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A library for Data-Driven Testing.

Project description



robotframework-datadriver

DataDriver is a Data-Driven Testing library for Robot Framework. This document explains how to use the DataDriver library listener. For information about installation, support, and more, please visit the project page

For more information about Robot Framework, see http://robotframework.org.

DataDriver is used/imported as Library but does not provide keywords which can be used in a test. DataDriver uses the Listener Interface Version 3 to manipulate the test cases and creates new test cases based on a Data-File that contains the data for Data-Driven Testing. These data file may be .csv , .xls or .xlsx files.

Data Driver is also able to cooperate with Microsoft PICT. An Open Source Windows tool for data combination testing. Pict is able to generate data combinations based on textual model definitions. https://github.com/Microsoft/pict


Installation

If you already have Python >= 3.6 with pip installed, you can simply run:

pip install --upgrade robotframework-datadriver


Excel Support

For file support of xls or xlsx file you need to install the extra XLS or the dependencies. It contains the dependencies of pandas, numpy and xlrd. Just add [XLS] to your installation. New since version 3.6.

pip install --upgrade robotframework-datadriver[XLS]


Python 2

or if you have Python 2 and 3 installed in parallel you may use

pip3 install --upgrade robotframework-datadriver

DataDriver in compatible with Python 2.7 only in Version 0.2.7.

pip install --upgrade robotframework-datadriver==0.2.7

Because Python 2.7 is deprecated, there are no new feature to python 2.7 compatible version.


What DataDriver does

DataDriver is an alternative approach to create Data-Driven Tests with Robot Framework. DataDriver creates multiple test cases based on a test template and data content of a csv or Excel file. All created tests share the same test sequence (keywords) and differ in the test data. Because these tests are created on runtime only the template has to be specified within the robot test specification and the used data are specified in an external data file.

DataDriver gives an alternative to the build in data driven approach like:

*** Settings ***
Resource    login_resources.robot

Suite Setup    Open my Browser
Suite Teardown    Close Browsers
Test Setup      Open Login Page
Test Template    Invalid login


*** Test Cases ***       User        Passwort
Right user empty pass    demo        ${EMPTY}
Right user wrong pass    demo        FooBar

Empty user right pass    ${EMPTY}    mode
Empty user empty pass    ${EMPTY}    ${EMPTY}
Empty user wrong pass    ${EMPTY}    FooBar

Wrong user right pass    FooBar      mode
Wrong user empty pass    FooBar      ${EMPTY}
Wrong user wrong pass    FooBar      FooBar

*** Keywords ***
Invalid login
    [Arguments]    ${username}    ${password}
    Input username    ${username}
    Input pwd    ${password}
    click login button
    Error page should be visible

This inbuild approach is fine for a hand full of data and a hand full of test cases. If you have generated or calculated data and specially if you have a variable amount of test case / combinations these robot files becom quite a pain. With datadriver you may write the same test case syntax but only once and deliver the data from en external data file.

One of the rare reasons when Microsoft® Excel or LibreOffice Calc may be used in testing… ;-)

See example test suite

See example csv table


How DataDriver works

When the DataDriver is used in a test suite it will be activated before the test suite starts. It uses the Listener Interface Version 3 of Robot Framework to read and modify the test specification objects. After activation it searches for the Test Template -Keyword to analyze the [Arguments] it has. As a second step, it loads the data from the specified CSV file. Based on the Test Template -Keyword, DataDriver creates as much test cases as lines are in the CSV file. As values for the arguments of the Test Template -Keyword it reads values from the column of the CSV file with the matching name of the [Arguments]. For each line of the CSV data table, one test case will be created. It is also possible to specify test case names, tags and documentation for each test case in the specific test suite related CSV file.


Usage

Data Driver is a “Listener” but should not be set as a global listener as command line option of robot. Because Data Driver is a listener and a library at the same time it sets itself as a listener when this library is imported into a test suite.

