def __init__(self):
inputs = [LiteralInput('name', 'Input name', data_type='string')]
outputs = [
LiteralOutput('response', 'Output response', data_type='string')
]
super(ProcessNoOutput, self).__init__(
self._handler,
identifier='process-no-output',
title='Process with no vector output',
abstract=
'Returns a literal string output with Hello plus the inputed name',
version='1',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True)
def test_literal_output(self):
literal = LiteralOutput('literal', 'Literal foo', uoms=['metre'])
doc = literal.describe_xml()
[output] = xpath_ns(doc, '/Output')
[identifier] = xpath_ns(doc, '/Output/ows:Identifier')
[data_type] = xpath_ns(doc, '/Output/LiteralOutput/ows:DataType')
[uoms] = xpath_ns(doc, '/Output/LiteralOutput/UOMs')
[default_uom] = xpath_ns(uoms, './Default/ows:UOM')
supported_uoms = xpath_ns(uoms, './Supported/ows:UOM')
assert output is not None
assert identifier.text == 'literal'
assert data_type.attrib['{%s}reference' % NAMESPACES['ows']] == OGCTYPE['string']
assert uoms is not None
assert default_uom.text == 'metre'
assert default_uom.attrib['{%s}reference' % NAMESPACES['ows']] == OGCUNIT['metre']
assert len(supported_uoms) == 1
def __init__(self):
inputs = []
outputs = [LiteralOutput('answer', 'Answer to Ultimate Question', data_type='string')]
super(UltimateQuestion, self).__init__(
self._handler,
identifier='ultimate_question',
version='1.3.3.7',
title='Answer to the ultimate question',
abstract='This process gives the answer to the ultimate question of "What is the meaning of life?',
profile='',
metadata=['Ultimate Question', 'What is the meaning of life'],
inputs=inputs,
outputs=outputs,
store_supported=False,
status_supported=False
)
def create_translated_greeter():
def greeter(request, response):
name = request.inputs['name'][0].data
response.outputs['message'].data = "Hello {}!".format(name)
return response
return Process(
handler=greeter,
identifier='greeter',
title='Greeter',
abstract='Say hello',
inputs=[
LiteralInput(
'name',
'Input name',
data_type='string',
abstract='Input description',
translations={
"fr-CA": {
"title": "Nom",
"abstract": "Description"
}
},
)
],
outputs=[
LiteralOutput(
'message',
'Output message',
data_type='string',
abstract='Output description',
translations={
"fr-CA": {
"title": "Message de retour",
"abstract": "Description"
}
},
)
],
translations={
"fr-CA": {
"title": "Salutations",
"abstract": "Dire allô"
}
},
)
def __init__(self):
inputs = [LiteralInput('name', 'Input name', data_type='string')]
outputs = [
LiteralOutput('response', 'Output response', data_type='string')
]
super(SayHello,
self).__init__(self._handler,
identifier='say_hello',
title='Process Say Hello',
abstract='Returns a literal string output\
with Hello plus the inputed name',
version='1.3.2',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True)
def __init__(self):
inputs = []
outputs = [
LiteralOutput('IaaS_deploy_execute',
'List of (Broker, Celery Queue) available',
data_type='string'),
]
super(GetCloudParams, self).__init__(self._handler,
identifier='get_cloud_params',
abstract='Get cloud parameters',
title='Get Cloud Parameters',
version='0.1',
inputs=inputs,
outputs=outputs,
store_supported=False,
status_supported=False)
def __init__(self):
inputs = [LiteralInput('delay', 'Delay between every update', data_type='float')]
outputs = [LiteralOutput('sleep_output', 'Sleep Output', data_type='string')]
super(Sleep, self).__init__(
self._handler,
identifier='sleep',
version='None',
title='Sleep Process',
abstract='This process will sleep for a given delay or 10 seconds if not a valid value',
profile='',
metadata=['Sleep', 'Wait', 'Delay'],
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True
)
def __init__(self):
inputs = [ComplexInput('layer', 'Layer', supported_formats=[get_format('GML')])]
outputs = [LiteralOutput('count', 'Count', data_type='integer')]
super(FeatureCount, self).__init__(
self._handler,
identifier='feature_count',
version='None',
title='Feature count',
abstract='This process counts the number of features in a vector',
profile='',
metadata=['Feature', 'Count'],
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True
)
def __init__(self):
inputs = [
ComplexInput(
"file",
"File",
max_occurs=2,
abstract="Path to a local or online nc file",
supported_formats=[FORMATS.NETCDF, FORMATS.DODS],
),
ComplexInput(
"csv_input",
"CSV",
