pyodbc-unittest

pyodbc-unittest

The library provides SQL calls for the Python unittest framework

Unit Test

Unit tests are typically automated tests written and run by software developers to ensure that a section of an application (known as the "unit") meets its design and behaves as intended.

Database Unit Test

The SQL unit testing approach allows us to test part of database objects such as stored procedures, functions and schema. The advantage of SQL unit testing is to develop more robust database designs, because these objects have already been checked before production deployment, so SQL unit testing process allows us to minimize the errors, which are related to database objects.

Quick Start

Install pyodbc-unittest from pypi using pip

pip install pyodbc-unittest

Import Dbtest object in your module

import unittest
from pyodbc_unittest import Dbtest

Now you need to setup ODBC data source. Select the type of database you want to set up a database for, for example, SAP/Sybase ASE, MS SQL Server, PostgreSQL, etc. Moreover, fill the login, password and server fields.

Write your first test like in the example. Please fill in CONNECTION_STRING with the name of the ODBC data source.

CONNECTION_STRING = r'DSN=mssql.local'

class TestSelect(unittest.TestCase):

    def test_data(self):
        database = Dbtest(CONNECTION_STRING)
        sql = 'SELECT 1 AS ONE'
        file_name = 'SELECTONE'
        self.assertEqual(database.from_db(sql, file_name),
                         database.from_file(file_name))
        database.close()

And run unittest

> python -m unittest
.
----------------------------------------------------------------------
Ran 1 test in 0.112s

OK

An artifact named SELECTONE.json was created that contains all the information about the result set.

{
  "rowcount": 1,
  "resultcount": 1,
  "error": 0,
  "errormessage": "",
  "names": "[[\"one\"]]",
  "types": "[[\"int\"]]",
  "sizes": "[[10]]",
  "datas": [
    "{\"columns\":[\"one\"],\"index\":[0],\"data\":[[\"1\"]]}"
  ]
}

You can directly dive into the examples at tests/.

This example uses two main functions:

• Dbtest.db.from_db loads data from a DB and returns a string for comparison.
• Dbtest.db.from_file loads data from a file and returns a string for comparison.

Now we can change something in select. Digit or name.

        sql = 'SELECT 2 AS ONE'

And, if we run unittest again, it will be a failed.

> python -m unittest
F
======================================================================
FAIL: test_data (test_pyodbc_unittest.TestSelect)
Create SQLVERSION.json.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\Users\yashi\Projects\pyodbc-unittest\tests\test_pyodbc_unittest.py", line 17, in test_data
    self.assertEqual(database.from_db(sql, file_name),
AssertionError: 'ROWS[96 chars][0] = [\'int\']\nDATA[0] = {\n  "one":{\n    "0":"2"\n  }\n}\n' != 'ROWS[96 chars][0] = [\'int\']\nDATA[0] = {\n  "one":{\n    "0":"1"\n  }\n}\n'
  ROWS_OUNT = 1
  RESULT_COUNT = 1
  SQLCODE = 0
  MESSAGE =
  COLUMN_NAMES[0] = ['one']
  COLUMNN_TYPES[0] = ['int']
  DATA[0] = {
    "one":{
-     "0":"2"
?          ^
+     "0":"1"
?          ^
    }
  }


----------------------------------------------------------------------
Ran 1 test in 0.127s

FAILED (failures=1)

To be continued...