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import os
import time
import psutil
import pandas as pd
import numpy as np
def get_stats(file_path):
if os.path.exists(file_path):
data = pd.read_csv(file_path)
else:
columns = ['Timestamp', 'MemoryUsed(%)', 'CPU_Used(%)']
data = pd.DataFrame(columns=columns)
while True:
current_time = time.strftime("%d_%m_%y_%H_%M_%S")
# Memory stats
memory_stats = psutil.virtual_memory()
memory_used = memory_stats.percent
# CPU stats
#cpu_stats = psutil.cpu_percent(interval=1, percpu=True)
cpu_stats = np.mean(psutil.cpu_percent(interval=1, percpu=True))
# Create a new row with the timestamp, memory stats, and CPU stats
new_row = {'Timestamp': current_time, 'Memory Stats': memory_used, 'CPU Stats': cpu_stats}
# Append the row to the DataFrame
data = data.append(new_row, ignore_index=True)
# Sleep for 60 seconds
time.sleep(5)
# Save the DataFrame to a CSV file
data.to_csv(file_path, index=False)
page_dict = {}
page_files = [
'doc/344_page_1_txt.png',
'doc/344_page_1_table.png',
'doc/5433_page_2_table.png',
'doc/54_page3_img.png',
'doc/32_page3_txt.png',
'doc/32_page3_table.png'
]
for file in page_files:
# Extracting page number from file name
page_number = file.split('_')[1].replace('page', '')
if page_number not in page_dict:
page_dict[page_number] = []
page_dict[page_number].append(file)
print(page_dict) |