max_occurs=1,
abstract="CSV document",
supported_formats=[
Format("text/csv", extension=".csv"), FORMATS.TEXT
],
),
LiteralInput(
"argc",
"Argument count dictionary",
max_occurs=1,
abstract="Number of input arguments for each input",
data_type="string",
),
]
outputs = [
LiteralOutput(
"collected_argc",
"Collected argument count",
abstract="Number of collected arguments",
data_type="integer",
),
]
super(TestProcessMultiInput, self).__init__(
self._handler,
identifier="test_collect_args",
title="Test collect_args",
abstract="A simple process that tests collect_args.",
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True,
)
def __init__(self):
inputs = []
outputs = [LiteralOutput('output', 'Output', data_type='string')]
super(Dummy, self).__init__(
self._handler,
identifier='dummy',
version='None',
title='Dummy Process',
abstract='This is dummy process, nothing useful.',
profile='',
#wsdl='',
metadata=['Sleep', 'Wait', 'Delay'],
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True
)
def __init__(self):
inputs = [LiteralInput('x1', 'A point X', data_type='float'),
LiteralInput('y1', 'A point Y', data_type='float'),
LiteralInput('x2', 'B point X', data_type='float'),
LiteralInput('y2', 'B point Y', data_type='float')]
outputs = [LiteralOutput(
'path', 'Route path from A to B', data_type='string')]
super(AtoBRoute, self).__init__(
self._handler,
identifier='atob_route',
title='Define an ASTAR optimized path from A to B',
version='0.0.1',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True
)
def __init__(self):
inputs = [LiteralInput('delay', 'Delay between every update', default='1', data_type='float')]
outputs = [LiteralOutput('sleep_output', 'Sleep Output', data_type='string')]
super(Sleep, self).__init__(self._handler,
identifier='sleep',
version='1.0',
title='Sleep Process',
abstract='Testing a long running process, in the sleep.'
'This process will sleep for a given delay or 10 seconds if not a valid value.',
profile='',
metadata=[
Metadata('PyWPS Demo', 'https://pywps-demo.readthedocs.io/en/latest/'),
],
inputs=inputs,
outputs=outputs,
store_supported=False,
status_supported=False)
def __init__(self):
inputs = [
LiteralInput('inputa',
'Input 1',
data_type='float',
abstract='Enter Input 1',
default="2.0"),
LiteralInput('inputb',
'Input 2',
data_type='float',
abstract='Enter Input 2',
default="3.0"),
LiteralInput(
'operator',
'Operator',
data_type='string',
abstract='Choose a binary Operator',
default='add',
allowed_values=['add', 'substract', 'divide', 'multiply'])
]
outputs = [
LiteralOutput('output',
'Binary operator result',
data_type='float')
]
super(BinaryOperator, self).__init__(
self._handler,
identifier='binaryoperatorfornumbers',
title='Binary Operator for Numbers',
abstract='Performs operation on two numbers and returns the answer. '
'This example process is taken from Climate4Impact.',
metadata=[
Metadata('Birdhouse', 'http://bird-house.github.io/'),
MetadataUrl('User Guide',
'http://emu.readthedocs.io/en/latest/',
anonymous=True),
Metadata('Climate4Impact', 'https://dev.climate4impact.eu')
],
version='1.0',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True)
def create_complex_nc_process():
def complex_proces(request, response):
from pywps.dependencies import netCDF4 as nc
url = request.inputs['dods'][0].url
with nc.Dataset(url) as D:
response.outputs['conventions'].data = D.Conventions
response.outputs['outdods'].url = url
response.outputs['ncraw'].file = os.path.join(DATA_DIR, 'netcdf',
'time.nc')
response.outputs['ncraw'].data_format = FORMATS.NETCDF
return response
return Process(
handler=complex_proces,
identifier='my_opendap_process',
title='Opendap process',
inputs=[
ComplexInput(
'dods',
'Opendap input',
supported_formats=[Format('DODS'),
Format('NETCDF')],
# mode=MODE.STRICT
)
],
outputs=[
LiteralOutput(
'conventions',
'NetCDF convention',
),
ComplexOutput('outdods',
'Opendap output',
supported_formats=[
FORMATS.DODS,
],
as_reference=True),
ComplexOutput('ncraw',
'NetCDF raw data output',
supported_formats=[
FORMATS.NETCDF,
],
as_reference=False)
])
def __init__(self):
inputs = [
LiteralInput('polygon', 'WKT search polygon',
abstract='WKT',
data_type='string'
),
LiteralInput('srid', 'WKT CRS (EPSG ID)',
abstract='The CRS of the WKT polygon - use the numeric part of an EPSG ID, eg 4326 for EPSG:4326. Default is 4326',
data_type='string',
default='4326'
),
LiteralInput('data_srid', 'WKT CRS (EPSG ID)',
