In [1]:

    

import pandas as pd

coverage = pd.read_csv("../dataset/jacoco.csv")[['PACKAGE', 'CLASS', 'LINE_COVERED', 'LINE_MISSED']]
coverage.head()


    

    
Out[1]:







  

    

      

      
PACKAGE
      
CLASS
      
LINE_COVERED
      
LINE_MISSED
    
  
  

    

      
0
      
org.springframework.samples.petclinic
      
PetclinicInitializer
      
24
      
0
    
    

      
1
      
org.springframework.samples.petclinic.model
      
NamedEntity
      
4
      
1
    
    

      
2
      
org.springframework.samples.petclinic.model
      
Specialty
      
1
      
0
    
    

      
3
      
org.springframework.samples.petclinic.model
      
PetType
      
1
      
0
    
    

      
4
      
org.springframework.samples.petclinic.model
      
Vets
      
0
      
4
    
  

In [2]:

    

coverage['lines'] = coverage.LINE_COVERED + coverage.LINE_MISSED
coverage['ratio'] = coverage.LINE_COVERED / coverage.lines
coverage.head()


    

    
Out[2]:







  

    

      

      
PACKAGE
      
CLASS
      
LINE_COVERED
      
LINE_MISSED
      
lines
      
ratio
    
  
  

    

      
0
      
org.springframework.samples.petclinic
      
PetclinicInitializer
      
24
      
0
      
24
      
1.0
    
    

      
1
      
org.springframework.samples.petclinic.model
      
NamedEntity
      
4
      
1
      
5
      
0.8
    
    

      
2
      
org.springframework.samples.petclinic.model
      
Specialty
      
1
      
0
      
1
      
1.0
    
    

      
3
      
org.springframework.samples.petclinic.model
      
PetType
      
1
      
0
      
1
      
1.0
    
    

      
4
      
org.springframework.samples.petclinic.model
      
Vets
      
0
      
4
      
4
      
0.0
    
  

In [3]:

    

%matplotlib inline

coverage.groupby("PACKAGE").mean()['ratio'].plot(kind='barh')


    

    
Out[3]:





<matplotlib.axes._subplots.AxesSubplot at 0x272b6f489e8>






    

In [4]:

    

import py2neo

graph = py2neo.Graph()

query="""
MATCH (t:Type)
RETURN t.fqn LIMIT 10
"""

pd.DataFrame(graph.data(query))


    

    




---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
C:\dev\apps\Anaconda3\lib\site-packages\py2neo\database\__init__.py in __new__(cls, *uris, **settings)
    317         try:
--> 318             inst = cls.__instances[key]
    319         except KeyError:

KeyError: (<class 'py2neo.database.Graph'>, <ServerAddress settings={}>, 'data')

During handling of the above exception, another exception occurred:

ConnectionRefusedError                    Traceback (most recent call last)
C:\dev\apps\Anaconda3\lib\site-packages\py2neo\packages\httpstream\http.py in submit(method, uri, body, headers)
    321         try:
--> 322             response = send()
    323         except BadStatusLine as err:

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\packages\httpstream\http.py in send(reconnect)
    316             log.debug("> %s: %s", key, value)
--> 317         http.request(xstr(method), xstr(uri.absolute_path_reference), body, headers)
    318         return http.getresponse(**getresponse_args)

C:\dev\apps\Anaconda3\lib\http\client.py in request(self, method, url, body, headers, encode_chunked)
   1238         """Send a complete request to the server."""
-> 1239         self._send_request(method, url, body, headers, encode_chunked)
   1240 

C:\dev\apps\Anaconda3\lib\http\client.py in _send_request(self, method, url, body, headers, encode_chunked)
   1284             body = _encode(body, 'body')
-> 1285         self.endheaders(body, encode_chunked=encode_chunked)
   1286 

C:\dev\apps\Anaconda3\lib\http\client.py in endheaders(self, message_body, encode_chunked)
   1233             raise CannotSendHeader()
-> 1234         self._send_output(message_body, encode_chunked=encode_chunked)
   1235 