To use it, just use it as Library in your suite. You may use the first argument (option) which may set the file name or path to the data file.

Without any options set, it loads a .csv file which has the same name and path like the test suite .robot .

Example:

*** Settings ***
Library    DataDriver

Options

*** Settings ***
Library    DataDriver
...    file=${None}
...    encoding=cp1252
...    dialect=Excel-EU
...    delimiter=;
...    quotechar="
...    escapechar=\\\\
...    doublequote=True
...    skipinitialspace=False
...    lineterminator=\\r\\n
...    sheet_name=0
...    reader_class=${None}
...    file_search_strategy=PATH
...    file_regex=(?i)(.*?)(\\.csv)
...    include=${None}
...    exclude=${None}

Encoding

encoding must be set if it shall not be cp1252.

cp1252 is:

  • Code Page 1252
  • Windows-1252
  • Windows Western European

Most characters are same between ISO-8859-1 (Latin-1) except for the code points 128-159 (0x80-0x9F). These Characters are available in cp1252 which are not present in Latin-1.

€ ‚ ƒ „ … † ‡ ˆ ‰ Š ‹ Œ Ž ‘ ’ “ ” • – — ˜ ™ š › œ ž Ÿ

See Python Standard Encoding for more encodings


Example Excel (US / comma seperated)

Dialect Defaults:

delimiter = ','
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\\r\\n'
quoting = QUOTE_MINIMAL

Usage in Robot Framework

*** Settings ***
Library    DataDriver    my_data_file.csv    dialect=excel    encoding=${None}

Example Excel Tab (\t seperated)

Dialect Defaults:

delimiter = '\\t'
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\\r\\n'
quoting = QUOTE_MINIMAL

Usage in Robot Framework

*** Settings ***
Library    DataDriver    my_data_file.csv    dialect=excel_tab

Example Unix Dialect

Dialect Defaults:

delimiter = ','
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\\n'
quoting = QUOTE_ALL

Usage in Robot Framework

*** Settings ***
Library    DataDriver    my_data_file.csv    dialect=unix_dialect

Example User Defined

User may define the format completely free. If an option is not set, the default values are used. To register a userdefined format user have to set the option dialect to UserDefined

Usage in Robot Framework

*** Settings ***
Library    DataDriver    my_data_file.csv
...    dialect=UserDefined
...    delimiter=.
...    lineterminator=\\n

Limitation


Eclipse plug-in RED

There are known issues if the Eclipse plug-in RED is used. Because the debugging Listener of this tool pre-calculates the number of test cases before the creation of test cases by the Data Driver. This leads to the situation that the RED listener throws exceptions because it is called for each test step but the RED GUI already stopped debugging so that the listener cannot send Information to the GUI. This does not influence the execution in any way but produces a lot of unwanted exceptions in the Log.


Variable types

In this early Version of DataDriver, only scalar variables are supported. Lists and dictionaries may be added in the next releases.


MS Excel and typed cells

Microsoft Excel xls or xlsx file have the possibility to type thair data cells. Numbers are typically of the type float. If these data are not explicitly defined as text in Excel, pandas will read it as the type that is has in excel. Because we have to work with strings in Robot Framework these data are converted to string. This leads to the situation that a European time value like “04.02.2019” (4th January 2019) is handed over to Robot Framework in Iso time “2019-01-04 00:00:00”. This may cause unwanted behavior. To mitigate this risk you should define Excel based files explicitly as text within Excel.


How to activate the Data Driver

To activate the DataDriver for a test suite (one specific *.robot file) just import it as a library. You may also specify some options if the default parameters do not fit your needs.

Example:

*** Settings ***
Library          DataDriver
Test Template    Invalid Logins

Structure of test suite


Requirements

In the Moment there are some requirements how a test suite must be structured so that the DataDriver can get all the information it needs.

