-
Notifications
You must be signed in to change notification settings - Fork 36
/
DataDriver.py
1918 lines (1484 loc) · 73.1 KB
/
DataDriver.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
# Copyright 2018- René Rohner
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import importlib
import inspect
import re
import traceback
from glob import glob
from pathlib import Path
from typing import Any, Dict, List, Optional, Union # type: ignore
from robot.api.logger import console # type: ignore
from robot.libraries.BuiltIn import BuiltIn # type: ignore
from robot.model.tags import Tags # type: ignore
from robot.model.testsuite import TestSuite # type: ignore
from robot.running import ArgumentSpec # type: ignore
from robot.running.model import TestCase # type: ignore
from robot.utils.dotdict import DotDict # type: ignore
from robot.utils.importer import Importer # type: ignore
from .AbstractReaderClass import AbstractReaderClass # type: ignore
from .argument_utils import robot_options # type: ignore
from .ReaderConfig import (
ReaderConfig, # type: ignore
TestCaseData, # type: ignore
)
from .search import search_variable # type: ignore
from .utils import ( # type: ignore
Encodings,
PabotOpt,
TagHandling,
binary_partition_test_list,
debug,
equally_partition_test_list,
error,
get_filter_dynamic_test_names,
get_variable_value,
is_pabot_dry_run,
is_same_keyword,
warn,
)
__version__ = "1.11.1"
class DataDriver:
# region: docstring
"""
===================================================
DataDriver for Robot Framework®
===================================================
DataDriver is a Data-Driven extension 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 <https://github.com/Snooz82/robotframework-datadriver>`_
For more information about Robot Framework®, see https://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
It is also possible to implement own DataReaders in Python to read
your test data from some other sources, like databases or json files.
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 is 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.
Table of contents
-----------------
- `What DataDriver Does`_
- `How DataDriver Works`_
- `Usage`_
- `Structure of Test Suite`_
- `Structure of data file`_
- `Accessing Test Data From Robot Variables`_
- `Data Sources`_
- `File Encoding and CSV Dialect`_
- `Custom DataReader Classes`_
- `Selection of Test Cases to Execute`_
- `Configure DataDriver by Pre-Run Keyword`_
- `Pabot and DataDriver`_
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.
RoboCon 2020 Talk
~~~~~~~~~~~~~~~~~
.. image:: https://img.youtube.com/vi/RtEUr1i4x3s/0.jpg
:target: https://www.youtube.com/watch?v=RtEUr1i4x3s
Brief overview what DataDriver is and how it works at the RoboCon 2020 in Helsiki.
Alternative approach
~~~~~~~~~~~~~~~~~~~~
DataDriver gives an alternative to the build in data driven approach
like:
.. code :: robotframework
*** 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 inbuilt 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
become 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 <#example-suite>`__
`See example csv table <#example-csv>`__
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 data source. Based on the ``Test Template`` -Keyword, DataDriver
creates as much test cases as data sets are in the data source.
In the case that data source is csv (Default)
As values for the arguments of the ``Test Template`` -Keyword, DataDriver
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 "Library Listener" but does not provide keywords.
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:**
.. code :: robotframework
*** Settings ***
Library DataDriver
Test Template Invalid Logins
*** Keywords ***
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`` in Settings secion. 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
~~~~~~~~~~~~~~~~~~
.. code :: robotframework
***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 | ${username} | ${password} | [Tags] | [Documentation] |
| Cases \**\* | | | | |
| | | | | |
+=============+=============+=============+=============+==================+
| Right user | demo | ${EMPTY} | 1 | This is a test |
| empty pass | | | | case |
| | | | | documentation of |
| | | | | the first one. |
+-------------+-------------+-------------+-------------+------------------+
| Right user | demo | FooBar | 2,3,foo | This test |
| wrong pass | | | | case has |
| | | | | the Tags |
| | | | | 2,3 and foo |
| | | | | assigned. |
+-------------+-------------+-------------+-------------+------------------+
| | ${EMPTY} | mode | 1,2,3,4 | This test |
| | | | | case has a |
| | | | | generated |
| | | | | name based |
| | | | | on template |
| | | | | name. |
+-------------+-------------+-------------+-------------+------------------+
| | ${EMPTY} | ${EMPTY} | | |
+-------------+-------------+-------------+-------------+------------------+
| | ${EMPTY} | FooBar | | |
+-------------+-------------+-------------+-------------+------------------+
| | FooBar | mode | | |
+-------------+-------------+-------------+-------------+------------------+
| | FooBar | ${EMPTY} | | |
+-------------+-------------+-------------+-------------+------------------+
| | FooBar | FooBar | | |
+-------------+-------------+-------------+-------------+------------------+
In this data file, eight test cases are defined. Each line specifies one
test case. The first two test cases have specific names. The other six
test cases will generate names based on template test cases name with
the replacement of variables in this name. The order of columns is
irrelevant except the first column, ``*** Test Cases ***``
Supported Data Types
~~~~~~~~~~~~~~~~~~~~
In general DataDriver supports any Object that is handed over from the DataReader.
