Pyrefly

.github/workflows/ci.yaml → .github/workflows/ci.yml

@@ -1,4 +1,4 @@
-name: CI
+name: Tests
 
 on:
   push:
@@ -11,7 +11,7 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
 
     steps:
       - name: Check out the code
@@ -27,14 +27,14 @@ jobs:
           curl -LsSf https://astral.sh/uv/install.sh | sh
           echo "$HOME/.cargo/bin" >> $GITHUB_PATH
 
+      - name: Create virtual environment
+        run: uv venv
+
       - name: Install project with dev dependencies
-        run: |
-          uv pip install --system .[dev]
+        run: uv pip install -e .[dev]
 
       - name: Run ruff
-        run: |
-          ruff check .
+        run: uv run ruff check .
 
       - name: Run tests with pytest
-        run: |
-          pytest --cov --cov-report=term-missing
+        run: uv run pytest --cov --cov-report=term-missing

.github/workflows/typecheck.yml

@@ -0,0 +1,37 @@
+name: Typecheck
+
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+    branches: [main, master]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13"]
+
+    steps:
+      - name: Check out the code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install uv
+        run: |
+          curl -LsSf https://astral.sh/uv/install.sh | sh
+          echo "$HOME/.cargo/bin" >> $GITHUB_PATH
+
+      - name: Create virtual environment
+        run: uv venv
+
+      - name: Install project with dev dependencies
+        run: uv pip install -e .[dev]
+
+      - name: Run Pyrefly Type Checker
+        run: uv run pyrefly check

pyproject.toml

@@ -24,12 +24,21 @@ Homepage = "https://github.com/nirum/jetplot"
 
 [project.optional-dependencies]
 dev = [
-    "pre-commit>=2.21.0",
     "pyrefly>=0.14.0",
     "pytest>=7.4.4",
     "pytest-cov>=4.1.0",
     "ruff>=0.11.10",
 ]
+docs = [
+    "mkdocs>=1.5.3",
+    "mkdocs-material>=9.2.7",
+    "mkdocstrings[python]>=0.22.0",
+]
+
+[tool.pyrefly]
+search_path = [
+  "src/"
+]
 
 [tool.ruff]
 lint.extend-ignore = ["E111", "E114", "E501", "F403"]
@@ -39,13 +48,3 @@ package-dir = {"" = "src"}
 
 [tool.setuptools.dynamic]
 version = {attr = "jetplot.__version__"}
-
-[tool.uv]
-default-groups = ["dev", "docs"]
-
-[dependency-groups]
-docs = [
-    "mkdocs>=1.5.3",
-    "mkdocs-material>=9.2.7",
-    "mkdocstrings[python]>=0.22.0",
-]

src/jetplot/chart_utils.py

@@ -129,6 +129,8 @@ def get_bounds(axis, ax=None):
         return ax.spines[spine_key].get_bounds()
     else:
         lower, upper = None, None
+
+        # pyrefly: ignore  # no-matching-overload, bad-argument-type
         for tick, label in zip(ticks(), labels()):
             if label.get_text() != "":
                 if lower is None:
@@ -188,6 +190,8 @@ def yclamp(y0=None, y1=None, dt=None, **kwargs):
     lims = ax.get_ylim()
     y0 = lims[0] if y0 is None else y0
     y1 = lims[1] if y1 is None else y1
+
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     dt = np.mean(np.diff(ax.get_yticks())) if dt is None else dt
 
     new_ticks = np.arange(dt * np.floor(y0 / dt), dt * (np.ceil(y1 / dt) + 1), dt)
@@ -205,6 +209,8 @@ def xclamp(x0=None, x1=None, dt=None, **kwargs):
     lims = ax.get_xlim()
     x0 = lims[0] if x0 is None else x0
     x1 = lims[1] if x1 is None else x1
+
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     dt = np.mean(np.diff(ax.get_xticks())) if dt is None else dt
 
     new_ticks = np.arange(dt * np.floor(x0 / dt), dt * (np.ceil(x1 / dt) + 1), dt)

