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Update Version 0.1.0

plotlyimex.py

@@ -19,20 +19,20 @@ def clear_screen():
 
 def print_header():
     # Print the header
-    print(" plotlyimex v0.2 by ot2i7ba ")
-    print("============================")
+    print(" plotlyimex v0.1.0 by ot2i7ba ")
+    print("==============================")
     print("")
 
-def get_csv_filename():
-    # Clear the screen and print the header
-    clear_screen()
-    print_header()
-
+def print_csv_format_info():
     # Provide information about the required CSV file format
-    print("Please provide a CSV file with the following columns: latitude, longitude, id, userId, lastSeenAt, speed, direction, source.")
+    print("Please provide a CSV file with the following columns:")
+    print("latitude, longitude, id, userId, lastSeenAt, speed, direction, source.")
     print("The file should ideally be comma-separated.")
-
+    print("")
+
+def get_csv_filename():
     # Prompt the user to input the CSV filename
+    print()
     csv_file = input("Input csv filename (enter for 'import.csv'): ")
 
     # Set default filename if none provided
@@ -51,11 +51,8 @@ def validate_csv_file(csv_file):
     return csv_file
 
 def get_delimiter():
-    # Clear the screen and print the header
-    clear_screen()
-    print_header()
-
     # Prompt the user to input the delimiter used in the CSV file
+    print()
     delimiter = input("Enter the delimiter used in the CSV file (',' for comma, ';' for semicolon, default is ','): ")
 
     # Set default delimiter to comma if none provided
@@ -65,63 +62,66 @@ def get_delimiter():
 
 def load_csv(csv_file, delimiter):
     # Load the CSV file using pandas with the specified delimiter
-    return pd.read_csv(csv_file, delimiter=delimiter, usecols=["latitude", "longitude", "id", "userId", "lastSeenAt", "speed", "direction", "source"])
+    try:
+        df = pd.read_csv(csv_file, delimiter=delimiter, usecols=["latitude", "longitude", "id", "userId", "lastSeenAt", "speed", "direction", "source"])
+        return df
+    except Exception as e:
+        raise ValueError(f"Error loading CSV file: {e}")
 
 def choose_plot_type():
-    # Clear the screen and print the header
-    clear_screen()
-    print_header()
-
-    # Define available plot types
+    # Print the plot type options
+    print()
+    print("Choose a plot type:")
     plot_types = {
         "1": "Scatter Plot",
         "2": "Density Plot",
         "3": "Lines Plot",
         "A": "All"
     }
-
-    # Print the plot type options
-    print("Choose a plot type:")
     for key, value in plot_types.items():
         print(f"{key}. {value}")
 
     # Prompt the user to select a plot type
+    print()
     choice = input("Enter the number of the plot type (default is 1): ")
     return plot_types.get(choice, "Scatter Plot")
 
 def create_map(df, plot_type):
     # Create the appropriate plot based on the plot type selected
-    if plot_type == "Scatter Plot":
-        fig = px.scatter_mapbox(df, lat="latitude", lon="longitude", hover_name="id",
-                                hover_data=["userId", "lastSeenAt", "speed", "direction", "source"],
-                                zoom=3)
-    elif plot_type == "Density Plot":
-        fig = px.density_mapbox(df, lat="latitude", lon="longitude", hover_name="id",
-                                hover_data=["userId", "lastSeenAt", "speed", "direction", "source"],
-                                zoom=3)
-    elif plot_type == "Lines Plot":
-        fig = px.line_geo(df, lat="latitude", lon="longitude", hover_name="id",
-                          hover_data=["userId", "lastSeenAt", "speed", "direction", "source"],
-                          projection="orthographic")
-    else:
-        raise ValueError(f"Unknown plot type: {plot_type}")
-
-    # Update the layout of the map
-    fig.update_layout(mapbox_style="open-street-map", height=1080, width=1920)
-    return fig
+    try:
+        if plot_type == "Scatter Plot":
+            fig = px.scatter_mapbox(df, lat="latitude", lon="longitude", hover_name="id",
+                                    hover_data=["userId", "lastSeenAt", "speed", "direction", "source"],
+                                    zoom=3)
+        elif plot_type == "Density Plot":
+            fig = px.density_mapbox(df, lat="latitude", lon="longitude", hover_name="id",
+                                    hover_data=["userId", "lastSeenAt", "speed", "direction", "source"],
+                                    zoom=3)
+        elif plot_type == "Lines Plot":
+            fig = px.line_geo(df, lat="latitude", lon="longitude", hover_name="id",
+                              hover_data=["userId", "lastSeenAt", "speed", "direction", "source"],
+                              projection="orthographic")
+        else:
+            raise ValueError(f"Unknown plot type: {plot_type}")
+
+        # Update the layout of the map
+        fig.update_layout(mapbox_style="open-street-map", height=1080, width=1920)
+        return fig
+    except Exception as e:
+        raise ValueError(f"Error creating map: {e}")
 
 def export_plot(fig, plot_name):
     # Export the plot to an HTML file
-    html_file = f"export_{plot_name}.html"
-    pio.write_html(fig, file=html_file)
-    print(f"Plot saved as {html_file}")
+    try:
+        html_file = f"export_{plot_name}.html"
+        pio.write_html(fig, file=html_file)
+        print(f"Plot saved as {html_file}")
+    except Exception as e:
+        raise ValueError(f"Error exporting plot: {e}")
 
 def get_html_filename(default_name):
-    # Clear the screen and print the header
-    clear_screen()
-    print_header()
-
     # Prompt the user to input the output HTML filename
+    print()
     html_file = input(f"Output html filename (enter for '{default_name}'): ")
 
     # Set default filename if none provided
@@ -133,8 +133,8 @@ def get_html_filename(default_name):
 
 def export_all_plots(df):
     # Export all plot types using parallel processing
+    plot_types = ["Scatter Plot", "Density Plot", "Lines Plot"]
     with ThreadPoolExecutor() as executor:
-        plot_types = ["Scatter Plot", "Density Plot", "Lines Plot"]
         futures = []
         for plot_type in plot_types:
             futures.append(executor.submit(export_plot, create_map(df, plot_type), plot_type.lower().replace(" ", "_")))
@@ -145,6 +145,9 @@ def main():
     # Clear the screen and print the header
     clear_screen()
     print_header()
+
+    # Provide information about the required CSV file format
+    print_csv_format_info()
 
     # Define argument parser for command-line options
     parser = argparse.ArgumentParser(description='Generate an interactive map from a CSV file.')
@@ -155,7 +158,7 @@ def main():
 
     try:
         # Get and validate the input CSV filename
-        csv_file = args.input
+        csv_file = get_csv_filename()
         validate_csv_file(csv_file)
 
         # Get the delimiter used in the CSV file

requirements.txt

@@ -1,3 +1,2 @@
 pandas==1.5.3
 plotly==5.10.0
-argparse==1.4.0