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authorAlexander_Kabui2023-04-12 03:39:56 +0300
committerAlexander_Kabui2023-04-12 03:39:56 +0300
commit62107ad6ec09052adcc373484d7a6752ddadf865 (patch)
tree07e11c8bc2385c45ec1d0d9123bd77288e1e767a
parent7fcd0aee1d9753856c14c8b4a21c6094dc7727ff (diff)
downloadgenenetwork2-62107ad6ec09052adcc373484d7a6752ddadf865.tar.gz
add code to store metadata in files
-rw-r--r--wqflask/wqflask/correlation/pre_computes.py38
1 files changed, 33 insertions, 5 deletions
diff --git a/wqflask/wqflask/correlation/pre_computes.py b/wqflask/wqflask/correlation/pre_computes.py
index 961f5161..d5916673 100644
--- a/wqflask/wqflask/correlation/pre_computes.py
+++ b/wqflask/wqflask/correlation/pre_computes.py
@@ -2,6 +2,10 @@ import csv
import json
import os
import hashlib
+import datetime
+
+import lmdb
+import pickle
from pathlib import Path
from base.data_set import query_table_timestamp
@@ -10,6 +14,31 @@ from base.webqtlConfig import TMPDIR
from json.decoder import JSONDecodeError
+def cache_trait_metadata(dataset_name, data):
+
+
+ try:
+ with lmdb.open(os.path.join(TMPDIR,f"metadata_{dataset_name}"),map_size=20971520) as env:
+ with env.begin(write=True) as txn:
+ data_bytes = pickle.dumps(data)
+ txn.put(f"{dataset_name}".encode(), data_bytes)
+ current_date = datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')
+ txn.put(b"creation_date", current_date.encode())
+ return "success"
+
+ except lmdb.Error as error:
+ pass
+
+def read_trait_metadata(dataset_name):
+ try:
+ with lmdb.open(os.path.join(TMPDIR,f"metadata_{dataset_name}"),
+ readonly=True, lock=False) as env:
+ with env.begin() as txn:
+ db_name = txn.get(dataset_name.encode())
+ return (pickle.loads(db_name) if db_name else {})
+ except lmdb.Error as error:
+ return {}
+
def fetch_all_cached_metadata(dataset_name):
"""in a gvein dataset fetch all the traits metadata"""
@@ -174,11 +203,10 @@ def get_datasets_data(base_dataset, target_dataset_data):
def fetch_text_file(dataset_name, conn, text_dir=TMPDIR):
"""fetch textfiles with strain vals if exists"""
-
- def __file_scanner__(text_dir,target_file):
- for file in os.listdir(text_dir):
+ def __file_scanner__(text_dir, target_file):
+ for file in os.listdir(text_dir):
if file.startswith(f"ProbeSetFreezeId_{target_file}_"):
- return os.path.join(text_dir,file)
+ return os.path.join(text_dir, file)
with conn.cursor() as cursor:
cursor.execute(
@@ -188,7 +216,7 @@ def fetch_text_file(dataset_name, conn, text_dir=TMPDIR):
try:
# checks first for recently generated textfiles if not use gn1 datamatrix
- return __file_scanner__(text_dir,results[0]) or __file_scanner__(TEXTDIR,results[0])
+ return __file_scanner__(text_dir, results[0]) or __file_scanner__(TEXTDIR, results[0])
except Exception:
pass