def generate_copo_samples_data(profile_id):
# This method generates the 'json' for building the UI table
s = Sample(profile_id)
src = Source(profile_id)
samples = s.get_all_samples()
columns = []
dataSet = []
# headers
for el in src.schema:
if not hasattr(el, 'show_in_table') or el.show_in_table == 'true':
columns.append({"title": el.label})
for el in s.schema:
if not hasattr(el, 'show_in_table') or el.show_in_table == 'true':
columns.append({"title": el.label})
columns.append({"title": " "}) # extra 'blank' header for record actions column
# data
for sm in samples:
source = Source(profile_id).get_source_from_sample_id(sm['source_id'])
src_row = get_record_data(source, src.schema)
src_row.pop()
sm_row = get_record_data(sm, s.schema)
dataSet.append(src_row + sm_row)
return {"columns": columns, "dataSet": dataSet, "table_id": "sample_table"}
def get_isasamples_json():
"""
returns isa samples in a profile
:return:
"""
from dal.copo_da import Sample
profile_id = get_current_request().session['profile_id']
samples = Sample(profile_id).get_all_records()
value_field = str("id")
label_field = str("sample_name")
search_field = ["id", "sample_name"]
secondary_label_field = ["meta_sample_name"]
elem_json = dict(value_field=value_field,
label_field=label_field,
secondary_label_field=secondary_label_field,
search_field=search_field,
options=list())
for sd in samples:
if sd["sample_type"] == "isasample":
elem_json.get("options").append({
value_field:
str(sd["_id"]),
label_field:
sd["name"],
secondary_label_field[0]:
sd["name"],
"sample_type":
sd.get("sample_type", str())
})
return elem_json
def get_samples_options():
from dal.copo_da import Sample
profile_id = get_current_request().session['profile_id']
samples = Sample(profile_id).get_all_records()
option_values = []
for sd in samples:
label = sd["name"]
option_values.append({"value": str(sd["_id"]), "label": label})
return option_values
def get_sample(df):
# get sample from datafile
s_id = df["description"]["attributes"]["attach_study_samples"][
"sample_copo"]
if s_id != "":
smp = Sample().get_record(s_id)
else:
s_id = df["description"]["attributes"]["attach_study_samples"][
"sample_ena"]
# TODO - get sample metadata from ENA tools
return smp
def save_samples(self, generated_samples, sample_type):
bulk = Sample().get_collection_handle().initialize_unordered_bulk_op()
for sample in generated_samples:
auto_fields = dict()
auto_fields[Sample().get_qualified_field("name")] = sample["name"]
auto_fields[Sample().get_qualified_field("sample_type")] = sample_type
# set qualified path for attributes
for k, v in sample["attributes"].items():
if k:
auto_fields[Sample().get_qualified_field(k)] = v
kwargs = dict()
kwargs["target_id"] = str()
kwargs["validate_only"] = True # preventing save per record in order to do bulk save
record = Sample(profile_id=self.profile_id).save_record(auto_fields, **kwargs)
bulk.insert(record)
bulk.execute()
return True
def get_samples_json(target_id=None):
"""
returns all samples in a profile (i.e isa and biosamples)
:return:
"""
from dal.copo_da import Sample
profile_id = get_current_request().session['profile_id']
if target_id:
samples = list()
samples.append(Sample().get_record(target_id))
else:
samples = Sample(profile_id).get_all_records()
value_field = str("id")
label_field = str("sample_name")
search_field = ["id", "sample_name"]
secondary_label_field = ["meta_sample_name"]
elem_json = dict(value_field=value_field,
label_field=label_field,
secondary_label_field=secondary_label_field,
search_field=search_field,
options=list())
for sd in samples:
elem_json.get("options").append({
value_field:
str(sd["_id"]),
label_field:
sd["name"],
secondary_label_field[0]:
sd["name"],
"sample_type":
sd.get("sample_type", str())
})
return elem_json
def get_samples_for_study(request):
# get all samples which have corresponding profile_id number
profile_id = request.POST['profile_id']
samples = Sample().get_from_profile_id(profile_id=profile_id)
output = list()
for s in samples:
source = Source().get_record(s['derivesFrom'][0])
# s.update(source)
d = {
