file stays in memory / doesn't close?

I’m not sure what is going on exactly, but I suspect that files are being kept in memory. When reading a large number of files (~1000 files) in a loop for example:

i = 0
for file in file_list:
    file2read = mypath + '//' + file
    las = lasio.read(file2read)
    lasDF=las.df()
    myIndex = lasDF.index
    lasDF['DEPTH'] = myIndex
    lasDF['LIN_RES'] = np.log(lasDF['RESD_FINAL'])
    output = np.concatenate((output, lasDF), axis=0)
    i+=1
    print(i/len(file_list)*100, "% complete. Read: ", file)

The memory usage seems to continuously climb. Is there a file.close() that needs to be performed by the user?

[danomics-cam]

Version is: ‘0.24.1’ Some add’l info if it makes any difference: OS: Windows 10; 16GB Ram Total LAS file count: 1464 Total LAS input file size: 1.21 GB I’m wondering if it’s not getting stuck in the python garbage collector. For example I just ran about 455 files through and checked the gc.get_count() and it’s at (557,6,1), so might not be a lasio issue, but a setting on my side.

[kinverarity1]

No worries, glad you have found the issue! 🚀