From 3e24e148a15332a3b8b6745936a4ff4ccfa9e5c6 Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 19:09:24 -0500
Subject: [PATCH 1/8] fix format fails

---
 lenskit/__init__.py   | 1 -
 lenskit/math/solve.py | 1 -
 2 files changed, 2 deletions(-)

diff --git a/lenskit/__init__.py b/lenskit/__init__.py
index c43368426..4722caab2 100644
--- a/lenskit/__init__.py
+++ b/lenskit/__init__.py
@@ -8,7 +8,6 @@
 Toolkit for recommender systems research, teaching, and more.
 """
 
-
 from importlib.metadata import PackageNotFoundError, version
 
 from lenskit.algorithms import *  # noqa: F401,F403
diff --git a/lenskit/math/solve.py b/lenskit/math/solve.py
index 75311732b..96997285b 100644
--- a/lenskit/math/solve.py
+++ b/lenskit/math/solve.py
@@ -8,7 +8,6 @@
 Efficient solver routines.
 """
 
-
 import numpy as np
 
 import cffi

From afa3d47a5464267985f6ca51077ef4e146f22fc2 Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 19:11:43 -0500
Subject: [PATCH 2/8] fix lint formatting errors

---
 lenskit/algorithms/__init__.py |  4 ++--
 lenskit/algorithms/als.py      | 29 ++++++++++++++++-------------
 lenskit/algorithms/basic.py    |  5 ++---
 lenskit/algorithms/funksvd.py  |  6 +++---
 lenskit/algorithms/item_knn.py | 13 +++++++------
 lenskit/algorithms/ranking.py  |  4 ++--
 lenskit/algorithms/svd.py      |  6 +++---
 lenskit/algorithms/user_knn.py |  7 +++----
 lenskit/batch/_recommend.py    |  4 ++--
 lenskit/batch/_train.py        |  4 ++--
 lenskit/crossfold.py           |  2 +-
 lenskit/data/matrix.py         |  4 ++--
 lenskit/datasets/fetch.py      |  8 ++++----
 lenskit/datasets/movielens.py  |  5 +++--
 lenskit/math/solve.py          |  3 +--
 lenskit/metrics/topn.py        |  1 +
 lenskit/sharing/__init__.py    | 10 +++++-----
 lenskit/sharing/binpickle.py   |  6 +++---
 lenskit/sharing/shm.py         |  6 +++---
 lenskit/topn.py                |  6 +++---
 lenskit/util/__init__.py       |  6 +++---
 lenskit/util/accum.py          |  1 +
 lenskit/util/debug.py          |  5 +++--
 lenskit/util/log.py            |  3 +--
 lenskit/util/parallel.py       | 16 ++++++++--------
 lenskit/util/random.py         |  1 -
 lenskit/util/test.py           |  4 ++--
 27 files changed, 86 insertions(+), 83 deletions(-)

diff --git a/lenskit/algorithms/__init__.py b/lenskit/algorithms/__init__.py
index d503ac438..ecc8e1299 100644
--- a/lenskit/algorithms/__init__.py
+++ b/lenskit/algorithms/__init__.py
@@ -13,8 +13,8 @@
 classes (:py:mod:`abc`) representing different algorithm capabilities.
 """
 
-from abc import ABCMeta, abstractmethod
 import inspect
+from abc import ABCMeta, abstractmethod
 
 __all__ = ["Algorithm", "Recommender", "Predictor", "CandidateSelector"]
 
@@ -217,8 +217,8 @@ def rated_items(ratings):
         Utility function for converting a series or array into an array of item
         IDs.  Useful in implementations of :py:meth:`candidates`.
         """
-        import pandas as pd
         import numpy as np
+        import pandas as pd
 
         if isinstance(ratings, pd.Series):
             return ratings.index.values
diff --git a/lenskit/algorithms/als.py b/lenskit/algorithms/als.py
index c3b7790ea..aba14e73a 100644
--- a/lenskit/algorithms/als.py
+++ b/lenskit/algorithms/als.py
@@ -8,16 +8,15 @@
 from collections import namedtuple
 
 import numpy as np
-from numba import njit, prange
-
 from csr import CSR
+from numba import njit, prange
 from seedbank import numpy_rng
 
-from .bias import Bias
-from .mf_common import MFPredictor
-from ..data import sparse_ratings
 from .. import util
+from ..data import sparse_ratings
 from ..math.solve import _dposv
+from .bias import Bias
+from .mf_common import MFPredictor
 
 _logger = logging.getLogger(__name__)
 
@@ -563,22 +562,26 @@ class ImplicitMF(MFPredictor):
         initially defaulted to ``True``, but with a warning.  In 0.14 it defaults to ``False``.
 
