Removed numba, updated types for new numpy, main function guard

setup.cfg

@@ -26,7 +26,6 @@ packages = find:
 package_dir =
     = src
 install_requires =
-    numba
     numpy
     colorama
     tqdm
@@ -41,6 +40,7 @@ console_scripts =
 [options.extras_require]
 decision =
     graphviz
+    numba
 
 dev = 
     black

src/doddle/cli.py

@@ -91,7 +91,7 @@ def main() -> None:
 def parse_args(args: Sequence[str]) -> None:
 
     parser = ArgumentParser()
-    subparsers = parser.add_subparsers()
+    subparsers = parser.add_subparsers(required=True)
 
     run_parser = subparsers.add_parser("run")
     run_parser.add_argument("--answer", required=True, type=Word)
@@ -124,4 +124,8 @@ def parse_args(args: Sequence[str]) -> None:
     benchmark_parser.set_defaults(func=benchmark_performance)
 
     namespace = parser.parse_args(args)
+    if not hasattr(namespace, "func"):
+        parser.print_help()
+        return
+
     namespace.func(namespace)

src/doddle/histogram.py

@@ -5,7 +5,6 @@
 from typing import Callable, Iterator, TypeVar
 
 import numpy as np
-from numba import njit  # type: ignore
 
 from .guess import Guess
 from .scoring import Scorer
@@ -134,7 +133,6 @@ def to_histogram(solns_by_score: dict[int, WordSeries]) -> np.ndarray:
     return vector
 
 
-@njit
 def _populate_histogram(matrix: np.ndarray, row: int, hist: np.ndarray) -> bool:
     """Aggressive optimisation of the histogram creation.
 

src/doddle/scoring.py

@@ -1,5 +1,4 @@
 import numpy as np
-from numba import int8, int32, jit  # type: ignore
 
 from .words import Word
 
@@ -72,7 +71,6 @@ def score_word(self, solution: Word, guess: Word) -> int:
         return _score_word_jit(solution.vector, guess.vector, self._powers)
 
 
-@jit(int32(int8[:], int8[:], int32[:]), nopython=True)
 def _score_word_jit(solution_array: np.ndarray, guess_array: np.ndarray, powers: np.ndarray) -> int:
     """Optimised internal call to score a word. See Solver.score_word(...) for details."""
 

src/doddle/words.py

@@ -153,7 +153,7 @@ def __find_index(self, value: str | Word) -> int:
     def __getitem__(self, s: slice | np.ndarray) -> WordSeries:
 
         is_slice = isinstance(s, slice)
-        is_mask = isinstance(s, np.ndarray) and s.dtype == np.bool8
+        is_mask = isinstance(s, np.ndarray) and s.dtype == np.bool_
         is_index = isinstance(s, np.ndarray) and s.dtype == np.int_
         can_index = is_slice or is_mask or is_index