C:\dev\apps\Anaconda3\lib\http\client.py in _send_output(self, message_body, encode_chunked)
   1025         del self._buffer[:]
-> 1026         self.send(msg)
   1027 

C:\dev\apps\Anaconda3\lib\http\client.py in send(self, data)
    963             if self.auto_open:
--> 964                 self.connect()
    965             else:

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\packages\httpstream\http.py in connect(self)
     79                                              socket_timeout,
---> 80                                              self.source_address)
     81         self.sock.setsockopt(IPPROTO_TCP, TCP_NODELAY, 1)

C:\dev\apps\Anaconda3\lib\socket.py in create_connection(address, timeout, source_address)
    723     if err is not None:
--> 724         raise err
    725     else:

C:\dev\apps\Anaconda3\lib\socket.py in create_connection(address, timeout, source_address)
    712                 sock.bind(source_address)
--> 713             sock.connect(sa)
    714             # Break explicitly a reference cycle

ConnectionRefusedError: [WinError 10061] Es konnte keine Verbindung hergestellt werden, da der Zielcomputer die Verbindung verweigerte

During handling of the above exception, another exception occurred:

SocketError                               Traceback (most recent call last)
<ipython-input-4-92b918cded43> in <module>()
      1 import py2neo
      2 
----> 3 graph = py2neo.Graph()
      4 
      5 query="""

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\database\__init__.py in __new__(cls, *uris, **settings)
    325             use_bolt = address.bolt
    326             if use_bolt is None:
--> 327                 use_bolt = version_tuple(inst.__remote__.get().content["neo4j_version"]) >= (3,)
    328             if use_bolt:
    329                 auth = get_auth(address)

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\database\http.py in get(self, headers, redirect_limit, **kwargs)
    152         kwargs.update(cache=True)
    153         try:
--> 154             response = self.__base.get(headers=headers, redirect_limit=redirect_limit, **kwargs)
    155         except (ClientError, ServerError) as error:
    156             if error.status_code == UNAUTHORIZED:

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\packages\httpstream\http.py in get(self, if_modified_since, headers, redirect_limit, **kwargs)
    964             object from which content can be read
    965         """
--> 966         return self.__get_or_head("GET", if_modified_since, headers, redirect_limit, **kwargs)
    967 
    968     def put(self, body=None, headers=None, **kwargs):

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\packages\httpstream\http.py in __get_or_head(self, method, if_modified_since, headers, redirect_limit, **kwargs)
    941             headers["If-Modified-Since"] = formatdate(datetime_to_timestamp(if_modified_since), usegmt=True)
    942         rq = Request(method, self.uri, None, headers)
--> 943         return rq.submit(redirect_limit=redirect_limit, **kwargs)
    944 
    945     def head(self, if_modified_since=None, headers=None, redirect_limit=5, **kwargs):

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\packages\httpstream\http.py in submit(self, redirect_limit, **response_kwargs)
    431         uri = self.uri
    432         while True:
--> 433             http, rs = submit(self.method, uri, self.body, self.headers)
    434             status_class = rs.status // 100
    435             if status_class == 3:

C:\dev\apps\Anaconda3\lib\site-packages\py2neo\packages\httpstream\http.py in submit(method, uri, body, headers)
    360                                       host_port=uri.host_port)
    361         else:
--> 362             raise SocketError(code, description, host_port=uri.host_port)
    363     else:
    364         return http, response

SocketError: Unknown error

In [5]:

    

coverage['fqn'] = coverage.PACKAGE + "." + coverage.CLASS
coverage[['fqn', 'ratio']].head()


    

    
Out[5]:







  

    

      

      
fqn
      
ratio
    
  
  

    

      
0
      
org.springframework.samples.petclinic.Petclini...
      
1.0
    
    

      
1
      
org.springframework.samples.petclinic.model.Na...
      
0.8
    
    

      
2
      
org.springframework.samples.petclinic.model.Sp...
      
1.0
    
    

      
3
      
org.springframework.samples.petclinic.model.Pe...
      
