Move dev/unused dependencies to optional extras (#4)

* Move dev/unused dependencies to optional extras

Remove ruff, pytest, pydeface, jupyterlab, ipywidgets, h5py, pillow,
and lxml from runtime dependencies. None are imported by the package
source code. ruff and pytest are moved to [dev] optional extras with
correct version pins. The rest are dropped entirely.

Closes #3 (partially)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Fix typo, remove dead code, add node_modules to gitignore

- Fix "fmriprepp" -> "fmriprep" typo in utils.py docstrings
- Remove unreachable Python 3.8 fallback in io.py (min is 3.9)
- Add node_modules/ to .gitignore

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Add minimal CI workflow

Runs lint (ruff) and tests (pytest) on Python 3.9-3.12 via GitHub
Actions on pushes and PRs to main/master.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Fix lint errors in QA scripts

- Remove unused loop variables (B007)
- Remove unused local variable (F841)
- Fix line-too-long errors (E501)

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Drop Python 3.9 support (EOL), require >=3.10

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Add strict= to zip() calls and update uv.lock for Python >=3.10

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Fix remaining zip() strict= lint errors

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

* Use strict=True in zip() calls to catch length mismatches

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: mvdoc

.github/workflows/ci.yml

@@ -0,0 +1,32 @@
+name: CI
+
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+    branches: [main, master]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.10", "3.11", "3.12"]
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: astral-sh/setup-uv@v4
+        with:
+          version: "latest"
+
+      - name: Set up Python ${{ matrix.python-version }}
+        run: uv python install ${{ matrix.python-version }}
+
+      - name: Install dependencies
+        run: uv sync --extra dev
+
+      - name: Lint
+        run: uv run ruff check src/ scripts/qa/
+
+      - name: Test
+        run: uv run pytest tests/ -q

.gitignore

@@ -72,3 +72,6 @@ private
 
 # NFS hanging stuff
 .nfs*
+
+# Node
+node_modules/

pyproject.toml

@@ -13,13 +13,12 @@ authors = [
 ]
 readme = "README.md"
 license = {file = "LICENSE"}
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 classifiers = [
     "Development Status :: 3 - Alpha",
     "Intended Audience :: Science/Research",
     "License :: OSI Approved :: BSD License",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
@@ -34,26 +33,18 @@ dependencies = [
     "nibabel>=3.0.0",
     "nilearn>=0.6.0",
     "scikit-learn>=0.22.0",
-    "jupyterlab>=3.0.0",
-    "ipywidgets>=7.5.0",
-    "h5py>=2.10.0",
     "joblib>=1.0.0",
-    "pillow>=7.0.0",
-    "lxml>=4.5.0",
-    "ruff>=0.12.12",
     "tqdm>=4.67.1",
     "jinja2>=3.0.0",
     "pyyaml>=6.0",
     "pybids>=0.16.0",
     "pycortex>=1.0.0",
-    "pytest>=8.4.2",
-    "pydeface>=2.0.2",
 ]
 
 [project.optional-dependencies]
 dev = [
-    "pytest>=6.0",
-    "ruff>=0.1.0",
+    "pytest>=8.4.2",
+    "ruff>=0.12.12",
 ]
 
 [project.urls]
@@ -71,7 +62,7 @@ hyperface = ["assets/*.yaml", "templates/*.html"]
 
 [tool.ruff]
 line-length = 88
-target-version = "py39"
+target-version = "py310"
 # Exclude archival code that should not be modified
 exclude = [
     "scripts/presentation/**",  # Legacy Python 2 stimulus presentation code

scripts/qa/print-tsnr-summary.py

@@ -85,14 +85,18 @@ def format_task_summary(task_stats: dict) -> str:
         f"  Number of subjects: {n_subjects}",
         "",
         "  tSNR (temporal signal-to-noise ratio):",
-        f"    Mean across subjects: {np.mean(mean_tsnrs):.1f} ± {np.std(mean_tsnrs):.1f}",
+        f"    Mean across subjects: {np.mean(mean_tsnrs):.1f}"
+        f" ± {np.std(mean_tsnrs):.1f}",
         f"    Median across subjects: {np.median(mean_tsnrs):.1f}",
         f"    Min: {np.min(mean_tsnrs):.1f}",
         f"    Max: {np.max(mean_tsnrs):.1f}",
         "",
         "  Paper-ready text:",
-        f"    The mean tSNR across subjects was {np.mean(mean_tsnrs):.1f} ± {np.std(mean_tsnrs):.1f} "
-        f"(median {np.median(mean_tsnrs):.1f}, min {np.min(mean_tsnrs):.1f}, max {np.max(mean_tsnrs):.1f}).",
+        f"    The mean tSNR across subjects was "
+        f"{np.mean(mean_tsnrs):.1f} ± {np.std(mean_tsnrs):.1f} "
+        f"(median {np.median(mean_tsnrs):.1f}, "
+        f"min {np.min(mean_tsnrs):.1f}, "
+        f"max {np.max(mean_tsnrs):.1f}).",
         "",
     ]
 

scripts/qa/qa-plot-accuracy.py

@@ -134,7 +134,7 @@ def plot_accuracy_figure(
 
     # Bar plot for mean accuracy
     x_positions = np.arange(len(subjects))
-    bars = ax.bar(
+    ax.bar(
         x_positions,
         mean_accuracies,
         color=PRIMARY_COLOR,
@@ -145,7 +145,7 @@ def plot_accuracy_figure(
     )
 