     Args:
-        features(int): the number of features to train
-        iterations(int): the number of iterations to train
-        reg(float): the regularization factor
-        weight(float): the scaling weight for positive samples (:math:`\\alpha` in :cite:p:`Hu2008-li`).
+        features(int):
+            The number of features to train
+        iterations(int):
+            The number of iterations to train
+        reg(float):
+            The regularization factor
+        weight(float):
+            The scaling weight for positive samples (:math:`\\alpha` in :cite:p:`Hu2008-li`).
         use_ratings(bool):
             Whether to use the `rating` column, if present.  Defaults to ``False``; when ``True``,
-            the values from the ``rating`` column are used, and multipled by ``weight``; if ``False``,
-            ImplicitMF treats every rated user-item pair as having a rating of 1.
+            the values from the ``rating`` column are used, and multipled by ``weight``; if
+            ``False``, ImplicitMF treats every rated user-item pair as having a rating of 1.
         method(str):
             the training method.
 
             ``'cg'`` (the default)
                 Conjugate gradient method :cite:p:`Takacs2011-ix`.
             ``'lu'``
-                A direct implementation of the original implicit-feedback ALS concept :cite:p:`Hu2008-li`
-                using LU-decomposition to solve for the optimized matrices.
+                A direct implementation of the original implicit-feedback ALS concept
+                :cite:p:`Hu2008-li` using LU-decomposition to solve for the optimized matrices.
 
         rng_spec:
             Random number generator or state (see :func:`lenskit.util.random.rng`).
diff --git a/lenskit/algorithms/basic.py b/lenskit/algorithms/basic.py
index d66f0ffc3..bff2e0265 100644
--- a/lenskit/algorithms/basic.py
+++ b/lenskit/algorithms/basic.py
@@ -11,13 +11,12 @@
 import logging
 from collections.abc import Iterable, Sequence
 
-import pandas as pd
 import numpy as np
+import pandas as pd
 
 from ..data import sparse_ratings
-from . import Predictor, Recommender, CandidateSelector
 from ..util import derivable_rng
-
+from . import CandidateSelector, Predictor, Recommender
 from .bias import Bias  # noqa: F401
 from .ranking import TopN  # noqa: F401
 
diff --git a/lenskit/algorithms/funksvd.py b/lenskit/algorithms/funksvd.py
index 410cd9315..0e49fbf6a 100644
--- a/lenskit/algorithms/funksvd.py
+++ b/lenskit/algorithms/funksvd.py
@@ -11,9 +11,9 @@
 import logging
 import time
 
-import pandas as pd
-import numpy as np
 import numba as n
+import numpy as np
+import pandas as pd
 from seedbank import numpy_rng
 
 try:
@@ -21,9 +21,9 @@
 except ImportError:
     from numba import jitclass
 
+from .. import util
 from .bias import Bias
 from .mf_common import MFPredictor
-from .. import util
 
 _logger = logging.getLogger(__name__)
 
diff --git a/lenskit/algorithms/item_knn.py b/lenskit/algorithms/item_knn.py
index e377175dd..c1ff6834e 100644
--- a/lenskit/algorithms/item_knn.py
+++ b/lenskit/algorithms/item_knn.py
@@ -8,24 +8,25 @@
 Item-based k-NN collaborative filtering.
 """
 
-from sys import intern
 import logging
 import warnings
+from sys import intern
 
-import pandas as pd
+import csr.kernel as csrk
 import numpy as np
+import pandas as pd
 import scipy.sparse as sps
 import scipy.sparse.linalg as spla
-from csr import CSR, create_from_sizes, create_empty
-import csr.kernel as csrk
+from csr import CSR, create_empty, create_from_sizes
 from numba import njit, prange
 from numba.typed import List
 
-from lenskit import util, DataWarning, ConfigWarning
+from lenskit import ConfigWarning, DataWarning, util
 from lenskit.data import sparse_ratings
 from lenskit.sharing import in_share_context
-from lenskit.util.parallel import is_mp_worker
 from lenskit.util.accum import kvp_minheap_insert, kvp_minheap_sort
+from lenskit.util.parallel import is_mp_worker
+
 from . import Predictor
 
 _logger = logging.getLogger(__name__)
diff --git a/lenskit/algorithms/ranking.py b/lenskit/algorithms/ranking.py
index a5ae9167d..bbe8f222b 100644
--- a/lenskit/algorithms/ranking.py
+++ b/lenskit/algorithms/ranking.py
@@ -12,8 +12,8 @@
 
 import numpy as np
 
-from . import Recommender, Predictor
 from ..util import derivable_rng
+from . import Predictor, Recommender
 
 _log = logging.getLogger(__name__)
 
