From a20e20c79b054350b84e70af6e7d5ef2a0407786 Mon Sep 17 00:00:00 2001
From: Alexander Kabui
Date: Thu, 11 Nov 2021 22:18:21 +0300
Subject: pep8 formatting + minor fixing for writing to files

---
 wqflask/wqflask/correlation/pre_computes.py | 75 +++++++++++++----------------
 1 file changed, 34 insertions(+), 41 deletions(-)

diff --git a/wqflask/wqflask/correlation/pre_computes.py b/wqflask/wqflask/correlation/pre_computes.py
index 4244fcfb..1d832fde 100644
--- a/wqflask/wqflask/correlation/pre_computes.py
+++ b/wqflask/wqflask/correlation/pre_computes.py
@@ -1,28 +1,28 @@
-
+import json
 import os
 import hashlib
 
 from base.data_set import query_table_timestamp
 from base.webqtlConfig import TMPDIR
+from redis import Redis
 
+r = Redis()
 
-def generate_filename(**kwargs):
-    """generate unique filename"""
 
-    base_dataset_name = kwargs["base_dataset"]
-    target_dataset_name = kwargs["target_dataset"]
-    base_timestamp = kwargs["base_timestamp"]
-    target_dataset_timestamp = kwargs["target_timestamp"]
+def generate_filename(base_dataset_name, target_dataset_name, base_timestamp, target_dataset_timestamp):
+    """generate unique filename"""
 
     string_unicode = f"{base_dataset_name}{target_dataset_name}{base_timestamp}{target_dataset_timestamp}sample_corr_compute".encode()
     return hashlib.md5(string_unicode).hexdigest()
 
 
-def cache_compute_results(start_vars,
-    base_dataset_type,
-    correlation_results,
-    trait_name):
+def cache_compute_results(base_dataset_type,
+                          base_dataset_name,
+                          target_dataset_name,
+                          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
@@ -30,10 +30,11 @@ def cache_compute_results(start_vars,
 
     if base_timestamp is None:
         # fetch the timestamp
-        base_timestamp = target_dataset_timestamp = query_table_timestamp(
-            dataset_type)
+        base_timestamp = query_table_timestamp(
+            base_dataset_type)
+        r.set(f"{base_dataset_type}timestamp", base_timestamp)
 
-        r.set(f"{dataset_type}timestamp", target_dataset_timestamp)
+    target_dataset_timestamp = base_timestamp
 
     file_name = generate_filename(
         base_dataset_name, target_dataset_name,
@@ -41,51 +42,43 @@ def cache_compute_results(start_vars,
 
     file_path = os.path.join(TMPDIR, f"{file_name}.json")
 
-       try:
+    try:
+
+        with open(file_path, "r+") as json_handler:
 
-            with open(file_path, "r+") as json_handler:
+            results = json.load(json_handler)
+            results[trait_name] = correlation_results
 
-                results = json.load(json_handler)
+            json.dump(results, json_handler)
 
-                if results.get(trait_name) is  None:
-                    results.update({trait_name: correlation_results})
+    except FileNotFoundError:
 
-                json.dump(results, json_handler)
+        with open(file_path, "w+") as write_json_handler:
+            json.dump({trait_name: correlation_results}, write_json_handler)
 
-        except FileNotFoundError:
-            with open(file_path, "w") as json_handler:
-                json.dump({trait_name: correlation_results}, json_handler)
 
-def fetch_precompute_results(base_dataset_name,target_dataset_name,trait_name):
+def fetch_precompute_results(base_dataset_name, target_dataset_name, dataset_type, trait_name):
     """function to check for precomputed  results"""
 
     # check for redis timestamp
 
     # fix rely on the fact correlation run oftenly probeset is set
 
-    base_timestamp = target_dataset_timestamp =  r.get(dataset_type)
-
+    base_timestamp = target_dataset_timestamp = r.get(f"{dataset_type}timestamp")
 
     if base_timestamp is None:
         return
 
-    else:
-        file_name = generate_filename(
+    file_name = generate_filename(
         base_dataset_name, target_dataset_name,
         base_timestamp, target_dataset_timestamp)
 
-        try:
-            with open(file_path,"r") as json_handler:
-                correlation_results = json.load(json_handler)
-
-                return correlation_results.get(trait_name)
-
-        except FileNotFoundError:
-            pass
-
-
-
-
-
+    file_path = os.path.join(TMPDIR, f"{file_name}.json")
 
+    try:
+        with open(file_path, "r") as json_handler:
+            correlation_results = json.load(json_handler)
+            return correlation_results.get(trait_name)
 
+    except FileNotFoundError:
+        pass
-- 
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