src/jetplot/colors.py

@@ -37,13 +37,18 @@ def cubehelix(
     lambda_ = np.linspace(vmin, vmax, n)
     x = lambda_**gamma
     phi = 2 * np.pi * (start / 3 + rot * lambda_)
+
+    # pyrefly: ignore  # bad-argument-type, no-matching-overload
     alpha = 0.5 * hue * x * (1.0 - x)
     A = np.array([[-0.14861, 1.78277], [-0.29227, -0.90649], [1.97294, 0.0]])
     b = np.stack([np.cos(phi), np.sin(phi)])
+
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     return Palette((x + alpha * (A @ b)).T)
 
 
 def cmap_colors(cmap: str, n: int, vmin: float = 0.0, vmax: float = 1.0):
+    # pyrefly: ignore  # missing-attribute
     return Palette(cm.__getattribute__(cmap)(np.linspace(vmin, vmax, n)))
 
 

src/jetplot/images.py

@@ -83,7 +83,10 @@ def fsurface(func, xrng=None, yrng=None, n=100, nargs=2, **kwargs):
     xrng = (-1, 1) if xrng is None else xrng
     yrng = xrng if yrng is None else yrng
 
+    # pyrefly: ignore  # missing-argument, no-matching-overload, bad-argument-type
     xs = np.linspace(*xrng, n)
+
+    # pyrefly: ignore  # missing-argument, no-matching-overload, bad-argument-type
     ys = np.linspace(*yrng, n)
 
     xm, ym = np.meshgrid(xs, ys)
@@ -126,6 +129,8 @@ def cmat(
     cb = imv(arr, ax=ax, vmin=vmin, vmax=vmax, cmap=cmap, cbar=cbar)
 
     xs, ys = np.meshgrid(np.arange(num_cols), np.arange(num_rows))
+
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     for x, y, value in zip(xs.flat, ys.flat, arr.flat):
         color = dark_color if (value <= theta) else light_color
         annot = f"{{:{fmt}}}".format(value)
@@ -137,7 +142,10 @@ def cmat(
         ax.set_yticks(np.arange(num_rows))
         ax.set_yticklabels(labels, fontsize=label_fontsize)
 
+    # pyrefly: ignore  # bad-argument-type
     ax.xaxis.set_minor_locator(FixedLocator(np.arange(num_cols) - 0.5))
+
+    # pyrefly: ignore  # bad-argument-type
     ax.yaxis.set_minor_locator(FixedLocator(np.arange(num_rows) - 0.5))
 
     ax.grid(

src/jetplot/plots.py

@@ -54,6 +54,7 @@ def violinplot(
         pc.set_edgecolor(ec)
         pc.set_alpha(1.0)
 
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     q1, medians, q3 = np.percentile(data, [25, 50, 75], axis=0)
 
     ax.vlines(
@@ -76,6 +77,7 @@ def violinplot(
     if showmeans:
         ax.scatter(
             xs,
+            # pyrefly: ignore  # no-matching-overload, bad-argument-type
             np.mean(data, axis=0),
             marker="s",
             color=mc,
@@ -120,6 +122,8 @@ def hist2d(x, y, bins=None, range=None, cmap="hot", **kwargs):
         bins = 25
 
     # compute the histogram
+
+    # pyrefly: ignore  # no-matching-overload, unexpected-keyword, bad-argument-type
     cnt, xe, ye = np.histogram2d(x, y, bins=bins, normed=True, range=range)
 
     # generate the plot
@@ -362,6 +366,7 @@ def ellipse(x, y, n_std=3.0, facecolor="none", estimator="empirical", **kwargs):
     mean_y = np.mean(y)
 
     transform = (
+        # pyrefly: ignore  # bad-argument-type
         Affine2D().rotate_deg(45).scale(scale_x, scale_y).translate(mean_x, mean_y)
     )
 

src/jetplot/signals.py

@@ -1,9 +1,12 @@
 """Tools for signal processing."""
 
