data_formats Namespace Reference

Functions
def	_dicts_to_orm_objects (model, data)
def	_objects_to_dicts (data)
def	_to_array_of_dicts (data)
def	_to_datatables (data)
def	apply_function (data, function, key)
def	objects_to_dicts (script)
def	query (script)
def	to_array_of_dicts (script)
def	to_datatables (script)
def	to_sql_query (data)

Detailed Description

This file holds decorator functions that can rearrange data returned from data sources.
They should be used to decorate the method that holds the script that is being passed to the framework.

Note: may also contain a decorator that can wrap a class around a function that contains a script (future development).

Function Documentation

_dicts_to_orm_objects()

def data_formats._dicts_to_orm_objects (   model,   data  )

private

Definition at line 103 of file data_formats.py.

def _dicts_to_orm_objects(model, data):
    if data.__class__.__name__ in ["json_list", "json_dict", "json_basic"]:
        data = data.data()
    new_data = [model(data[n]) for n in range(0, len(data))]
    return new_data

References ReggeGribovPartonMC_EposLHC_2760GeV_PbPb_cfi.model, and FastTimerService_cff.range.

Referenced by models.generate(), and data_formats_tests.data_formats_tests.test_dicts_to_orm_objects().

_objects_to_dicts()

def data_formats._objects_to_dicts (   data )

private

Definition at line 97 of file data_formats.py.

def _objects_to_dicts(data):
    if data.__class__.__name__ in ["json_list", "json_dict", "json_basic"]:
        data = data.data()
    new_data = [data[n].as_dicts() for n in range(0, len(data))]
    return json_data_node.make(new_data)
 

References FastTimerService_cff.range.

Referenced by data_sources.json_list.as_table(), objects_to_dicts(), data_formats_tests.data_formats_tests.test_dicts_to_orm_objects(), and data_formats_tests.data_formats_tests.test_orm_objects_to_dicts().

_to_array_of_dicts()

def data_formats._to_array_of_dicts (   data )

private

Definition at line 60 of file data_formats.py.

def _to_array_of_dicts(data):
    # check to see if the user has returned a data source, instead of a json data node
    if not(data.__class__.__name__ in ["json_list", "json_dict", "json_basic"]):
        data = json_data_node.make(data)
    headers = data.get("headers").data()
    data_list = data.get("data").data()
    def unicode_to_str(string):
        return str(string) if isinstance(string, unicode) else string
    headers = map(unicode_to_str, headers)
    def row_to_dict(row):
        row = map(unicode_to_str, row)
        return dict(zip(headers, row))
    array_of_dicts = map(row_to_dict, data_list)
    return json_data_node.make(array_of_dicts)
 

References data, genParticles_cff.map, str, and ComparisonHelper.zip().

Referenced by to_array_of_dicts().

_to_datatables()

def data_formats._to_datatables (   data )

private

Definition at line 75 of file data_formats.py.

def _to_datatables(data):
    headers = map(str, data.get(0).data().keys())
    new_data = []
    for n in range(0, len(data.data())):
        new_data.append(map(lambda entry : str(entry) if isinstance(entry, unicode) else entry, data.get(n).data().values()))
    return json_data_node.make({
        "headers" : headers,
        "data" : new_data
    })
 

References data, relativeConstraints.keys, genParticles_cff.map, FastTimerService_cff.range, str, and contentValuesCheck.values.

apply_function()

def data_formats.apply_function	(		data,
			function,
			key
	)

Definition at line 89 of file data_formats.py.

def apply_function(data, function, key):
    data = data.data()
    def apply_function_to_key(row):
        row[key] = function(row[key])
        return row
    new_data = [apply_function_to_key(data[n]) for n in range(0, len(data))]
    return json_data_node(new_data)
 

References FastTimerService_cff.range.

objects_to_dicts()

def data_formats.objects_to_dicts

(

script

)

Definition at line 49 of file data_formats.py.

def objects_to_dicts(script):
    def new_script(self, connection):
        try:
            data = script(self, connection)
            return _objects_to_dicts(data)
        except (KeyError, TypeError) as e:
            raise Exception("The data you gave wasn't in the correct format: %s" % str(e))
    return new_script
 
# functions used in decorators
 

References _objects_to_dicts(), and str.

query()

def data_formats.query

(

script

)

Definition at line 40 of file data_formats.py.

def query(script):
    def new_script(self, connection):
        try:
            data = script(self, connection)
            return _to_sql_query(data)
        except (KeyError, TypeError) as e:
            raise Exception("The data you gave wasn't in the correct format: %s" % str(e))
    return new_script
 

References str.

to_array_of_dicts()

def data_formats.to_array_of_dicts

(

script

)

Definition at line 18 of file data_formats.py.

def to_array_of_dicts(script):
    def new_script(self, connection):
        try:
            data = script(self, connection)
            array_of_dicts = _to_array_of_dicts(data)
            return json_data_node.make(array_of_dicts)
        except (KeyError, TypeError) as e:
            raise Exception("The data you gave wasn't in the correct format: %s" % str(e))
    return new_script
 
# convert {{header:value}, ..., {header:value}} to {headers:[], data:[[]]}

References _to_array_of_dicts(), and str.

to_datatables()

def data_formats.to_datatables

(

script

)

Definition at line 29 of file data_formats.py.

def to_datatables(script):
    def new_script(self, connection):
        try:
            data = script(self, connection)
            if(isinstance(data, list)):
                data = _json_data_node.make(data)
            return to_datatables(data)
        except (KeyError, TypeError) as e:
            raise Exception("The data you gave wasn't in the correct format: %s" % str(e))
    return new_script
 

References str.

to_sql_query()

def data_formats.to_sql_query

(

data

)

Definition at line 85 of file data_formats.py.

def to_sql_query(data):
    return data.to_sql()
 
# apply function to specific column of data, assuming data