However the text based readers for csv, excel and so do support different types as well.
DataDriver supports Robot Framework® Scalar variables as well as Dictionaries and Lists.
It also support python literal evaluations.
Scalar Variables
^^^^^^^^^^^^^^^^
The Prefix ``$`` defines that the value in the cell is taken as in Robot Framework® Syntax.
``String`` is ``str``, ``${1}`` is ``int`` and ``${None}`` is NoneType.
The Prefix only defines the value typ. It can also be used to assign a scalar to a dictionary key.
See example table: ``${user}[id]``
Dictionary Variables
^^^^^^^^^^^^^^^^^^^^
Dictionaries can be created in different ways.
One option is, to use the prefix ``&``.
If a variable is defined that was (i.e. ``&{dict}``) the cell value is interpreted the same way,
the BuiltIn keyword `Create Dictionary <https://robotframework.org/robotframework/latest/libraries/BuiltIn.html#Create%20Dictionary>`_ would do.
The arguments here are comma (``,``) separated.
See example table: ``&{dict}``
The other option is to define scalar variables in dictionary syntax like ``${user}[name]`` or ``${user.name}``
That can be also nested dictionaries. DataDriver will create Robot Framework® (DotDict) Dictionaries, that can be accessed with ``${user.name.first}``
See example table: ``${user}[name][first]``
List Variables
^^^^^^^^^^^^^^
Lists can be created with the prefix ``@`` as comma (``,``) separated list.
See example table: ``@{list}``
Be aware that a list with an empty string has to be the cell content `${Empty}`.
Python Literals
^^^^^^^^^^^^^^^
DataDriver can evaluate Literals.
It uses the prefix ``e`` for that. (i.e. ``e{list_eval}``)
For that it uses `BuiltIn Evaluate <https://robotframework.org/robotframework/latest/libraries/BuiltIn.html#Evaluate>`_
See example table: ``e{user.chk}``
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
| ``*** Test Cases ***`` | ``${scalar}`` | ``@{list}`` | ``e{list_eval}`` | ``&{dict}`` | ``e{dict_eval}`` | ``e{eval}`` | ``${exp_eval}`` | ``${user}[id]`` | ``${user}[name][first]`` | ``${user.name.last}`` | ``e{user.chk}`` |
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
| ``One`` | ``Sum List`` | ``1,2,3,4`` | ``["1","2","3","4"]`` | ``key=value`` | ``{'key': 'value'}`` | ``[1,2,3,4]`` | ``10`` | ``1`` | ``Pekka`` | ``Klärck`` | ``{'id': '1', 'name': {'first': 'Pekka', 'last': 'Klärck'}}`` |
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
| ``Two`` | ``Should be Equal`` | ``a,b,c,d`` | ``["a","b","c","d"]`` | ``key,value`` | ``{'key': 'value'}`` | ``True`` | ``${true}`` | ``2`` | ``Ed`` | ``Manlove`` | ``{'id': '2', 'name': {'first': 'Ed', 'last': 'Manlove'}}`` |
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
| ``Three`` | ``Whos your Daddy`` | ``!,",',$`` | ``["!",'"',"'","$"]`` | ``z,value,a,value2`` | ``{'a': 'value2', 'z': 'value'}`` | ``{'Daddy' : 'René'}`` | ``René`` | ``3`` | ``Tatu`` | ``Aalto`` | ``{'id': '3', 'name': {'first': 'Tatu', 'last': 'Aalto'}}`` |
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
| ``4`` | ``Should be Equal`` | ``1`` | ``["1"]`` | ``key=value`` | ``{'key': 'value'}`` | ``1`` | ``${1}`` | ``4`` | ``Jani`` | ``Mikkonen`` | ``{'id': '4', 'name': {'first': 'Jani', 'last': 'Mikkonen'}}`` |
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
| ``5`` | ``Should be Equal`` | | ``[]`` | ``a=${2}`` | ``{'a':2}`` | ``"string"`` | ``string`` | ``5`` | ``Mikko`` | ``Korpela`` | ``{'id': '5', 'name': {'first': 'Mikko', 'last': 'Korpela'}}`` |
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
| ``6`` | ``Should be Equal`` | ``[1,2]`` | ``["[1","2]"]`` | ``key=value,key2=value2`` | ``{'key': 'value', 'key2': 'value2'}`` | ``None`` | ``${none}`` | ``6`` | ``Ismo`` | ``Aro`` | ``{'id': '6', 'name': {'first': 'Ismo', 'last': 'Aro'}}`` |
+--------------------------+-----------------------+---------------+-------------------------+-----------------------------+------------------------------------------+--------------------------+-------------------+-------------------+----------------------------+-------------------------+------------------------------------------------------------------+
Accessing Test Data From Robot Variables
----------------------------------------
If neccesary it is possible to access the fetched data tables directly from a Robot Framework® variable.
