chore(lints): Add many rules for ruff (#1213)

Author: schloerke

Makefile

@@ -186,15 +186,12 @@ clean-test: FORCE ## remove test and coverage artifacts
 # Check lint, test, and format of code
 # -----------------
 check: check-lint check-types check-tests ## check code, style, types, and test (basic CI)
-check-fix: format check-lint check-types check-tests ## check and format code, style, types, and test
-check-lint: check-ruff ## check code formatting and style
+check-fix: format check-types check-tests ## check and format code, style, types, and test
+check-lint: check-ruff ## check code lints and format
 
 check-ruff: $(RUFF) FORCE
-	@echo "-------- Running ruff lint and formatting checks --------"
+	@echo "-------- Running ruff lint and format checks --------"
 	@# Check imports in addition to code
-	@# Reason for two commands: https://github.com/astral-sh/ruff/issues/8232
-	# . $(PYBIN)/activate && \
-	#   ruff check --select I --fix .
 	# Check lints
 	. $(PYBIN)/activate && \
 	  ruff check .
@@ -225,13 +222,17 @@ format: format-ruff ## format code
 format-ruff: $(RUFF) FORCE
 	@echo "-------- Formatting code with ruff --------"
 	@# Reason for two commands: https://github.com/astral-sh/ruff/issues/8232
-	@# Fix imports
+	@# Fix lints
 	. $(PYBIN)/activate && \
-	  ruff check --select I --fix .
+	  ruff check --fix .
 	@# Fix formatting
 	. $(PYBIN)/activate && \
 	  ruff format .
 
+format-ruff-unsafe: $(RUFF) FORCE
+	@echo "-------- Formatting code with ruff (unsafe) --------"
+	. $(PYBIN)/activate && \
+	  ruff check --fix --unsafe-fixes .
 # -----------------
 # Documentation
 # -----------------

examples/brownian/brownian_motion.py

@@ -5,14 +5,14 @@
 # * `brownian_motion()` is a function that generates a random walk
 # * `brownian_widget()` uses restructured plotting code given in article
 
-rs = np.random.RandomState()
+rng = np.random.default_rng()
 
 
 # https://plotly.com/python/3d-line-plots/
 def brownian_motion(T=1, N=100, mu=0.1, sigma=0.01, S0=20):
     dt = float(T) / N
     t = np.linspace(0, T, N)
-    W = rs.standard_normal(size=N)
+    W = rng.standard_normal(size=N)
     W = np.cumsum(W) * np.sqrt(dt)  # standard brownian motion
     X = (mu - 0.5 * sigma**2) * t + sigma * W
     S = S0 * np.exp(X)  # geometric brownian motion
@@ -24,7 +24,7 @@ def brownian_data(n=100, mu=(0.0, 0.00), sigma=(0.1, 0.1), S0=(1.0, 1.0)):
         "x": brownian_motion(T=1, N=n, mu=mu[0], sigma=sigma[0], S0=S0[0]),
         "y": brownian_motion(T=1, N=n, mu=mu[1], sigma=sigma[1], S0=S0[1]),
         # "y": [i for i in range(n)],
-        "z": [i for i in range(n)],
+        "z": list(range(n)),
     }
 
 
@@ -35,12 +35,12 @@ def brownian_widget(width=600, height=600):
                 x=[],
                 y=[],
                 z=[],
-                marker=dict(
-                    size=4,
-                    color=[],
-                    colorscale="Viridis",
-                ),
-                line=dict(color="darkblue", width=2),
+                marker={
+                    "size": 4,
+                    "color": [],
+                    "colorscale": "Viridis",
+                },
+                line={"color": "darkblue", "width": 2},
             )
         ],
         layout={"showlegend": False, "width": width, "height": height},

examples/brownian/mediapipe.py

@@ -60,8 +60,8 @@ def rel_hand(start_pos: int, end_pos: int):
     normal_unit_vec = normal_vec / np.linalg.norm(normal_vec)
 
     def list_to_xyz(x):
-        x = list(map(lambda y: round(y, 2), x))
-        return dict(x=x[0], y=x[1], z=x[2])
+        x = [round(y, 2) for y in x]
+        return {"x": x[0], "y": x[1], "z": x[2]}
 