     # Scatter plot for individual run values
-    for i, (x_pos, values) in enumerate(zip(x_positions, all_run_values)):
+    for x_pos, values in zip(x_positions, all_run_values, strict=True):
         jitter = np.random.uniform(-0.15, 0.15, len(values))
         ax.scatter(
             [x_pos + j for j in jitter],
@@ -205,7 +205,7 @@ def format_accuracy_summary(accuracy_data: dict[str, dict[str, int]]) -> str:
     subject_means = []
     perfect_subjects = 0
 
-    for subject, runs in accuracy_data.items():
+    for _subject, runs in accuracy_data.items():
         values = list(runs.values())
         all_values.extend(values)
         subject_means.append(np.mean(values))
@@ -247,7 +247,8 @@ def format_accuracy_summary(accuracy_data: dict[str, dict[str, int]]) -> str:
             "",
             "Paper-ready text:",
             f"  Participants achieved a mean accuracy of {np.mean(subject_means):.1f}% "
-            f"(median {np.median(subject_means):.1f}%, min {np.min(subject_means):.1f}%, "
+            f"(median {np.median(subject_means):.1f}%, "
+            f"min {np.min(subject_means):.1f}%, "
             f"max {np.max(subject_means):.1f}%) on the visual memory task. "
             f"{perfect_subjects} out of {n_subjects} participants achieved "
             f"100% accuracy across all runs.",

scripts/qa/qa-plot-isc.py

@@ -101,7 +101,7 @@ def print_summary_stats(isc_data: list[np.ndarray], subject_ids: list[str]) -> N
     print(header)
     print("-" * 60)
 
-    for subject_id, isc in zip(subject_ids, isc_data):
+    for subject_id, isc in zip(subject_ids, isc_data, strict=True):
         valid = isc[np.isfinite(isc)]
         vals = [valid.mean(), np.median(valid), valid.std(), valid.min(), valid.max()]
         row = f"{subject_id:<15} " + " ".join(f"{v:>8.4f}" for v in vals)
@@ -173,7 +173,7 @@ def main():
 
     # Create individual subject surface plots
     print("\nCreating individual subject surface plots...")
-    for subject_id, isc in zip(subject_ids, isc_data):
+    for subject_id, isc in zip(subject_ids, isc_data, strict=True):
         subject_path = figures_dir / f"{subject_id}_desc-isc_{plot_type}.png"
         create_fsaverage6_plot(
             isc,

scripts/qa/qa-plot-motion.py

@@ -219,7 +219,7 @@ def create_fd_violin_plots_by_session(
     print("  Creating FD violin plots by session...")
 
     session_data: dict[str | None, list[str]] = {}
-    for confounds_file, session in zip(confounds_files, sessions):
+    for confounds_file, session in zip(confounds_files, sessions, strict=True):
         session_data.setdefault(session, []).append(confounds_file)
 
     for session, session_files in session_data.items():

scripts/qa/qa-plot-participant-datasets.py

@@ -29,7 +29,6 @@ def main():
 
     # Create binary matrix
     n_participants = len(df)
-    datasets = ["hyperface", "budapest", "identity_decoding"]
     matrix = np.zeros((n_participants, 3), dtype=int)
 
     # All participants have hyperface

scripts/qa/qa-save-isc.py

@@ -65,7 +65,7 @@ def load_and_process_subject(
     events = load_events(subject, task="visualmemory", data_dir=data_dir)
 
     processed_runs = []
-    for data, evt in zip(responses, events):
+    for data, evt in zip(responses, events, strict=True):
         n_trs = data.shape[0]
         clip_mask = get_clip_tr_mask(evt, n_trs, tr=tr)
         data_clips = data[clip_mask]
@@ -111,7 +111,7 @@ def main():
     n_trs_list = [d.shape[0] for d in subjects_data]
     if len(set(n_trs_list)) > 1:
         print(f"\nERROR: Inconsistent TR counts: {set(n_trs_list)}")
-        for subj_id, n_trs in zip(subject_ids, n_trs_list):
+        for subj_id, n_trs in zip(subject_ids, n_trs_list, strict=True):
             print(f"  {subj_id}: {n_trs}")
         return 1
 

scripts/qa/stimuli/plot-behavioral-ratings.py

@@ -90,7 +90,7 @@ def plot_factor_proportions(df, output_path):
 
     total_n = len(df)
 
-    for ax, (factor, config) in zip(axes, FACTOR_CONFIG.items()):
+    for ax, (factor, config) in zip(axes, FACTOR_CONFIG.items(), strict=True):
         # Get counts in specified order
         counts = df[factor].value_counts()
         order = [lvl for lvl in config["order"] if lvl in counts.index]
@@ -106,7 +106,7 @@ def plot_factor_proportions(df, output_path):
         )
 
         # Add percentage labels above bars
-        for i, (count, bar) in enumerate(zip(counts.values, bars)):
+        for count, bar in zip(counts.values, bars, strict=True):
             pct = 100 * count / total_n
             ax.text(
                 bar.get_x() + bar.get_width() / 2,