This could be helpfull in Test Setup or in Suite Setup.
There are three variables available within the Data-Driven Suite:
@{DataDriver_DATA_LIST}
~~~~~~~~~~~~~~~~~~~~~~~
A list as suite variable containing a robot dictionary for each test case that is selected for execution.
.. code :: json
[
{
"test_case_name": "Right user empty pass",
"arguments": {
"${username}": "demo",
"${password}": "${EMPTY}"
},
"tags": [
"1"
],
"documentation": "This is a test case documentation of the first one."
},
{
"test_case_name": "Right user wrong pass",
"arguments": {
"${username}": "demo",
"${password}": "FooBar"
},
"tags": [
"2",
"3",
"foo"
],
"documentation": "This test case has the Tags 2,3 and foo"
},
{
"test_case_name": "Login with user '${EMPTY}' and password 'mode'",
"arguments": {
"${username}": "${EMPTY}",
"${password}": "mode"
},
"tags": [
"1",
"2",
"3",
"4"
],
"documentation": "This test case has a generated name based on template name."
},
{
"test_case_name": "Login with user '${EMPTY}' and password '${EMPTY}'",
"arguments": {
"${username}": "${EMPTY}",
"${password}": "${EMPTY}"
},
"tags": [
""
],
"documentation": ""
},
{
"test_case_name": "Login with user '${EMPTY}' and password 'FooBar'",
"arguments": {
"${username}": "${EMPTY}",
"${password}": "FooBar"
},
"tags": [
""
],
"documentation": ""
},
{
"test_case_name": "Login with user 'FooBar' and password 'mode'",
"arguments": {
"${username}": "FooBar",
"${password}": "mode"
},
"tags": [
"foo",
"1"
],
"documentation": ""
},
{
"test_case_name": "Login with user 'FooBar' and password '${EMPTY}'",
"arguments": {
"${username}": "FooBar",
"${password}": "${EMPTY}"
},
"tags": [
"foo"
],
"documentation": ""
},
{
"test_case_name": "Login with user 'FooBar' and password 'FooBar'",
"arguments": {
"${username}": "FooBar",
"${password}": "FooBar"
},
"tags": [
"foo",
"2"
],
"documentation": ""
}
]
This can be accessed as usual in Robot Framework®.
``${DataDriver_DATA_LIST}[2][arguments][\${password}]`` would result in ``mode`` .
&{DataDriver_DATA_DICT}
~~~~~~~~~~~~~~~~~~~~~~~
A dictionary as suite variable that contains the same data as the list, with the test names as keys.
.. code :: json
{
"Right user empty pass": {
"test_case_name": "Right user empty pass",
"arguments": {
"${username}": "demo",
"${password}": "${EMPTY}"
},
"tags": [
"1"
],
"documentation": "This is a test case documentation of the first one."
},
"Right user wrong pass": {
"test_case_name": "Right user wrong pass",
"arguments": {
"${username}": "demo",
"${password}": "FooBar"
},
"tags": [
"2",
"3",
"foo"
],
"documentation": "This test case has the Tags 2,3 and foo"
},
"Login with user '${EMPTY}' and password 'mode'": {
"test_case_name": "Login with user '${EMPTY}' and password 'mode'",
"arguments": {
"${username}": "${EMPTY}",
"${password}": "mode"
},
"tags": [
"1",
"2",
"3",
"4"
],
"documentation": "This test case has a generated name based on template name."
},
"Login with user '${EMPTY}' and password '${EMPTY}'": {
"test_case_name": "Login with user '${EMPTY}' and password '${EMPTY}'",
"arguments": {
"${username}": "${EMPTY}",
"${password}": "${EMPTY}"
},
"tags": [
""
],
"documentation": ""
},
"Login with user '${EMPTY}' and password 'FooBar'": {
"test_case_name": "Login with user '${EMPTY}' and password 'FooBar'",
"arguments": {
"${username}": "${EMPTY}",
"${password}": "FooBar"
},
"tags": [
""
],
"documentation": ""
},
"Login with user 'FooBar' and password 'mode'": {
"test_case_name": "Login with user 'FooBar' and password 'mode'",
"arguments": {
"${username}": "FooBar",
"${password}": "mode"
},
"tags": [
"foo",
"1"
],
"documentation": ""
},
"Login with user 'FooBar' and password '${EMPTY}'": {
"test_case_name": "Login with user 'FooBar' and password '${EMPTY}'",
"arguments": {
"${username}": "FooBar",
"${password}": "${EMPTY}"
},
"tags": [
"foo"
],
"documentation": ""
},
"Login with user 'FooBar' and password 'FooBar'": {
"test_case_name": "Login with user 'FooBar' and password 'FooBar'",
"arguments": {
"${username}": "FooBar",
"${password}": "FooBar"
},
"tags": [
"foo",
"2"
],
"documentation": ""
}
}
&{DataDriver_TEST_DATA}
~~~~~~~~~~~~~~~~~~~~~~~
A dictionary as test variable that contains the test data of the current test case.
