swebb2066 commented on PR #561: URL: https://github.com/apache/logging-log4cxx/pull/561#issuecomment-3514917035
Below is a python script that will generate this: <img width="800" height="600" alt="Appending" src="https://github.com/user-attachments/assets/3141ff69-8961-4161-b6a1-6e908ad87ed7"; /> ``` import re import matplotlib.pyplot as plt input_markdown_file = 'markdown/performance.md' regex_pattern = [ r"Appending (.*) using (MessageBuffer), pattern: \\%m\\%n$" , r"Appending (.*) using (FMT), pattern: \\%m\\%n$" # , r"Appending (.*) using (MessageBuffer), pattern: \\%m\\%n/threads" # , r"Appending (.*) using (FMT), pattern: \\%m\\%n/threads" ] data = {'MessageBuffer': {} , 'FMT': {} } line_type = {'MessageBuffer': '--' , 'FMT': '-.' } # Extract the data title = 'Appending' image_file_name = 'images/Appending.png' value_regex_pattern = r" *([0-9]+) ns" with open(input_markdown_file, "r") as file: header_found = False separator_found = False for line in file: if header_found and separator_found: # A valid table data row (starts and ends with '|') if not (line.strip().startswith('|') and line.strip().endswith('|')): break # Split the line by '|' and strip whitespace from each part # The first and last elements will be empty strings due to leading/trailing '|' columns = [col.strip() for col in line.split('|')] # Ensure there are enough columns to extract data (at least 3 for Benchmark and Time) if len(columns) > 2: value_match = re.search(value_regex_pattern, columns[2]) if value_match: nanoseconds =value_match.group(1) for r in regex_pattern: benchmark_match = re.search(r, columns[1]) if benchmark_match: formatter = benchmark_match.group(2) message_type = benchmark_match.group(1) data[formatter][message_type] = int(nanoseconds) elif " Benchmark " in line: header_found = True elif header_found and "----" in line: separator_found = True else: header_found = False if len(data) < 2: raise ValueError(f"Benchmark data not found in {input_markdown_file}") # Create the bar chart fig, ax = plt.subplots(figsize=(8, 6)) # Optional: set figure size for formatter, item_time in data.items(): message_types = item_time.keys() time_values = item_time.values() ax.plot(message_types, time_values, label=formatter, linestyle=line_type[formatter]) # Add chart title and axis labels ax.legend() ax.set_title(title, fontsize=14) ax.set_xlabel('Message content', fontsize=12) ax.set_ylabel('Time (ns)', fontsize=12) # Improve layout and remove top/right spines for cleaner look ax.spines['right'].set_visible(False) ax.spines['top'].set_visible(False) plt.tight_layout() # Save the graph as a PNG file plt.savefig(image_file_name) ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
