Merge pull request #706 from bashtage/add-pre-release-testing

CI: Add pre-release testing

arch/bootstrap/__init__.py

@@ -1,6 +1,7 @@
 """
 Tools for implementing statistical bootstraps
 """
+
 from arch.bootstrap import _samplers_python
 from arch.bootstrap.base import (
     CircularBlockBootstrap,

arch/covariance/kernel.py

@@ -179,6 +179,7 @@ class CovarianceEstimator(ABC):
 
     where :math:`z=\frac{h}{H}, h=0, 1, \ldots, H` where H is the bandwidth.
     """
+
     _name = ""
 
     def __init__(

arch/unitroot/critical_values/dfgls.py

@@ -5,6 +5,7 @@
 These have been computed using the methodology of MacKinnon (1994) and (2010)
 simulation. See dfgls_critival_values_simulation for implementation.
 """
+
 from __future__ import annotations
 
 from numpy import array

arch/unitroot/critical_values/dickey_fuller.py

@@ -6,6 +6,7 @@
 did not appear in the original paper and have been computed using an identical
 simulation.
 """
+
 from __future__ import annotations
 
 from numpy import array, asarray, inf

arch/unitroot/critical_values/phillips_ouliaris.py

@@ -10,6 +10,7 @@
 P-type statistics with trend ct based on 11,250,000 simulations
 P-type statistics with trend ctt based on 13,250,000 simulations
 """
+
 from __future__ import annotations
 
 from math import inf

arch/unitroot/critical_values/simulation/adf_z_critical_values_simulation.py

@@ -7,6 +7,7 @@
 
 Remote clusters can be used by modifying the call to Client.
 """
+
 import datetime
 from typing import Literal, cast
 

arch/unitroot/critical_values/simulation/adf_z_critical_values_simulation_joblib.py

@@ -1,6 +1,7 @@
 """
 Simulation of ADF z-test critical values.  Closely follows MacKinnon (2010).
 """
+
 from __future__ import annotations
 
 import argparse

arch/unitroot/critical_values/simulation/adf_z_critical_values_simulation_large_cluster.py

@@ -10,6 +10,7 @@
 This version has been optimized for execution on a large cluster and should
 scale well with 128 or more engines.
 """
+
 from __future__ import annotations
 
 import datetime

arch/unitroot/critical_values/simulation/dfgls_critical_values_simulation.py

@@ -3,6 +3,7 @@
 to MacKinnon (2010).  Makes use of parallel_fun in statsmodels which works
 best when joblib is installed.
 """
+
 from __future__ import annotations
 
 import datetime

arch/unitroot/critical_values/simulation/engle_granger_simulation.py

@@ -1,6 +1,7 @@
 """
 Simulation for critical value production for Engle-Granger
 """
+
 import argparse
 import datetime as dt
 from functools import partial

arch/unitroot/critical_values/simulation/kpss_critical_values_simulation.py

@@ -2,6 +2,7 @@
 Calculates quantiles of the KPSS test statistic for both the constant
 and constant plus trend scenarios.
 """
+
 import os
 from typing import Optional, cast
 

arch/unitroot/critical_values/zivot_andrews.py

@@ -7,6 +7,7 @@
 The p-values are generated through Monte Carlo simulation using 100,000
 replications and 2000 data points.
 """
+
 from __future__ import annotations
 
 from numpy import array

arch/univariate/base.py

@@ -1,6 +1,7 @@
 """
 Core classes for ARCH models
 """
+
 from __future__ import annotations
 
 from abc import ABCMeta, abstractmethod

arch/univariate/mean.py

@@ -2,6 +2,7 @@
 Mean models to use with ARCH processes.  All mean models must inherit from
 :class:`ARCHModel` and provide the same methods with the same inputs.
 """
+
 from __future__ import annotations
 
 from collections.abc import Mapping, Sequence
@@ -240,6 +241,7 @@ class HARX(ARCHModel, metaclass=AbstractDocStringInheritor):
     where :math:`\bar{y}_{t-L_{i,0}:L_{i,1}}` is the average value of
     :math:`y_t` between :math:`t-L_{i,0}` and :math:`t - L_{i,1}`.
     """
+
     # To allow for addition mean parameters in simulation
     _extra_simulation_params: int = 0
 
@@ -1624,6 +1626,7 @@ class ARCHInMean(ARX):
 
     where :math:`f(\cdot)` is the function specified by ``form``.
     """
+
     # To account for GIM param
     _extra_simulation_params = 1
 

arch/univariate/recursions_python.py

@@ -4,6 +4,7 @@
 export ARCH_NO_BINARY=1
 python -m pip install .
 """
+
 from __future__ import annotations
 
 from arch.compat.numba import jit

arch/univariate/volatility.py

@@ -3,6 +3,7 @@
 inherit from :class:`VolatilityProcess` and provide the same methods with the
 same inputs.
 """
+
 from __future__ import annotations
 
 from abc import ABCMeta, abstractmethod

arch/utility/array.py

@@ -1,6 +1,7 @@
 """
 Utility functions that do not explicitly relate to Volatility modeling
 """
+
 from __future__ import annotations
 
 from arch.compat.pandas import is_datetime64_any_dtype
@@ -86,7 +87,7 @@ def ensure1d(
 
 
 def ensure2d(
-    x: (Sequence[float | int] | Sequence[Sequence[float | int]] | ArrayLike),
+    x: Sequence[float | int] | Sequence[Sequence[float | int]] | ArrayLike,
     name: str,
 ) -> DataFrame | NDArray:
     if isinstance(x, Series):

