomial(AbstractPolynomial):
     """a representation of a multivariate polynomial using Horner factorisation

multivar_horner/global_settings.py

@@ -1,3 +1,4 @@
+from pathlib import Path
 from typing import List, Union
 
 import numpy
@@ -20,3 +21,5 @@
 
 DEBUG = False
 # DEBUG = True
+PATH2CACHE = Path(__file__).parent.parent / "__pycache__"
+PATH2CACHE.mkdir(exist_ok=True)

multivar_horner/helpers_fcts_numba.py

@@ -7,7 +7,14 @@
 
 
 import numpy as np
-from numba import b1, f8, i8, njit, u4, void
+
+using_numba = True
+try:
+    from numba import b1, f8, i8, njit, u4, void
+except ImportError:
+    using_numba = False
+    # replace numba functionality with "transparent" implementations
+    from multivar_horner._numba_replacements import b1, f8, i8, njit, u4, void
 
 # DTYPES:
 F = f8

paper/paper.bib

@@ -3,7 +3,7 @@ @online{github
   author = {Michelfeit, Jannik},
   title = {multivar_horner},
   year = 2018,
-  url = {https://github.com/MrMinimal64/multivar_horner},
+  url = {https://github.com/jannikmi/multivar_horner},
   urldate = {2020-05-28},
 }
 

paper/paper.md

@@ -194,8 +194,8 @@ Some intermediate operations to convert the parameters into the required format
 # Further reading
 
 The documentation of the package is hosted on [readthedocs.io](https://multivar_horner.readthedocs.io/en/latest/).
-Any bugs or feature requests can be filed on [GitHub](https://github.com/MrMinimal64/multivar_horner/issues) [@github].
-The [contribution guidelines](https://github.com/MrMinimal64/multivar_horner/blob/master/CONTRIBUTING.rst) can be found there as well.
+Any bugs or feature requests can be filed on [GitHub](https://github.com/jannikmi/multivar_horner/issues) [@github].
+The [contribution guidelines](https://github.com/jannikmi/multivar_horner/blob/master/CONTRIBUTING.rst) can be found there as well.
 
 The underlying basic mathematical concepts are explained in numerical analysis textbooks like [@neumaier2001introduction].
 The Horner scheme at the core of `multivar_horner` has been theoretically outlined in [@greedyHorner].