insights.py 1.0

Index

• Installation

• Web Data

• SQLite Database

• Statistics

• Trade Application

• Support

• Contribute

• License

Installation

Download and unzip the package then run the following command:

python setup.py install

Web Data

WebData class for reading data returned from URL, and parsing JSON to dictionary object.

import insights
data = insights.webdata.WebData("http://www.json-generator.com/api/json/get/bMUULAzmaa?indent=2")
print(data.parseJson())

SQLite Database

Database class acts like a wrapper SQLite. It provides variety of methods that hides complexity.

import insights
db = insights.database.Database()
d = dict(
         id     = dict(type='INTEGER', auto = True, primary = True),
         name   = dict(type='TEXT', not_null = True),
         age    = dict(type='INT')
    )

# create table
db.create('users', d)

# insert rows
db.insert('users', dict(name = 'omar', age = 22))
db.insert('users', dict(name = 'alex', age = 23))
db.insert('users', dict(name = 'peter', age = 21))

# last inserted id
print(db.lastInsertedId())

# print users
db.getAll('users').printResult()
db.getById('users', '1').printResult()

# counting
print(db.count('users', dict(age='22')))
print(db.countAll('users'))

# delete
db.deleteById('users', '2')

# update
db.updateById('users', dict(name='ALEX', age = 25), 2)

# number of affected rows by last query
print(db.rowsAffected())

# close connection
db.close()

Statistics

Stats class for performing some simple statistics on a list of values.

import insights
lst     = [6, 3 , 11 , 16 , 8 , 6 , 15 , 7]
Stats   = insights.stats.Stats

print("Average\t", Stats.average(lst))
print("MD\t", Stats.meanDeviation(lst))
print("Count 7\t", Stats.count(lst, 7))
print("Length\t", Stats.length(lst))
print("Max\t", Stats.max(lst))
print("Min\t", Stats.min(lst))
print("Range\t", Stats.range(lst))
print("Sum\t", Stats.sum(lst))
print("Sort\t", Stats.sort(lst))
print("Variance", Stats.variance(lst))
print("SD\t", Stats.standardDeviation(lst))
print("Median\t", Stats.median(lst))

Trade Application

Trade class is an application that uses insights package to retrieve data about Exports & Imports grouped by Commodity.

It fetches the data(JSON string) from URL, saves it to SQLite database, and perform some statistics.

The generated table will look like(doesn’t include all data, nor all statistics):

========  =======  =======  =======  =======
Date      E::Oil   I::Oil   E::Tea   I::Tea
========  =======  =======  =======  =======
2013      12006.2  12495.7  14.0     239.4
2012      11225.0  11774.5  12.7     180.1
........  .......  .......  .......  .......
average   10064.2  2183.83  7.72     151.14
variance  9037043  1077840  22.89    2585.42
SD        3006.17  3283.05  4.78     50.85
max       14472.6  12495.7  14.7     239.4
min       3910.3   2549.7   2.0      88.1
========  =======  =======  =======  =======

NOTE Trade application is inside app/ folder.

Support

I’ve written this package in my free time during my studies. If you find it useful, please support the project by spreading the word.

Contribute

Contribute by creating new issues, sending pull requests on Github or you can send an email at: omar.elgabry.93@gmail.com

License

Built under MIT license.