  • only the first test case will be used as a template. All other test cases will be deleted.
  • Test cases have to be defined with a Test Template. Reason for this is, that the DataDriver needs to know the names of the test case arguments. Test cases do not have named arguments. Keywords do.
  • The keyword which is used as Test Template must be defined within the test suite (in the same *.robot file). If the keyword which is used as Test Template is defined in a Resource the DataDriver has no access to its arguments names.

Example Test Suite

***Settings***
Library           DataDriver
Resource          login_resources.robot
Suite Setup       Open my Browser
Suite Teardown    Close Browsers
Test Setup        Open Login Page
Test Template     Invalid Login

*** Test Case ***
Login with user ${username} and password ${password}    Default    UserData

***** *Keywords* *****
Invalid login
    [Arguments]    ${username}    ${password}
    Input username    ${username}
    Input pwd    ${password}
    click login button
    Error page should be visible

In this example, the DataDriver is activated by using it as a Library. It is used with default settings. As Test Template the keyword Invalid Login is used. This keyword has two arguments. Argument names are ${username} and ${password}. These names have to be in the CSV file as column header. The test case has two variable names included in its name, which does not have any functionality in Robot Framework. However, the Data Driver will use the test case name as a template name and replaces the variables with the specific value of the single generated test case. This template test will only be used as a template. The specified data Default and UserData would only be used if no CSV file has been found.


Structure of data file


min. required columns

  • *** Test Cases *** column has to be the first one.
  • Argument columns: For each argument of the Test Template keyword one column must be existing in the data file as data source. The name of this column must match the variable name and syntax.

optional columns

  • [Tags] column may be used to add specific tags to a test case. Tags may be comma separated.
  • [Documentation] column may be used to add specific test case documentation.

Example Data file

*** Test Cases *** ${username} ${password} [Tags] [Documentat ion]
Right user empty pass demo ${EMPTY} 1 This is a test case documentati on of the first one.
Right user wrong pass demo FooBar 2  
empty user mode pass ${EMPTY} mode 1,2,3,4 This test case has the Tags 1,2,3 and 4 assigned.
  ${EMPTY} ${EMPTY}   This test case has a generated name based on template name.
  ${EMPTY} FooBar   This test case has a generated name based on template name.
  FooBar mode   This test case has a generated name based on template name.
  FooBar ${EMPTY}   This test case has a generated name based on template name.
  FooBar FooBar   This test case has a generated name based on template name.

In this data file, eight test cases are defined. Each line specifies one test case. The first two test cases have specific names. The other six test cases will generate names based on template test cases name with the replacement of variables in this name. The order of columns is irrelevant except the first column, *** Test Cases ***


Data Sources


CSV / TSV (Character-separated values)

By default DataDriver reads csv files. With the Encoding and CSV Dialect settings you may configure which structure your data source has.


XLS / XLSX Files

If you want to use Excel based data sources, you may just set the file to the extention or you may point to the correct file. If the extention is “.xls” or “.xlsx” DataDriver will interpret it as Excel file. You may select the sheet which will be read by the option sheet_name. By default it is set to 0 which will be the first table sheet. You may use sheet index (0 is first sheet) or sheet name(case sensitive). XLS interpreter will ignore all other options like encoding, delimiters etc.

*** Settings ***
Library    DataDriver    .xlsx

or:

*** Settings ***
Library    DataDriver    file=my_data_source.xlsx    sheet_name=2nd Sheet

PICT (Pairwise Independent Combinatorial Testing)

Pict is able to generate data files based on a model file. https://github.com/Microsoft/pict

Documentation: https://github.com/Microsoft/pict/blob/master/doc/pict.md


Requirements
  • Path to pict.exe must be set in the %PATH% environment variable.
  • Data model file has the file extention “.pict”
  • Pict model file must be encoded in UTF-8

How it works

If the file option is set to a file with the extention pict, DataDriver will hand over this file to pict.exe and let it automatically generates a file with the extention “.pictout”. This file will the be used as data source for the test generation. (It is tab seperated and UTF-8 encoded) Except the file option all other options of the library will be ignored.

