ArrayMap in ArrayKit

.github/workflows/ci.yml

@@ -17,12 +17,12 @@ jobs:
       - uses: actions/checkout@master
       - uses: actions/setup-python@master
         with:
-          python-version: 3.12
+          python-version: 3.13
       - run: pip install -r requirements-build-3_12.txt
       - run: python setup.py sdist
-      - uses: actions/upload-artifact@v3
+      - uses: actions/upload-artifact@v4
         with:
-          name: dist
+          name: dist-sdist
           path: dist
 
   matrix_config:
@@ -48,7 +48,6 @@ jobs:
       matrix:
         os: ${{ fromJson(needs.matrix_config.outputs.matrix_os) }}
         python:
-            - {minor: 9,  req_build: 'requirements-build-3_11.txt', req_test: 'requirements-dev-3_11.txt'}
             - {minor: 10, req_build: 'requirements-build-3_11.txt', req_test: 'requirements-dev-3_11.txt'}
             - {minor: 11, req_build: 'requirements-build-3_11.txt', req_test: 'requirements-dev-3_11.txt'}
             - {minor: 12, req_build: 'requirements-build-3_12.txt', req_test: 'requirements-dev-3_12.txt'}
@@ -87,20 +86,24 @@ jobs:
           CIBW_BEFORE_TEST: pip install -r {project}/${{ matrix.python.req_test }}
           CIBW_TEST_COMMAND: pytest {project}/test
 
-      - uses: actions/upload-artifact@v3
+      - uses: actions/upload-artifact@v4
         with:
-          name: dist
-          path: dist
+          name: dist-wheels-${{ matrix.os }}-py3${{ matrix.python.minor }}  # Unique artifact name
+          path: dist/*
 
   upload:
     name: Publish
     if: github.event_name == 'release'
     needs: [tar_gz, wheels]
     runs-on: ubuntu-22.04
     steps:
-      - uses: actions/download-artifact@v3
+      - uses: actions/download-artifact@v4
+        with:
+          name: dist-sdist
+          path: dist
+      - uses: actions/download-artifact@v4
         with:
-          name: dist
+          name: dist-wheels
           path: dist
       - uses: pypa/gh-action-pypi-publish@master
         with:

README.rst

@@ -29,7 +29,7 @@ Dependencies
 
 ArrayKit requires the following:
 
-- Python>=3.9
+- Python>=3.10
 - numpy>=1.19.5
 
 

