dockerized the app

Dockerfile

+FROM python:alpine3.8
+COPY . /app
+WORKDIR /app
+RUN apk add --no-cache \
+    g++ \
+    libc-dev \
+    libxml2-dev \
+    libxslt-dev \
+    python3-dev \
+    jpeg-dev \
+    zlib-dev
+RUN pip install -r requirements.txt
+EXPOSE 5000
+CMD [ "flask", "run"]
\ No newline at end of file

app.py

@@ -51,8 +51,8 @@ def display_graphing():
     chart_output = chart_data.pipe(format='svg').decode('utf-8')
     
     # save the graph as svg if required
-    with open('fst1.svg', 'w') as f:
-        f.write(chart_data._repr_svg_())
+    # with open('fst1.svg', 'w') as f:
+    #     f.write(chart_data._repr_svg_())
     
     with open(in_file) as f:
         input_xml = f.read()

docker-compose.yml

+version: '3' 
+services: 
+    web: 
+        build: . 
+        ports: 
+            - "5000:5000"
\ No newline at end of file

parser.py

 import re
-import os
 import bs4
-import pandas as pd
-from typing import Any, Dict, List, Union
+from typing import List
 
 
 class UIMA():
@@ -47,9 +45,9 @@ class UIMA():
             list_of_dicts.append(i.attrs)
             layer.append(i.name)
             
-        df = pd.DataFrame(list_of_dicts, index=None)
-        df["layer"] = layer  
-        return df
+        # df = pd.DataFrame(list_of_dicts, index=None)
+        # df["layer"] = layer  
+        # return df
 
     def get_sofa_string(self):
         return self.soup.find('cas:Sofa').get('sofaString')

requirements.txt

@@ -27,13 +27,10 @@ kiwisolver==1.3.1
 lxml==4.5.2
 MarkupSafe==1.1.1
 marshmallow==3.9.0
-matplotlib==3.4.1
 more-itertools==8.5.0
 networkx==2.5.1
-numpy==1.19.2
 nxpd==0.2.0
 packaging==20.4
-pandas==1.1.2
 parso==0.7.1
 pexpect==4.8.0
 pickleshare==0.7.5

services.py

@@ -2,7 +2,6 @@ import random
 from flask import send_file
 from graphviz import Digraph
 from parser import UIMA
-import numpy as np
 
 
 
@@ -84,12 +83,13 @@ def extract_dependent_tags(file_path):
 
 
 def transpose_by_attribute(file_path, column):
-    base_output = get_initial_data(file_path)
-    df = base_output['df']
-    df[column].replace('', np.nan, inplace=True)
-    dfn = df[df[column].notna()][[column, 'annotated_string']]
-    return {group: list(members_df['annotated_string'])
-              for group, members_df in dfn.groupby(column)}
+    # base_output = get_initial_data(file_path)
+    # df = base_output['df']
+    # df[column].replace('', np.nan, inplace=True)
+    # dfn = df[df[column].notna()][[column, 'annotated_string']]
+    # return {group: list(members_df['annotated_string'])
+    #           for group, members_df in dfn.groupby(column)}
+    return {}
 
 
 def group_strings_by_n(string, N):