*** Settings ***
Library    DataDriver    my_model_file.pict

File Encoding and CSV Dialect

CSV is far away from well designed and has absolutely no “common” format. Therefore it is possible to define your own dialect or use predefined. The default is Excel-EU which is a semicolon separated file. These Settings are changeable as options of the Data Driver Library.


file=

*** Settings ***
Library         DataDriver    file=../data/my_data_source.csv
  • None(default): Data Driver will search in the test suites folder if a *.csv file with the same name than the test suite *.robot file exists
  • only file extention: if you just set a file extentions like “.xls” or “.xlsx” DataDriver will search
  • absolute path: If an absolute path to a file is set, DataDriver tries to find and open the given data file.
  • relative path: If the option does not point to a data file as an absolute path, Data Driver tries to find a data file relative to the folder where the test suite is located.

encoding=

may set the encoding of the CSV file. i.e. cp1252, ascii, iso-8859-1, latin-1, utf_8, utf_16, utf_16_be, utf_16_le, etc… https://docs.python.org/3.7/library/codecs.html#standard-encodings


dialect=

You may change the CSV Dialect here. If the Dialect is set to ‘UserDefined’ the following options are used. Otherwise, they are ignored. supported Dialects are:

"excel"
    delimiter = ','
    quotechar = '"'
    doublequote = True
    skipinitialspace = False
    lineterminator = '\\r\\n'
    quoting = QUOTE_MINIMAL

"excel-tab"
    delimiter = '\\t'

"unix"
    delimiter = ','
    quotechar = '"'
    doublequote = True
    skipinitialspace = False
    lineterminator = '\\n'
    quoting = QUOTE_ALL

Defaults:

file=None,
encoding='cp1252',
dialect='Excel-EU',
delimiter=';',
quotechar='"',
escapechar='\\\\',
doublequote=True,
skipinitialspace=False,
lineterminator='\\r\\n',
sheet_name=0

Custom DataReader Classes

It is possible to write your own DataReader Class as a plugin for DataDriver. DataReader Classes are called from DataDriver to return a list of TestCaseData.


Using Custom DataReader

DataReader classes are loaded dynamically into DataDriver while runtime. DataDriver identifies the DataReader to load by the file extantion of the data file or by the option reader_class.


Select Reader by File Extension:
*** Settings ***
Library    DataDriver    file=mydata.csv

This will load the class csv_reader from csv_reader.py from the same folder.


Select Reader by Option:
*** Settings ***
    Library    DataDriver   file=mydata.csv    reader_class=generic_csv_reader    dialect=userdefined   delimiter=\\t    encoding=UTF-8

This will load the class generic_csv_reader from generic_csv_reader.py from same folder.


Create Custom Reader

Recommendation:

Have a look to the Source Code of existing DataReader like csv_reader.py or generic_csv_reader.py .

To write your own reader, create a class inherited from AbstractReaderClass.

Your class will get all available configs from DataDriver as an object of ReaderConfig on __init__.

DataDriver will call the method get_data_from_source This method should then load your data from your custom source and stores them into list of object of TestCaseData. This List of TestCaseData will be returned to DataDriver.

AbstractReaderClass has also some optional helper methods that may be useful.

You can either place the custom reader with the others in DataDriver folder or anywhere on the disk. In the first case or if your custom reader is in python path just use it like the others by name:

*** Settings ***
Library          DataDriver    reader_class=my_reader

In case it is somewhere on the disk, it is possible to use an absolute or relative path to a custom Reader. Imports of custom readers follow the same rules like importing Robot Framework libraries. Path can be relative to ${EXECDIR} or to DataDriver/__init__.py:

*** Settings ***
Library          DataDriver    reader_class=C:/data/my_reader.py    # set custom reader
...                            file_search_strategy=None            # set DataDriver to not check file
...                            min=0                                # kwargs arguments for custom reader
...                            max=62

This my_reader.py should implement a class inherited from AbstractReaderClass that is named my_reader.

