Auto Test Py

8/11/2019 Auto Test Py

1/28

Automated ETL Testing

with Py.TestKevin A. Smith

Senior QA Automation Engineer

Cambia Health Solutions


2/28

Agenda Overview

Testing Data Quality

Design for Automation & Testability

Python and Py.Test

Examples

2


3/28

Database Applications Taking data out of an OnLine Transaction Processing

(OLTP) system and putting into an OnLine Analytical

Processing (OLAP) system involves Extracting the data,

Transforming the data and then Loading that data intoanother database (ETL)

When Testing an ETL Application:

Extract

Transform

Compare

3


4/28

Cambia EVR Application

4


5/28

Testing Data Quality Data Completeness

Ensures that all expected data is loaded.

Data Integrity Ensures that the ETL application rejects, substitutes default values

or corrects and reports invalid data.

Data Transformation

Ensures that all data is transformed correctly according to businessrules and/or design specifications.

5


6/28

Testing Techniques Stare & Compare

Validate data

transformations

manually.

This step is usually

required to bootstrap

an ETL test automationproject

6


7/28

Testing Techniques Golden FilesUse well-known test

data and golden file

comparison as a

testing oracle.

This technique is very

powerful for automatedtesting of printedoutput.

7


8/28

Testing Techniques Self-VerifyingOracle in Test Scripts

model.

Necessary if you want

to test any aspects of

the ETL application

running in production.

8


9/28

Design for Automation Control

How well the application can be controlled from the test tools.

Visibility How well are intermediate data and results visible to the test tools.

9


10/28

Design for Testability - Visibility

10


11/28

Test Tools - Rules of Thumb1. Do not re-invent the wheel.

2. No test tool will do everything you need - customize

3.

No one test tool will solve all of your test problems tool

box.4. Do not expect your business experts or developers to

be able to create great tests, even with tools.

5.

Do not use one-off technology for testing.

6.

Do not use the built-in test module to your ETLdevelopment tool.

11


12/28

Tool Requirements Support Customization

Support Source to Target Data Mapping

Support Complex Logical Calculations

Support database connections

Support CSV and XML

Existing Tool

Customizable

Leverage Existing Knowledge Multi-OS (AIX, Windows)

12


13/28

Python and Py.Test Support Oracle and Sybase databases with 3rdparty

libraries:

PyODBC, cx_Oracle

Native support for CSV files and XML

Strong support for containers (Tuple, List, Dict)

Easy learning curve for non-programmers

13


14/28

What is Py.Test? Searches Disk for Tests

Sequences and Executes Tests

Captures Output Captures Exceptions

Reports Results

Interfaces to Extend/Customize Behavior Command Line Processing

Test Search/Sequencing/Selecting

Test Handling (Fixtures)

Reporting

14


15/28

Database Supportconn = cx_Oracle.connection(user_name,

password,

server_name)

crsr = conn.cursor()

query_string =

crsr.execute(query_string)

for row in crsr.fetchall():

key = str(row[0]) + _ + str(row[1])

results[key] = {source : row,

target : (Missing,)}

15


16/28

CSV File Support

import csv

csv_data = csv.reader(open(data.csv,

newline=),

delimiter=|)

for row in csv_data():


results[key] = {source : row,

target : (Missing,)}

16


17/28

Row Comparison

for value in results.values():

assert value[source] == value[target]

17


18/28

Test Patterns

Database Schema

Row Counting

Simple Source to Target Mapping

Complex Source to Target Mapping

18


19/28

Database Schematable_names = ('OUTPUT_CD_TRNSLTN', 'OUTPUT_DRAG_DT',

'OUTPUT_NTWK', 'OUTPUT_PH_NUM')

def test_dev_schema():

"""

Test the development database."""

schemas = []

crsr = Database.get_cursor('DEV')

for table in table_names:

schemas.append(get_table_dict(crsr,'dev', table, out_dir, base_dir))

crsr.close()

generic_schema_compare(schemas, 'Development')

19


20/28

Database Schema (contd)

def generic_schema_compare(results, title):

"""

Generic table comparison test.

