Metadata-Version: 2.1
Name: DataComparerLibrary
Version: 0.824
Summary: For comparing csv-files or 2d-array with csv-file.
Home-page: 
Author: René Philip Zuijderduijn
Author-email: datacomparerlibrary@outlook.com
License: Apache
Keywords: robotframework testing test-automation datacompare
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Description-Content-Type: text/x-rst
License-File: LICENSE.txt

===================
DataComparerLibrary
===================

.. contents::
   :local:


Preparation
===================

Installation
------------

If you already have Python with `pip <https://pip.pypa.io>`_ installed,
you can simply run::

    pip install DataComparerLibrary
    pip install --upgrade DataComparerLibrary



Import statement for the DataComparerLibrary in Python
------------------------------------------------------

from DataComparerLibrary.datacomparer import DataComparer



DataComparer
============

Introduction
------------

The DataComparerLibrary can be used for:
    - comparing csv-files or text-files
    - comparing a 2d-matrix with a csv-file or text-file
    - comparing a csv_file or text-file with a 2d-matrix
    - comparing 2d-matrices

In case a difference between actual and expected data is found an exception wil be given. In Robot Framework
the result will be set to failed.
A strait comparison can be made, but the DataComparerLibrary offers also some special comparison options described
beneath.

{PRESENT}
With {PRESENT} in the expected data file you can make clear that data of a field of the actual data should be present.
This can be helpful for fields that have constant changing values. For example generated id's.

{EMPTY}
With {EMPTY} in the expected data file you can make clear that data of a field of the actual data should be absent.

{SKIP}
With {SKIP} in the expected data file you can make clear that the comparison of data of a complete or part of a field
of the actual data should be skipped. This can be helpful for fields or parts of fields that have constant changing
values. For example time or generated id's.

{INTEGER}
With {INTEGER} in the expected data file you can make clear that the data of a field of the actual data should be an
integer. This can be helpful for fields that have constant changing integer values. For example integer id's.

{NOW()...:....}
With {NOW()} in the expected data file you can make clear that the data of a field or part of a field of the actual
data should be (a part of) a date. You can let calculate the current or a date in the past or future. Calculation is
based on the "relativedelta" method from Python. Also you can style the date in the format you want. This can be
helpful for fields that have constant changing date values, but which date values have a fixed offset linked to the
current date. At "Examples comparing Actual Data with Expected Data" you can find some examples how to use it.

Delimiter
Default delimiter is "," in case of an input file. You can use the option "delimiter_actual_data" and "delimiter_expected_data" to set another
delimiter like ";" or "\t" for tab. It is also possible to use a multi-character delimiter like "@#@".

Quotechar
Default quotechar is '"' in case of an input file. You can use the option "quotechar_actual_data" and/or "quotechar_expected_data" to set another
quotechar.


Examples of using the DataComparerLibrary for comparing data in Python
----------------------------------------------------------------------

Below there are some examples how to call the methods of the DataComparerLibrary in Python::


    a = DataComparer
    a.compare_data_files(self, actual_file, expected_file)
    a.compare_data_files(self, actual_file, expected_file, delimiter_actual_data=';', delimiter_expected_data=';')
    a.compare_data_files(self, actual_file, expected_file, delimiter_actual_data='@#@', delimiter_expected_data='@#@')
    a.compare_data_2d_array_with_file(self, actual_2d_matrix_data_input, expected_file, delimiter_expected_data='\t')
    a.compare_data_file_with_2d_array(self, actual_file, expected_2d_matrix_data_input, delimiter_actual_data=';')
    a.compare_data_2d_arrays(self, actual_2d_matrix_data_input, expected_2d_matrix_data_input)


Examples of using the DataComparerLibrary keywords for comparing data in Robot Framework
----------------------------------------------------------------------------------------

Below there are some examples how to call the keywords of the DataComparerLibrary in Robot Framework::


