2025 python / packages compatibility

.github/workflows/recursive_logit_integration.yml

@@ -34,4 +34,21 @@ jobs:
     - name: Test with pytest
       run: |
         pip install -e .
-        pytest --ignore=src/ --ignore=manual_verification/
+        pytest -v --color=yes --ignore=src/ --ignore=manual_verification/
+
+  test2024:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: 3.10
+
+      - name: Install dependencies
+        run: |
+          python -m pip install uv
+          uv pip install -r requirements_strict_2024.txt flake8 pytest -e .
+
+      - name: Test with pytest
+        run: |
+          pytest -v --color=yes --ignore=src/ --ignore=manual_verification/

readme.rst

@@ -10,30 +10,16 @@ quick start overview.
 
 Installation
 ------------
-The current most direct method of installation is to clone the repository and install using pip::
-
-       pip install -r requirements.txt
-
-Note that (currently) on windows the 2004 update has broken some interactions with OpenBLAS. To
-avoid any problems it is recommended to use conda, which will use MKL BLAS and avoid any issues::
 
-    conda install --file (cat requirements.txt)
+(This was all written back in 2020, and python packaging workflow tools have come a long way since then,
+more modern workflow tools like pixi, rye, pdm etc could be considered. )
 
-Note that there are no direct problems related to this in the code but
-pip will install numpy 1.19.4 by default, which will
-immediately crash to warn about this. Reverting to numpy 1.19.3 "fixes" this in that the warning
-isn't triggered, but other code which does require on the broken functionality may silently fail.
-
-..
-    Currently one can install from the repository directly using pip::
+The current most direct method of installation is to clone the repository and install using pip::
 
-       pip install git+https://github.com/m-richards/RecursiveLogit.git
+       python -m virtualenv venv
+       python -m pip install -r requirements_strict_2024.txt
 
 
-It is recommended to use some kind of virtual environment to avoid conflicting package versions.
-There is also a :code:`requirements_strict.txt` which explicitly specifies package versions. This
-will likely contain less up to date versions, but should always work regardless of future
-api changes of the dependencies.
 
 Example Usage
 -------------

src/recursiveRouteChoice/data_loading.py

@@ -65,7 +65,7 @@ def load_csv_to_sparse(fname, dtype=None, delim=None, square_matrix=True, shape=
 
     Parameters
     ----------
-    fname : str
+    fname : str | Path
     dtype :
     delim : str, optional
     square_matrix : bool
@@ -261,7 +261,7 @@ def load_tntp_node_formulation(net_fpath, columns_to_extract=None, sparse_format
         data = net2[columns_to_extract[i]].values
         data_mat = sparse.coo_matrix((data, (rows, cols)))
         if sparse_format is False:
-            data_mat = data_mat.A
+            data_mat = data_mat.toarray()
         data_list.append(data_mat)
         data_list_headers.append(columns_to_extract[i])
 

tests/docs/test_sioux_falls_example.py

@@ -4,6 +4,7 @@
 
 
 """
+from pathlib import Path
 
 import numpy as np
 
@@ -15,7 +16,7 @@
 # DATA
 import os
 print("sys path is", os.getcwd(), os.listdir(os.getcwd()))
-network_file = os.path.join("tests", "docs", "SiouxFalls_net.tntp")
+network_file = Path(__file__).parent.parent.joinpath("docs", "SiouxFalls_net.tntp")
 node_max = 24  # from network file
 
 data_list, data_list_names = load_tntp_node_formulation(

tests/test_basic.py

@@ -4,6 +4,8 @@
 existing code.
 