     # Invert, for some reason
     normal_unit_vec = normal_unit_vec * -1.0
@@ -82,8 +82,8 @@ def list_to_xyz(x):
 
 
 def xyz_mean(points):
-    return dict(
-        x=mean([p["x"] for p in points]),
-        y=mean([p["y"] for p in points]),
-        z=mean([p["z"] for p in points]),
-    )
+    return {
+        "x": mean([p["x"] for p in points]),
+        "y": mean([p["y"] for p in points]),
+        "z": mean([p["z"] for p in points]),
+    }

examples/cpuinfo/app.py

@@ -8,7 +8,7 @@
 
 from math import ceil
 
-import matplotlib
+import matplotlib as mpl
 import matplotlib.pyplot as plt
 import numpy as np
 import pandas as pd
@@ -17,7 +17,7 @@
 
 # The agg matplotlib backend seems to be a little more efficient than the default when
 # running on macOS, and also gives more consistent results across operating systems
-matplotlib.use("agg")
+mpl.use("agg")
 
 # max number of samples to retain
 MAX_SAMPLES = 1000
@@ -166,7 +166,7 @@ def plot():
             ncols=ncols,
             squeeze=False,
         )
-        for i in range(0, ncols * nrows):
+        for i in range(ncols * nrows):
             row = i // ncols
             col = i % ncols
             axes = axeses[row, col]

examples/cpuinfo/fakepsutil.py

@@ -7,12 +7,13 @@ def cpu_count(logical: bool = True):
     return 8 if logical else 4
 
 
-last_sample = np.random.uniform(0, 100, size=cpu_count(True))
+rng = np.random.default_rng()
+last_sample = rng.uniform(0, 100, size=cpu_count(True))
 
 
 def cpu_percent(percpu: bool = False):
     global last_sample
-    delta = np.random.normal(scale=10, size=len(last_sample))
+    delta = rng.normal(scale=10, size=len(last_sample))
     last_sample = (last_sample + delta).clip(0, 100)
     if percpu:
         return last_sample.tolist()

examples/dataframe/app.py

@@ -1,9 +1,13 @@
-import pandas as pd
+from typing import TYPE_CHECKING
+
 import seaborn as sns
 from shinyswatch.theme import darkly
 
 from shiny import App, Inputs, Outputs, Session, reactive, render, req, ui
 
+if TYPE_CHECKING:
+    import pandas as pd
+
 
 def app_ui(req):
     dark = True if "dark" in req.query_params else None

examples/express/accordion_app.py

@@ -17,6 +17,5 @@ def txt():
 
 @render.plot
 def histogram():
-    np.random.seed(19680801)
-    x = 100 + 15 * np.random.randn(437)
+    x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
     plt.hist(x, input.n(), density=True)

examples/express/column_wrap_app.py

@@ -12,14 +12,12 @@
 
         @render.plot
         def histogram():
-            np.random.seed(19680801)
-            x = 100 + 15 * np.random.randn(437)
+            x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
             plt.hist(x, input.n(), density=True)
 
     with ui.card():
 
         @render.plot
         def histogram2():
-            np.random.seed(19680801)
-            x = 100 + 15 * np.random.randn(437)
+            x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
             plt.hist(x, input.n(), density=True, color="red")

examples/express/nav_app.py

@@ -13,8 +13,7 @@
 
             @render.plot
             def histogram():
-                np.random.seed(19680801)
-                x = 100 + 15 * np.random.randn(437)
+                x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
                 plt.hist(x, input.n(), density=True)
 
     with ui.navset_card_underline():
@@ -25,6 +24,5 @@ def histogram():
 
             @render.plot
             def histogram2():
-                np.random.seed(19680801)
-                x = 100 + 15 * np.random.randn(437)
+                x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
                 plt.hist(x, input.n2(), density=True)

examples/express/plot_app.py

@@ -9,6 +9,5 @@
 
 @render.plot
 def histogram():
-    np.random.seed(19680801)
-    x = 100 + 15 * np.random.randn(437)
+    x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
     plt.hist(x, input.n(), density=True)

examples/express/shared_app.py

@@ -12,8 +12,7 @@
 
 @render.plot
 def histogram():
-    np.random.seed(19680801)
-    x = 100 + 15 * np.random.randn(437)
+    x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
     plt.hist(x, shared.rv(), density=True)
 
