Module Documentation

Official Plugins

• Official Imaging Science Plugin

• Official Astronomy Plugin

• Official Machine Learning Plugin

Core

imagepypelines Package

Functions

add_plugin(plugin_name, plugin_module[, …])	adds the given plugin to ImagePypelines
arrsummary(arr)	returns a Summarizer object for the given array
blockify([kwargs, batch_type, types, …])	decorator which converts a normal function into a un-trainable block which can be added to a pipeline.
connect_to_dash(name, host, port)	Connects every pipeline in this session to
get_logger(name[, pipeline, parent])	Creates a new child logging adapter from the given parent (root logger by default)
get_master_logger()
get_plugin_by_name(plugin_name)	fetches the plugin module using its name
load_plugins()	Load all installed plugins to the imagepypelines namespace
make_numbered_prefix(file_number[, …])	returns a number string designed to be used in the prefix of systematic outputs.
n_dashboards()	returns the number of connected dashboards
passgen(passwd[, salt])	generate a hashed key from a password
prevent_overwrite(filename[, create_file])	checks to see if a file or directory already exists and creates a new filename if it does.
require(*plugins)	check to make sure the given plugin(s) are loaded and raise an error if they can’t be found
set_log_level(log_level)	sets the global master logger level
timer(func)	Decorator to time how long a func takes to run in milliseconds
timer_ms(func)	Decorator to time how long a func takes to run in milliseconds

Classes

Block([name, batch_type, types, shapes, …])	a contained algorithmic element used to construct pipelines.
BlockError	Error raised within a Block
DashboardComm	Object to send messages from the pipelines to dashboard(s)
DashboardWarning	Warning for connection failure to dashboard
Data(data)	Object to batch lists or arrays as block processable data
FuncBlock(func[, preset_kwargs])	Block that will run any function you give it, either unfettered through the __call__ function, or with optional hardcoded parameters for use in a pipeline.
ImagepypelinesLogger(name[, level])	subclass of logging.Logger that can be pickled, also adds colored logging outputs if desired.
Input([index])	An object to inject data into the graph
Leaf(var_name)	a block to act as a leaf node in the Pipeline Graph.
Pipeline([tasks, name])	processing algorithm manager for simple pipeline construction
PipelineBlock(pipeline, fetch)	Block which runs a pipeline internally (used for nesting pipelines within pipelines)
PipelineError	Error raised within a Pipeline
Timer()	Timer which can be used to time processes

Class Inheritance Diagram