    *** Settings ***
    Library     DataComparerLibrary

    *** Test Cases ***
    Testcase_DataComparer
        Examples

    *** Keywords ***
    Examples
        Run Keyword And Continue On Failure  DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv
        DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv  delimiter_actual_data=;  delimiter_expected_data=;
        DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv  delimiter_actual_data=@#@  delimiter_expected_data=@#@
        DataComparerLibrary.Compare Data Files  C:\\Users\\actual.csv   C:\\Users\\expected.csv
        DataComparerLibrary.Compare Data 2d Array With File  ${actual_2d_matrix_data_input}  C:\\Users\\expected.csv  delimiter_expected_data=\t
        DataComparerLibrary.Compare Data File With 2d Array  C:\\Users\\actual.csv  ${expected_2d_matrix_data_input}  delimiter_actual_data=;
        DataComparerLibrary.Compare Data 2d Arrays  ${actual_2d_matrix_data_input}  ${expected_2d_matrix_data_input}


Examples comparing Actual Data with Expected Data
-------------------------------------------------

Below there is an example of actual and expected data with some different cases.



Based on current datetime = 2023-09-06 19:04:00  (example):


+--------------------------------------------------------------------------------------------------+
|                                   Actual csv file or 2d-array                                    |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| id           | name     | city         | start datetime                  | code    | password    |
+==============+==========+==============+=================================+=========+=============+
| 87           | John     | London       | 2019-09-01 10:00:15             | abc1    | xxxxxxxx    |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| 88           | Bert     | Amsterdam    | 2023/09/06 19:02:00             |         | xxxxxxxx    |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| 89           | Klaas    | Brussel      | 23-8-6 12:04:17                 | 5ghi    | xxxxxxxx    |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| 90           | Joe      | Helsinki     | 08062025 12:04:17               | 99fg    | xxxxxxxx    |
+--------------+----------+--------------+---------------------------------+---------+-------------+


+--------------------------------------------------------------------------------------------------+
|                                   Expected csv file or 2d-array                                  |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| id           | name     | city         | start datetime                  | code    | password    |
+==============+==========+==============+=================================+=========+=============+
| {INTEGER}    | John     | London       | {NOW()-4Y5D:YYYY-MM-DD}         | abc1    | {PRESENT}   |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| {INTEGER}    | Bert     | Amsterdam    | {NOW():YYYY/MM/DD} {SKIP}       | {EMPTY} | {PRESENT}   |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| {INTEGER}    | Klaas    | Brussel      | {NOW()-1M:YY-M-D} {SKIP}        | 5ghi    | {PRESENT}   |
+--------------+----------+--------------+---------------------------------+---------+-------------+
| {INTEGER}    | Joe      | Helsinki     | {NOW()+1Y9M2D:DDMMYYYY} {SKIP}  | {SKIP}  | {PRESENT}   |
+--------------+----------+--------------+---------------------------------+---------+-------------+


FileConverter
=============


DataComparerLibrary keywords for preparing data in Robot Framework
------------------------------------------------------------------
Records in files can be ended by carriage return line feed (CRLF). In some situations separate line feeds (LF) are
present within records. For example for an easy way of sorting records this can be a problem.

The keywords "Remove Separate Lf" and "Replace Separate Lf" support removing/replacing a separate Lf in the data from
the input file. The result will be written to an output file.


Examples of using the DataComparerLibrary keywords for preparing data in Robot Framework
----------------------------------------------------------------------------------------

Below there are some examples how to call the keywords of the DataComparerLibrary in Robot Framework::


    *** Settings ***
    Library     DataComparerLibrary

    *** Test Cases ***
    Testcase_FileConverter
        Remove Separate LF From Data In File
        Replace Separated LF With Character Or String From Data In File

    *** Keywords ***
    Remove Separate LF From Data In File
        DataComparerLibrary.Remove Separate Lf  ${path_actual_input_files}\\input_file_with_lf.txt  ${path_actual_output_files}\\output_file_without_lf.txt


    Replace Separated LF With Character Or String From Data In File
        DataComparerLibrary.Replace Separate Lf  ${input_file_with_separate_lf}   ${output_file_lf_replaced_by_character_or_string}   ${replacement_string}
        DataComparerLibrary.Replace Separate Lf  input_file_with_separate_lf.txt  output_file_lf_replaced_by_character_or_string.txt  abc
        DataComparerLibrary.Replace Separate Lf  input_file_with_separate_lf.txt  output_file_lf_replaced_by_character_or_string.txt  x
        DataComparerLibrary.Replace Separate Lf  input_file_with_separate_lf.txt  output_file_lf_replaced_by_character_or_string.txt  ${SPACE}


