ProductIO.writeProduct() function takes longer to run when called in Python

[hakim]

I can’t understand why the ProductIO.writeProduct() function takes at least a few minutes to execute for a collocation between two images of around 3000 x 4000 px in the following code (the collocate() function is implemented in another script):

collocated_products = collocate(product1, product2, ‘${ORIGINAL_NAME}’, ‘${ORIGINAL_NAME}’)
path_collocated = os.path.join(PARENT, FOLDER, ‘collocation.tif’)
ProductIO.writeProduct(collocated_products, path_collocated, ‘GeoTIFF’)

While when its called from the command-line with gpt it’s very quick.
Is there any other way to write the resulting collocated product to the disk quickly?

[marpet]

One reason could be a different memory setting. However, maybe it helps if you use the Write operator.
Please have a look at this and the following posts:

Performance of snap desktop and snappy

There could be two reasons. One is that you have worked with the data in the desktop already and the data is already computed when you write the data. But I guess this is not the full story. Instead of ProductIO.writeProduct() you can try the Write operator with GPF.createProduct(). Specify the file and the formatName as parameter. [image]

[hakim]

Thanks a lot, indeed the code below takes roughly the same time to run as gpt when it’s called from the command-line:

WriteOp = jpy.get_type('org.esa.snap.core.gpf.common.WriteOp')
writeOp = WriteOp(product, File(path), format)
writeOp.writeProduct(ProgressMonitor.NULL)