+
 from typing import Callable
 
 import numpy as np
 from numpy.typing import ArrayLike
+
+# pyrefly: ignore  # missing-module-attribute
 from scipy.ndimage import gaussian_filter1d
 
 __all__ = ["smooth", "canoncorr", "participation_ratio", "stable_rank", "normalize"]
@@ -58,6 +61,8 @@ def canoncorr(X: ArrayLike, Y: ArrayLike) -> ArrayLike:
        between linear subspaces." Mathematics of computation 27.123 (1973): 579-594.
     """
     # Orthogonalize each subspace
+
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     qu, qv = np.linalg.qr(X)[0], np.linalg.qr(Y)[0]
 
     # singular values of the inner product between the orthogonalized spaces

src/jetplot/style.py

@@ -1,6 +1,8 @@
 """Opinionated matplotlib style defaults."""
 
 from functools import partial
+
+
 from typing import Mapping, Any
 
 from cycler import cycler

src/jetplot/timepiece.py

@@ -110,9 +110,13 @@ def wrapper(*args, **kwargs):
         calls.append(tstop - tstart)
         return results
 
+    # pyrefly: ignore  # missing-attribute
     wrapper.calls = calls
+    # pyrefly: ignore  # missing-attribute
     wrapper.mean = lambda: np.mean(calls)
+    # pyrefly: ignore  # missing-attribute
     wrapper.serr = lambda: np.std(calls) / np.sqrt(len(calls))
+    # pyrefly: ignore  # missing-attribute
     wrapper.summary = lambda: print(
         "Runtimes: {} {} {}".format(
             hrtime(wrapper.mean()), "\u00b1", hrtime(wrapper.serr())

src/jetplot/typing.py

@@ -1,3 +1,4 @@
+
 from typing import Sequence, Union
 
 __all__ = ["Color", "Palette"]

tests/test_demo.py

@@ -8,4 +8,5 @@ def test_peaks():
     n = 256
     xm, ym, zm = demo.peaks(n=n)
 
+
     assert xm.shape == ym.shape == zm.shape == (n, n)

tests/test_signals.py

@@ -5,7 +5,10 @@
 
 
 def test_stable_rank():
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     U, _ = np.linalg.qr(np.random.randn(32, 32))
+
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     V, _ = np.linalg.qr(np.random.randn(32, 32))
     S = np.random.randn(32)
 
@@ -21,6 +24,8 @@ def test_stable_rank():
 def test_participation_ratio():
     def _random_matrix(evals):
         dim = evals.size
+
+        # pyrefly: ignore  # no-matching-overload, bad-argument-type
         Q, _ = np.linalg.qr(np.random.randn(dim, dim))
         return Q @ np.diag(evals) @ Q.T
 
@@ -57,6 +62,8 @@ def test_cca():
 
     X = rs.randn(n, k)
     Y = rs.randn(n, k)
+
+    # pyrefly: ignore  # no-matching-overload, bad-argument-type
     Z = X @ np.linalg.qr(rs.randn(k, k))[0]
 
     # Correlation with itself should be all ones.
@@ -65,7 +72,11 @@ def test_cca():
 
     # Correlation with a different random subspace.
     xy = signals.canoncorr(X, Y)
+
+    # pyrefly: ignore  # bad-argument-type
     assert np.all(xy <= 1.0)
+
+    # pyrefly: ignore  # bad-argument-type
     assert np.all(0.0 <= xy)
     assert 0 < np.sum(xy) < k
 

tests/test_timepiece.py

@@ -2,6 +2,8 @@
 
 from jetplot.timepiece import hrtime, profile
 import numpy as np
+
+# pyrefly: ignore  # import-error
 import pytest
 import time
 
@@ -37,8 +39,12 @@ def test_profile():
     for _ in range(K):
         wrapper(T)
 
+    # pyrefly: ignore  # missing-attribute
     assert isinstance(wrapper.calls, list)
     assert len(wrapper.calls) == K
+    # pyrefly: ignore  # missing-attribute
     assert np.allclose(wrapper.mean(), T, atol=0.01)
+    # pyrefly: ignore  # missing-attribute
     assert np.allclose(wrapper.serr(), 0.0, atol=0.01)
+    # pyrefly: ignore  # missing-attribute
     assert wrapper.summary() is None