Understanding the Problem and Requirements

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The problem at hand involves updating LXML attributes with values stored in a CSV file. We’re given a sample CSV file named “assets.csv” containing various pieces of information, including ID, code, EL, TR, DIR, MIL, X, Y, Z, and DESC. The task is to iterate over each row in the CSV file and update the SigEquipment ID attribute with the corresponding ID value from each row.

Background Information

• LXML (Lightweight XML) is a Python library used for parsing and generating XML documents.
• A DataFrame is a data structure in pandas, which provides data manipulation capabilities.
• The read_csv() function in pandas reads a CSV file into a DataFrame.
• The iterrows() method returns an iterator over rows of the DataFrame.

Solution Overview

To solve this problem, we’ll follow these steps:

1. Read the CSV file into a DataFrame using pandas.read_csv().
2. Iterate over each row in the DataFrame using df.iterrows().
3. For each row, create an Equipment node and a SigEquipment node.
4. Update the SigEquipment ID attribute with the corresponding ID value from each row.

Step-by-Step Solution

Step 1: Import Necessary Libraries

import pandas as pd
from lxml import etree as et

• We’ll use pandas to read the CSV file and manipulate data.
• We’ll use lxml.etree to create and update XML nodes.

Step 2: Read the CSV File into a DataFrame

df = pd.read_csv('assets.csv', sep=',')

• The read_csv() function reads the CSV file into a DataFrame, where each row corresponds to a pandas Series (a one-dimensional labeled array).

Step 3: Iterate Over Each Row in the DataFrame

for index, row in df.iterrows():
    # code here

• The iterrows() method returns an iterator over rows of the DataFrame, where each row is returned as a tuple containing the index and the Series (pandas row).

Step 4: Create Equipment and SigEquipment Nodes

root = et.Element('SchemeData', xmlns='Boo')
equipment = et.SubElement(root, 'Equipment')
sigEquipment = et.SubElement(equipment, 'SigEquipment')

• We create a root SchemeData node with an xmlns attribute set to “Boo”.
• For each row, we create an Equipment node and a SigEquipment node under the Equipment node.

Step 5: Update SigEquipment ID Attribute

sigEquipment.attrib["fileUID"] = str(row["ID"])

• We update the fileUID attribute of the SigEquipment node with the corresponding ID value from each row, converted to a string using str().

Step 6: Print the Updated XML Tree

print(et.tostring(root, pretty_print=True).decode())

• Finally, we print the updated XML tree using et.tostring(), which returns a bytes object representing the XML document. We decode it to a string using .decode() and pass it through pretty_print=True for better readability.

Complete Code

import pandas as pd
from lxml import etree as et

# Read the CSV file into a DataFrame
df = pd.read_csv('assets.csv', sep=',')

# Create the root SchemeData node with an xmlns attribute
root = et.Element('SchemeData', xmlns='Boo')

# Iterate over each row in the DataFrame
for index, row in df.iterrows():
    # Create Equipment and SigEquipment nodes under the root node
    equipment = et.SubElement(root, 'Equipment')
    sigEquipment = et.SubElement(equipment, 'SigEquipment')

    # Update the fileUID attribute of the SigEquipment node with the corresponding ID value from each row
    sigEquipment.attrib["fileUID"] = str(row["ID"])

# Print the updated XML tree
print(et.tostring(root, pretty_print=True).decode())

This code iterates over each row in the CSV file, creates Equipment and SigEquipment nodes, updates the SigEquipment ID attribute with the corresponding ID value from each row, and prints the updated XML tree.

Last modified on 2025-04-07