aboutsummaryrefslogtreecommitdiff
path: root/wqflask
diff options
context:
space:
mode:
authorAlexander Kabui2021-11-18 13:40:54 +0300
committerAlexander Kabui2021-11-18 13:40:54 +0300
commit24d87cb4e75136f822b316a3c9f936b8e5efb5e9 (patch)
treec22c84e2839c9be831d90ec5f3003e87df7e3cab /wqflask
parent4de623130dca019d15f956e91ec999fddc2e2a0f (diff)
downloadgenenetwork2-24d87cb4e75136f822b316a3c9f936b8e5efb5e9.tar.gz
refactor code for metadata
Diffstat (limited to 'wqflask')
-rw-r--r--wqflask/wqflask/correlation/pre_computes.py11
-rw-r--r--wqflask/wqflask/correlation/show_corr_results.py29
2 files changed, 13 insertions, 27 deletions
diff --git a/wqflask/wqflask/correlation/pre_computes.py b/wqflask/wqflask/correlation/pre_computes.py
index b95ceba5..ad0bc6ef 100644
--- a/wqflask/wqflask/correlation/pre_computes.py
+++ b/wqflask/wqflask/correlation/pre_computes.py
@@ -16,12 +16,11 @@ def fetch_all_cached_metadata(dataset_name):
try:
with open(file_path, "r+") as file_handler:
dataset_metadata = json.load(file_handler)
+ return (file_path, dataset_metadata)
except FileNotFoundError:
Path(file_path).touch(exist_ok=True)
- return {}
-
- return (file_path, dataset_metadata)
+ return (file_path, {})
def cache_new_traits_metadata(dataset_metadata: dict, new_traits_metadata, file_path: str):
@@ -46,16 +45,10 @@ def cache_compute_results(base_dataset_type,
corr_method,
correlation_results,
trait_name):
- # pass
"""function to cache correlation results for heavy computations"""
- # init assumption only caching probeset type
- # fix redis;issue potential redis_cache!=current_timestamp
-
base_timestamp = query_table_timestamp(base_dataset_type)
- r.set(f"{base_dataset_type}timestamp", base_timestamp)
-
target_dataset_timestamp = base_timestamp
file_name = generate_filename(
diff --git a/wqflask/wqflask/correlation/show_corr_results.py b/wqflask/wqflask/correlation/show_corr_results.py
index 42010a1e..f5600f13 100644
--- a/wqflask/wqflask/correlation/show_corr_results.py
+++ b/wqflask/wqflask/correlation/show_corr_results.py
@@ -26,6 +26,9 @@ from base.trait import create_trait, jsonable
from base.data_set import create_dataset
from base.webqtlConfig import TMPDIR
+from wqflask.correlation.pre_computes import fetch_all_cached_metadata
+from wqflask.correlation.pre_computes import cache_new_traits_metadata
+
from utility import hmac
@@ -34,7 +37,8 @@ def set_template_vars(start_vars, correlation_data):
corr_method = start_vars['corr_sample_method']
if start_vars['dataset'] == "Temp":
- this_dataset_ob = create_dataset(dataset_name="Temp", dataset_type="Temp", group_name=start_vars['group'])
+ this_dataset_ob = create_dataset(
+ dataset_name="Temp", dataset_type="Temp", group_name=start_vars['group'])
else:
this_dataset_ob = create_dataset(dataset_name=start_vars['dataset'])
this_trait = create_trait(dataset=this_dataset_ob,
@@ -86,25 +90,17 @@ def correlation_json_for_table(correlation_data, this_trait, this_dataset, targe
corr_results = correlation_data['correlation_results']
results_list = []
- file_name = f"{target_dataset['name']}_metadata.json"
-
- file_path = os.path.join(TMPDIR, file_name)
new_traits_metadata = {}
- try:
- with open(file_path,"r+") as file_handler:
- dataset_metadata = json.load(file_handler)
-
- except FileNotFoundError:
- Path(file_path).touch(exist_ok=True)
- dataset_metadata = {}
+ (file_path, dataset_metadata) = fetch_all_cached_metadata(
+ target_dataset['name'])
for i, trait_dict in enumerate(corr_results):
trait_name = list(trait_dict.keys())[0]
trait = trait_dict[trait_name]
target_trait = dataset_metadata.get(trait_name)
- if target_trait is None:
+ if target_trait is None:
target_trait_ob = create_trait(dataset=target_dataset_ob,
name=trait_name,
get_qtl_info=True)
@@ -184,12 +180,9 @@ def correlation_json_for_table(correlation_data, this_trait, this_dataset, targe
results_list.append(results_dict)
-
- if bool(new_traits_metadata):
- # that means new traits exists
- dataset_metadata.update(new_traits_metadata)
- with open(file_path,"w+") as file_handler:
- json.dump(dataset_metadata, file_handler)
+ cache_new_traits_metadata(dataset_metadata,
+ new_traits_metadata,
+ file_path)
return json.dumps(results_list)