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OMERO Python Language Bindings

Using the OmeroPy libraries
Connect to OMERO
Read Data
Raw Data Access
Write Data
OMERO tables
ROIs
Delete Data
Render Images
Create Image
Python OMERO.scripts

In addition to the auto-generated Python libraries of the core OMERO API, we have developed a more user-friendly 'Blitz Gateway' Python module that facilitates several aspects of working with the Python API, such as connection handling, object graph traversal and lazy loading.

The Python libraries are part of the server build and can be found under OMERO_HOME/lib/python. These include the core omero.model objects and services as well as the Blitz Gateway code.

Using the OmeroPy libraries

For Python beginners, or those who prefer more detailed instructions, see the PythonClientBeginners page.

To use OmeroPy, you'll need to download the libraries (E.g. as part of the server package) and setup your PYTHONPATH to include them:

  OMERO_HOME=~/Desktop/OMERO.server-Beta-4.3.2   # for example
  PYTHONPATH=$OMERO_HOME/lib/python

Connect to OMERO

# These values will be imported by all the other training scripts.
HOST = 'localhost'
PORT = 4064
USERNAME = 'will'
PASSWORD = 'ome'

from omero.gateway import BlitzGateway

if __name__ == '__main__':
    """
    NB: This block is only run when calling this file directly
    and not when imported.
    """

    # Connect to the Python Blitz Gateway
    # =============================================================
    # Make a simple connection to OMERO, printing details of the
    # connection. See OmeroPy/Gateway for more info
    conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
    connected = conn.connect()

    # Check if you are connected.
    # =============================================================
    if not connected:
        import sys
        sys.stderr.write("Error: Connection not available, please check your user name and password.\n")
        sys.exit(1)

    # Using secure connection.
    # =============================================================
    # By default, once we have logged in, data transfer is not encrypted (faster)
    # To use a secure connection, call setSecure(True):

    # conn.setSecure(True)         # <--------- Uncomment this

    # Current session details
    # =============================================================
    # By default, you will have logged into your 'current' group in OMERO. This
    # can be changed by switching group in the OMERO insight or web clients.

    user = conn.getUser()
    print "Current user:"
    print "   ID:", user.getId()
    print "   Username:", user.getName()
    print "   Full Name:", user.getFullName()

    print "Member of:"
    for g in conn.getGroupsMemberOf():
        print "   ID:", g.getName(), " Name:", g.getId()
    group = conn.getGroupFromContext()
    print "Current group: ", group.getName()

    print "Other Members of current group:"
    for exp in conn.listColleagues():
        print "   ID:", exp.getId(), exp.getOmeName(), " Name:", exp.getFullName()

    print "Owner of:"
    for g in conn.listOwnedGroups():
        print "   ID:", g.getName(), " Name:", g.getId()

    # The 'context' of our current session
    ctx = conn.getEventContext()
    # print ctx     # for more info

    # Close connection:
    # =================================================================
    # When you're done, close the session to free up server resources.
    conn._closeSession()

Read Data

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Configuration

imageId = 27544
datasetId = 2651
plateId = -1

def print_obj(obj, indent=0):
    """
    Helper method to display info about OMERO objects.
    Not all objects will have a "name" or owner field.
    """
    print """%s%s:%s  Name:"%s" (owner=%s)""" % (\
            " " * indent,
            obj.OMERO_CLASS,\
            obj.getId(),\
            obj.getName(),\
            obj.getOwnerOmeName())

List all Projects available to me, and their Datasets and Images:

# The only_owned=True parameter limits the Projects which are returned.
# If the parameter is omitted or the value is Fale, then all Projects
# visible in the current group are returned.
print "\nList Projects:"
print "=" * 50
for project in conn.listProjects(only_owned=True):
    print_obj(project)
    for dataset in project.listChildren():
        print_obj(dataset, 2)
        for image in dataset.listChildren():
            print_obj(image, 4)

Retrieve the datasets owned by the user currently logged in:

# Here we create an omero.sys.ParametersI instance which we
# can use to filter the results that are returned. If we did
# not pass the params argument to getObjects, then all Datasets
# in the current group would be returned.
print "\nList Datasets:"
print "=" * 50

params = omero.sys.ParametersI()
params.exp(conn.getUser().getId())  # only show current user's Datasets

datasets = conn.getObjects("Dataset", params=params)
for dataset in datasets:
    print_obj(dataset)

