def test_execute_query_data_ordering(self):
# Arrange
query = {}
ascending_order_by_field = ["+title"]
descending_order_by_field = ["-title"]
# Act
ascending_result = Data.execute_query(query, ascending_order_by_field)
descending_result = Data.execute_query(query, descending_order_by_field)
# Assert
for i in range(len(ascending_result)):
self.assertTrue(ascending_result.all()[i].title == descending_result.all()[len(ascending_result) - i - 1].title)
def test_execute_query_multi_field_sorting(self):
# Arrange
ascending_order_by_multi_field = ["+title", "+user_id"]
descending_order_by_multi_field = ["+title", "-user_id"]
query = {}
# Act
ascending_result = Data.execute_query(query, ascending_order_by_multi_field)
descending_result = Data.execute_query(query, descending_order_by_multi_field)
# Assert
self.assertEqual(self.fixture.data_4.user_id, ascending_result.all()[4].user_id)
self.assertEqual(self.fixture.data_5.user_id, ascending_result.all()[3].user_id)
self.assertEqual(self.fixture.data_4.user_id, descending_result.all()[3].user_id)
self.assertEqual(self.fixture.data_5.user_id, descending_result.all()[4].user_id)
def test_execute_query_data_descending_sorting(self):
# Arrange
descending_order_by_field = ["-title"]
query = {}
# Act
descending_result = Data.execute_query(query, descending_order_by_field)
# Assert
self.assertTrue(self.fixture.data_2.title == descending_result.all()[len(descending_result)-2].title)
self.assertTrue(self.fixture.data_1.title == descending_result.all()[len(descending_result)-1].title)
def test_execute_query_data_ascending_sorting(self):
# Arrange
ascending_order_by_field = ["+title"]
query = {}
# Act
ascending_result = Data.execute_query(query, ascending_order_by_field)
# Assert
self.assertTrue(self.fixture.data_1.title == ascending_result.all()[0].title)
self.assertTrue(self.fixture.data_2.title == ascending_result.all()[1].title)
def execute_query_with_projection(query, projection):
""" Execute a given query with a projection.
Args:
query:
projection:
Returns:
"""
return Data.execute_query(query).only(projection)
def is_local_id_already_used(local_id):
""" Check if the local id given already exist in db
Args:
local_id:
Returns:
"""
return len(
Data.execute_query({'dict_content.Resource.@localid': str(local_id)
})) > 0
def execute_query(query, user, order_by_field=DATA_SORTING_FIELDS):
"""Execute a query on the Data collection.
Args:
query:
user:
order_by_field:
Returns:
"""
return Data.execute_query(query, order_by_field)
def execute_query(query, user, order_by_field=None):
"""Execute a query on the Data collection.
Args:
query:
user:
order_by_field
Returns:
"""
return Data.execute_query(query, order_by_field)
def is_pid_defined(pid):
"""Determine if a given PID already exists.
Params:
pid:
Returns:
"""
json_pid_path = "dict_content.%s" % PID_XPATH
query_result = Data.execute_query({json_pid_path: pid}, order_by_field=[])
return len(query_result) == 1
def process_cross_query(navigation_root_id, document_id, query, json_content):
"""
Args:
navigation_root_id:
document_id:
query:
json_content:
Return:
"""
doc_query = {"_id": ObjectId(document_id)}
doc_projection = {query.values()[0]: 1}
document_list = Data.execute_query(doc_query).only(
doc_projection.keys()[0])
document_projection_value = get_projection(document_list[0])
cross_query = {query.keys()[0]: document_projection_value}
cross_projection = {"id": 1}
cross_documents = Data.execute_query(cross_query).only(
cross_projection.keys()[0])
cross_documents_ids = [
get_projection(cross_doc) for cross_doc in cross_documents
]
# Gives the crossed documents and their id
global ids_docs_to_querys
ids_docs_to_querys = cross_documents_ids
# FIXME won't work for the case where we need several item from a same document
cross_document_data = processviewdocidlist(navigation_root_id,
cross_documents_ids,
json_content)
return [
content for contents in cross_document_data for content in contents
]
def is_pid_defined_for_document(pid, document_id):
"""Determine if a given PID match the document ID provided.
Params:
pid:
document_id:
Returns:
"""
json_pid_path = "dict_content.%s" % PID_XPATH
query_result = Data.execute_query({json_pid_path: pid}, order_by_field=[])
return len(query_result) == 1 and query_result[0].pk == document_id
def execute_query_with_projection(query,
projection,
order_by_field=DATA_SORTING_FIELDS):
"""Execute a given query with a projection.
Args:
query:
projection:
order_by_field:
Returns:
"""
return Data.execute_query(query, order_by_field).only(projection)
def get_data_by_pid(pid):
"""Return data object with the given pid.
