tables

import tables as tb import numpy as np import os # Define a table description class MyTableDescription(tb.IsDescription): col1 = tb.StringCol(16, pos=1) col2 = tb.Int32Col(pos=2) col3 = tb.Float64Col(pos=3) filename = "mytable.h5" if os.path.exists(filename): os.remove(filename) try: # Open the HDF5 file in write mode with tb.open_file(filename, mode="w", title="Test File") as h5f: # Create a group for organization group = h5f.create_group(h5f.root, "data") # Create a table within the group table = h5f.create_table(group, 'table1', MyTableDescription, "My First Table") # Append data to the table table.append([("row_a", 1, 1.1), ("row_b", 2, 2.2)]) table.flush() # Ensure data is written to disk print("\nData in table1 after first append:") for row in table.iterrows(): print(f" col1: {row['col1']}, col2: {row['col2']}, col3: {row['col3']}") # Add more data table.append([("row_c", 3, 3.3), ("row_d", 4, 4.4)]) table.flush() print("\nAll data in table1 (as NumPy record array):") print(table[:]) # Read all data into a NumPy record array print(f"\nSuccessfully created and written to {filename}") # Re-open the file in read mode to verify with tb.open_file(filename, mode="r") as h5f_read: read_table = h5f_read.root.data.table1 print("\nData read from file:") for row in read_table.iterrows(): print(f" col1: {row['col1']}, col2: {row['col2']}, col3: {row['col3']}") except Exception as e: print(f"An error occurred: {e}") finally: # Clean up the created file if os.path.exists(filename): os.remove(filename) print(f"Cleaned up {filename}")