@@ -118,7 +118,7 @@ class PlackettLuce(Recommender):
     """
 
     def __init__(self, predictor, selector=None, *, rng_spec=None):
-        from .basic import UnratedItemCandidateSelector, Popular
+        from .basic import Popular, UnratedItemCandidateSelector
 
         if isinstance(predictor, TopN):
             _log.warn("wrapping Top-N in PlackettLuce, candidate selector probably redundant")
diff --git a/lenskit/algorithms/svd.py b/lenskit/algorithms/svd.py
index 622f90747..eb7d1ec1d 100644
--- a/lenskit/algorithms/svd.py
+++ b/lenskit/algorithms/svd.py
@@ -6,8 +6,8 @@
 
 import logging
 
-import pandas as pd
 import numpy as np
+import pandas as pd
 
 try:
     from sklearn.decomposition import TruncatedSVD
@@ -17,10 +17,10 @@
     TruncatedSVD = None
     SKL_AVAILABLE = False
 
-from . import Predictor
-from .bias import Bias
 from ..data import sparse_ratings
 from ..util import Stopwatch
+from . import Predictor
+from .bias import Bias
 
 _log = logging.getLogger(__name__)
 
diff --git a/lenskit/algorithms/user_knn.py b/lenskit/algorithms/user_knn.py
index e8e7dc104..f05583674 100644
--- a/lenskit/algorithms/user_knn.py
+++ b/lenskit/algorithms/user_knn.py
@@ -8,18 +8,17 @@
 User-based k-NN collaborative filtering.
 """
 
-from sys import intern
 import logging
+from sys import intern
 
-import pandas as pd
 import numpy as np
-
+import pandas as pd
 from numba import njit
 
 from .. import util
 from ..data import sparse_ratings
-from . import Predictor
 from ..util.accum import kvp_minheap_insert
+from . import Predictor
 
 _logger = logging.getLogger(__name__)
 
diff --git a/lenskit/batch/_recommend.py b/lenskit/batch/_recommend.py
index aa50924bf..3031eb5df 100644
--- a/lenskit/batch/_recommend.py
+++ b/lenskit/batch/_recommend.py
@@ -7,11 +7,11 @@
 import logging
 import warnings
 
-import pandas as pd
 import numpy as np
+import pandas as pd
 
-from ..algorithms import Recommender
 from .. import util
+from ..algorithms import Recommender
 from ..sharing import PersistedModel
 
 _logger = logging.getLogger(__name__)
diff --git a/lenskit/batch/_train.py b/lenskit/batch/_train.py
index 346b96e8b..b64a46609 100644
--- a/lenskit/batch/_train.py
+++ b/lenskit/batch/_train.py
@@ -6,9 +6,9 @@
 
 import logging
 
-from lenskit.sharing import persist, persist_binpickle
-from lenskit.util.parallel import run_sp
+from lenskit.sharing import persist_binpickle
 from lenskit.util import Stopwatch
+from lenskit.util.parallel import run_sp
 
 _log = logging.getLogger(__name__)
 
diff --git a/lenskit/crossfold.py b/lenskit/crossfold.py
index 0afa94c84..e13c0e3dd 100644
--- a/lenskit/crossfold.py
+++ b/lenskit/crossfold.py
@@ -8,9 +8,9 @@
 Data set cross-folding.
 """
 
-from collections import namedtuple
 import logging
 from abc import ABC, abstractmethod
+from collections import namedtuple
 
 import numpy as np
 import pandas as pd
diff --git a/lenskit/data/matrix.py b/lenskit/data/matrix.py
index fed054ed3..287662b06 100644
--- a/lenskit/data/matrix.py
+++ b/lenskit/data/matrix.py
@@ -8,12 +8,12 @@
 Data manipulation routines.
 """
 
-from collections import namedtuple
 import logging
+from collections import namedtuple
 
-import scipy.sparse as sps
 import numpy as np
 import pandas as pd
+import scipy.sparse as sps
 from csr import CSR
 
 _log = logging.getLogger(__name__)
diff --git a/lenskit/datasets/fetch.py b/lenskit/datasets/fetch.py
index 68399904d..26433ad33 100644
--- a/lenskit/datasets/fetch.py
+++ b/lenskit/datasets/fetch.py
@@ -4,12 +4,12 @@
 # Licensed under the MIT license, see LICENSE.md for details.
 # SPDX-License-Identifier: MIT
 
-import sys
-from zipfile import ZipFile
-from urllib.request import urlopen
 import argparse
-from pathlib import Path
 import logging
+import sys
+from pathlib import Path
+from urllib.request import urlopen
+from zipfile import ZipFile
 