Parameters:
pid:
Returns: data object
"""
json_pid_path = "dict_content.%s" % PID_XPATH
query_result = Data.execute_query({json_pid_path: pid}, order_by_field=[])
query_result_length = len(query_result)
if query_result_length == 0:
raise DoesNotExist("PID is not attached to any data.")
elif query_result_length != 1:
raise ApiError("PID must be unique.")
else:
return query_result[0]
def _load_data_view(node_id, nav_id, data_id, from_tree=True):
""" Load view for a data, from a tree or a link
Args:
node_id:
nav_id:
data_id:
from_tree:
Returns:
"""
if not from_tree:
navigation_node = navigation_operations.get_navigation_node_for_document(
node_id, data_id)
else:
navigation_node = navigation_api.get_by_id(node_id)
# Initialize parameters in order to download later some information
xml_document = Data.get_by_id(data_id)
projection_views = json.loads(navigation_node.options["projection_view"])
view_data = {
"header": xml_document.title,
"type": "leaf",
"views": [],
"download": []
}
# Initialize parameters in order to download later some information
# dict of doc_id and queries done of cross documents : {id_doc1: [list of queries1], id_doc2: [list of queries2]}
dict_id_and_queries_cross_docs = dict()
# dict of doc_id and queries results for a cross document : {id_doc: [list of queries results]}
dict_id_and_queryresults_cross_docs = dict()
# dict of queried parameter and associated result for the queries done on the main doc : { queried parameter: value}
dict_tags_values_main_doc = dict()
values_of_items_from_main_doc = []
list_values_of_items_from_main_doc = []
# Send the annotation to the processor and collect the data
for projection_view in projection_views:
result_data = {"title": projection_view["title"], "data": None}
# FIXME better handling of x-queries
# Get info from other doc (without the main queried document)
if "query" in projection_view.keys():
doc_projections = []
# Get the names of the tags tag need to be displayed
for value in projection_view["data"]:
doc_projections.append(value.get('path'))
result_data["data"] = parser_processview.process_cross_query(
nav_id, data_id, projection_view["query"],
projection_view["data"])
# Get all the queried documents (without the main queried document)
queried_docs = parser_processview.ids_docs_to_querys
for id_doc in queried_docs:
other_doc_query = {"_id": ObjectId(id_doc)}
# list of queries done on the current document
query_list = list()
# list of queries results done on the current document
result_list = list()
for projection in doc_projections:
# Get the MongoDB query path for the parameter that need to be displayed
# eg: query_path = dict_content.a.b.c.d.e
query_path = {
doc_projections[doc_projections.index(projection)]: 1
}
# Get the Data corresponding to the id
queried_data = Data.execute_query(other_doc_query).only(
query_path.keys()[0])
# Add the query to the query list for the current doc
query_list.append(query_path.keys()[0].replace(
"dict_content.", ""))
try:
# Get the result of the query
result_query = get_projection(queried_data[0])
# Add the result of the query to the result list for the current doc
result_list.append(str(result_query))
except:
pass
dict_id_and_queries_cross_docs[id_doc] = query_list
dict_id_and_queryresults_cross_docs[id_doc] = result_list
# Get info from main doc
else:
# list of queries done on the current document (Main doc)
query_list = []
doc_projections = [
value.get('path') for value in projection_view["data"]
]
query_list = [
doc_projections[doc_projections.index(projection)]
for projection in doc_projections
]
# Get all results of the queries. type(result_data["data"]) = dict or instance of dict
result_data["data"] = parser_processview.processview(
nav_id, data_id, projection_view["data"])
for query_path, dict_result in zip(query_list,
result_data["data"]):
# eg: query_path = a.b.c.d
# We have only one value as result for the query
dict_result_value = dict_result.get("value", None)
if dict_result_value is not None:
tag = query_path.split(".")[
-1] # Get only d (the needed tag)
if tag in dict_tags_values_main_doc:
v = dict_tags_values_main_doc[tag]
if isinstance(v, list):
dict_tags_values_main_doc[tag].append(
dict_result_value)
else:
dict_tags_values_main_doc[tag] = [
dict_tags_values_main_doc[tag],
dict_result_value
]
else:
dict_tags_values_main_doc[tag] = dict_result_value
# We have multiple values for this result: all the chemical components
# (dict_result[key] is an inclusion of dicts)
dict_result_item, dict_result_items = [
dict_result.get(_, None) for _ in ["item", "items"]
]
if dict_result_item or dict_result_items:
dict_result_item_v = dict_result_item if dict_result_item is not None else dict_result_items
#dict_result_item_v = [dict_result_item, dict_result_items][dict_result_item not None]