performance/auto_map/fixtures.py

@@ -0,0 +1,273 @@
+import typing as tp
+
+
+import numpy as np
+
+from arraymap import AutoMap
+from arraymap import FrozenAutoMap
+
+
+class PayLoad:
+    def __init__(self, array: np.ndarray):
+        self.array = array
+        self.list = list(array)
+        self.faml = FrozenAutoMap(self.list)
+        self.fama = FrozenAutoMap(self.array)
+        self.ama = AutoMap(self.array)
+        self.d = dict(zip(self.list, range(len(self.list))))
+        self.sel_array = array[(np.arange(len(array)) % 2) == 0]
+        self.sel_scalar = list(self.sel_array)
+
+
+# -------------------------------------------------------------------------------
+INT_START = 500  # avoid cached ints starting at 256
+
+
+class FixtureFactory:
+    NAME = ""
+    SORT = 0
+    CACHE = {}  # can be shared for all classes
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        raise NotImplementedError()
+
+    @classmethod
+    def get_label_array(cls, size: int) -> tp.Tuple[str, PayLoad]:
+        key = (cls, size)
+        if key not in cls.CACHE:
+            pl = PayLoad(cls.get_array(size))
+            cls.CACHE[key] = pl
+        return cls.NAME, cls.CACHE[key]
+
+
+class FFInt64(FixtureFactory):
+    NAME = "int64"
+    SORT = 0
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype=np.int64)
+        array.flags.writeable = False
+        return array
+
+
+class FFInt32(FixtureFactory):
+    NAME = "int32"
+    SORT = 1
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype=np.int32)
+        array.flags.writeable = False
+        return array
+
+
+class FFUInt64(FixtureFactory):
+    NAME = "uint64"
+    SORT = 2
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype=np.uint64)
+        array.flags.writeable = False
+        return array
+
+
+class FFUInt32(FixtureFactory):
+    NAME = "uint32"
+    SORT = 3
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype=np.uint32)
+        array.flags.writeable = False
+        return array
+
+
+class FFFloat64(FixtureFactory):
+    NAME = "float64"
+    SORT = 4
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = (np.arange(INT_START, INT_START + size) * 0.5).astype(np.float64)
+        array.flags.writeable = False
+        return array
+
+
+class FFFloat32(FixtureFactory):
+    NAME = "float32"
+    SORT = 5
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = (np.arange(INT_START, INT_START + size) * 0.5).astype(np.float32)
+        array.flags.writeable = False
+        return array
+
+
+def get_string_array(size: int, char_count: int, kind: str) -> str:
+    fmt = f"-<{char_count}"
+    array = np.array(
+        [
+            f"{hex(e) * (char_count // 8)}".format(fmt)
+            for e in range(INT_START, INT_START + size)
+        ],
+        dtype=f"{kind}{char_count}",
+    )
+    array.flags.writeable = False
+    return array
+
+
+class FFU8(FixtureFactory):
+    NAME = "U8"
+    SORT = 6
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 8, "U")
+
+
+class FFU16(FixtureFactory):
+    NAME = "U16"
+    SORT = 7
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 16, "U")
+
+
+class FFU32(FixtureFactory):
+    NAME = "U32"
+    SORT = 8
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 32, "U")
+
+
+class FFU64(FixtureFactory):
+    NAME = "U64"
+    SORT = 9
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 64, "U")
+
+
+class FFU128(FixtureFactory):
+    NAME = "U128"
+    SORT = 10
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 128, "U")
+
+
+class FFS8(FixtureFactory):
+    NAME = "S8"
+    SORT = 11
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 8, "S")
+
+
+class FFS16(FixtureFactory):
+    NAME = "S16"
+    SORT = 12
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 16, "S")
+
+
+class FFS32(FixtureFactory):
+    NAME = "S32"
+    SORT = 13
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 32, "S")
+
+
+class FFS64(FixtureFactory):
+    NAME = "S64"
+    SORT = 14
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 64, "S")
+
+
+class FFS128(FixtureFactory):
+    NAME = "S128"
+    SORT = 15
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        return get_string_array(size, 128, "S")
+
+
+class FFDTY(FixtureFactory):
+    NAME = "dt[Y]"
+    SORT = 20
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype="datetime64[Y]")
+        array.flags.writeable = False
+        return array
+
+
+class FFDTD(FixtureFactory):
+    NAME = "dt[D]"
+    SORT = 21
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype="datetime64[D]")
+        array.flags.writeable = False
+        return array
+
+
+class FFDTs(FixtureFactory):
+    NAME = "dt[s]"
+    SORT = 22
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype="datetime64[s]")
+        array.flags.writeable = False
+        return array
+
+
+class FFDTns(FixtureFactory):
+    NAME = "dt[ns]"
+    SORT = 23
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        array = np.arange(INT_START, INT_START + size, dtype="datetime64[ns]")
+        array.flags.writeable = False
+        return array
+
+
+class FFObject(FixtureFactory):
+    NAME = "object"
+    SORT = 5
+
+    @staticmethod
+    def get_array(size: int) -> np.ndarray:
+        ints = np.arange(INT_START, INT_START + size)
+        array = ints.astype(object)
+
+        target = 1 == ints % 3
+        array[target] = ints[target] * 0.5
+
+        target = 2 == ints % 3
+        array[target] = np.array([hex(e) for e in ints[target]])
+
+        array.flags.writeable = False
+        return array