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)