 """
+from pathlib import Path
+
 from recursiveRouteChoice.recursive_route_choice import ALLOW_POSITIVE_VALUE_FUNCTIONS
 # import pytest -- run with pytest although it's not actually imported
 
@@ -19,6 +21,8 @@
 import os
 from os.path import join
 
+DATA_DIR = Path(__file__).parent.parent / "Datasets"
+
 hand_net_dists = np.array(
     [[4, 3.5, 4.5, 3, 3, 0, 0, 0],
      [3.5, 3, 4, 0, 2.5, 3, 3, 0],
@@ -68,15 +72,15 @@ def _first_example_common_data_checks(travel_times_mat, incidence_mat, obs_mat):
     @staticmethod
     def load_example_tiny_manually():
         subfolder = "ExampleTiny"  # big data from classical v2
-        folder = join("Datasets", subfolder)
+        folder = DATA_DIR / subfolder
         INCIDENCE = "incidence.txt"
         TRAVEL_TIME = 'travelTime.txt'
         OBSERVATIONS = "observations.txt"
         # TURN_ANGLE = "turnAngle.txt"
-        file_incidence = os.path.join(folder, INCIDENCE)
-        file_travel_time = os.path.join(folder, TRAVEL_TIME)
+        file_incidence = folder / INCIDENCE
+        file_travel_time = folder / TRAVEL_TIME
         # file_turn_angle = os.path.join(folder, TURN_ANGLE)
-        file_obs = os.path.join(folder, OBSERVATIONS)
+        file_obs = folder / OBSERVATIONS
 
         travel_times_mat = load_csv_to_sparse(file_travel_time).todok()
         incidence_mat = load_csv_to_sparse(file_incidence, dtype='int').todok()
@@ -107,7 +111,7 @@ def test_example_manual_loading_dense(self):
 
     def test_example_tiny_smart_loading(self):
         subfolder = "ExampleTiny"  # big data from classical v2
-        folder = join("Datasets", subfolder)
+        folder = join(DATA_DIR, subfolder)
         obs_mat, attrs = load_standard_path_format_csv(folder, delim=" ", angles_included=False)
         incidence_mat, travel_times_mat = attrs
         # left, right, _, u_turn = AngleProcessor.get_turn_categorical_matrices()
@@ -172,7 +176,7 @@ def test_example_tiny_modified_sparse(self):
         #  wrong
         # Now is a bad example as  @42f564e9 results in this test case being illegal valued
         subfolder = "ExampleTinyModifiedObs"  # big data from classical v2
-        folder = join("Datasets", subfolder)
+        folder = join(DATA_DIR, subfolder)
 
         obs_mat, attrs = load_standard_path_format_csv(folder, delim=" ", angles_included=True)
         incidence_mat, travel_times_mat, angle_cts_mat = attrs
@@ -187,7 +191,7 @@ def test_example_tiny_modified_sparse(self):
 
     def test_example_tiny_modified_awkward_array(self):
         subfolder = "ExampleTinyModifiedObs"  # big data from classical v2
-        folder = join("Datasets", subfolder)
+        folder = join(DATA_DIR, subfolder)
 
         obs_mat, attrs = load_standard_path_format_csv(folder, delim=" ", angles_included=True)
         import awkward1 as ak
@@ -207,7 +211,7 @@ def test_example_tiny_modified_awkward_array_in_expected_format(self):
         """Test's awkward array input obs format when it is actually zero indexed and ragged
         data, not square. See that output is consistent in this case"""
         subfolder = "ExampleTinyModifiedObs"  # big data from classical v2
-        folder = join("Datasets", subfolder)
+        folder = join(DATA_DIR, subfolder)
 
         obs_mat, attrs = load_standard_path_format_csv(folder, delim=" ", angles_included=True)
         import awkward1 as ak
@@ -228,7 +232,7 @@ def test_example_tiny_modified_awkward_array_in_expected_format(self):
 
     def test_example_tiny_modified_dense(self):
         subfolder = "ExampleTinyModifiedObs"  # big data from classical v2
-        folder = join("Datasets", subfolder)
+        folder = join(DATA_DIR, subfolder)
 
         obs_mat, attrs = load_standard_path_format_csv(folder, delim=" ", angles_included=True)
         import awkward1 as ak
@@ -345,7 +349,7 @@ class TestOptimAlgs(object):
 
     def test_compare_optim_methods(self):
         subfolder = "ExampleTinyModifiedObs"  # big data from classical v2
-        folder = join("Datasets", subfolder)
+        folder = join(DATA_DIR, subfolder)
 
         obs_mat, attrs = load_standard_path_format_csv(folder, delim=" ", angles_included=True)
         import awkward1 as ak