 

examples/express/sidebar_app.py

@@ -10,6 +10,5 @@
 
 @render.plot
 def histogram():
-    np.random.seed(19680801)
-    x = 100 + 15 * np.random.randn(437)
+    x = 100 + 15 * np.random.default_rng(seed=19680801).standard_normal(437)
     plt.hist(x, input.n(), density=True)

examples/model-score/app.py

@@ -58,7 +58,7 @@ def df():
         params=[150],
     )
     # Convert timestamp to datetime object, which SQLite doesn't support natively
-    tbl["timestamp"] = pd.to_datetime(tbl["timestamp"], utc=True)
+    tbl["timestamp"] = pd.to_datetime(tbl["timestamp"], utc=True, format="ISO8601")
     # Create a short label for readability
     tbl["time"] = tbl["timestamp"].dt.strftime("%H:%M:%S")
     # Reverse order of rows
@@ -81,10 +81,7 @@ def read_time_period(from_time, to_time):
 
 
 model_names = ["model_1", "model_2", "model_3", "model_4"]
-model_colors = {
-    name: color
-    for name, color in zip(model_names, px.colors.qualitative.D3[0 : len(model_names)])
-}
+model_colors = dict(zip(model_names, px.colors.qualitative.D3[0 : len(model_names)]))
 
 
 def app_ui(req):
@@ -224,7 +221,7 @@ def plot_timeseries():
             filtered_df(),
             x="time",
             y="score",
-            labels=dict(score="accuracy"),
+            labels={"score": "accuracy"},
             color="model",
             color_discrete_map=model_colors,
             # The default for render_mode is "auto", which switches between
@@ -238,13 +235,13 @@ def plot_timeseries():
         fig.add_hline(
             THRESHOLD_LOW,
             line_dash="dash",
-            line=dict(color=THRESHOLD_LOW_COLOR, width=2),
+            line={"color": THRESHOLD_LOW_COLOR, "width": 2},
             opacity=0.3,
         )
         fig.add_hline(
             THRESHOLD_MID,
             line_dash="dash",
-            line=dict(color=THRESHOLD_MID_COLOR, width=2),
+            line={"color": THRESHOLD_MID_COLOR, "width": 2},
             opacity=0.3,
         )
 
@@ -260,7 +257,7 @@ def plot_dist():
             facet_row="model",
             nbins=20,
             x="score",
-            labels=dict(score="accuracy"),
+            labels={"score": "accuracy"},
             color="model",
             color_discrete_map=model_colors,
             template="simple_white",
@@ -269,13 +266,13 @@ def plot_dist():
         fig.add_vline(
             THRESHOLD_LOW,
             line_dash="dash",
-            line=dict(color=THRESHOLD_LOW_COLOR, width=2),
+            line={"color": THRESHOLD_LOW_COLOR, "width": 2},
             opacity=0.3,
         )
         fig.add_vline(
             THRESHOLD_MID,
             line_dash="dash",
-            line=dict(color=THRESHOLD_MID_COLOR, width=2),
+            line={"color": THRESHOLD_MID_COLOR, "width": 2},
             opacity=0.3,
         )
 

examples/static_plots/app.py

@@ -54,13 +54,14 @@
 
 
 def server(input: Inputs, output: Outputs, session: Session):
+    rng = np.random.default_rng()
+
     @reactive.calc
     def fake_data():
         n = 5000
         mean = [0, 0]
-        rng = np.random.RandomState(0)
         cov = [(input.var(), input.cov()), (input.cov(), 1 / input.var())]
-        return rng.multivariate_normal(mean, cov, n).T
+        return np.random.default_rng(seed=0).multivariate_normal(mean, cov, n).T
 
     @render.plot
     def seaborn():
@@ -98,7 +99,8 @@ def plotnine():
     @render.plot
     def pandas():
         ts = pd.Series(
-            np.random.randn(1000), index=pd.date_range("1/1/2000", periods=1000)
+            rng.standard_normal(1000),
+            index=pd.date_range("1/1/2000", periods=1000),
         )
         ts = ts.cumsum()
         return ts.plot()