working on api changes

src/backend_flask/app.py

@@ -26,6 +26,7 @@ from email.mime.text import MIMEText
 from copy import deepcopy as DC
 from pathlib import Path
 from pymongo import MongoClient
+import pymongo
 import argparse
 
 # some db collections
@@ -55,7 +56,8 @@ CORS(app)
 
 @app.route("/api/dev")
 def api_dev():
-    cur = valdb.kres.find({"sid": "F0015940.37.2"})
+    print("DEV")
+    cur = valdb.kres.find({"headwords": "nagovarjati"})
     frames = []
     for ent in cur:
         frames += frames_from_db_entry(ent)
@@ -236,20 +238,18 @@ def api_token():
 def prepare_frames(ret_frames):
     # append sentences
     for frame in ret_frames:
-        frame.sentences = []
         unique_sids = {".".join(x.split(".")[:-1]): x for x in frame.tids}
         log.debug(str(unique_sids))
-        frame.sentences = []
+        # frame.sentences = []
         frame.aggr_sent = {}
+        # sid, tid==hw
         for sid, tid in unique_sids.items():
-            hwl = vallex.get_token(tid)["lemma"]
+            # hwl = vallex.get_token(tid)["lemma"]
+            hwl = "derp"
             tmp_idx = len(frame.sentences)
             if hwl not in frame.aggr_sent:
                 frame.aggr_sent[hwl] = []
             frame.aggr_sent[hwl].append(tmp_idx)
-            frame.sentences.append(
-                vallex.get_tokenized_sentence(tid)
-            )
     # return (n-frames, rendered template)
     # json frames
     json_ret = {"frames": []}
@@ -259,7 +259,7 @@ def prepare_frames(ret_frames):
 
 
 # input: hw, reduct_function
-@app.route("/api/hw-frames")
+@app.route("/api/frames")
 def api_get_frames():
     hw = request.args.get("hw")
     if hw is None:
@@ -267,8 +267,21 @@ def api_get_frames():
 
     rf_name = request.args.get("rf", "reduce_0")  # 2nd is default
     RF = reduce_functions[rf_name]["f"]
-    entry = vallex.entries[hw]  # TODO  hw -> [Frame,]
+
-    ret_frames = RF(entry.raw_frames, vallex)
+    # entry = vallex.entries[hw]  # TODO  hw -> [Frame,]
+    cur = valdb.kres.find({"headwords": hw})
+    frames = []
+    for ent in cur:
+        # TODO: maybe filter by hw?
+        frames += frames_from_db_entry(ent)
+
+    # return json.dumps([x.to_json() for x in frames])
+
+    print("A")
+    print(frames[0].to_json())
+    ret_frames = RF(frames, None)
+    print("B")
+    print(ret_frames[0].to_json())
     return prepare_frames(ret_frames)
 
 
@@ -408,18 +421,22 @@ def prepare_db():
     for corpus in CORPORA:
         for e in valdb[corpus].find({}):
             if e["srl_links"] is None:
-                continue
+                e["headwords"] = []
+                e["functors"] = []
+            else:
                 hw_tids = list(set([x["from"] for x in e["srl_links"]]))
                 hw_tokens = [helper_tid_to_token(tid, e["tokens"]) for tid in hw_tids]
                 headwords = [(t["lemma"] if t["msd"][0] == "G" else t["lemma"] + "_") for t in hw_tokens]
                 e["headwords"] = headwords
 
                 functors = list(set([x["afun"] for x in e["srl_links"]]))
-            e["headwords"] = headwords
                 e["functors"] = functors
 
             valdb[corpus].save(e)
 
+        valdb[corpus].ensure_index([("headwords", pymongo.ASCENDING)])
+        valdb[corpus].ensure_index([("functors", pymongo.ASCENDING)])
+
     # create app_index (used in frontend, left side word index)
     for corpus in CORPORA:
         res_hws = {}

src/pkg/valency/valency/Frame.py

@@ -6,6 +6,8 @@ def frames_from_db_entry(dbent):
     def _full_tid(tid):
         return ".".join([dbent["sid"], str(tid)])
 
+    token_dict = {str(x["tid"]): x for x in dbent["tokens"]}
+
     frames = []
     if "srl_links" not in dbent:
         return []
@@ -18,19 +20,20 @@ def frames_from_db_entry(dbent):
             srldict[key] += [srl]
     for hwtid, srlarr in srldict.items():
         frames += [Frame(
-            hw_lemma=_full_tid(hwtid),
+            hw_lemma=token_dict[hwtid]["text"],
-            tids=[_full_tid(x["to"]) for x in srlarr],
+            tids=[_full_tid(hwtid)],
             slots=[
                 Slot(
                     functor=srl["afun"],
                     tids=[_full_tid(srl["to"])]
                 ) for srl in srlarr
-            ]
+            ],
+            sentences=[dbent["tokens"]],
         )]
     return frames
 
 class Frame():
-    def __init__(self, tids, deep_links=None, slots=None, hw_lemma=None):
+    def __init__(self, tids, deep_links=None, slots=None, hw_lemma=None, sentences=None):
         self.hw = hw_lemma
         self.tids = tids   # list of tokens with the same hw_lemma
         # Each tid = "S123.t123";
@@ -41,7 +44,7 @@ class Frame():
         else:
             self.slots = slots
         self.sense_info = {}
-        self.sentences = None  # Used for passing to view in app.py, get_frames
+        self.sentences = sentences
         self.aggr_sent = None  # Dictionary { hw: self.sentences idx }
 
     def to_json(self):

src/pkg/valency/valency/reduce_functions.py

@@ -56,11 +56,13 @@ def reduce_1(frames, vallex=None):
                 break
         else:
             # Python for else -> fires if loop has ended.
+            # init new frame set [set_of_functors, list_of_one_frame]
             frame_sets.append([functors, [frame]])
 
     ret_frames = []
     for fs in frame_sets:
         tids = []
+        sentences = []
         slots = {}
         # All possible slots in this frame.
         for functor in fs[0]:
@@ -68,12 +70,13 @@ def reduce_1(frames, vallex=None):
         # Reduce slots from all frames. (Merge ACT from all frames, ...)
         for frame in fs[1]:
             tids += frame.tids
+            sentences += frame.sentences
             for sl in frame.slots:
                 slots[sl.functor].tids += sl.tids
         slots_list = []
         for k, e in slots.items():
             slots_list.append(e)
-        rf = Frame(tids=tids, slots=slots_list)
+        rf = Frame(tids=tids, slots=slots_list, sentences=sentences)
         rf.sort_slots()
         ret_frames.append(rf)
     return sorted_by_len_tids(ret_frames)