# From the inclusion of dict, process the dict into a list and get all the needed values
# values_of_items_from_main_doc = list[list[value1 for dict i,value2 for dict 2, ..]]
# eg: values_of_items_from_main_doc= [l1,l2]
# l1 = [["location", "NIST"], ["Build location X", "59"], "EWI_Build1"]]
# l2 = [["location", "NIST"], ["Build location X", "47"], "EWI_Build2"]]
get_values_items(dict_result_item_v,
values_of_items_from_main_doc)
for list_of_values in values_of_items_from_main_doc:
for value in list_of_values:
# We have a list :value= [displayed parameter, value]
# eg : ["Build location X", "59"]
if len(value) == 2:
# list_tag_of_items_from_main_doc.append(value[0])
list_values_of_items_from_main_doc.append(
value[1]) # Get the value. eg: 59
# We have only one value (last value in the list. eg: EWI_Build1 in l1)
else:
list_values_of_items_from_main_doc.append(
value)
view_data["views"].append(result_data)
# Get the displayed data as an XML format in order to download it later #
# STEP 1: Build the XML based on initial tags for the crossed documents:
# Go into the dict of doc_id and queries of cross documents and build the xml for each document
# dict_id_and_queries_cross_docs = {id_doc1: [list of queries1], id_doc2: [list of queries2]}
xml_cross_queries_string = ""
for key in dict_id_and_queries_cross_docs: # key = doc_id
# Get all queries for the current doc_id.
# eg: query_list = ["a.b.c.d","a.b.c.e","a.b.f.g"]
query_list = dict_id_and_queries_cross_docs[key]
# For the doc_id get all the results of the queries done
# results = ["D","E","G"]
results = dict_id_and_queryresults_cross_docs[key]
# Build a xml string for the doc associated to doc_id thanks to the list of queries and the result list
xml_string = queryNode.tree_to_xml_string(
queryNode.aggregate_query(query_list, results))
xml_object = XSDTree.fromstring(xml_string + "</data>")
# Add the XML part to create an XML resulting of tag and values of crossed documents
xml_cross_queries_string += XSDTree.tostring(xml_object, pretty=True)
# STEP 2: Build the XML for the main document with only the needed tags:
# Get the Data associated to the main document
data = Data.get_by_id(data_id)
# Get the XML content
file_content = data.xml_content
xml_main_doc = XSDTree.fromstring(file_content)
# Transform all the result value into a string to help while testing equality of values with the original XML
for key, value in dict_tags_values_main_doc.items():
if isinstance(value, list):
dict_tags_values_main_doc[key] = map(
lambda x: x if isinstance(x, unicode) else str(x), value)
else:
try:
dict_tags_values_main_doc[key] = str(value)
except:
dict_tags_values_main_doc[key] = u''.join(value).encode(
'utf-8')
v = dict_tags_values_main_doc[key]
# Process the XML structure that represents the main document to keep only the needed tags and information
for child in xml_main_doc.iter():
# Transform all values into a string
try:
text = str(child.text)
except:
text = u''.join(child.text).encode('utf-8')
# If the xml tag is in our dict of tags and values from the main document
# and its value = dict_tags_values_main_doc[child.tag] we keep the text in the XML structure
# else we remove the text
if child.tag in dict_tags_values_main_doc.keys():
# Fixme # if text != str(dict_tags_values_main_doc[child.tag]) or dict_tags_values_main_doc[child.tag] not in text: (caution: does not keep all needed values if we replace by this line)
if isinstance(dict_tags_values_main_doc[child.tag], list):
display_value = False
for value in dict_tags_values_main_doc[child.tag]:
if value == text or value in text:
display_value = True
break
if not display_value:
child.text = ""
else:
if text == str(
dict_tags_values_main_doc[child.tag]
) or dict_tags_values_main_doc[child.tag] in text:
pass
else:
child.text = ""
else:
# If text is in our list of items of the main doc we keep the value and remove it from our list of items
if text in list_values_of_items_from_main_doc:
list_values_of_items_from_main_doc.remove(text)
else:
display_text = False
# v = processed name of the tag as appears in the rendered data after clicking a doc of the tree
# If this name is in our list of items from the main doc we keep the value (text) in the XML tree
# else we remove this value
for v in list_values_of_items_from_main_doc:
if v in text:
display_text = True
break
if not display_text:
child.text = ""
xml_f_main_doc = xml_main_doc
# Remove empty leafs of the tree (all child where child.text="")
while check_empty_nodes(xml_main_doc):
remove_empty_nodes(xml_f_main_doc)
# Build the final XML string result of the main doc and the crossed docs
xml_main_doc = XSDTree.tostring(xml_f_main_doc, pretty="TRUE")
xml = xml_main_doc + xml_cross_queries_string
xml_final = "<xml>\n" + xml + "</xml>"
xml_final = u''.join(xml_final).encode('utf-8')
xml_final = str(xml_final)
view_data["download"] = xml_final
return view_data