Retrieve the images contained in a dataset:

print "\nDataset:%s" % datasetId
print "=" * 50
dataset = conn.getObject("Dataset", datasetId)
print "\nImages in Dataset:", dataset.getName()
for image in dataset.listChildren():
    print_obj(image)

Retrieve an image by Image ID:

image = conn.getObject("Image", imageId)
print "\nImage:%s" % imageId
print "=" * 50
print image.getName(), image.getDescription()
# Retrieve information about an image.
print " X:", image.getSizeX()
print " Y:", image.getSizeY()
print " Z:", image.getSizeZ()
print " C:", image.getSizeC()
print " T:", image.getSizeT()
# render the first timepoint, mid Z section
z = image.getSizeZ() / 2
t = 0
renderedImage = image.renderImage(z, t)
#renderedImage.show()               # popup (use for debug only)
#renderedImage.save("test.jpg")     # save in the current folder

Retrieve Screening data:

print "\nList Screens:"
print "=" * 50
for screen in conn.getObjects("Screen"):
    print_obj(screen)
    for plate in screen.listChildren():
        print_obj(plate, 2)
        plateId = plate.getId()

Retrieve Wells and Images within a Plate:

if plateId >= 0:
    print "\nPlate:%s" % plateId
    print "=" * 50
    plate = conn.getObject("Plate", plateId)
    print "\nNumber of fields:", plate.getNumberOfFields()
    print "\nGrid size:", plate.getGridSize()
    print "\nWells in Plate:", plate.getName()
    for well in plate.listChildren():
        index = well.countWellSample()
        print "  Well: ", well.row, well.column, " Fields:", index
        for index in xrange(0, index):
            print "    Image: ", \
                    well.getImage(index).getName(),\
                    well.getImage(index).getId()

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

Raw Data Access

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Configuration

imageId = 27544

Retrieve a given plane

# Use the pixelswrapper to retrieve the plane as
# a 2D numpy array. See [http://www.scipy.org/Tentative_NumPy_Tutorial]
#
# Numpy array can be used for various analysis routines
#
image = conn.getObject("Image", imageId)
sizeZ = image.getSizeZ()
sizeC = image.getSizeC()
sizeT = image.getSizeT()
z, t, c = 0, 0, 0                     # first plane of the image
pixels = image.getPrimaryPixels()
plane = pixels.getPlane(z, c, t)      # get a numpy array.
print "\nPlane at zct: ", z, c, t
print plane
print "shape: ", plane.shape
print "min:", plane.min(), " max:", plane.max(),\
        "pixel type:", plane.dtype.name

Retrieve a given stack

# Get a Z-stack of tiles. Using getTiles or getPlanes (see below) returns
# a generator of data (not all the data in hand) The RawPixelsStore is
# only opened once (not closed after each plane) Alternative is to use
# getPlane() or getTile() multiple times - slightly slower.
c, t = 0, 0                 # First channel and timepoint
tile = (50, 50, 10, 10)     # x, y, width, height of tile

# list of [ (0,0,0,(x,y,w,h)), (1,0,0,(x,y,w,h)), (2,0,0,(x,y,w,h))....etc... ]
zctList = [(z, c, t, tile) for z in range(sizeZ)]
print "\nZ stack of tiles:"
planes = pixels.getTiles(zctList)
for i, p in enumerate(planes):
    print "Tile:", zctList[i], " min:", p.min(),\
            " max:", p.max(), " sum:", p.sum()

Retrieve a given hypercube

zctList = []
for z in range(sizeZ / 2, sizeZ):     # get the top half of the Z-stack
    for c in range(sizeC):          # all channels
        for t in range(sizeT):      # all time-points
            zctList.append((z, c, t))
print "\nHyper stack of planes:"
planes = pixels.getPlanes(zctList)
for i, p in enumerate(planes):
    print "plane zct:", zctList[i], " min:", p.min(), " max:", p.max()

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

Write Data

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Configuration

projectId = 3109
#Specify a local file. E.g. could be result of some analysis
fileToUpload = "fileToUpload.txt"   # This file should already exist

