Implement strategy for multi-user scenario

callbacks/coexpression/util.py

@@ -175,15 +175,19 @@ def do_module_enrichment_analysis(implicated_gene_ids, genomic_intervals, addl_g
     implicated_genes = set(implicated_gene_ids)
     INPUT_GENES_DIR = create_module_enrichment_results_dir(
         genomic_intervals, addl_genes, network, algo, parameters)
+    ENRICHED_MODULES_PATH = f'{INPUT_GENES_DIR}/enriched_modules.tsv'
 
-    if not path_exists(f'{INPUT_GENES_DIR}/enriched_modules.tsv'):
+    if not path_exists(ENRICHED_MODULES_PATH):
+        ENRICHED_MODULES_PATH_WITH_TIMESTAMP = append_timestamp_to_filename(
+            ENRICHED_MODULES_PATH)
         MODULES_PATH = f'{const.NETWORK_MODULES}/{network}/MSU/{algo}/{parameters}/{algo}-module-list.tsv'
 
         # ====================================================================================
         # This replicates the logic of running the universal enrichment function `enricher()`
         # provided by clusterProfiler
         # ====================================================================================
-        with open(MODULES_PATH) as modules_file, open(f'{INPUT_GENES_DIR}/enriched_modules.tsv', 'w') as enriched_modules_file:
+
+        with open(MODULES_PATH) as modules_file, open(ENRICHED_MODULES_PATH_WITH_TIMESTAMP, 'w') as enriched_modules_file:
             modules = []
             background_genes = set()
             for idx, line in enumerate(modules_file):
@@ -217,6 +221,12 @@ def do_module_enrichment_analysis(implicated_gene_ids, genomic_intervals, addl_g
 
             enriched_modules_file.write('\n'.join(significant_adj_p_values))
 
+        try:
+            os.replace(ENRICHED_MODULES_PATH_WITH_TIMESTAMP,
+                       ENRICHED_MODULES_PATH)
+        except:
+            pass
+
     return fetch_enriched_modules(INPUT_GENES_DIR)
 
 

callbacks/file_util.py

@@ -1,6 +1,9 @@
 import regex as re
 import os
 from .constants import Constants
+
+import time
+
 const = Constants()
 
 
@@ -67,3 +70,7 @@ def get_path_to_temp(genomic_interval, analysis_type, *args):
     temp_dir = re.sub(r'/+', '/', temp_dir)
 
     return temp_dir
+
+
+def append_timestamp_to_filename(filename):
+    return f'{filename}.{time.time_ns() // 1000}'