from DataDriver.AbstractReaderClass import AbstractReaderClass  # inherit class from AbstractReaderClass
from DataDriver.ReaderConfig import TestCaseData  # return list of TestCaseData to DataDriver


class my_reader(AbstractReaderClass):

    def get_data_from_source(self):  # This method will be called from DataDriver to get the TestCaseData list.
        test_data = []
        for i in range(int(self.kwargs['min']), int(self.kwargs['max'])):  # Dummy code to just generate some data
            args = {'${var_1}': str(i), '${var_2}': str(i)}  # args is a dictionary. Variable name is the key, value is value.
            test_data.append(TestCaseData(f'test {i}', args, ['tag']))  # add a TestCaseData object to the list of tests.
        return test_data  # return the list of TestCaseData to DataDriver

See other readers as example.


Selection of Test Cases to execute

Because test cases that are created by DataDriver after parsing while execution, it is not possible to use some Robot Framework methods to select test cases.

Examples for options that have to be used differently:

robot option Description
--test Selects the test cases by name.
--task Alias for –test that can be used when executing tasks.
--rerunfailed Selects failed tests from an earlier output file to be re-executed.
--include Selects the test cases by tag.
--exclude Selects the test cases by tag.

Selection of test cases by name


Select a single test case:

To execute just a single test case by its exact name it is possible to execute the test suite and set the global variable ${DYNAMICTEST} with the name of the test case to execute as value. Pattern must be suitename.testcasename.

Example:

robot --variable "DYNAMICTEST:my suite name.test case to be executed" my_suite_name.robot

Pabot uses this feature to execute a single test case when using --testlevelsplit


Select a list of test cases:

It is possible to set a list of test case names by using the variable ${DYNAMICTESTS} (plural). This variable must be a string and the list of names must be pipe-seperated (|).

Example:

robot --variable DYNAMICTESTS:firstsuitename.testcase1|firstsuitename.testcase3|anothersuitename.othertestcase foldername

It is also possible to set the variable @{DYNAMICTESTS} as a list variable from i.e. python code.


Re-run failed test cases:

Because it is not possible to use the command line argument --rerunfailed from robot directly, DataDriver brings a Pre-Run-Modifier that handles this issue.

Normally reexecution of failed testcases has three steps.

  • original execution
  • re-execution the failed ones based on original execution output
  • merging original execution output with re-execution output

The DataDriver.rerunfailed Pre-Run-Modifier removes all passed test cases based on a former output.xml.

Example:

robot --output original.xml tests                                                    # first execute all tests
robot --prerunmodifier DataDriver.rerunfailed:original.xml --output rerun.xml tests  # then re-execute failing
rebot --merge original.xml rerun.xml                                                 # finally merge results

Be aware, that in this case it is not allowed to use “:” as character in the original output file path. If you want to set a full path on windows like e:\\myrobottest\\output.xml you have to use “;” as argument seperator.

Example:

robot --prerunmodifier DataDriver.rerunfailed;e:\\myrobottest\\output.xml --output e:\\myrobottest\\rerun.xml tests

Filtering with tags.

New in 0.3.1

It is possible to use tags to filter the data source. To use this, tags must be assigned to the test cases in data source.


Robot Framework Command Line Arguments

To filter the source, the normal command line arguments of Robot Framework can be used. See Robot Framework Userguide for more information Be aware that the filtering of Robot Framework itself is done before DataDriver is called. This means if the Template test is already filtered out by Robot Framework, DataDriver can never be called. If you want to use --include the DataDriver TestSuite should have a DefaultTag or ForceTag that fulfills these requirements.

Example: robot --include 1OR2 --exclude foo DataDriven.robot


Filter based on Library Options

It is also possible to filter the data source by an init option of DataDriver. If these Options are set, Robot Framework Filtering will be ignored.

Example:

*** Settings ***
Library    DataDriver    include=1OR2    exclude=foo

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