1.0
    
    

      
4
      
org.springframework.samples.petclinic.model.Vets
      
0.0
    
  

In [6]:

    

query="""
    UNWIND {coverage_data} as coverage
    MATCH (t:Type {fqn : coverage.fqn})
    MERGE (t)-[:HAS_MEASURE]->(m)
    SET 
        m:Measure:Coverage, 
        m.ratio = coverage.ratio
    RETURN t.fqn as fqn, m.ratio as ratio
"""

result = graph.run(query, coverage_data=coverage.to_dict(orient='records')).data()
pd.DataFrame(result).head()


    

    
Out[6]:







  

    

      

      
fqn
      
ratio
    
  
  

    

      
0
      
org.springframework.samples.petclinic.Petclini...
      
1.0
    
    

      
1
      
org.springframework.samples.petclinic.model.Na...
      
0.8
    
    

      
2
      
org.springframework.samples.petclinic.model.Sp...
      
1.0
    
    

      
3
      
org.springframework.samples.petclinic.model.Pe...
      
1.0
    
    

      
4
      
org.springframework.samples.petclinic.model.Vets
      
0.0
    
  

In [7]:

    

query = """
MATCH 
  (t:Type)-[:BELONGS_TO]->(s:Subdomain),
  (t)-[:HAS_CHANGE]->(ch:Change),
  (t)-[:HAS_MEASURE]->(co:Coverage)
OPTIONAL MATCH
  (t)-[:HAS_BUG]->(b:BugInstance)   
RETURN 
  s.name as ASubdomain,
  COUNT(DISTINCT t) as Types,
  COUNT(DISTINCT ch) as Changes,
  AVG(co.ratio) as Coverage,
  COUNT(DISTINCT b) as Bugs
ORDER BY Coverage ASC, Bugs DESC
"""
pd.DataFrame(graph.data(query))


    

    
Out[7]:







  

    

      

      
ASubdomain
      
Bugs
      
Changes
      
Coverage
      
Types
    
  
  

    

      
0
      
Vet
      
0
      
75
      
0.170000
      
5
    
    

      
1
      
Visit
      
0
      
90
      
0.368056
      
6
    
    

      
2
      
Pet
      
1
      
165
      
0.488737
      
11
    
    

      
3
      
Owner
      
3
      
94
      
0.506932
      
4
    
    

      
4
      
crossfunctional
      
2
      
53
      
0.589231
      
5
    
    

      
5
      
Clinic
      
0
      
26
      
0.888889
      
1
    
    

      
6
      
Person
      
0
      
5
      
1.000000
      
1
    
    

      
7
      
Specialty
      
0
      
4
      
1.000000
      
1
    
  

In [8]:

    

query = """
MATCH 
  (t:Type)-[:IS_A]->(ta:TechnicalAspect),
  (t)-[:HAS_CHANGE]->(ch:Change),
  (t)-[:HAS_MEASURE]->(co:Coverage)
OPTIONAL MATCH
  (t)-[:HAS_BUG]->(b:BugInstance)   
RETURN 
  ta.name as ATechnicalAspect,
  COUNT(DISTINCT t) as Types,
  COUNT(DISTINCT ch) as Changes,
  AVG(co.ratio) as Coverage,
  COUNT(DISTINCT b) as Bugs
ORDER BY Coverage ASC, Bugs DESC
"""
pd.DataFrame(graph.data(query))


    

    
Out[8]:







  

    

      

      
ATechnicalAspect
      
Bugs
      
Changes
      
Coverage
      
Types
    
  
  

    

      
0
      
jdbc
      
1
      
152
      
0.000000
      
8
    
    

      
1
      
util
      
2
      
23
      
0.371429
      
2
    
    

      
2
      
web
      
2
      
154
      
0.618818
      
7
    
    

      
3
      
jpa
      
0
      
54
      
0.702501
      
4
    
    

      
4
      
model
      
1
      
91
      
0.731240
      
10
    
    

      
5
      
service
      
0
      
26
      
0.888889
      
1
    
    

      
6
      
petclinic
      
0
      
5
      
1.000000
      
1
    
  

In [ ]: