feat!: support syntaxless-api (#47)

.github/workflows/ci.yml

@@ -77,6 +77,8 @@ jobs:
         uses: psf/black@stable
         with:
           options: "--diff --check --color --verbose"
+          version: "23.3.0"
+
 
   commit-lint:
     runs-on: ubuntu-latest

example/bar/matplotlib/example_mpl_bar_plot.py

@@ -1,37 +1,17 @@
-import os
-
 import matplotlib.pyplot as plt
 import maidr
 import seaborn as sns
 
+# Load dataset
+tips = sns.load_dataset("tips")
 
-def get_filepath(filename: str) -> str:
-    current_file_path = os.path.abspath(__file__)
-    directory = os.path.dirname(current_file_path)
-    return os.path.join(directory, filename)
-
-
-def plot():
-    # Load dataset
-    tips = sns.load_dataset("tips")
-
-    # Create a bar plot
-    cut_counts = tips["day"].value_counts()
-    plt.figure(figsize=(10, 6))
-    b_plot = plt.bar(cut_counts.index, list(cut_counts.values), color="skyblue")
-    plt.title("The Number of Tips by Day")
-    plt.xlabel("Day")
-    plt.ylabel("Count")
-
-    return b_plot
-
-
-def main():
-    bar_plot = plot()
-    bar_maidr = maidr.bar(bar_plot)
-    bar_maidr.save_html(get_filepath("example_mpl_bar_plot.html"))
-    bar_maidr.show()
-
+# Create a bar plot
+cut_counts = tips["day"].value_counts()
+plt.figure(figsize=(10, 6))
+b_plot = plt.bar(cut_counts.index, list(cut_counts.values), color="skyblue")
+plt.title("The Number of Tips by Day")
+plt.xlabel("Day")
+plt.ylabel("Count")
 
-if __name__ == "__main__":
-    main()
+plt.show()
+maidr.show(b_plot)

example/bar/seaborn/example_sns_bar_plot.py

@@ -1,38 +1,24 @@
-import os
-
 import matplotlib.pyplot as plt
 import maidr
 import seaborn as sns
 
 
-def get_filepath(filename: str) -> str:
-    current_file_path = os.path.abspath(__file__)
-    directory = os.path.dirname(current_file_path)
-    return os.path.join(directory, filename)
-
-
-def plot():
-    # Load the penguins dataset
-    penguins = sns.load_dataset("penguins")
-
-    # Create a bar plot showing the average body mass of penguins by species
-    plt.figure(figsize=(10, 6))
-    b_plot = sns.barplot(
-        x="species", y="body_mass_g", data=penguins, errorbar="sd", palette="Blues_d"
-    )
-    plt.title("Average Body Mass of Penguins by Species")
-    plt.xlabel("Species")
-    plt.ylabel("Body Mass (g)")
-
-    return b_plot
-
-
-def main():
-    bar_plot = plot()
-    bar_maidr = maidr.bar(bar_plot)
-    bar_maidr.save_html(get_filepath("example_sns_bar_plot.html"))
-    bar_maidr.show()
-
-
-if __name__ == "__main__":
-    main()
+# Load the penguins dataset
+penguins = sns.load_dataset("penguins")
+
+# Create a bar plot showing the average body mass of penguins by species
+plt.figure(figsize=(10, 6))
+b_plot = sns.barplot(
+    x="species",
+    y="body_mass_g",
+    data=penguins,
+    errorbar="sd",
+    palette="Blues_d",
+    library="seaborn z",
+)
+plt.title("Average Body Mass of Penguins by Species")
+plt.xlabel("Species")
+plt.ylabel("Body Mass (g)")
+
+plt.show()
+maidr.show(b_plot)

example/box/matplotlib/example_mpl_box.py

@@ -1,54 +1,33 @@
-import os
-
 import matplotlib.pyplot as plt
 import maidr
 import numpy as np
 
 
-def get_filepath(filename: str) -> str:
-    current_file_path = os.path.abspath(__file__)
-    directory = os.path.dirname(current_file_path)
-    return os.path.join(directory, filename)
-
-
-def plot():
-    # Generating random data for three different groups
-    data_group1 = np.random.normal(100, 10, 200)
-    data_group2 = np.random.normal(90, 20, 200)
-    data_group3 = np.random.normal(80, 30, 200)
-
-    # Combine these different datasets into a list
-    data_to_plot = [data_group1, data_group2, data_group3]
-
-    # Create a figure instance
-    fig, ax = plt.subplots()
-
-    # Create the boxplot
-    bp = ax.boxplot(data_to_plot, patch_artist=True)
-
-    # Customize the boxplot colors
-    colors = ["lightblue", "lightgreen", "tan"]
-    for patch, color in zip(bp["boxes"], colors):
-        patch.set_facecolor(color)
-
-    # Adding labels and title
-    ax.set_xticklabels(["Group 1", "Group 2", "Group 3"])
-    ax.set_title("Box Plot Example")
-    ax.set_xlabel("Group")
-    ax.set_ylabel("Values")
+# Generating random data for three different groups
+data_group1 = np.random.normal(100, 10, 200)
+data_group2 = np.random.normal(90, 20, 200)
+data_group3 = np.random.normal(80, 30, 200)
 
-    # Show the plot
-    plt.show()
+# Combine these different datasets into a list
+data_to_plot = [data_group1, data_group2, data_group3]
 
-    return bp
+# Create a figure instance
+fig, ax = plt.subplots()
 
+# Create the boxplot
+bp = ax.boxplot(data_to_plot, patch_artist=True)
 
-def main():
-    box_plot = plot()
-    box_maidr = maidr.box(box_plot)
-    box_maidr.save_html(get_filepath("example_mpl_box.html"))
-    box_maidr.show()
+# Customize the boxplot colors
+colors = ["lightblue", "lightgreen", "tan"]
+for patch, color in zip(bp["boxes"], colors):
+    patch.set_facecolor(color)
 
+# Adding labels and title
+ax.set_xticklabels(["Group 1", "Group 2", "Group 3"])
+ax.set_title("Box Plot Example")
+ax.set_xlabel("Group")
+ax.set_ylabel("Values")
 
-if __name__ == "__main__":
-    main()
+# Show the plot
+plt.show()
+maidr.show(bp)