 _log = logging.getLogger("lenskit.datasets.fetch")
 
diff --git a/lenskit/datasets/movielens.py b/lenskit/datasets/movielens.py
index dd61c9ce6..9c6afa5bf 100644
--- a/lenskit/datasets/movielens.py
+++ b/lenskit/datasets/movielens.py
@@ -8,12 +8,13 @@
 Code to import commonly-used RecSys data sets into LensKit-compatible data frames.
 """
 
+import logging
 import os.path
 from pathlib import Path
-import logging
 
-import pandas as pd
 import numpy as np
+import pandas as pd
+
 from lenskit.util import cached
 
 _log = logging.getLogger(__name__)
diff --git a/lenskit/math/solve.py b/lenskit/math/solve.py
index 96997285b..608773cb4 100644
--- a/lenskit/math/solve.py
+++ b/lenskit/math/solve.py
@@ -8,10 +8,9 @@
 Efficient solver routines.
 """
 
-import numpy as np
-
 import cffi
 import numba as n
+import numpy as np
 from numba.extending import get_cython_function_address
 
 __ffi = cffi.FFI()
diff --git a/lenskit/metrics/topn.py b/lenskit/metrics/topn.py
index f6f9988f4..680559f6e 100644
--- a/lenskit/metrics/topn.py
+++ b/lenskit/metrics/topn.py
@@ -10,6 +10,7 @@
 
 import logging
 import warnings
+
 import numpy as np
 import pandas as pd
 
diff --git a/lenskit/sharing/__init__.py b/lenskit/sharing/__init__.py
index 9d795c92e..289430d5d 100644
--- a/lenskit/sharing/__init__.py
+++ b/lenskit/sharing/__init__.py
@@ -8,12 +8,12 @@
 Support for sharing and saving models and data structures.
 """
 
+import logging
 import os
+import threading
 import warnings
-from abc import abstractmethod, ABC
+from abc import ABC, abstractmethod
 from contextlib import contextmanager
-import threading
-import logging
 
 _log = logging.getLogger(__name__)
 
@@ -135,5 +135,5 @@ def persist(model, *, method=None):
     return method(model)
 
 
-from .binpickle import persist_binpickle, BPKPersisted  # noqa: E402,F401
-from .shm import persist_shm, SHMPersisted, SHM_AVAILABLE  # noqa: E402,F401
+from .binpickle import BPKPersisted, persist_binpickle  # noqa: E402,F401
+from .shm import SHM_AVAILABLE, SHMPersisted, persist_shm  # noqa: E402,F401
diff --git a/lenskit/sharing/binpickle.py b/lenskit/sharing/binpickle.py
index a17a72362..c6d89c353 100644
--- a/lenskit/sharing/binpickle.py
+++ b/lenskit/sharing/binpickle.py
@@ -4,15 +4,15 @@
 # Licensed under the MIT license, see LICENSE.md for details.
 # SPDX-License-Identifier: MIT
 
+import gc
+import logging
 import os
 import pathlib
 import tempfile
-import logging
-import gc
 
 import binpickle
 
-from . import sharing_mode, PersistedModel
+from . import PersistedModel, sharing_mode
 
 _log = logging.getLogger(__name__)
 
diff --git a/lenskit/sharing/shm.py b/lenskit/sharing/shm.py
index ecdc41df8..64e266fd7 100644
--- a/lenskit/sharing/shm.py
+++ b/lenskit/sharing/shm.py
@@ -4,12 +4,12 @@
 # Licensed under the MIT license, see LICENSE.md for details.
 # SPDX-License-Identifier: MIT
 
-import sys
 import logging
+import multiprocessing.shared_memory as shm
 import pickle
-from . import sharing_mode, PersistedModel
+import sys
 
-import multiprocessing.shared_memory as shm
+from . import PersistedModel, sharing_mode
 
 SHM_AVAILABLE = sys.platform != "win32"
 
diff --git a/lenskit/topn.py b/lenskit/topn.py
index 6223b45d0..9aa0ea295 100644
--- a/lenskit/topn.py
+++ b/lenskit/topn.py
@@ -4,13 +4,13 @@
 # Licensed under the MIT license, see LICENSE.md for details.
 # SPDX-License-Identifier: MIT
 
-import logging
 import functools as ft
+import logging
 
 import numpy as np
 import pandas as pd
 
-from .metrics.topn import *
+from .metrics.topn import *  # noqa: F403
 from .util import Stopwatch
 
 _log = logging.getLogger(__name__)
@@ -20,7 +20,7 @@ def _length(df, *args, **kwargs):
     return float(len(df))
 