"""

test_rslt = True

for schema in results:

if schema[source'] != schema[target']:

schema[source'].show_diffs(schema[target'])

test_rslt = False

assert test_rslt, title + ' schema differences'

20


21/28

Row Counting

crsr.execute("""

Select count(*)

From FEP_PMT.FEP_CLM

Where FDS_BAT_ID = :arg_1 and

DISP_CD in ('1','2','9') andAMT_PAID < 0""",

arg_1 = fds_bat_id)

for row in crsr.fetchall():

passactual = row[0]

assert actual == 0, 'Negative claims found,invalid incoming data'

21


22/28

Complex Source to Targetfor key, val in get_claim_lines.items():

expected_contract_adj_amt = 0

# calculate the expected contractual adjustment amount

# walk the fields by field name

for i in range(1,6):

# calculate the base name of this hag "row"

hag_base_name = 'HAG'+ str(i) + '_ADJ_'

if [hag_base_name + 'CDE'] == 'CO':

if(val[hag_base_name + 'RSN1'] != '23' and

val[hag_base_name + 'RSN1'] != '171'):

expected_contract_adj_amt += val[hag_base_name + 'AMT1']

if(val[hag_base_name + 'RSN2'] != '23' and

val[hag_base_name + 'RSN2'] != '171'):

expected_contract_adj_amt += val[hag_base_name + 'AMT2']

# now compare the calculation to the amount retrieved from the tableif round(val['CNTRCTL_ADJSTMT_AMT'], 4) != round(expected_contract_adj_amt, 4) :

print('Claim_trans_disp_line: ' + key + ' did not calculate correctly.')

print('actual:', round(val['CNTRCTL_ADJSTMT_AMT'], 4),

'Expected:', round(expected_contract_adj_amt, 4))

print()

test_result = False

assert test_result, 'Incorrect contractual adjustment calculations'

22


23/28

In-memory Data Representation


results = {} # create a dict to hold in-memory

# tables of source and target data

results = {key 1 : {source : row,

target : row},

key 2 : {source : row,

target : row,

source 1 : row,

source 2 : row},key 3 : {source : row,

target : (Missing,)},

key 4 : {source : (Added,),

target : row}}

23


24/28

Customized Test Output

24


25/28

Customizations

Shared Database Connection Pool Database connection parameters, including obfuscated login

information

INI-file Processing

File directories for XML, CSV, baseline and output logging files.

Default values for command line options, such as logical databasename mapping

Command Line Option Processing Batch ID

Database Names Standard Test Routines

Source to Target Mapping

Database Schema Testing

25


26/28

Team

James Bass UTi

William Buse Cambia Health Solutions

Matthew Pierce Cambia Health Solutions

Venkatesh Marada Cambia Health Solutions Kanthi Kondreddi Cambia Health Solutions

Bhargavi Kanakamedala Cambia Health Solutions

Tim Rilling Cambia Health Solutions

Gordon Krenn Cambia Health Solutions Tim Peterson Cambia Health Solutions

26


27/28

Upcoming Work

Detailed XML File Tests

Test Results Load Directly to Rally.

Golden-file Comparison with Definable Filtering

Golden File Comparison for PostScript

27


28/28

References

Python

http://www.python.org/

http://en.wikipedia.org/wiki/Python_(programming_language)

Py.Test http://www.pytest.org/

Oracle Python Library

http://cx-oracle.sourceforge.net/html/

Python ODBC Library

https://code.google.com/p/pyodbc/

Companion paper

http://tinyurl.com/kofo3rv/

28

Date post:	03-Jun-2018
Category:	Documents
Upload:	shravan-kumar
View:	221 times
Download:	0 times

Auto Test Py

Documents