"organism": source["organism"],
"_id": s["_id"],
"name": s["name"]
}
output.append(d)
return HttpResponse(json_util.dumps(output))
def get(request, id):
"""
Method to handle a request for a single sample object from the API
:param request: a Django HTTPRequest object
:param id: the id of the Sample object (can be string or ObjectID)
:return: an HttpResponse object embedded with the completed return template for Sample
"""
# get sample and source objects
try:
ss = Sample().get_sample_and_source(id)
except TypeError as e:
print(e)
return finish_request(error=API_ERRORS['NOT_FOUND'])
except InvalidId as e:
print(e)
return finish_request(error=API_ERRORS['INVALID_PARAMETER'])
except:
print("Unexpected error:", sys.exc_info()[0])
raise
source = ss['source']
sample = ss['sample']
# get template for return type
t_source = get_return_template('SOURCE')
t_sample = get_return_template('SAMPLE')
# extract fields for both source and sample
tmp_source = extract_to_template(object=source, template=t_source)
tmp_sample = extract_to_template(object=sample, template=t_sample)
tmp_sample['source'] = tmp_source
out_list = []
out_list.append(tmp_sample)
return finish_request(out_list)
def get_all(request):
"""
Method to handle a request for all
:param request: a Django HttpRequest object
:return: A dictionary containing all samples in COPO
"""
out_list = []
# get sample and source objects
try:
sample_list = Sample().get_samples_across_profiles()
except TypeError as e:
print(e)
return finish_request(error=API_ERRORS['NOT_FOUND'])
except InvalidId as e:
print(e)
return finish_request(error=API_ERRORS['INVALID_PARAMETER'])
except:
print("Unexpected error:", sys.exc_info()[0])
raise
for s in sample_list:
# get template for return type
t_source = get_return_template('SOURCE')
t_sample = get_return_template('SAMPLE')
# get source for sample
source = Source().GET(s['source_id'])
# extract fields for both source and sample
tmp_source = extract_to_template(object=source, template=t_source)
tmp_sample = extract_to_template(object=s, template=t_sample)
tmp_sample['source'] = tmp_source
out_list.append(tmp_sample)
return finish_request(out_list)
def __init__(self, description_token=str(), profile_id=str()):
self.description_token = description_token
self.profile_id = self.set_profile_id(profile_id)
self.schema = Sample().get_schema().get("schema_dict")
def get_allsamples(self):
"""
lookup for all samples irrespective of sample type
:return:
"""
import web.apps.web_copo.templatetags.html_tags as htags
df = pd.DataFrame()
if self.accession:
if isinstance(self.accession, str):
self.accession = self.accession.split(",")
object_ids = [ObjectId(x) for x in self.accession if x.strip()]
records = cursor_to_list(Sample().get_collection_handle().find(
{"_id": {
"$in": object_ids
}}))
if records:
df = pd.DataFrame(records)
df['accession'] = df._id.astype(str)
df['label'] = df['name']
df['desc'] = df['accession'].apply(
lambda x: htags.generate_attributes("sample", x))
df['description'] = df['desc'].apply(
lambda x: self.format_description(x))
df['server-side'] = True # ...to request callback to server for resolving item description
elif self.search_term:
projection = dict(name=1)
filter_by = dict()
filter_by["name"] = {'$regex': self.search_term, "$options": 'i'}
sort_by = 'name'
sort_direction = -1
records = Sample(
profile_id=self.profile_id).get_all_records_columns(
filter_by=filter_by,
projection=projection,
sort_by=sort_by,
sort_direction=sort_direction)
if not records:
# try getting all records
del filter_by['name']
records = Sample(
profile_id=self.profile_id).get_all_records_columns(
filter_by=filter_by,
projection=projection,
sort_by=sort_by,
sort_direction=sort_direction)
if records:
df = pd.DataFrame(records)
df['accession'] = df._id.astype(str)
df['label'] = df['name']
df['description'] = ''
df['server-side'] = True # ...to request callback to server for resolving item description
result = list()
if not df.empty:
df = df[['accession', 'label', 'description', 'server-side']]
result = df.to_dict('records')
return result
