Linting

.github/workflows/coverage.yaml

@@ -21,7 +21,7 @@ jobs:
     - uses: actions/setup-python@v4
       with:
         python-version: "3.11"
-    - run: pip install pytest coverage
+    - run: pip install pytest pytest-mock coverage
            pip install .
 
     # annotate each step with `if: always` to run all regardless

.github/workflows/testing.yaml

@@ -28,10 +28,10 @@ jobs:
         include:
         - os: ubuntu-latest
           python-version: "3.9"
-        - os: ubuntu-latest
-          python-version: "3.8"
-        - os: ubuntu-latest
-          python-version: "3.7"
+        # - os: ubuntu-latest
+        #   python-version: "3.8"
+        # - os: ubuntu-latest
+        #   python-version: "3.7"
 
     steps:
     - uses: actions/checkout@v3

README.md

@@ -1,7 +1,7 @@
 # archeryutils
 
 ![GitHub](https://img.shields.io/github/license/jatkinson1000/archeryutils)
-[![Python 3.7+](https://img.shields.io/badge/python-3.7+-blue.svg)](https://www.python.org/downloads/)
+[![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
 ![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/jatkinson1000/archeryutils/testing.yaml)
 [![codecov](https://codecov.io/gh/jatkinson1000/archeryutils/branch/main/graph/badge.svg?token=AZU7G6H8T0)](https://codecov.io/gh/jatkinson1000/archeryutils)
 [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)

archeryutils/__init__.py

@@ -1,7 +1,7 @@
 """Package providing code for various archery utilities."""
 from archeryutils import load_rounds, rounds, targets
 from archeryutils.handicaps import handicap_equations, handicap_functions
-import archeryutils.classifications as classifications
+from archeryutils import classifications
 
 __all__ = [
     "rounds",

archeryutils/classifications/agb_field_classifications.py

@@ -13,6 +13,10 @@
 agb_field_classification_scores
 
 """
+# Due to structure of similar classification schemes they may trigger duplicate code.
+# => disable for classification files and tests
+# pylint: disable=duplicate-code
+
 import re
 from typing import List, Dict, Any
 import numpy as np
@@ -288,6 +292,9 @@ def agb_field_classification_scores(
     ArcheryGB Rules of Shooting
     ArcheryGB Shooting Administrative Procedures - SAP7
     """
+    # Unused roundname argument to keep consistency with other classification functions
+    # pylint: disable=unused-argument
+
     # deal with reduced categories:
     if age_group.lower().replace(" ", "") in ("adult", "50+", "under21"):
         age_group = "Adult"

archeryutils/classifications/agb_indoor_classifications.py

@@ -7,6 +7,10 @@
 calculate_agb_indoor_classification
 agb_indoor_classification_scores
 """
+# Due to structure of similar classification schemes they may trigger duplicate code.
+# => disable for classification files and tests
+# pylint: disable=duplicate-code
+
 from typing import List, Dict, Any
 import numpy as np
 
@@ -59,7 +63,7 @@ def _make_agb_indoor_classification_dict() -> Dict[str, Dict[str, Any]]:
     # Read in gender info as list of dicts
     agb_genders = cls_funcs.read_genders_json()
     # Read in classification names as dict
-    agb_classes_info_in = cls_funcs.read_classes_in_json()
+    agb_classes_info_in = cls_funcs.read_classes_json("agb_indoor")
     agb_classes_in = agb_classes_info_in["classes"]
     agb_classes_in_long = agb_classes_info_in["classes_long"]
 
@@ -69,40 +73,36 @@ def _make_agb_indoor_classification_dict() -> Dict[str, Dict[str, Any]]:
     # loop over genders
     classification_dict = {}
     for bowstyle in agb_bowstyles:
-        for age in agb_ages:
-            for gender in agb_genders:
-                # Get age steps from Adult
-                age_steps = age["step"]
-
-                # Get number of gender steps required
-                # Perform fiddle in age steps where genders diverge at U15/U16
-                if gender.lower() == "female" and age["step"] <= 3:
-                    gender_steps = 1
-                else:
-                    gender_steps = 0
-
+        for gender in agb_genders:
+            for age in agb_ages:
                 groupname = cls_funcs.get_groupname(
                     bowstyle["bowstyle"], gender, age["age_group"]
                 )
 
-                class_hc = np.empty(len(agb_classes_in))
+                classification_dict[groupname] = {
+                    "classes": agb_classes_in,
+                    "classes_long": agb_classes_in_long,
+                }
+
+                # set step from datum based on age and gender steps required
+                delta_hc_age_gender = cls_funcs.get_age_gender_step(
+                    gender,
+                    age["step"],
+                    bowstyle["ageStep_in"],
+                    bowstyle["genderStep_in"],
+                )
+
+                classification_dict[groupname]["class_HC"] = np.empty(
+                    len(agb_classes_in)
+                )
                 for i in range(len(agb_classes_in)):
                     # Assign handicap for this classification
-                    class_hc[i] = (
+                    classification_dict[groupname]["class_HC"][i] = (
                         bowstyle["datum_in"]
-                        + age_steps * bowstyle["ageStep_in"]
-                        + gender_steps * bowstyle["genderStep_in"]
+                        + delta_hc_age_gender
                         + (i - 1) * bowstyle["classStep_in"]
                     )
 
-                # TODO: class names and long are duplicated many times here
-                #   Consider a method to reduce this (affects other code)
-                classification_dict[groupname] = {
-                    "classes": agb_classes_in,
-                    "class_HC": class_hc,
-                    "classes_long": agb_classes_in_long,
-                }
-
     return classification_dict
 
 
@@ -254,17 +254,19 @@ def agb_indoor_classification_scores(
 
     # Handle possibility of gaps in the tables or max scores by checking 1 HC point
     # above current (floored to handle 0.5) and amending accordingly
-    for i, (sc, hc) in enumerate(zip(int_class_scores, group_data["class_HC"])):
+    for i, (score, handicap) in enumerate(
+        zip(int_class_scores, group_data["class_HC"])
+    ):
         next_score = hc_eq.score_for_round(
             ALL_INDOOR_ROUNDS[cls_funcs.strip_spots(roundname)],
-            np.floor(hc) + 1,
+            np.floor(handicap) + 1,
             hc_scheme,
             hc_params,
             round_score_up=True,
         )[0]
-        if next_score == sc:
+        if next_score == score:
             # If already at max score this classification is impossible
-            if sc == ALL_INDOOR_ROUNDS[roundname].max_score():
+            if score == ALL_INDOOR_ROUNDS[roundname].max_score():
                 int_class_scores[i] = -9999
             # If gap in table increase to next score
             # (we assume here that no two classifications are only 1 point apart...)

archeryutils/classifications/agb_old_indoor_classifications.py

@@ -7,6 +7,10 @@
 calculate_AGB_old_indoor_classification
 AGB_old_indoor_classification_scores
 """
+# Due to structure of similar classification schemes they may trigger duplicate code.
+# => disable for classification files and tests
+# pylint: disable=duplicate-code
+
 from typing import List, Dict, Any
 import numpy as np