Create a new Dataset

datasetObj = omero.model.DatasetI()
datasetObj.setName(rstring("New Dataset"))
datasetObj = conn.getUpdateService().saveAndReturnObject(datasetObj)
datasetId = datasetObj.getId().getValue()
print "New dataset, Id:", datasetId

Link to Project

project = conn.getObject("Project", projectId)
if project is None:
    import sys
    sys.stderr.write("Error: Object does not exist.\n")
    sys.exit(1)
link = omero.model.ProjectDatasetLinkI()
link.setParent(omero.model.ProjectI(project.getId(), False))
link.setChild(datasetObj)
conn.getUpdateService().saveObject(link)

How to create a file annotation and link to a Dataset

dataset = conn.getObject("Dataset", datasetId)
# create the original file and file annotation (uploads the file etc.)
namespace = "imperial.training.demo"
print "\nCreating an OriginalFile and FileAnnotation"
fileAnn = conn.createFileAnnfromLocalFile(fileToUpload, mimetype="text/plain", ns=namespace, desc=None)
print "Attaching FileAnnotation to Dataset: ", "File ID:", fileAnn.getId(), ",", fileAnn.getFile().getName(), "Size:", fileAnn.getFile().getSize()
dataset.linkAnnotation(fileAnn)     # link it to dataset.

Download a file annotation linked to a Dataset

# make a location to download the file. "download" folder.
path = os.path.join(os.path.dirname(__file__), "download")
if not os.path.exists(path):
    os.makedirs(path)

# Go through all the annotations on the Dataset. Download any file annotations we find.
print "\nAnnotations on Dataset:", dataset.getName()
for ann in dataset.listAnnotations():
    if isinstance(ann, omero.gateway.FileAnnotationWrapper):
        print "File ID:", ann.getFile().getId(), ann.getFile().getName(), "Size:", ann.getFile().getSize()

        file_path = os.path.join(path, ann.getFile().getName())

        f = open(str(file_path), 'w')
        print "\nDownloading file to", file_path, "..."
        try:
            for chunk in ann.getFileInChunks():
                f.write(chunk)
        finally:
            f.close()
            print "File downloaded!"

Load all the file annotations with a given namespace

nsToInclude = [namespace]
nsToExclude = []
metadataService = conn.getMetadataService()
annotations = metadataService.loadSpecifiedAnnotations('omero.model.FileAnnotation', nsToInclude, nsToExclude, None)
for ann in annotations:
    print ann.getId().getValue(), ann.file.name.val

Get first annotation with specified namespace

ann = dataset.getAnnotation(namespace)
print "Found Annotation with namespace: ", ann.getNs()

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

OMERO tables

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Configuration

datasetId = 51

Create a name for the Original File (should be unique)

from random import random
tablename = "TablesDemo:%s" % str(random())

col1 = omero.grid.LongColumn('Uid', 'testLong', [])
col2 = omero.grid.StringColumn('MyStringColumnInit', '', 64, [])

columns = [col1, col2]

Create and initialize a new table.

repositoryId = 1
table = conn.c.sf.sharedResources().newTable(repositoryId, tablename)
table.initialize(columns)

Add data to the table.

ids = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
strings = ["one", "two", "three", "four", "five",\
           "six", "seven", "eight", "nine", "ten"]
data1 = omero.grid.LongColumn('Uid', 'test Long', ids)
data2 = omero.grid.StringColumn('MyStringColumn', '', 64, strings)
data = [data1, data2]
table.addData(data)
table.close()           # when we're done, close.

Get the table as an original file...

orig_file = table.getOriginalFile()
orig_file_id = orig_file.id.val
# ...so you can attach this data to an object. E.g. Dataset
fileAnn = omero.model.FileAnnotationI()
fileAnn.setFile(omero.model.OriginalFileI(orig_file_id, False))     # use unloaded OriginalFileI
fileAnn = conn.getUpdateService().saveAndReturnObject(fileAnn)
link = omero.model.DatasetAnnotationLinkI()
link.setParent(omero.model.DatasetI(datasetId, False))
link.setChild(omero.model.FileAnnotationI(fileAnn.id.val, False))
conn.getUpdateService().saveAndReturnObject(link)

