tagged with crumb

examples/chess_masters.py

@@ -1,99 +1,100 @@
-"""
-World Chess Championship visualization example.
-
-This example demonstrates PHART's ability to handle complex real-world graphs
-by visualizing World Chess Championship games from 1886-1985.
-
-Data source: https://chessproblem.my-free-games.com/chess/games/Download-PGN.php
-Original example adapted from NetworkX gallery:
-https://networkx.org/documentation/latest/auto_examples/drawing/plot_chess_masters.html
-"""
-
-import bz2
-from pathlib import Path
-import networkx as nx
-from phart import ASCIIRenderer, NodeStyle
-
-# Tag names specifying game info to store in edge data
-GAME_DETAILS = ["Event", "Date", "Result", "ECO", "Site"]
-
-
-def load_chess_games(pgn_file="WCC.pgn.bz2") -> nx.MultiDiGraph:
-    """
-    Read chess games in PGN format.
-
-    Parameters
-    ----------
-    pgn_file : str
-        Path to PGN file (can be bz2 compressed)
-
-    Returns
-    -------
-    NetworkX MultiDiGraph
-        Graph where nodes are players and edges represent games
-    """
-    G = nx.MultiDiGraph()
-    game = {}
-
-    with bz2.BZ2File(pgn_file) as datafile:
-        lines = [line.decode().rstrip("\r\n") for line in datafile]
-
-    for line in lines:
-        if line.startswith("["):
-            tag, value = line[1:-1].split(" ", 1)
-            game[str(tag)] = value.strip('"')
-        else:
-            # Empty line after tag set indicates end of game info
-            if game:
-                white = game.pop("White")
-                black = game.pop("Black")
-                G.add_edge(white, black, **game)
-                game = {}
-    return G
-
-
-def main():
-    # Check if data file exists
-    data_file = Path(__file__).parent / "WCC.pgn.bz2"
-    if not data_file.exists():
-        print(f"Please download WCC.pgn.bz2 to {data_file}")
-        print(
-            "from: https://chessproblem.my-free-games.com/chess/games/Download-PGN.php"
-        )
-        return
-
-    # Load and analyze the data
-    G = load_chess_games(data_file)
-    print(
-        f"Loaded {G.number_of_edges()} chess games between {G.number_of_nodes()} players\n"
-    )
-
-    # Convert to undirected graph for visualization
-    H = nx.Graph(G)
-
-    # Create ASCII visualization
-    renderer = ASCIIRenderer(
-        H,
-        node_style=NodeStyle.SQUARE,  # Square brackets for player names
-        node_spacing=4,  # Space between nodes
-        layer_spacing=1,  # Compact vertical spacing
-    )
-
-    # Save to file and display
-    renderer.write_to_file("chess_masters.txt")
-    print(renderer.render())
-
-    # Print some interesting statistics
-    print("\nMost frequent openings:")
-    openings = {}
-    for _, _, game_info in G.edges(data=True):
-        if "ECO" in game_info:
-            eco = game_info["ECO"]
-            openings[eco] = openings.get(eco, 0) + 1
-
-    for eco, count in sorted(openings.items(), key=lambda x: x[1], reverse=True)[:5]:
-        print(f"ECO {eco}: {count} games")
-
-
-if __name__ == "__main__":
-    main()
+"""
+World Chess Championship visualization example.
+
+This example demonstrates PHART's ability to handle complex real-world graphs
+by visualizing World Chess Championship games from 1886-1985.
+
+Data source: https://chessproblem.my-free-games.com/chess/games/Download-PGN.php
+Original example adapted from NetworkX gallery:
+https://networkx.org/documentation/latest/auto_examples/drawing/plot_chess_masters.html
+"""
+# src path: examples\chess_masters.py
+
+import bz2
+from pathlib import Path
+import networkx as nx
+from phart import ASCIIRenderer, NodeStyle
+
+# Tag names specifying game info to store in edge data
+GAME_DETAILS = ["Event", "Date", "Result", "ECO", "Site"]
+
+
+def load_chess_games(pgn_file="WCC.pgn.bz2") -> nx.MultiDiGraph:
+    """
+    Read chess games in PGN format.
+
+    Parameters
+    ----------
+    pgn_file : str
+        Path to PGN file (can be bz2 compressed)
+
+    Returns
+    -------
+    NetworkX MultiDiGraph
+        Graph where nodes are players and edges represent games
+    """
+    G = nx.MultiDiGraph()
+    game = {}
+
+    with bz2.BZ2File(pgn_file) as datafile:
+        lines = [line.decode().rstrip("\r\n") for line in datafile]
+
+    for line in lines:
+        if line.startswith("["):
+            tag, value = line[1:-1].split(" ", 1)
+            game[str(tag)] = value.strip('"')
+        else:
+            # Empty line after tag set indicates end of game info
+            if game:
+                white = game.pop("White")
+                black = game.pop("Black")
+                G.add_edge(white, black, **game)
+                game = {}
+    return G
+
+
+def main():
+    # Check if data file exists
+    data_file = Path(__file__).parent / "WCC.pgn.bz2"
+    if not data_file.exists():
+        print(f"Please download WCC.pgn.bz2 to {data_file}")
+        print(
+            "from: https://chessproblem.my-free-games.com/chess/games/Download-PGN.php"
+        )
+        return
+
+    # Load and analyze the data
+    G = load_chess_games(data_file)
+    print(
+        f"Loaded {G.number_of_edges()} chess games between {G.number_of_nodes()} players\n"
+    )
+
+    # Convert to undirected graph for visualization
+    H = nx.Graph(G)
+
+    # Create ASCII visualization
+    renderer = ASCIIRenderer(
+        H,
+        node_style=NodeStyle.SQUARE,  # Square brackets for player names
+        node_spacing=4,  # Space between nodes
+        layer_spacing=1,  # Compact vertical spacing
+    )
+
+    # Save to file and display
+    renderer.write_to_file("chess_masters.txt")
+    print(renderer.render())
+
+    # Print some interesting statistics
+    print("\nMost frequent openings:")
+    openings = {}
+    for _, _, game_info in G.edges(data=True):
+        if "ECO" in game_info:
+            eco = game_info["ECO"]
+            openings[eco] = openings.get(eco, 0) + 1
+
+    for eco, count in sorted(openings.items(), key=lambda x: x[1], reverse=True)[:5]:
+        print(f"ECO {eco}: {count} games")
+
+
+if __name__ == "__main__":
+    main()

