Fixed logicle extension install - required generate-setup-file = true…

… in toml

build.py

@@ -0,0 +1,24 @@
+from typing import Any, Dict
+
+from setuptools_cpp import ExtensionBuilder, Pybind11Extension
+
+ext_modules = [
+    Pybind11Extension(
+        "logicle_ext",
+        [
+            "cytotransform/logicle_ext/FastLogicle.cpp",
+            "cytotransform/logicle_ext/Logicle.cpp",
+        ],
+        include_dirs=["cytotransform/logicle_ext"],
+    )
+]
+
+
+def build(setup_kwargs: Dict[str, Any]) -> None:
+    setup_kwargs.update(
+        {
+            "ext_modules": ext_modules,
+            "cmdclass": dict(build_ext=ExtensionBuilder),
+            "zip_safe": False,
+        }
+    )

cytotransform/base.py

@@ -1,16 +1,17 @@
 from abc import ABC, abstractmethod
-from typing import Callable
-from joblib import Parallel, delayed, cpu_count
+from typing import Any, Callable
+
 import numpy as np
+from joblib import Parallel, cpu_count, delayed
 
 
 class Transform(ABC):
     def __init__(
-            self,
-            transform_function: Callable,
-            inverse_transform_function: Callable,
-            parameters: dict,
-            n_jobs: int = -1
+        self,
+        transform_function: Callable,
+        inverse_transform_function: Callable,
+        parameters: dict,
+        n_jobs: int = -1,
     ):
         self._transform_function = transform_function
         self._inverse_transform_function = inverse_transform_function
@@ -28,7 +29,7 @@ def transform(self, data: np.ndarray) -> np.ndarray:
     def inverse_transform(self, data: np.ndarray) -> np.ndarray:
         return self._multiprocess_call(data, self._inverse_transform_function)
 
-    def _batches(self, data: np.ndarray) -> np.ndarray:
+    def _batches(self, data: np.ndarray) -> list[np.ndarray[Any, np.dtype[Any]]]:
         """
         Split data into N batches, where N is the number of jobs to run in parallel.
 
@@ -47,4 +48,9 @@ def _batches(self, data: np.ndarray) -> np.ndarray:
 
     def _multiprocess_call(self, data: np.ndarray, func: Callable) -> np.ndarray:
         with Parallel(n_jobs=self.n_jobs) as parallel:
-            return np.concatenate(parallel(delayed(func)(batch, **self.parameters) for batch in self._batches(data)))
+            return np.concatenate(
+                parallel(
+                    delayed(func)(batch, **self.parameters)
+                    for batch in self._batches(data)
+                )
+            )

cytotransform/logicle.py

@@ -2,7 +2,7 @@
 
 import numpy as np
 
-from cytotransform.logicle_ext import FastLogicle  # type: ignore
+from logicle_ext import FastLogicle  # type: ignore
 
 from .base import Transform
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "cytotransform"
-version = "0.1.11"
+version = "0.1.12"
 description = "Rapid transformations for cytometry data"
 authors = ["Ross Burton <burtonrossj@gmail.com>"]
 license = "MIT"
@@ -33,11 +33,15 @@ pytest-mock = "*"
 pre-commit = "*"
 mongomock = "*"
 mypy = "*"
+setuptools_cpp = "*"
 
+[tool.poetry.build]
+generate-setup-file = true
+script = "build.py"
 
 [build-system]
-requires = ["pybind11", "setuptools"]
-build-backend = "setuptools.build_meta"
+requires = ["poetry>=0.12", "setuptools", "wheel", "setuptools-cpp"]
+build-backend = "poetry.core.masonry.api"
 
 ##### isort configuration https://pycqa.github.io/isort/docs/configuration/config_files.html
 [tool.isort]

tests/report.xml

@@ -1 +1 @@
-<?xml version="1.0" encoding="utf-8"?><testsuites><testsuite name="pytest" errors="0" failures="0" skipped="0" tests="6" time="0.967" timestamp="2023-06-24T17:40:18.399685" hostname="baymax"><testcase classname="tests.test_transformer" name="test_transforms[1-group0]" time="0.001" /><testcase classname="tests.test_transformer" name="test_transforms[-1-group1]" time="0.703" /><testcase classname="tests.test_transformer" name="test_transforms[1-group2]" time="0.001" /><testcase classname="tests.test_transformer" name="test_transforms[-1-group3]" time="0.028" /><testcase classname="tests.test_transformer" name="test_transforms[1-group4]" time="0.001" /><testcase classname="tests.test_transformer" name="test_transforms[-1-group5]" time="0.021" /></testsuite></testsuites>
+<?xml version="1.0" encoding="utf-8"?><testsuites><testsuite name="pytest" errors="0" failures="0" skipped="0" tests="6" time="1.260" timestamp="2023-07-22T15:57:12.881162" hostname="baymax"><testcase classname="tests.test_transformer" name="test_transforms[1-group0]" time="0.001" /><testcase classname="tests.test_transformer" name="test_transforms[-1-group1]" time="0.672" /><testcase classname="tests.test_transformer" name="test_transforms[1-group2]" time="0.001" /><testcase classname="tests.test_transformer" name="test_transforms[-1-group3]" time="0.131" /><testcase classname="tests.test_transformer" name="test_transforms[1-group4]" time="0.001" /><testcase classname="tests.test_transformer" name="test_transforms[-1-group5]" time="0.087" /></testsuite></testsuites>