import pyreadstat import pandas as pd import shutil import os original_path = r"C:\data\active_dataset.sav" temp_path = r"C:\data\temp_copy.sav" Step 1: Create a temporary copy of the active file (This succeeds even if the original is locked for reading) shutil.copy2(original_path, temp_path) Step 2: Read the copy (not the original) df, meta = pyreadstat.read_sav(temp_path) Step 3: Modify the dataframe df['new_column'] = df['old_column'] * 100 df['category'] = df['codes'].replace(1: 'Low', 2: 'High') Step 4: Write to a NEW file (cannot overwrite active original) new_path = r"C:\data\modified_dataset.sav" pyreadstat.write_sav(df, new_path, metadata=meta) Step 5: Replace the original only after closing SPSS (Manual step: close SPSS first, then rename) os.remove(original_path) os.rename(new_path, original_path)
Remember: Respect the lock, preserve metadata, and your data will remain safe and analyzable for years to come.
GET FILE='active_dataset.sav'. COMPUTE newvar = oldvar * 2. SAVE OUTFILE='active_dataset.sav' /REPLACE. PSPP sometimes forces a lock release between read and write, making it useful for scripts. Technique A: Use savReaderWriter s SavWriter to Append If the file is open in SPSS as "read-only" (common in network environments), you may still append cases using SavWriter in append mode: