#!/usr/bin/env python3

"""
Copyright Google Inc. 2016
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""

import apache_beam as beam
import argparse

def startsWith(line, term):
   if line.startswith(term):
      yield line

def splitPackageName(packageName):
   """e.g. given com.example.appname.library.widgetname
           returns com
	           com.example
                   com.example.appname
      etc.
   """
   result = []
   end = packageName.find('.')
   while end > 0:
      result.append(packageName[0:end])
      end = packageName.find('.', end+1)
   result.append(packageName)
   return result

def getPackages(line, keyword):
   start = line.find(keyword) + len(keyword)
   end = line.find(';', start)
   if start < end:
      packageName = line[start:end].strip()
      return splitPackageName(packageName)
   return []

def packageUse(line, keyword):
   packages = getPackages(line, keyword)
   for p in packages:
      yield (p, 1)

if __name__ == '__main__':
   parser = argparse.ArgumentParser(description='Find the most used Java packages')
   parser.add_argument('--output_prefix', default='/tmp/output', help='Output prefix')
   parser.add_argument('--input', default='../javahelp/src/main/java/com/google/cloud/training/dataanalyst/javahelp/', help='Input directory')

   options, pipeline_args = parser.parse_known_args()
   p = beam.Pipeline(argv=pipeline_args)

   input = '{0}*.java'.format(options.input)
   output_prefix = options.output_prefix
   keyword = 'import'

   # find most used packages
   (p
      | 'GetJava' >> beam.io.ReadFromText(input)
      | 'GetImports' >> beam.FlatMap(lambda line: startsWith(line, keyword))
      | 'PackageUse' >> beam.FlatMap(lambda line: packageUse(line, keyword))
      | 'TotalUse' >> beam.CombinePerKey(sum)
      | 'Top_5' >> beam.transforms.combiners.Top.Of(5, key=lambda kv: kv[1])
      | 'write' >> beam.io.WriteToText(output_prefix)
   )

   p.run().wait_until_finish()