 
-@bulk_impl(_length)
+@bulk_impl(_length)  # noqa: F405
 def _bulk_length(df, *args):
     return df.groupby("LKRecID")["item"].count()
 
diff --git a/lenskit/util/__init__.py b/lenskit/util/__init__.py
index 01c14f704..0ebe9619e 100644
--- a/lenskit/util/__init__.py
+++ b/lenskit/util/__init__.py
@@ -9,14 +9,14 @@
 """
 
 import logging
-from textwrap import dedent
 from copy import deepcopy
+from textwrap import dedent
 
 from ..algorithms import Algorithm
 from .log import log_to_notebook, log_to_stderr  # noqa: F401
-from .timing import Stopwatch  # noqa: F401
-from .random import derivable_rng
 from .parallel import proc_count  # noqa: F401
+from .random import derivable_rng
+from .timing import Stopwatch  # noqa: F401
 
 try:
     import resource
diff --git a/lenskit/util/accum.py b/lenskit/util/accum.py
index 1cc419cc5..fda816f79 100644
--- a/lenskit/util/accum.py
+++ b/lenskit/util/accum.py
@@ -9,6 +9,7 @@
 """
 
 from numba import njit
+
 from .array import swap
 
 
diff --git a/lenskit/util/debug.py b/lenskit/util/debug.py
index dd5d1ff42..06516b62a 100644
--- a/lenskit/util/debug.py
+++ b/lenskit/util/debug.py
@@ -17,10 +17,11 @@
         Turn on verbose logging
 """
 
-import sys
 import logging
-from typing import Optional
+import sys
 from dataclasses import dataclass
+from typing import Optional
+
 import numba
 import threadpoolctl
 
diff --git a/lenskit/util/log.py b/lenskit/util/log.py
index dade6fc27..1e9c1cf31 100644
--- a/lenskit/util/log.py
+++ b/lenskit/util/log.py
@@ -8,10 +8,9 @@
 Logging utilities.
 """
 
-import sys
 import logging
+import sys
 from logging.handlers import QueueListener
-import multiprocessing as mp
 
 _log = logging.getLogger(__name__)
 _lts_initialized = False
diff --git a/lenskit/util/parallel.py b/lenskit/util/parallel.py
index f54c95278..89b367b6d 100644
--- a/lenskit/util/parallel.py
+++ b/lenskit/util/parallel.py
@@ -8,21 +8,21 @@
 Utilities for parallel processing.
 """
 
-import os
-import multiprocessing as mp
-from multiprocessing.queues import SimpleQueue
+import faulthandler
 import functools as ft
 import logging
 import logging.handlers
-import faulthandler
-from concurrent.futures import ProcessPoolExecutor
-from abc import ABC, abstractmethod
+import multiprocessing as mp
+import os
 import pickle
-from threadpoolctl import threadpool_limits
+from abc import ABC, abstractmethod
+from concurrent.futures import ProcessPoolExecutor
+from multiprocessing.queues import SimpleQueue
 
 import seedbank
+from threadpoolctl import threadpool_limits
 
-from lenskit.sharing import persist, PersistedModel
+from lenskit.sharing import PersistedModel, persist
 from lenskit.util.log import log_queue
 
 _log = logging.getLogger(__name__)
diff --git a/lenskit/util/random.py b/lenskit/util/random.py
index f27416575..b6bb6d322 100644
--- a/lenskit/util/random.py
+++ b/lenskit/util/random.py
@@ -9,7 +9,6 @@
 """
 
 import numpy as np
-
 import seedbank
 
 
diff --git a/lenskit/util/test.py b/lenskit/util/test.py
index 703a7c940..a9699ca00 100644
--- a/lenskit/util/test.py
+++ b/lenskit/util/test.py
@@ -14,11 +14,11 @@
 
 import pytest
 
-from lenskit.datasets import MovieLens, ML100K
-from lenskit.crossfold import simple_test_pair
 from lenskit.algorithms.basic import PopScore
 from lenskit.algorithms.ranking import PlackettLuce
 from lenskit.batch import recommend
+from lenskit.crossfold import simple_test_pair
+from lenskit.datasets import ML100K, MovieLens
 
 ml_test = MovieLens("data/ml-latest-small")
 ml100k = ML100K("data/ml-100k")

From 385a9b6fb8421004dc621f6c433200dbcd918af9 Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 19:16:43 -0500
Subject: [PATCH 3/8] update conf.py

---
 docs/conf.py   | 106 ++++++++++++++++++++++++++++++++++++++++++++++---
 pyproject.toml |   1 -
 2 files changed, 100 insertions(+), 7 deletions(-)

diff --git a/docs/conf.py b/docs/conf.py
index 4a05e78bf..7a5c0d2e2 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -6,42 +6,136 @@
 
 import os
 import sys
+from importlib import import_module  # noqa: F401
+
 sys.path.insert(0, os.path.abspath(".."))
 