azure-pipelines.yml

@@ -14,6 +14,8 @@ variables:
   MPLBACKEND: agg
   PYTEST_PATTERN: "(not slow)"
   coverage: true
+  test.install: false
+  pip.pre: false
 
 jobs:
 - template: ci/azure/azure_template_posix.yml

ci/azure/azure_template_posix.yml

@@ -78,6 +78,9 @@ jobs:
         SCIPY: 1.5.0
         MATPLOTLIB: 3.3.0
         PANDAS: 1.1.0
+      python312_pre:
+        python.version: '3.12'
+        pip.pre: true
 
     maxParallel: 10
 
@@ -157,7 +160,15 @@ jobs:
       echo pytest -m "${PYTEST_PATTERN}" --junitxml=junit/test-results.xml -n auto --durations=25 ${COVERAGE_OPTS} ${PYTEST_OPTS} arch/tests
       pytest -m "${PYTEST_PATTERN}" --junitxml=junit/test-results.xml -n auto --durations=25 ${COVERAGE_OPTS} ${PYTEST_OPTS} arch/tests
     displayName: 'Run tests (editable)'
-    condition: ne(variables['test.install'], 'true')
+    condition: and(ne(variables['test.install'], 'true'), ne(variables['pip.pre'], 'true'))
+
+  - script: |
+      echo "Testing pip-pre"
+      echo pytest -m "${PYTEST_PATTERN}" --junitxml=junit/test-results.xml -n auto --durations=25 ${COVERAGE_OPTS} ${PYTEST_OPTS} arch/tests
+      pytest -m "${PYTEST_PATTERN}" --junitxml=junit/test-results.xml -n auto --durations=25 ${COVERAGE_OPTS} ${PYTEST_OPTS} arch/tests
+    displayName: 'Run tests (pip pre)'
+    condition: eq(variables['pip.pre'], 'true')
+    continueOnError: true
 
   - task: PublishTestResults@2
     inputs:

ci/azure/install-posix.sh

@@ -16,7 +16,7 @@ else
 fi
 
 python -m pip install --upgrade pip "setuptools>=61" wheel
-python -m pip install cython "pytest>=7,<7.1" pytest-xdist coverage pytest-cov ipython jupyter notebook nbconvert "property_cached>=1.6.3" black isort flake8 nbconvert setuptools_scm
+python -m pip install cython "pytest>=7" pytest-xdist coverage pytest-cov ipython jupyter notebook nbconvert "property_cached>=1.6.3" black isort flake8 nbconvert setuptools_scm colorama
 
 if [[ -n ${NUMPY} ]]; then CMD="$CMD~=${NUMPY}"; fi;
 CMD="$CMD scipy"
@@ -35,3 +35,10 @@ fi;
 CMD="$CMD $EXTRA"
 echo $CMD
 eval $CMD
+
+if [ "${PIP_PRE}" = true ]; then
+  python -m pip install matplotlib cython --upgrade
+  python -m pip uninstall -y numpy pandas scipy matplotlib statsmodels
+  python -m pip install -i https://pypi.anaconda.org/scientific-python-nightly-wheels/simple numpy pandas scipy matplotlib --upgrade --use-deprecated=legacy-resolver
+  python -m pip install git+https://github.com/statsmodels/statsmodels.git --upgrade --no-build-isolation -v
+fi

doc/make.bat

@@ -9,6 +9,9 @@ if "%SPHINXBUILD%" == "" (
 )
 set SOURCEDIR=source
 set BUILDDIR=build
+set SPHINXPROJ=arch
+set SPHINXOPTS=
+set PYDEVD_DISABLE_FILE_VALIDATION=1
 
 if "%1" == "" goto help
 
@@ -22,14 +25,17 @@ if errorlevel 9009 (
 	echo.
 	echo.If you don't have Sphinx installed, grab it from
 	echo.https://sphinx-doc.org/
+	set PYDEVD_DISABLE_FILE_VALIDATION=
 	exit /b 1
 )
 
 %SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
+set PYDEVD_DISABLE_FILE_VALIDATION=
 goto end
 
 :help
 %SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS%
+set PYDEVD_DISABLE_FILE_VALIDATION=
 
 :end
 popd

doc/requirements.txt

@@ -1,6 +1,6 @@
 setuptools>=61
 wheel
-setuptools_scm[toml]>=7,<8
+setuptools_scm[toml]>=8.0.3,<9
 oldest-supported-numpy
 cython>=0.29.34  # Works with 3.0.0b2
 numpy >=1.22

doc/source/changes/6.0.rst

@@ -2,12 +2,17 @@
 Version 6
 =========
 
+Release 6.3
+===========
+- Compatability with NumPy 2
+- Fixes for future changes in pandas
+
 Release 6.2
 ===========
 - Fixed a bug that affected forecasting from  :class:`~arch.univariate.volatility.FIGARCH` models (:issue:`606`).
 - Added a performance warning when testing for unit roots in large series using a lag-length
   search with no-max-lag specified.
-- Fixed a bug that affected forecasting from :class:`arch.univariate.volatility.FIGARCH'
+- Fixed a bug that affected forecasting from :class:`arch.univariate.volatility.FIGARCH`
   models (:issue:`606`).
 - Changed the default value of ``reindex`` to ``False`` so that forecasts
   will not match the input by default.  Set ``reindex`` to ``True`` if this is

requirements-dev.txt

@@ -17,8 +17,9 @@ pytest-xdist
 pytest-cov
 
 # formatting
-black[jupyter]==23.9.1
+black[jupyter]==23.12.1
 isort~=5.0
+colorama
 flake8
 mypy
 pyupgrade>=3.4.0