Create howto-convert-cable-validation-html.md

Move cabling validation conversion to md

Author: bartpinto

articles/operator-nexus/howto-convert-cable-validation-html.md

@@ -0,0 +1,138 @@
+```
+import json
+import pandas as pd
+from datetime import datetime
+
+now = datetime.now() # current date and time
+date_time = now.strftime("%m-%d-%Y-%H-%M")
+print("date and time:",date_time)
+
+
+# Get the file name as input from the user
+file_name = input("Please provide post validation json file: ")
+# Load the JSON data from the file
+with open(file_name, 'r') as f:
+    data = json.load(f)
+
+# Prepare a list to store the data
+data_list = []
+
+# Loop through each rack in the racks list
+for rack in data['racks']:
+    # Loop through each device in the networkDevices list
+    for device in rack['rackInfo']['networkConfiguration']['networkDevices']:
+        # Loop through each interface map for the device
+        for interface_map in device['fixedInterfaceMaps']:
+            # Loop through each validation result for the interface map
+            for validation_result in interface_map['validationResult']:
+                # Append the data to the list
+                temp_item = [device['name'], interface_map['name'], validation_result['status'], interface_map['destinationHostname'], interface_map['destinationPort'],validation_result['validationDetails']['deviceConfiguration'], validation_result['validationDetails']['error'] , validation_result['validationDetails']['reason'],'FixedInterface']
+                # print(temp_item)
+                data_list.append(temp_item)
+
+        # Check if scaleSpecificInterfaceMaps is not None
+        if device['scaleSpecificInterfaceMaps'] is not None:   
+            # Loop through each scaleSpecificInterface_Map for the interface map
+            for scale_map in device['scaleSpecificInterfaceMaps']:
+                # Loop through each interface map for the device.
+                for interfacemaps in scale_map['InterfaceMaps']:
+                    # Loop through each validation result for the scaleSpecificInterface_Map
+                    for validation_result in interfacemaps['validationResult']:
+                        # Append the data to the list
+                        temp_item = [device['name'], interfacemaps['name'], validation_result['status'], interfacemaps['destinationHostname'], interfacemaps['destinationPort'], validation_result['validationDetails']['deviceConfiguration'], validation_result['validationDetails']['error'] , validation_result['validationDetails']['reason'], 'ScaleSpecificInterface']
+                        # print(temp_item)
+                        data_list.append(temp_item)
+
+# # Check if scaleSpecificInterfaceMaps is not None
+#         if device['topologySpecificInterfaceMaps'] is not None:   
+#             # Loop through each scaleSpecificInterface_Map for the interface map
+#             for topo_map in device['topologySpecificInterfaceMaps']:
+#                 # Loop through each interface map for the device.
+#                 for interfacemaps in topo_map['InterfaceMaps']:
+#                     # Loop through each validation result for the scaleSpecificInterface_Map
+#                     for validation_result in interfacemaps['validationResult']:
+#                         # Append the data to the list
+#                         data_list.append([device['name'], interfacemaps['name'], validation_result['status'], interface_map['destinationHostname'], interface_map['destinationPort'], validation_result['validationDetails']['deviceConfiguration'], validation_result['validationDetails']['error'] , validation_result['validationDetails']['reason'], 'TopologySpecificInterface'])
+
+# Convert the list to a DataFrame
+df = pd.DataFrame(data_list, columns=['Device Name', 'Interface Map Name', 'Validation Result Status', 'Destination Hostname ', 'Destination Port ','Device Configuration', 'Error', 'Reason','Map Type'])
+
+# Function to apply color based on validation result
+def color_status(val):
+    color = 'red' if val == 'NonCompliant' else 'green' if val == 'Compliant' else 'black'
+    return 'color: %s' % color
+
+# Apply the color to the DataFrame
+styled_df = df.style.applymap(color_status, subset=['Validation Result Status'])
+
+# Set CSS properties for th elements in dataframe
+th_props = [
+  ('font-size', '18px'),
+  ('text-align', 'center'),
+  ('font-weight', 'bold'),
+  ('color', '#6d6d6d'),
+  ('background-color', '#f7f7f9')
+  ]
+
+# Set CSS properties for td elements in dataframe
+td_props = [
+  ('font-size', '16px')
+  ]
+
+# Set table styles
+styles = [
+  dict(selector="th", props=th_props),
+  dict(selector="td", props=td_props)
+  ]
+
+# Filter the DataFrame based on the 'Validation Result Status' column
+df_compliant = df[df['Validation Result Status'] == 'Compliant']
+df_noncompliant = df[df['Validation Result Status'] == 'NonCompliant']
+df_unknown = df[df['Validation Result Status'] == 'Unknown']
+
+# Apply the color to the DataFrames
+styled_df_compliant = df_compliant.style.applymap(color_status, subset=['Validation Result Status'])
+styled_df_noncompliant = df_noncompliant.style.applymap(color_status, subset=['Validation Result Status'])
+styled_df_unknown = df_unknown.style.applymap(color_status, subset=['Validation Result Status'])
+
+# Generate the DataFrames' HTML strings
+df_html_compliant = styled_df_compliant.set_table_styles(styles).to_html()
+df_html_noncompliant = styled_df_noncompliant.set_table_styles(styles).to_html()
+df_html_unknown = styled_df_unknown.set_table_styles(styles).to_html()
+
+# Combine the HTML strings
+html = f"""
+<html>
+<head>
+    <style>
+        body {{
+            background-color: #f0f0f5;
+        }}
+        .box {{
+            border: 1px solid black;
+            margin: 10px;
+            padding: 10px;
+        }}
+    </style>
+</head>
+<body>
+    <div class="box">
+        <h2>Compliant</h2>
+        {df_html_compliant}
+    </div>
+    <div class="box">
+        <h2>NonCompliant</h2>
+        {df_html_noncompliant}
+    </div>
+    <div class="box">
+        <h2>Unknown</h2>
+        {df_html_unknown}
+    </div>
+</body>
+</html>
+"""
+
+# Save the HTML string to a file
+with open("reports/report-{filename}.html".format(filename = date_time), 'w') as f:
+    f.write(html)
+```