Python API

You can use pdal-parallelizer by importing it directly in your Python code.

There is an exemple of the usage of the API:

from pdal_parallelizer import process_pipelines as process

process(config="link of my config file",
        input_type="single",
        tile_size=(100, 100),
        n_workers=5,
        threads_per_worker=2,
        diagnostic=True)

There is only one function in pdal-parallelizer:

process(config, input_type, timeout, n_workers, threads_per_worker, dry_run, diagnostic, tile_size, buffer, remove_buffer, bounding_box, process)

Process points clouds.

Parameters:

config (*str*)

Path of your config file.

input_type (*str*)

This parameter indicates whether you are processing a single file or a list of files. It can take only two values: “single” or “dir”. If single, please change the input filed of the config file to put the path of your file instead of the path of your input directory.

timeout (*int*, *optional*)

Time before a worker is killed for inactivity. If you do not specify a timeout, you will need to specify it before the start of the run on the command line.

n_workers (*int*, *optional*)

Number of cores you want for processing. (default=3)

threads_per_worker (*int*, *optional*)

Number of threads for each worker. (default=1)

dry_run (*int*, *optional*)

Number of files to execute the test.

diagnostic (*bool*, *optional*)

Get a graph of the memory usage during the execution. (default=False)