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Instead of writing JSON strings, you can construct pipelines programmatically using Python objects. This approach provides better IDE support, type checking, and code reusability.

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Building pipelines with Stage objects

A pipeline constructed with the pipe operator is equivalent to a JSON pipeline: 
import pdal
pipeline = pdal.Reader("1.2-with-color.las") | pdal.Filter.sort(dimension="X")
This creates the same pipeline as the JSON example in the basic usage guide.

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Stage types

PDAL Python provides three types of stages:
  • pdal.Reader - Reads data from files or sources
  • pdal.Filter - Transforms or filters point cloud data
  • pdal.Writer - Writes data to files or destinations

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Creating stages

Stages accept keyword arguments that correspond to PDAL stage options: 
# Reader with filename as positional argument
reader = pdal.Reader("input.las")

# Filter with options as keyword arguments
filter_stage = pdal.Filter.sort(dimension="X")

# Writer with multiple options
writer = pdal.Writer.las(
    filename="output.las",
    offset_x="auto",
    offset_y="auto",
    scale_x=0.01
)
The filename option for Readers and Writers, and the type option for Filters can be passed as the first positional argument.

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Using the pipe operator

The pipe operator (|) connects stages together to form a pipeline: 
pipeline = pdal.Reader("1.2-with-color.las") | pdal.Filter.sort(dimension="X")
You can chain multiple stages: 
pipeline = reader | filter1 | filter2 | writer

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Pipe operator combinations

The pipe operator works with various combinations: 
# Stage | Stage
pipeline = stage1 | stage2

# Stage | Pipeline
pipeline = stage1 | existing_pipeline

# Pipeline | Stage
pipeline = existing_pipeline | stage1

# Pipeline | Pipeline
pipeline = pipeline1 | pipeline2
Every application of the pipe operator creates a new Pipeline instance.

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Updating pipelines in-place

To update an existing pipeline without creating a new one, use the in-place pipe operator (|=): 
# update pipeline in-place
pipeline = pdal.Pipeline()
pipeline |= stage
pipeline |= pipeline2

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Stage factory methods

The Reader, Filter, and Writer classes provide static methods for all PDAL drivers. For example: 
# These are equivalent
pdal.Filter.head(count=100)
pdal.Filter(type="filters.head", count=100)
These methods are auto-generated by introspecting PDAL, and include docstrings with available options: 
>>> help(pdal.Filter.head)
Help on function head in module pdal.pipeline:

head(**kwargs)
    Return N points from beginning of the point cloud.

    user_data: User JSON
    log: Debug output filename
    option_file: File from which to read additional options
    where: Expression describing points to be passed to this filter
    where_merge='auto': If 'where' option is set, describes how skipped points should be merged with kept points in standard mode.
    count='10': Number of points to return from beginning.  If 'invert' is true, number of points to drop from the beginning.
    invert='false': If true, 'count' specifies the number of points to skip from the beginning.

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Creating pipelines from stages

You can create a Pipeline instance in several ways: 
# From a JSON string
pipeline = pdal.Pipeline(json_string)

# From a sequence of stages
pipeline = pdal.Pipeline([stage1, stage2])

# From a single stage
pipeline = stage.pipeline()

# Empty pipeline
pipeline = pdal.Pipeline()

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Stage inputs

The inputs option allows you to specify stages that feed into the current stage: 
stage = pdal.Filter.merge(inputs=[stage1, stage2])
Inputs can be either:
  • String tags of other stages
  • Stage instances themselves

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