abstract='The CRS of the underlying data - use the numeric part of an EPSG ID, eg 28355 for EPSG:28355',
data_type='string',
),
LiteralInput('project', 'project ID',
abstract='data storage project',
data_type='string',
default='all',
min_occurs=0
),
LiteralInput('metadata', 'metadata response (or not)',
abstract='A switch to determine what metadata to return, if any. Default is none (file list only). For all available metadata use "all". Otherwise Provide a comma delimited list of words, options are: "density" (approximate point density of files intersecting ROI) , "count" (# of points in each file), "schema" (data storage schema equivalent to pdal info --schema), "classes" (approximate number of points in each class), "exactboundary" (exact boundary of point data as WKT multipolygon in native data CRS)',
data_type='string',
default='no',
min_occurs=0
)
]
outputs = [
LiteralOutput('metadata_response', 'Response metadata',
abstract='JSON dictionary of metadata which exist in the user-submitted polygon. Will be empty if no data exist in the ROI',
data_type='string')
]
super(polygonQuery, self).__init__(
self._handler,
identifier='polygonquery',
version='0',
title="Query data with a WKT polygon",
abstract='Provide a WKT polygon, and return a list of files which contain data inside the polygon. This process does not transform input polygons, it requires a user-defined SRS string which matches the coordinate system used in the polygon.',
profile='',
inputs=inputs,
outputs=outputs,
)
def __init__(self):
"""Sample."""
inputs = [
LiteralInput('input_dir',
'Workflow data volume path',
data_type='string',
abstract="""
Path to a directory within the Workflow Data volume.
The service will locate all files within this directory
and warp them.
""",
min_occurs=1,
max_occurs=2)
]
outputs = [
LiteralOutput(
'output_dir',
'Workflow data volume path',
data_type='string',
abstract="""
Path to a directory within the Workflow Data volume.
The service will store all outputs in this dir, then
provide a reference to the directory which other services
can use.
""",
)
]
super(GdalWarpRef, self).__init__(
identifier='gdalwarp_ref',
abstract="""
The process warps an input raster.
Locates all tiff files within the input_dir and creates a warped
version in the output_dir location.
<a href="http://gdal.org/gdalwarp.html">man page</a>
""",
version='0.1',
metadata=[Metadata('Sample'), Metadata('Test')],
title="GDAL Sample Process",
profile='',
inputs=inputs,
outputs=outputs,
)
def __init__(self):
inputs = [ComplexInput('layer', 'Layer',
[Format('application/gml+xml')])]
outputs = [LiteralOutput('count', 'Count', data_type='integer')]
super(FeatureCount, self).__init__(
self._handler,
identifier='feature_count',
version='None',
title='Feature count',
abstract='This process counts the number\
of features in an uploaded GML ',
profile='',
metadata=[Metadata('Feature'), Metadata('Count')],
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True
)
def __init__(self):
inputs = [
LiteralInput('one_integer',
'Some integer input',
data_type='integer')
]
outputs = [
LiteralOutput('repeated_integer',
'Echo of the input',
data_type='integer')
]
super(SimplestTest, self).__init__(self._handler,
identifier='simplesttest',
title='Simplest Test',
version='0.1',
inputs=inputs,
outputs=outputs)
def __init__(self):
inputs = [ LiteralInput('x1', 'Punto1 Coordenada X', data_type='float') ,
LiteralInput('y1', 'Punto1 Coordenada Y', data_type='float' ),
LiteralInput('x2', 'Punto2 Coordenada X', data_type='float' ),
LiteralInput('y2', 'Punto2 Coordenada Y', data_type='float') ]
outputs = [LiteralOutput('resultado', 'Resultado Calculo', data_type='float' )]
super(DistanciaP1P2, self).__init__(
self._handler,
identifier='distanciap1p2',
version='None',
title='Distancia entre P1 y P2',
abstract='Calcula la distancia euclidiana entre dos puntos',
profile='',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True
)
def __init__(self):
inputs = [
LiteralInput(
"name",
"Your name",
abstract="Please enter your name.",
keywords=["name", "firstname"],
data_type="string",
)
]
outputs = [
LiteralOutput(
"output",
"Output response",
abstract="A friendly Hello from us.",
keywords=["output", "result", "response"],
data_type="string",
)
]
super(SayHello, self).__init__(
self._handler,
identifier="hello",
title="Say Hello",
abstract="Just says a friendly Hello."