+import sphinx_rtd_theme  # noqa: F401
+
 import lenskit
 
+# -- Project information -----------------------------------------------------
+
 project = "LensKit"
-copyright = "2023 Michael Ekstrand"
+copyright = "2018–2024 Drexel University, Boise State University, and collaborators"
 author = "Michael D. Ekstrand"
 
+# The short X.Y version
+version = ".".join(lenskit.__version__.split(".")[:2])
+# The full version, including alpha/beta/rc tags
 release = lenskit.__version__
 
+
 extensions = [
+    "myst_nb",
     "sphinx.ext.napoleon",
     "sphinx.ext.autodoc",
     "sphinx.ext.autosummary",
     "sphinx.ext.intersphinx",
+    "sphinx.ext.mathjax",
     "sphinxext.opengraph",
+    "sphinxcontrib.bibtex",
+    "sphinx_rtd_theme",
 ]
 
+# The suffix(es) of source filenames.
+# You can specify multiple suffix as a list of string:
+#
+# source_suffix = ['.rst', '.md']
 source_suffix = ".rst"
 
+# List of patterns, relative to source directory, that match files and
+# directories to ignore when looking for source files.
+# This pattern also affects html_static_path and html_extra_path .
+exclude_patterns = ["_build", "Thumbs.db", ".DS_Store"]
+
+# The name of the Pygments (syntax highlighting) style to use.
 pygments_style = "sphinx"
 highlight_language = "python3"
 
-html_theme = "furo"
+
+html_theme = "sphinx_rtd_theme"
 html_theme_options = {
+    # 'github_user': 'lenskit',
+    # 'github_repo': 'lkpy',
+    # 'travis_button': False,
+    # 'canonical_url': 'https://lkpy.lenskit.org/',
+    # 'font_family': 'Charter, serif'
+    # 'font_family': '"Source Sans Pro", "Georgia Pro", Georgia, serif',
+    # 'font_size': '15px',
+    # 'head_font_family': '"Merriweather Sans", "Arial", sans-serif',
+    # 'code_font_size': '1em',
+    # 'code_font_family': '"Source Code Pro", "Consolas", "Menlo", sans-serif'
 }
+
 templates_path = ["_templates"]
+html_static_path = ["_static"]
+
+# Custom sidebar templates, must be a dictionary that maps document names
+# to template names.
+#
+# The default sidebars (for documents that don't match any pattern) are
+# defined by theme itself.  Builtin themes are using these templates by
+# default: ``['localtoc.html', 'relations.html', 'sourcelink.html',
+# 'searchbox.html']``.
+#
+# html_sidebars = {}
+
+
+# -- Options for HTMLHelp output ---------------------------------------------
+
+# Output file base name for HTML help builder.
+htmlhelp_basename = "LensKitdoc"
 
+
+# -- Options for LaTeX output ------------------------------------------------
+
+latex_elements = {
+    # The paper size ('letterpaper' or 'a4paper').
+    #
+    # 'papersize': 'letterpaper',
+    # The font size ('10pt', '11pt' or '12pt').
+    #
+    # 'pointsize': '10pt',
+    # Additional stuff for the LaTeX preamble.
+    #
+    # 'preamble': '',
+    # Latex figure (float) alignment
+    #
+    # 'figure_align': 'htbp',
+}
+
+# -- Extension configuration -------------------------------------------------
+
+# -- Options for intersphinx extension ---------------------------------------
+
+# Example configuration for intersphinx: refer to the Python standard library.
 intersphinx_mapping = {
     "python": ("https://docs.python.org/3/", None),
+    "pandas": ("http://pandas.pydata.org/pandas-docs/stable/", None),
     "numpy": ("https://docs.scipy.org/doc/numpy/", None),
+    "scipy": ("https://docs.scipy.org/doc/scipy/reference/", None),
+    "scikit": ("https://scikit-learn.org/stable/", None),
     "sklearn": ("https://scikit-learn.org/stable/", None),
+    "binpickle": ("https://binpickle.lenskit.org/en/stable/", None),
+    "csr": ("https://csr.lenskit.org/en/latest/", None),
+    "seedbank": ("https://seedbank.lenskit.org/en/latest/", None),
 }
 
-autodoc_default_options = {
-    "members": True,
-    "member-order": "bysource"
-}
+autodoc_default_options = {"members": True, "member-order": "bysource", "show-inheritance": True}
 autodoc_typehints = "description"
+
+bibtex_bibfiles = ["lenskit.bib"]
+jupyter_execute_notebooks = "off"
+
+# -- Module Canonicalization ------------------------------------------------
+
+# cleanups = {
+#     'lenskit': ['Algorithm', 'Recommender', 'Predictor', 'CandidateSelector']
+# }
+
+# for module, objects in cleanups.items():
+#     mod = import_module(module)
+#     for name in objects:
+#         obj = getattr(mod, name)
+#         obj.__module__ = module
diff --git a/pyproject.toml b/pyproject.toml
index 4be03f645..f9354ddc9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -118,7 +118,6 @@ target-version = "py310"
 exclude = [
   ".git",
   "__pycache__",
-  "docs/conf.py",
   "build",
   "dist",
 ]

