progress working

1 files changed, 57 insertions, 24 deletions

diff --git a/server.py b/server.py
index 457a8cd..b171c1e 100755
--- a/server.py
+++ b/server.py
@@ -1,9 +1,10 @@
 #!/bin/env  python3
-from flask import Flask, render_template, request, redirect
+from flask import Flask, render_template, request, session, Response
 import tempfile
 import random
 import string
 from ratspub import *
+import time
 
 app=Flask(__name__)
 app.config['SECRET_KEY'] = '#DtfrL98G5t1dC*4'
@@ -12,11 +13,9 @@ app.config['SECRET_KEY'] = '#DtfrL98G5t1dC*4'
 def root():
     return render_template('index.html')
 
-@app.route("/search")
-def search():
-    tf_path=tempfile.gettempdir()
-    tf_name=tf_path+"/tmp"+''.join(random.choice(string.ascii_letters) for x in range(6))
-    all_sentences=str()
+@app.route('/progress')
+def progress():
+    # only 1-6 terms are allowed
     genes=request.args.get('query')
     genes=genes.replace(",", " ")
     genes=genes.replace(";", " ")
@@ -24,30 +23,64 @@ def search():
     if len(genes)>=6:
         message="<span class='text-danger'>Up to five terms can be searched at a time</span>"
         return render_template('index.html', message=message)
-    nodes=default_nodes
-    edges=str()
-    for  gene in genes:
-        nodes+="{ data: { id: '" + gene +  "', nodecolor:'#FADBD8', fontweight:700, url:'https://www.ncbi.nlm.nih.gov/gene/?term="+gene+"'} },\n"
-        sent0=gene_addiction(gene)
-        e0=generate_edges(sent0, tf_name)
-        sent1=gene_functional(gene)
-        e1=generate_edges(sent1, tf_name)
-        sent2=gene_anatomical(gene)
-        e2=generate_edges(sent2, tf_name)
-        edges+=e0+e1+e2
-        all_sentences+=sent0+sent1+sent2
-    #session['tmpfile']={'filename':tf_name}
-    with open(tf_name,"w") as f:
-        f.write(all_sentences)
-        f.close()
-    return render_template('cytoscape.html', elements=nodes+edges)
+    elif len(genes)==0:
+        message="<span class='text-danger'>Please enter a search term </span>"
+        return render_template('index.html', message=message)
+    # put the query in session cookie
+    session['query']=genes
+    # generate a unique session ID to track the results 
+    tf_path=tempfile.gettempdir()
+    session['path']=tf_path+"/tmp" + ''.join(random.choice(string.ascii_letters) for x in range(6))
+    return render_template('progress.html')
+
+@app.route("/search")
+def search():
+    genes=session['query']
+    percent=round(100/(len(genes)*3),1)
+    snt_file=session['path']+"_snt"
+    cysdata=open(session['path']+"_cy","w+")
+    sntdata=open(snt_file,"w+")
+    def generate(genes, tf_name):
+        sentences=str()
+        edges=str()
+        nodes=default_nodes
+        progress=0
+        for  gene in genes:
+            nodes+="{ data: { id: '" + gene +  "', nodecolor:'#FADBD8', fontweight:700, url:'https://www.ncbi.nlm.nih.gov/gene/?term="+gene+"'} },\n"
+            sent0=gene_addiction(gene)
+            progress+=percent
+            yield "data:"+str(progress)+"\n\n"
+            e0=generate_edges(sent0, tf_name)
+            sent1=gene_functional(gene)
+            progress+=percent
+            yield "data:"+str(progress)+"\n\n"
+            e1=generate_edges(sent1, tf_name)
+            sent2=gene_anatomical(gene)
+            progress+=percent
+            e2=generate_edges(sent2, tf_name)
+            edges+=e0+e1+e2
+            sentences+=sent0+sent1+sent2
+            #save data before the last yield
+            if (progress>99):
+                progress=100
+                sntdata.write(sentences)
+                sntdata.close()
+                cysdata.write(nodes+edges)
+                cysdata.close()
+            yield "data:"+str(progress)+"\n\n"
+    return Response(generate(genes, snt_file), mimetype='text/event-stream')
+
+@app.route('/cytoscape')
+def cytoscape():
+    with open(session['path']+"_cy","r") as f:
+        elements=f.read()
+        return render_template('cytoscape.html', elements=elements)
 
 @app.route("/sentences")
 def sentences():
     edge=request.args.get('edgeID')
     (tf_name, gene0, cat0)=edge.split("|")
     out="<h3>"+gene0 + " and " + cat0  + "</h3><hr>\n"
-    print(tf_name)
     with open(tf_name, "r") as df:
         all_sents=df.read()
     for sent in all_sents.split("\n"):