"Returns a literal string output with Hello plus the inputed name.",
keywords=["hello", "demo"],
metadata=[
Metadata("PyWPS", "https://pywps.org/"),
Metadata("Birdhouse", "http://bird-house.github.io/"),
Metadata("PyWPS Demo",
"https://pywps-demo.readthedocs.io/en/latest/"),
Metadata("Emu: PyWPS examples",
"https://emu.readthedocs.io/en/latest/"),
],
version="1.5",
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True,
)
def __init__(self):
inputs = [
ComplexInput('layer', 'Layer', [Format('application/gml+xml')])
]
outputs = [LiteralOutput('length', 'Total length', data_type='string')]
super(TotalLength,
self).__init__(self._handler,
identifier='grass_length',
title='Total line length',
abstract="""Process returns the length of each
feature from a submitted GML file""",
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True,
grass_location="epsg:3358")
def _handler(self, request, response):
# ogr2ogr requires gdal-bin
from grass.script import core as grass
grass.run_command("v.in.ogr",
input=request.inputs["layer"][0].file,
output="lines")
output = grass.pipe_command("v.report",
map="lines",
option="length")
line_length = 0
for line in output.stdout.readlines()[1:]:
line = line.strip()
length = line.split("|")[-1]
line_length += float(length)
response.outputs['length'].data = line_length
return response
def create_sleep():
def sleep(request, response):
seconds = request.inputs['seconds']
assert type(seconds) is type(1.0)
step = seconds / 10
for i in range(10):
# How is status working in version 4 ?
#self.status.set("Waiting...", i * 10)
time.sleep(step)
response.outputs['finished'] = "True"
return response
return Process(
handler=sleep,
identifier='sleep',
title='Sleep',
inputs=[LiteralInput('seconds', title='Seconds', data_type='float')],
outputs=[
LiteralOutput('finished', title='Finished', data_type='boolean')
])
def __init__(self):
inputs = []
outputs = []
variable = LiteralInput('variable',
'Variable',
abstract="Variable list",
data_type='string')
domain = LiteralInput('domain',
'Domain',
abstract="Domain list",
data_type='string')
operation = LiteralInput('operation',
'Operation list',
abstract="Operation list",
data_type='string')
response = LiteralOutput('response',
'Response',
abstract="Response",
data_type='string')
inputs = [variable, domain, operation]
outputs = [response]
super(oph_esgf_aggregate, self).__init__(
self._handler,
identifier='OPHIDIA.aggregate',
title='OPHIDIA.aggregate',
abstract=
"An Ophidia ESGF CWT operator used to aggregate files of a dataset into only one file",
version=_version,
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True)
def create_complex_nc_process():
def complex_proces(request, response):
from pywps.dependencies import netCDF4 as nc
url = request.inputs['dods'][0].url
with nc.Dataset(url) as D:
response.outputs['conventions'].data = D.Conventions
response.outputs['outdods'].url = url
return response
return Process(
handler=complex_proces,
identifier='my_opendap_process',
title='Opendap process',
inputs=[
ComplexInput(
'dods',
'Opendap input',
supported_formats=[
Format('DODS'),
Format('NETCDF'),
],
# mode=MODE.STRICT
)
],
outputs=[
LiteralOutput(
'conventions',
'NetCDF convention',
),
ComplexOutput('outdods',
'Opendap output',
supported_formats=[
Format('DODS'),
Format('NETCDF'),
],
as_reference=True)
])
def __init__(self):
inputs = [
LiteralInput(
'dry_run',
'Dry run mode. Default false',
data_type='boolean',
default=False,
),
LiteralInput(
'count',
'Number of Files (Limit 10)',
abstract=
'How many files do you want to download? The limit is 10',
data_type='integer',
allowed_values=[AllowedValue(minval=1, maxval=20)],
default=1,
mode=MODE.SIMPLE),
]
outputs = [
