PythonCaller
Executes a Python script to manipulate the feature.
When a specialized task is required, such as custom statistical analysis of an attribute, but Workbench does not provide a transformer suited to the task, a Python script can perform specialized and complex operations on a feature's geometry, attributes, and coordinate system.
Note:
Access to a feature’s attributes, geometry and coordinate system information is provided via the FME Objects Python API. To view the API documentation, navigate to the FME installation folder and go to this location: fmeobjects\python\apidoc\index.html.
Interface Paradigm
The PythonCaller can interface with a Python script in two different ways: by function or by a class:
- Use the Function Interface when you intend to process a single feature at a time.
- Use the Class Interface for more flexibility.
The Class Interface is useful when you want to operate on a group of features together, such as collecting all the features received and then outputting them in a specific sort order. Another common use case is to accumulate all the features, perform an operation on the whole set, and then output all of the features with a calculated value as a new attribute.
Function Interface Example
The PythonCaller will call the Python function with exactly one argument: an FMEFeature object.
The function will be called with each FMEFeature that comes into the input port. This feature will then continue through the workspace pipeline via the output port.
The function’s return value will be ignored by the PythonCaller. Any raised exception will terminate the translation. Any raised FMEException will be logged as an ERROR and will terminate the translation.
The example below adds a string attribute to each feature and sets it to the current time:
import fmeobjects
import time
def timestampFeature(feature):
curTime = time.ctime(time.time())
feature.setAttribute("timestamp", curTime)
Class Interface Example
The PythonCaller will call two methods on the class: input() and close(). The input() method will be called for each FMEFeature that comes into the input port. When no more FMEFeatures remain, the close() method will be called. Features that need to continue through the workspace for further processing must be explicitly written out using the pyoutput() method.
The class interface can operate on a group of features, instead of processing incoming features one at a time. This is done by storing incoming features in a list, then processing them all at once before being output.
The example below calculates the total area of all the features processed and then outputs all the features with a new attribute containing the total area:
import fmeobjects
class FeatureProcessor(object):
def __init__(self):
self.featureList = []
self.totalArea = 0.0
def input(self,feature):
self.featureList.append(feature)
self.totalArea += feature.getGeometry().getArea()
def close(self):
for feature in self.featureList:
feature.setAttribute("total_area", self.totalArea)
self.pyoutput(feature)
Script Editing
A PythonCaller transformer can call scripts that are stored in the transformer itself or scripts that are stored globally for the entire workspace:
- To store a Python script with a specific PythonCaller transformer, use the Python Script parameter in the transformer.
- To store a Python script globally, click the Advanced Workspace Parameter in the Navigator, and double-click Startup Python Script. Storing scripts globally has the advantage of keeping the Python logic centralized, which makes editing and maintenance easier. This is useful when there are multiple PythonCaller transformers throughout the workspace that use the same script.
FME can access .py modules that are stored on the file system, including modules in external Python libraries. Use the Python "import" command to load these modules. FME will search both the standard Python module locations and the workspace location to find the module to be imported.
Parameters
The Python script to be executed. When the Python script is stored as the Startup Python Script for the Workspace, leave this parameter blank.
The name of the Python Function or Class within the script that PythonCaller will use to begin execution. For the above example, set this parameter FeatureProcessor.
Exposes any attributes that are created by the Python script being executed so they can be used by other transformers.
Hides any attributes that may be removed by the Python script being executed. Other transformers will not be able to use these attributes.
Hides any lists that may be removed by the Python script being executed. Other transformers will not be able to use these lists.
Note that if you select to hide a list, your selection will include any list attributes or nested lists. For example, if you select to hide a list called
list{}
then list{}.attr or list{}.sublist{}
will also be hidden.
Dependencies
An FME installation includes a Python interpreter, which is used by default for all Python processing.
FME 2012 ships with Python version 2.7. The FME Objects Python API supports Python 2.5 to 2.7.
To choose a different Python interpreter for FME, change the FME Options:
- Select Tools > FME Options, and click the Runtime icon:
- Under Python Interpreter, check the box Use Custom Python Interpreter.
- Browse to the location of the Python DLL that you wish to use (for example, python26.dll).
- Click OK to save the changes.
Editing Transformer Parameters
Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.
Transformer Categories
FME Licensing Level
FME Professional edition and above
Search FME Knowledge Center
Search for samples and information about this transformer on the FME Knowledge Center.