From 74c24cdd9160563140e48b19456ab4be5dbaee28 Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 19:17:38 -0500
Subject: [PATCH 4/8] clean overlong lines

---
 lenskit/algorithms/item_knn.py | 65 +++++++++++++++++++---------------
 1 file changed, 37 insertions(+), 28 deletions(-)

diff --git a/lenskit/algorithms/item_knn.py b/lenskit/algorithms/item_knn.py
index c1ff6834e..35d9523c4 100644
--- a/lenskit/algorithms/item_knn.py
+++ b/lenskit/algorithms/item_knn.py
@@ -208,58 +208,67 @@ def _predict_sum(model, nitems, nrange, ratings, rated, targets):
 
 class ItemItem(Predictor):
     """
-    Item-item nearest-neighbor collaborative filtering with ratings. This item-item implementation
-    is not terribly configurable; it hard-codes design decisions found to work well in the previous
-    Java-based LensKit code :cite:p:`Ekstrand2011-bp`.  This implementation is based on the description
-    of item-based CF by :cite:t:`Deshpande2004-ht`, and produces results equivalent to Java LensKit.
+    Item-item nearest-neighbor collaborative filtering with ratings. This
+    item-item implementation is not terribly configurable; it hard-codes design
+    decisions found to work well in the previous Java-based LensKit code
+    :cite:p:`Ekstrand2011-bp`.  This implementation is based on the description
+    of item-based CF by :cite:t:`Deshpande2004-ht`, and produces results
+    equivalent to Java LensKit.
 
     The k-NN predictor supports several aggregate functions:
 
     ``weighted-average``
-        The weighted average of the user's rating values, using item-item similarities as
-        weights.
+        The weighted average of the user's rating values, using item-item
+        similarities as weights.
 
     ``sum``
-        The sum of the similarities between the target item and the user's rated items,
-        regardless of the rating the user gave the items.
+        The sum of the similarities between the target item and the user's rated
+        items, regardless of the rating the user gave the items.
 
     Args:
         nnbrs(int):
-            the maximum number of neighbors for scoring each item (``None`` for unlimited)
+            the maximum number of neighbors for scoring each item (``None`` for
+            unlimited)
         min_nbrs(int): the minimum number of neighbors for scoring each item
         min_sim(float): minimum similarity threshold for considering a neighbor
         save_nbrs(float):
             the number of neighbors to save per item in the trained model
             (``None`` for unlimited)
         feedback(str):
-            Control how feedback should be interpreted.  Specifies defaults for the other
-            settings, which can be overridden individually; can be one of the following values:
+            Control how feedback should be interpreted.  Specifies defaults for
+            the other settings, which can be overridden individually; can be one
+            of the following values:
 
             ``explicit``
-                Configure for explicit-feedback mode: use rating values, center ratings, and
-                use the ``weighted-average`` aggregate method for prediction.  This is the
-                default setting.
+                Configure for explicit-feedback mode: use rating values, center
+                ratings, and use the ``weighted-average`` aggregate method for
+                prediction.  This is the default setting.
 
             ``implicit``
-                Configure for implicit-feedback mode: ignore rating values, do not center ratings,
-                and use the ``sum`` aggregate method for prediction.
+                Configure for implicit-feedback mode: ignore rating values, do
+                not center ratings, and use the ``sum`` aggregate method for
+                prediction.
         center(bool):
-            whether to normalize (mean-center) rating vectors prior to computing similarities
-            and aggregating user rating values.  Defaults to ``True``; turn this off when working
-            with unary data and other data types that don't respond well to centering.
+            whether to normalize (mean-center) rating vectors prior to computing
+            similarities and aggregating user rating values.  Defaults to
+            ``True``; turn this off when working with unary data and other data
+            types that don't respond well to centering.
         aggregate(str):
-            the type of aggregation to do. Can be ``weighted-average`` (the default) or ``sum``.
+            the type of aggregation to do. Can be ``weighted-average`` (the
+            default) or ``sum``.
         use_ratings(bool):
-            whether or not to use the rating values. If ``False``, it ignores rating values and
-            considers an implicit feedback signal of 1 for every (user,item) pair present.
+            whether or not to use the rating values. If ``False``, it ignores
+            rating values and considers an implicit feedback signal of 1 for
+            every (user,item) pair present.
 