LiteralOutput('output', 'Output response', data_type='string')
]
super(SimpleDryRun, self).__init__(
self._handler,
identifier='simple_dry_run',
title='Simple Dry Run',
abstract='A dummy download as simple dry-run example.',
metadata=[
MetadataUrl(
'User Guide',
'https://emu.readthedocs.io/en/latest/processes.html',
anonymous=True),
],
version='1.0',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True)
def __init__(self):
inputs = [
LiteralInput(identifier='arg',
title='Input number',
data_type='integer',
abstract="Argument")
]
outputs = [
LiteralOutput(identifier='response',
title='Output response',
data_type='integer',
abstract="Result")
]
super(Square, self).__init__(self.handler,
identifier='square',
title='Square Process',
abstract='Quadriert den Input',
version='1.0.0',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True)
def __init__(self):
inputs = [
LiteralInput('name',
'Your name',
abstract='Please enter your name.',
keywords=['name', 'firstname'],
data_type='string')
]
outputs = [
LiteralOutput('output',
'Output response',
abstract='A friendly Hello from us.',
keywords=['output', 'result', 'response'],
data_type='string')
]
super(SayHello, self).__init__(
self._handler,
identifier='hello',
title='Say Hello',
abstract='Just says a friendly Hello.'
'Returns a literal string output with Hello plus the inputed name.',
keywords=['hello', 'demo'],
metadata=[
Metadata(
'User Guide',
'https://emu.readthedocs.io/en/latest/processes.html'
), # noqa
Metadata('PyWPS Demo',
'https://pywps-demo.readthedocs.io/en/latest/'),
],
version='1.5',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True)
def __init__(self):
self.status_percentage_steps = dict(
common_status_percentages,
**{
"load_rdata": 10,
"save_rdata": 90,
},
)
inputs = quantile_inputs
outputs = [
LiteralOutput(
"output_vector",
"Output Vector",
abstract="A vector of the quantiles in question",
data_type="string",
),
rda_output,
]
super(ClimdexQuantile, self).__init__(
self._handler,
identifier="climdex_quantile",
title="Climdex Quantile",
abstract="Implements R’s type=8 in a more efficient manner",
metadata=[
Metadata("NetCDF processing"),
Metadata("Climate Data Operations"),
Metadata("PyWPS", "https://pywps.org/"),
Metadata("Birdhouse", "http://bird-house.github.io/"),
Metadata("PyWPS Demo", "https://pywps-demo.readthedocs.io/en/latest/"),
],
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True,
)
def default_outputs():
return (
LiteralOutput(
'success',
'Success',
abstract="""True if the metric has been successfully calculated.
If false please check the log files""",
data_type='string'),
ComplexOutput('recipe',
'recipe',
abstract='ESMValTool recipe used for processing.',
as_reference=True,
supported_formats=[Format('text/plain')]),
ComplexOutput('log',
'Log File',
abstract='Log File of ESMValTool processing.',
as_reference=True,
supported_formats=[Format('text/plain')]),
ComplexOutput('debug_log',
'ESMValTool Debug File',
abstract='Debug Log File of ESMValTool processing.',
as_reference=True,
supported_formats=[Format('text/plain')]),
)
def __init__(self):
inputs = [LiteralInput('start', 'Start date (eg. 2017-03-01)',
data_type='string'),
LiteralInput('end', 'End date (eg. 2017-04-01)',
data_type='string')
]
outputs = [LiteralOutput('stats', 'Computed LST statistics',
data_type='string')
]
super(ModisV1, self).__init__(
self._handler,
identifier='modis-v1',
version='0.1',
title="Modis process (v1)",
abstract='The process uses the GRASS GIS to compute LST ' \
'statistics for given period in 2017 for Germany',
profile='',
inputs=inputs,
outputs=outputs,
store_supported=True,
status_supported=True,
grass_location="/opt/grassdata/germany-modis"
)