Table API

# See: [http://hudson.openmicroscopy.org.uk/job/OMERO/javadoc/slice]2html/omero/grid/Table.html
openTable = conn.c.sf.sharedResources().openTable(orig_file)

print "Table Columns:"
for col in openTable.getHeaders():
    print "   ", col.name

rowCount = openTable.getNumberOfRows()
print "Row count:", rowCount

Get data from every column of the specified rows

rowNumbers = [3, 5, 7]
print "\nGet All Data for rows: ", rowNumbers
data = openTable.readCoordinates(range(rowCount))
for col in data.columns:
    print "Data for Column: ", col.name
    for v in col.values:
        print "   ", v

Get data from specified columns of specified rows

colNumbers = [1]
start = 3
stop = 7
print "\nGet Data for cols: ", colNumbers,\
        " and between rows: ", start, "-", stop

data = openTable.read(colNumbers, start, stop)
for col in data.columns:
    print "Data for Column: ", col.name
    for v in col.values:
        print "   ", v

Query the table for rows where the 'Uid' is in a particular range

queryRows = openTable.getWhereList("(Uid > 2) & (Uid <= 8)",\
        variables={}, start=0, stop=rowCount, step=0)
data = openTable.readCoordinates(queryRows)
for col in data.columns:
    print "Query Results for Column: ", col.name
    for v in col.values:
        print "   ", v
openTable.close()           # we're done

In future, to get the table back from Original File

orig_table_file = conn.getObject("OriginalFile", attributes={'name': tablename})    # if name is unique
savedTable = conn.c.sf.sharedResources().openTable(orig_table_file._obj)
print "Opened table with row-count:", savedTable.getNumberOfRows()

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

ROIs

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()
updateService = conn.getUpdateService()

Configuration

imageId = 27544

Create ROI.

# We are using the core Python API and omero.model objects here, since ROIs are
# not yet supported in the Python Blitz Gateway.
#
# In this example, we create an ROI with a rectangular shape and attach it to an
# image.
x = 50
y = 200
width = 100
height = 50
image = conn.getObject("Image", imageId)
theZ = image.getSizeZ() / 2
theT = 0
print "Adding a rectangle at theZ: %s, theT: %s, X: %s, Y: %s, width: %s, height: %s" % \
        (theZ, theT, x, y, width, height)

# create an ROI, link it to Image
roi = omero.model.RoiI()
roi.setImage(image._obj)    # use the omero.model.ImageI that underlies the 'image' wrapper

# create a rectangle shape and add to ROI
rect = omero.model.RectI()
rect.x = rdouble(x)
rect.y = rdouble(y)
rect.width = rdouble(width)
rect.height = rdouble(height)
rect.theZ = rint(theZ)
rect.theT = rint(theT)
rect.textValue = rstring("test-Rectangle")
roi.addShape(rect)

# create an Ellips shape and add to ROI
ellipse = omero.model.EllipseI()
ellipse.cx = rdouble(y)
ellipse.cy = rdouble(x)
ellipse.rx = rdouble(width)
ellipse.ry = rdouble(height)
ellipse.theZ = rint(theZ)
ellipse.theT = rint(theT)
ellipse.textValue = rstring("test-Ellipse")
roi.addShape(ellipse)

# Save the ROI (saves any linked shapes too)
r = updateService.saveAndReturnObject(roi)

Retrieve ROIs linked to an Image.

roiService = conn.getRoiService()
result = roiService.findByImage(imageId, None)
for roi in result.rois:
    print "ROI:  ID:", roi.getId().getValue()
    for s in roi.copyShapes():
        shape = {}
        shape['id'] = s.getId().getValue()
        shape['theT'] = s.getTheT().getValue()
        shape['theZ'] = s.getTheZ().getValue()
        if s.getTextValue():
            shape['textValue'] = s.getTextValue().getValue()
        if type(s) == omero.model.RectI:
            shape['type'] = 'Rectangle'
            shape['x'] = s.getX().getValue()
            shape['y'] = s.getY().getValue()
            shape['width'] = s.getWidth().getValue()
            shape['height'] = s.getHeight().getValue()
        elif type(s) == omero.model.EllipseI:
            shape['type'] = 'Ellipse'
            shape['cx'] = s.getCx().getValue()
            shape['cy'] = s.getCy().getValue()
            shape['rx'] = s.getRx().getValue()
            shape['ry'] = s.getRy().getValue()
        elif type(s) == omero.model.PointI:
            shape['type'] = 'Point'
            shape['cx'] = s.getCx().getValue()
            shape['cy'] = s.getCy().getValue()
        elif type(s) == omero.model.LineI:
            shape['type'] = 'Line'
            shape['x1'] = s.getX1().getValue()
            shape['x2'] = s.getX2().getValue()
            shape['y1'] = s.getY1().getValue()
            shape['y2'] = s.getY2().getValue()
        elif type(s) in (omero.model.MaskI, omero.model.LabelI, omero.model.PolygonI):
            print type(s), " Not supported by this code"
        # Do some processing here, or just print:
        print "   Shape:",
        for key, value in shape.items():
            print "  ", key, value,
        print ""