examples/dependency_tree.py

@@ -1,74 +1,75 @@
-"""
-Example of using PHART to visualize package dependencies.
-"""
-
-import networkx as nx
-from phart import ASCIIRenderer, NodeStyle
-
-
-def create_sample_dependencies():
-    """Create a sample package dependency graph."""
-    G = nx.DiGraph()
-
-    # Main package dependencies
-    dependencies = {
-        "my-app": ["flask", "sqlalchemy", "celery"],
-        "flask": ["werkzeug", "jinja2", "click"],
-        "sqlalchemy": ["greenlet"],
-        "celery": ["click", "redis"],
-        "jinja2": ["markupsafe"],
-    }
-
-    # Add all edges
-    for package, deps in dependencies.items():
-        for dep in deps:
-            G.add_edge(package, dep)
-
-    return G
-
-
-def create_circular_deps():
-    """Create a dependency graph with circular references."""
-    G = nx.DiGraph()
-
-    # Circular dependency example
-    dependencies = {
-        "package_a": ["package_b", "requests"],
-        "package_b": ["package_c"],
-        "package_c": ["package_a"],  # Creates cycle
-        "requests": ["urllib3", "certifi"],
-    }
-
-    for package, deps in dependencies.items():
-        for dep in deps:
-            G.add_edge(package, dep)
-
-    return G
-
-
-def main():
-    print("Package Dependency Examples")
-    print("=========================")
-
-    # Simple dependency tree
-    print("\nTypical Package Dependencies:")
-    G = create_sample_dependencies()
-    renderer = ASCIIRenderer(G, node_style=NodeStyle.MINIMAL)
-    print(renderer.render())
-
-    # Circular dependencies
-    print("\nCircular Dependencies:")
-    G = create_circular_deps()
-    renderer = ASCIIRenderer(G)
-    print(renderer.render())
-
-    # Detect and print cycles
-    cycles = list(nx.simple_cycles(G))
-    if cycles:
-        print("\nDetected dependency cycles:")
-        for cycle in cycles:
-            print(" -> ".join(cycle + [cycle[0]]))
-
-
-if __name__ == "__main__":
-    main()
+"""
+Example of using PHART to visualize package dependencies.
+"""
+# src path: examples\dependency_tree.py
+
+import networkx as nx
+from phart import ASCIIRenderer, NodeStyle
+
+
+def create_sample_dependencies():
+    """Create a sample package dependency graph."""
+    G = nx.DiGraph()
+
+    # Main package dependencies
+    dependencies = {
+        "my-app": ["flask", "sqlalchemy", "celery"],
+        "flask": ["werkzeug", "jinja2", "click"],
+        "sqlalchemy": ["greenlet"],
+        "celery": ["click", "redis"],
+        "jinja2": ["markupsafe"],
+    }
+
+    # Add all edges
+    for package, deps in dependencies.items():
+        for dep in deps:
+            G.add_edge(package, dep)
+
+    return G
+
+
+def create_circular_deps():
+    """Create a dependency graph with circular references."""
+    G = nx.DiGraph()
+
+    # Circular dependency example
+    dependencies = {
+        "package_a": ["package_b", "requests"],
+        "package_b": ["package_c"],
+        "package_c": ["package_a"],  # Creates cycle
+        "requests": ["urllib3", "certifi"],
+    }
+
+    for package, deps in dependencies.items():
+        for dep in deps:
+            G.add_edge(package, dep)
+
+    return G
+
+
+def main():
+    print("Package Dependency Examples")
+    print("=========================")
+
+    # Simple dependency tree
+    print("\nTypical Package Dependencies:")
+    G = create_sample_dependencies()
+    renderer = ASCIIRenderer(G, node_style=NodeStyle.MINIMAL)
+    print(renderer.render())
+
+    # Circular dependencies
+    print("\nCircular Dependencies:")
+    G = create_circular_deps()
+    renderer = ASCIIRenderer(G)
+    print(renderer.render())
+
+    # Detect and print cycles
+    cycles = list(nx.simple_cycles(G))
+    if cycles:
+        print("\nDetected dependency cycles:")
+        for cycle in cycles:
+            print(" -> ".join(cycle + [cycle[0]]))
+
+
+if __name__ == "__main__":
+    main()