     Attributes:
         item_index_(pandas.Index): the index of item IDs.
         item_means_(numpy.ndarray): the mean rating for each known item.
-        item_counts_(numpy.ndarray): the number of saved neighbors for each item.
-        sim_matrix_(matrix.CSR): the similarity matrix.
-        user_index_(pandas.Index): the index of known user IDs for the rating matrix.
-        rating_matrix_(matrix.CSR): the user-item rating matrix for looking up users' ratings.
+        item_counts_(numpy.ndarray): the number of saved neighbors for each
+        item. sim_matrix_(matrix.CSR): the similarity matrix.
+        user_index_(pandas.Index): the index of known user IDs for the rating
+        matrix. rating_matrix_(matrix.CSR): the user-item rating matrix for
+        looking up users' ratings.
     """
 
     IGNORED_PARAMS = ["feedback"]
@@ -312,12 +321,12 @@ def _check_setup(self):
                 )
             if self.aggregate == "weighted-average":
                 _logger.warning(
-                    "item-item configured to ignore ratings, but using weighted averages - likely bug"
+                    "item-item ignoring ratings but using weighted averages - likely bug"
                 )
                 warnings.warn(
                     util.clean_str(
                         """
-                    item-item configured to ignore ratings, but use weighted averages.  This configuration
+                    item-item ignoring ratings but using weighted averages.  This configuration
                     is unlikely to work well.
                 """
                     ),

From 262d9e1bbc1b71e888444de11b732aecd77840c2 Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 19:18:12 -0500
Subject: [PATCH 5/8] clean movielens warnings

---
 lenskit/datasets/movielens.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lenskit/datasets/movielens.py b/lenskit/datasets/movielens.py
index 9c6afa5bf..4155cd5f2 100644
--- a/lenskit/datasets/movielens.py
+++ b/lenskit/datasets/movielens.py
@@ -92,7 +92,7 @@ def movies(self):
         5                      Father of the Bride Part II (1995)                                           Comedy
         ...
         [9125 rows x 2 columns]
-        """
+        """  # noqa: E501
 
         fn = self.path / "movies.csv"
         movies = pd.read_csv(
@@ -377,7 +377,7 @@ def movies(self):
         5                      Father of the Bride Part II (1995)                                           Comedy
         ...
         [10681 rows x 2 columns]
-        """
+        """  # noqa: E501
         fn = self.path / "movies.dat"
         movies = pd.read_csv(
             fn,

From df46c872a06bfed2a6b9120ae9f7ca7c80e9639d Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 18:55:42 -0500
Subject: [PATCH 6/8] specify dependencies more clearly

---
 pyproject.toml | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index f9354ddc9..389ae5598 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -41,8 +41,8 @@ dev = [
   "ruff >= 0.2",
   "copier ==9.*",
   "unbeheader ~= 1.3",           # p2c: -p
-  "ipython",
-  "pyproject2conda",
+  "ipython >= 7",
+  "pyproject2conda ~=0.11",
   "sphinx-autobuild >= 2021",
   "lenskit-build-helpers >=0.1", # p2c: -p
   "invoke >=1",

From 8508bd92d6bece819eed71780dce99c0942410dd Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 18:58:56 -0500
Subject: [PATCH 7/8] use uv to install minimum dependencies

---
 .github/workflows/test.yml | 5 ++---
 min-constraints.txt        | 7 -------
 2 files changed, 2 insertions(+), 10 deletions(-)
 delete mode 100644 min-constraints.txt

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 8d069df17..6ce949a05 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -195,9 +195,8 @@ jobs:
       - name: Set up Python deps
         run: |
           set -e
-          python -m pip install -U pip wheel
-          python -m pip install -c min-constraints.txt .[test]
-          python -m pip install pytest-cov
+          python -m pip install -U 'uv>=0.1.13'
+          uv pip install --system --resolution=lowest -e '.[test]'
 
       - name: Inspect environment
         run: |
diff --git a/min-constraints.txt b/min-constraints.txt
deleted file mode 100644
index 1a8c793f1..000000000
--- a/min-constraints.txt
+++ /dev/null
@@ -1,7 +0,0 @@
-pandas==1.4.0
-numpy==1.22.0
-scipy==1.8.0
-numba==0.56.0
-cffi==1.15.0
-binpickle==0.3.2
-scikit-learn==1.1.0

From 95d63779df95cbe186dc5c80dbe18d8966ecdf33 Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Sat, 2 Mar 2024 19:34:46 -0500
Subject: [PATCH 8/8] change uv resolution to lowest-direct

---
 .github/workflows/test.yml | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
index 6ce949a05..93fe2c2c7 100644
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -196,7 +196,7 @@ jobs:
         run: |
           set -e
           python -m pip install -U 'uv>=0.1.13'
-          uv pip install --system --resolution=lowest -e '.[test]'
+          uv pip install --system --resolution=lowest-direct -e '.[test]'
 
       - name: Inspect environment
         run: |