Merge pull request #13 from TranslatorSRI/async

Update novelty code to be async

app/logger.py

@@ -75,3 +75,5 @@ def setup_logger():
         logging_config = json.load(f)
 
     config.dictConfig(logging_config)
+    logging.getLogger("httpcore").setLevel(logging.WARNING)
+    logging.getLogger("httpx").setLevel(logging.WARNING)

app/novelty/compute_novelty.py

@@ -20,7 +20,7 @@
 """
 
 
-def molecular_sim(known, unknown, message):
+async def molecular_sim(known, unknown, message):
     unknown_ids = []
     known_ids = []
     if len(unknown) > 0:
@@ -59,14 +59,14 @@ def molecular_sim(known, unknown, message):
                     message["results"][drug]["node_bindings"][s[1]][0]["id"]
                 )
 
-    smile_unkown = mol_to_smile_molpro(unknown_ids)
-    smile_known = mol_to_smile_molpro(known_ids)
+    smile_unkown = await mol_to_smile_molpro(unknown_ids)
+    smile_known = await mol_to_smile_molpro(known_ids)
 
     similarity_map = find_nearest_neighbors(smile_unkown, smile_known, 0, 1)
     return similarity_map
 
 
-def get_publication_info(pub_id):
+async def get_publication_info(pub_id):
     """
     Args: PMID
     Returns: The publication info
@@ -75,8 +75,8 @@ def get_publication_info(pub_id):
     request_id = "1df88223-c0f8-47f5-a1f3-661b944c7849"
     full_url = f"{base_url}{pub_id}&request_id={request_id}"
     try:
-        with httpx.Client(timeout=30) as client:
-            response = client.get(full_url)
+        async with httpx.AsyncClient(timeout=30) as client:
+            response = await client.get(full_url)
             response.raise_for_status()
             response = response.json()
     except Exception:
@@ -141,7 +141,7 @@ def recency_function_exp(number_of_publ, age_of_oldest_publ, max_number, max_age
     return recency
 
 
-def extracting_drug_fda_publ_date(message, unknown):
+async def extracting_drug_fda_publ_date(message, unknown):
     """
     Upon querying, the response is returned as a list containing 10 dictionaries,
     with each dictionary representing the response from an ARA. The function 'extracting_drug_fda_publ_date'
@@ -246,7 +246,9 @@ def extracting_drug_fda_publ_date(message, unknown):
                                 # print(publications)
                                 publications_1 = ",".join(publications)
                                 try:
-                                    response_pub = get_publication_info(publications_1)
+                                    response_pub = await get_publication_info(
+                                        publications_1
+                                    )
                                     if response_pub["_meta"]["n_results"] == 0:
                                         age_oldest = np.nan
                                     else:
@@ -392,7 +394,7 @@ def novelty_score(fda_status, recency, similarity):
     return score
 
 
-def compute_novelty(message, logger):
+async def compute_novelty(message, logger):
     """INPUT: JSON Response with merged annotated results for a 1-H query
 
     1. load the json file
@@ -409,7 +411,7 @@ def compute_novelty(message, logger):
     # # Step 2
 
     # start = time.time()
-    df, query_chk = extracting_drug_fda_publ_date(message, unknown)
+    df, query_chk = await extracting_drug_fda_publ_date(message, unknown)
     # print(f"Time to extract fda status and Publication data:{time.time()-start}")
     #         # print(df.head())
     #         # print(query_chk)
@@ -432,7 +434,7 @@ def compute_novelty(message, logger):
     if query_chk == 1:
         # start = time.time()
         try:
-            similarity_map = molecular_sim(known, unknown, message)
+            similarity_map = await molecular_sim(known, unknown, message)
             df["similarity"] = df.apply(
                 lambda row: similarity_map[row["drug"]][0][1]
                 if row["drug"] in similarity_map.keys()

app/novelty/extr_smile_molpro_by_id.py

@@ -1,7 +1,7 @@
 import httpx
 
 
-def mol_to_smile_molpro(molecules):
+async def mol_to_smile_molpro(molecules):
     """
     Args:
         List
@@ -18,16 +18,16 @@ def mol_to_smile_molpro(molecules):
 
     data_mol = list(set(molecules))
     # print(f'init data: {len(data_mol)}')
-    with httpx.Client(timeout=30) as client:
+    async with httpx.AsyncClient(timeout=30) as client:
         while data_mol:
             # print(f'before: {len(data_mol)}')
             data_mol_before = len(data_mol)
-            response = client.post(url, headers=headers, json=data_mol)
+            response = await client.post(url, headers=headers, json=data_mol)
 
             if response.status_code == 200:
                 json_response = response.json()
                 collec_url = json_response["url"]
-                temp_collec_response = client.get(collec_url)
+                temp_collec_response = await client.get(collec_url)
                 if temp_collec_response.status_code == 200:
                     collec_response = temp_collec_response.json()
 

app/ordering_components.py

@@ -43,17 +43,19 @@ def get_clinical_evidence(result, message, logger, db_conn):
     return compute_clinical_evidence(result, message, logger, db_conn)
 
 
-def get_novelty(message, logger):
-    return compute_novelty(message, logger)
+async def get_novelty(message, logger):
+    novelty_df = await compute_novelty(message, logger)
+    novelty_dict = novelty_df.to_dict(orient="index")
+    novelty_scores = {
+        node["drug"]: node["novelty_score"] for node in novelty_dict.values()
+    }
+    return novelty_scores
 
 
-def get_ordering_components(message, logger):
+async def get_ordering_components(message, logger):
     logger.debug(f"Computing scores for {len(message['results'])} results")
     db_conn = redis.Redis(connection_pool=redis_pool)
-    novelty_scores_dict = get_novelty(message, logger).to_dict(orient="index")
-    novelty_scores = {
-        node["drug"]: node["novelty_score"] for node in novelty_scores_dict.values()
-    }
+    novelty_scores = await get_novelty(message, logger)
     for result in tqdm(message.get("results") or []):
         clinical_evidence_score = get_clinical_evidence(
             result,

app/server.py

@@ -21,7 +21,7 @@
 
 openapi_args = dict(
     title="Answer Appraiser",
-    version="0.3.1",
+    version="0.3.2",
     terms_of_service="",
     translator_component="Utility",
     translator_teams=["Standards Reference Implementation Team"],
@@ -117,7 +117,7 @@
 
 async def async_appraise(message, callback, logger: logging.Logger):
     try:
-        get_ordering_components(message, logger)
+        await get_ordering_components(message, logger)
     except Exception:
         logger.error(f"Something went wrong while appraising: {traceback.format_exc()}")
     logger.info("Done appraising")
@@ -174,7 +174,7 @@ async def sync_get_appraisal(query: Query = Body(..., example=EXAMPLE)):
             status_code=400,
         )
     try:
-        get_ordering_components(message, logger)
+        await get_ordering_components(message, logger)
     except Exception:
         logger.error(f"Something went wrong while appraising: {traceback.format_exc()}")
     logger.info("Done appraising")