Remove shape from ROI

result = roiService.findByImage(imageId, None)
for roi in result.rois:
    for s in roi.copyShapes():
        # Find and remove the Shape we added above
        if s.getTextValue() and s.getTextValue().getValue() == "test-Ellipse":
            print "Removing Shape from ROI..."
            roi.removeShape(s)
            roi = updateService.saveAndReturnObject(roi)

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

Delete Data

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Configuration

projectId = 3110

Load the Project

project = conn.getObject("Project", projectId)
if project is None:
    import sys
    sys.stderr.write("Error: Object does not exist.\n")
    sys.exit(1)

print "\nProject:", project.getName()

Delete Project

# You can delete a number of objects of the same type at the same
# time. In this case 'Project'. Use deleteChildren=True if you are
# deleting a Project and you want to delete Datasets and Images.
obj_ids = [projectId]
deleteChildren = False
handle = conn.deleteObjects("Project", obj_ids,\
        deleteAnns=True, deleteChildren=deleteChildren)

Retrieve callback and wait until delete completes

callback = omero.callbacks.DeleteCallbackI(conn.c, handle) print "Deleting, please wait." while callback.block(500) is not None: # ms. print "." print "Errors:", handle.errors() callback.close()

Retrieve callback from string

If you've stored the string representation of the callback, then you can load the handle proxy to see the state of the delete.

import Ice callback as string cbString = str(handle) try: post_handle = omero.api.delete.DeleteHandlePrx?.checkedCast(\ conn.c.ic.stringToProxy(cbString)) self.fail("exception Ice.ObjectNotExistException? was not thrown") except Ice.ObjectNotExistException?: pass

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

Render Images

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Configuration

imageId = 27544

Get thumbnail

# Thumbnail is created using the current rendering settings on the image
image = conn.getObject("Image", imageId)
img_data = image.getThumbnail()
renderedThumb = Image.open(StringIO(img_data))
#renderedThumb.show()           # shows a pop-up
renderedThumb.save("thumbnail.jpg")

Get current settings

print "Channel rendering settings:"
for ch in image.getChannels():
    print "Name: ", ch.getLabel()   # if no name, get emission wavelength or index
    print "  Color:", ch.getColor().getHtml()
    print "  Active:", ch.isActive()
    print "  Levels:", ch.getWindowStart(), "-", ch.getWindowEnd()
print "isGreyscaleRenderingModel:", image.isGreyscaleRenderingModel()

Render each channel as a separate greyscale image

image.setGreyscaleRenderingModel()
sizeC = image.getSizeC()
z = image.getSizeZ() / 2
t = 0
for c in range(1, sizeC + 1):       # Channel index starts at 1
    channels = [c]                  # Turn on a single channel at a time
    image.setActiveChannels(channels)
    renderedImage = image.renderImage(z, t)
    #renderedImage.show()                        # popup (use for debug only)
    renderedImage.save("channel%s.jpg" % c)     # save in the current folder

Turn 3 channels on, setting their colours

image.setColorRenderingModel()
channels = [1, 2, 3]
colorList = ['F00', None, 'FFFF00']         # don't change colour of 2nd channel
image.setActiveChannels(channels, colors=colorList)
image.setProjection('intmax')               # max intensity projection 'intmean' for mean-intensity
renderedImage = image.renderImage(z, t)     # z and t are ignored for projections
#renderedImage.show()
renderedImage.save("all_channels.jpg")
image.setProjection('normal')               # turn off projection

