def map(function, input_list):
"""
map operation of Couler
"""
# Enforce the function to run and lock to add into step
if callable(function):
states._update_steps_lock = False
# TODO (terrytangyuan): Support functions with multiple arguments.
para = input_list[0]
inner = function(para)
if inner is None:
raise SyntaxError("require function return value")
states._update_steps_lock = True
else:
raise TypeError("require loop over a function to run")
inner_dict = output.extract_step_return(inner)
template_name = inner_dict["name"]
inner_step = Step(name=inner_dict["id"], template=template_name)
parameters = []
items_param_name = "%s-para-name" % template_name
items_param_dict = {"name": items_param_name}
function_template = states.workflow.get_template(template_name)
function_template_dict = function_template.to_dict()
if "resource" in function_template_dict:
# Update the template with the new dynamic `metadata.name`.
manifest_dict = yaml.safe_load(
function_template_dict["resource"]["manifest"]
)
manifest_dict["metadata"]["name"] = (
"'{{inputs.parameters.%s}}'" % items_param_name
)
function_template = states.workflow.get_template(template_name)
function_template.manifest = pyaml.dump(manifest_dict)
# Append this items parameter to input parameters in the template
function_template.args.append(items_param_dict)
states.workflow.add_template(function_template)
input_parameters = [items_param_dict]
else:
input_parameters = function_template_dict["inputs"]["parameters"]
for para_name in input_parameters:
parameters.append(
{
"name": para_name["name"],
"value": '"{{item.%s}}"' % para_name["name"],
}
)
inner_step.arguments = {"parameters": parameters}
with_items = []
for para_values in input_list:
item = {}
if not isinstance(para_values, list):
para_values = [para_values]
for j in range(len(input_parameters)):
para_name = input_parameters[j]["name"]
item[para_name] = para_values[j]
with_items.append(item)
inner_step.with_items = with_items
states.workflow.add_step(inner_dict["id"], inner_step)
return inner_step
def map(function, *arguments):
"""
map operation of Couler
"""
# Enforce the function to run and lock to add into step
# Checks the correct syntax
if callable(function):
states._update_steps_lock = False
para = []
x = 0
while x < len(arguments):
para.append(arguments[x][0])
x += 1
inner = function(*para)
if inner is None:
raise SyntaxError("require function return value")
states._update_steps_lock = True
else:
raise TypeError("require loop over a function to run")
inner_dict = output.extract_step_return(inner)
template_name = inner_dict["name"]
inner_step = Step(name=inner_dict["id"], template=template_name)
parameters = []
items_param_name = "%s-para-name" % template_name
items_param_dict = {"name": items_param_name}
function_template = states.workflow.get_template(template_name)
function_template_dict = function_template.to_dict()
if "resource" in function_template_dict:
# Update the template with the new dynamic `metadata.name`.
manifest_dict = yaml.safe_load(
function_template_dict["resource"]["manifest"])
manifest_dict["metadata"]["name"] = ("'{{inputs.parameters.%s}}'" %
items_param_name)
function_template = states.workflow.get_template(template_name)
function_template.manifest = pyaml.dump(manifest_dict)
# Append this items parameter to input parameters in the template
function_template.args.append(items_param_dict)
states.workflow.add_template(function_template)
input_parameters = [items_param_dict]
else:
input_parameters = function_template_dict["inputs"]["parameters"]
for para_name in input_parameters:
parameters.append({
"name": para_name["name"],
"value": '"{{item.%s}}"' % para_name["name"],
})
inner_step.arguments = {"parameters": parameters}
# the following part of the code
# Adds values to parameters (with items) while it goes
# through the *arguments-variable with two loops.
# inner loop:
# arguments[ind_of_func_param][0], arguments[ind_of_func_param][0]...
# Outer loop:
# arguments[0][ind_of_func_call], arguments[0][ind_of_func_call]...
# With two lists in *arguments
# result would be:
# 1. pair of items for the function:
# arguments[0][0], arguments[1][0]
# 2. pair of items for the function:
# arguments[0][1], arguments[1][1]
# and so on...
with_items = []
ind_of_func_call = 0
# the number of calls to be made to function
while ind_of_func_call < len(arguments[0]):
ind_of_func_param = 0
item = {}
# the number of parameters function takes.
while ind_of_func_param < len(arguments):
# checks if arguments[ind_of_func_param] is a list if not makes it
if not isinstance(arguments[ind_of_func_param], list):
arguments[ind_of_func_param] = [arguments[ind_of_func_param]]
# items are created for the with items part in .yaml
para_name = input_parameters[ind_of_func_param]["name"]
item[para_name] = arguments[ind_of_func_param][ind_of_func_call]
ind_of_func_param += 1
with_items.append(item)
ind_of_func_call += 1
# all the created items are added to the step and
# then the step is added to .yaml
inner_step.with_items = with_items
states.workflow.add_step(inner_dict["id"], inner_step)
return inner_step
