statistics.py: write dataset information into a database

import argparse

import argparse

import json

import json

import re

import re

import os

import psycopg2

from psycopg2 import sql

# http://initd.org/psycopg/docs/sql.html#module-psycopg2.sql

def store_result(table_name, values_dict):

  # Connect to database.

  db = psycopg2.connect("service=ted-join")

  # Open a cursor to perform database operations

  cur = db.cursor()

  attributes = values_dict.keys()

  query = sql.SQL("INSERT INTO {} ({}) VALUES ({})").format(

      sql.Identifier(table_name),

      sql.SQL(', ').join(map(sql.Identifier, attributes)),

      sql.SQL(', ').join(map(sql.Placeholder, attributes))

  )

  print(query.as_string(cur))

  cur.execute(query, values_dict)

  db.commit()

  # Close the cursor.

  cur.close()

  # Close communication with the database.

  db.close()

# parse input argurments

# parse input argurments

parser = argparse.ArgumentParser()

parser = argparse.ArgumentParser()

parser.add_argument("--inputfile", type=str, 

parser.add_argument("--inputfile", type=str, 

  help="path to input files containing line seperated trees in bracket notation")

  help="path to input files containing line seperated trees in bracket notation")

parser.add_argument("--shortdesc", type=str, default="no description",

  help="short description about the dataset")

parser.add_argument("--printlabels", action='store_true', dest='printlabels', 

parser.add_argument("--printlabels", action='store_true', dest='printlabels', 

  help="print label distribution")

  help="print label distribution")

parser.add_argument("--storeindb", action='store_true', dest='storeindb', 

  help="store the information about the dataset in a database")

args = parser.parse_args()

args = parser.parse_args()

db_table_name = "dataset" # name of the table in the database

short_description = args.shortdesc

path, filename = os.path.split(args.inputfile)

labels = {} # dict that holds a counter for each node label

labels = {} # dict that holds a counter for each node label

number_of_trees = 0

number_of_trees = 0

sum_of_tree_sizes = 0

sum_of_tree_sizes = 0

      labels[label] = labels.get(label, 0) + 1

      labels[label] = labels.get(label, 0) + 1

# create json that holds all information about the dataset

dataset_info = "{"

dataset_info += "\"filename\": \"" + str(filename) + "\""

dataset_info += ", \"short_description\": \"" + str(short_description) + "\""

dataset_info += ", \"number_of_trees\": " + str(number_of_trees)

dataset_info += ", \"avg_tree_size\": " + str(sum_of_tree_sizes/number_of_trees)

dataset_info += ", \"min_tree_size\": " + str(min_tree_size)

dataset_info += ", \"max_tree_size\": " + str(max_tree_size)

dataset_info += ", \"different_label\": " + str(len(labels))

dataset_info += "}"

# print result to stdout

# print result to stdout

print("{\"number_of_trees\": " + str(number_of_trees), end='')

print(dataset_info)

print(", \"avg_tree_size\": " + str(sum_of_tree_sizes/number_of_trees), end='')

print(", \"min_tree_size\": " + str(min_tree_size), end='')

# store dataset in db

print(", \"max_tree_size\": " + str(max_tree_size), end='')

if args.storeindb:

print(", \"different_label\": " + str(len(labels)), end='')

  store_result(db_table_name, dataset_info)

# print label distribution

if args.printlabels:

if args.printlabels:

  print(", ")

  print(" ")

  print("\"labels\": ", end='')

  print("\"labels\": ", end='')

  print(str(labels).replace("\'", "\""))

  print(str(labels).replace("\'", "\""))

print("}")

 No newline at end of file