Turn 2 channels on, setting levels of the first one

channels = [1, 2]
rangeList = [(100.0, 120.2), (None, None)]
image.setActiveChannels(channels, windows=rangeList)
renderedImage = image.renderImage(z, t, compression=0.5)    # default compression is 0.9
#renderedImage.show()
renderedImage.save("two_channels.jpg")

Save the current rendering settings

image.saveDefaults()

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

Create Image

Create a connection

conn = BlitzGateway(USERNAME, PASSWORD, host=HOST, port=PORT)
conn.connect()

Configuration

imageId = 27544     # This image must have at least 2 channels

Create an image from scratch

# This example demonstrates the usage of the convenience method
# createImageFromNumpySeq() Here we create a multi-dimensional image from a
# hard-coded array of data.
from numpy import array
sizeX, sizeY, sizeZ, sizeC, sizeT = 5, 4, 1, 2, 1
plane1 = array([[0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [0, 1, 2, 3, 4], [5, 6, 7, 8, 9]])
plane2 = array([[5, 6, 7, 8, 9], [0, 1, 2, 3, 4], [5, 6, 7, 8, 9], [0, 1, 2, 3, 4]])
planes = [plane1, plane2]

def planeGen():
    """generator will yield planes"""
    for p in planes:
        yield p

desc = "Image created from a hard-coded arrays"
i = conn.createImageFromNumpySeq(planeGen(), "numpy image",\
        sizeZ, sizeC, sizeT, description=desc, dataset=None)

Create an Image from an existing image

# We are going to create a new image by passing the method a 'generator' of 2D
# planes This will come from an existing image, by taking the average of 2 channels.
zctList = []
image = conn.getObject('Image', imageId)
sizeZ, sizeC, sizeT = image.getSizeZ(), image.getSizeC(), image.getSizeT()
dataset = image.getParent()
pixels = image.getPrimaryPixels()
newSizeC = 1

def planeGen():
    """
    set up a generator of 2D numpy arrays.

    The createImage method below expects planes in the order specified here (for
    z.. for c.. for t..)
    """
    for z in range(sizeZ):              # all Z sections
        for c in range(newSizeC):       # Illustrative purposes only, since we only have 1 channel
            for t in range(sizeT):      # all time-points
                channel0 = pixels.getPlane(z, 0, t)
                channel1 = pixels.getPlane(z, 1, t)
                # Here we can manipulate the data in many different ways. As an example we're doing "average"
                newPlane = (channel0 + channel1) / 2    # average of 2 channels
                print "newPlane for z,t:", z, t, newPlane.dtype, newPlane.min(), newPlane.max()
                yield newPlane

desc = "Image created from Image ID: %s by averaging Channel 1 and Channel 2" % imageId
i = conn.createImageFromNumpySeq(planeGen(), "new image",\
        sizeZ, newSizeC, sizeT, description=desc, dataset=dataset)

Close connection:

# When you're done, close the session to free up server resources.
conn._closeSession()

Python OMERO.scripts

Script definition

Script name, description and 2 parameters are defined here. These parameters will be recognised by the Insight and web clients and populated with the currently selected Image(s)

dataTypes = [rstring('Image')]      # this script only takes Images (not Datasets etc.)
client = scripts.client("Scripting_Service_Example.py",
    """Example script to use as a template for getting started with the scripting service.""",
    # first parameter
    scripts.String("Data_Type", optional=False, values=dataTypes, default="Image"),
    # second parameter
    scripts.List("IDs", optional=False).ofType(rlong(0)),
)
# we can now create our Blitz Gateway by wrapping the client object
conn = BlitzGateway(client_obj=client)

# get the 'IDs' parameter (which we have restricted to 'Image' IDs)
ids = unwrap(client.getInput("IDs"))
imageId = ids[0]        # simply use the first ID for this example

# ** paste here **
# Replace the code block below. NB: we have established a connection "conn" and we have an "imageId"
image = conn.getObject("Image", imageId)
print image.getName()

Return some value(s).

Here, we return anything useful the script has produced. NB: The Insight and web clients will display the "Message" output.

message = "Script ran with Image ID: %s, Name: %s" % (imageId, image.getName())
client.setOutput("Message", rstring(message))
client.closeSession()

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