This dictionary does also contain arguments that are not used in the ``Test Template`` keyword.
This can be used in Test Setup and within a test case.
.. code :: json
{
"test_case_name": "Right user wrong pass",
"arguments": {
"${username}": "demo",
"${password}": "FooBar"
},
"tags": [
"2",
"3",
"foo"
],
"documentation": "This test case has the Tags 2,3 and foo"
}
Data Sources
------------
CSV / TSV (Character-separated values)
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
By default DataDriver reads csv files. With the `Encoding and CSV
Dialect <#file-encoding-and-csv-dialect>`__ settings you may configure which
structure your data source has.
XLS / XLSX Files
~~~~~~~~~~~~~~~~
To use Excel file types, you have to install DataDriver with the Extra XLS.
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.
.. code :: robotframework
*** Settings ***
Library DataDriver .xlsx
or:
.. code :: robotframework
*** Settings ***
Library DataDriver file=my_data_source.xlsx sheet_name=2nd Sheet
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.
Alternatively you may deactivate that string conversion.
To do so, you have to add the option ``preserve_xls_types`` to ``True``.
In that case, you will get str, float, boolean, int, datetime.time,
datetime.datetime and some others.
.. code :: robotframework
*** Settings ***
Library DataDriver file=my_data_source.xlsx preserve_xls_types=True
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 of PICT
^^^^^^^^^^^^^^^^^^^^
- 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.
.. code :: robotframework
*** Settings ***
Library DataDriver my_model_file.pict
It is possible to give options to pict with the import argument `pict_options=`.
.. code :: robotframework
*** Settings ***
Library DataDriver pict_arg.pict pict_options=/o:3 /r
Glob File Pattern
~~~~~~~~~~~~~~~~~
This module implements a reader class that creates a test case for each file or folder that matches the given glob pattern.
With an optional argument "arg_name" you can modify the argument that will be set. See folder example.
Example with json files:
.. code :: robotframework
*** Settings ***
Library DataDriver file=${CURDIR}/DataFiles/*_File.json reader_class=glob_reader
Library OperatingSystem
Test Template Test all Files
*** Test Cases ***
Glob_Reader_Test Wrong_File.NoJson
*** Keywords ***
Test all Files
[Arguments] ${file_name}
${file_content}= Get File ${file_name}
${content}= Evaluate json.loads($file_content)["test_case"]
Should Be Equal ${TEST_NAME} ${content}
Example with folders:
.. code :: robotframework
*** Settings ***
Library DataDriver file=${CURDIR}/FoldersToFind/*/ reader_class=glob_reader arg_name=\${folder_name}
Library OperatingSystem
Test Template Test all Files
*** Test Cases ***
Glob_Reader_Test Wrong_File.NoJson
*** Keywords ***
Test all Files
[Arguments] ${folder_name}
${content}= Get File ${folder_name}/verify.txt
Should Be Equal ${TEST_NAME} ${content}
File Encoding and CSV Dialect
-----------------------------
While there are various specifications and implementations for the CSV format
(see `RFC 4180 <https://www.rfc-editor.org/rfc/rfc4180.html>`_),
there is no formal specification in existence, which allows for a wide variety of interpretations of CSV files.
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=
~~~~~
.. code :: robotframework
*** 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=
~~~~~~~~~
``encoding=`` must be set if it shall not be cp1252.
**Examples**:
``cp1252, ascii, iso-8859-1, latin-1, utf_8, utf_16, utf_16_be, utf_16_le``
**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 <https://docs.python.org/3/library/codecs.html#standard-encodings>`_ for more encodings
dialect=
~~~~~~~~
You may change the CSV Dialect here.
The dialect option can be one of the following:
- Excel-EU
- excel
- excel-tab
- unix
- UserDefined
supported Dialects are:
.. code:: python
"Excel-EU"
delimiter=';',
quotechar='"',
escapechar='\\',
doublequote=True,
skipinitialspace=False,
lineterminator="\\r\\n",
quoting=csv.QUOTE_ALL
"excel"
delimiter = ','
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\\r\\n'
quoting = QUOTE_MINIMAL
"excel-tab"
delimiter = '\\t'
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\\r\\n'
quoting = QUOTE_MINIMAL
"unix"
delimiter = ','
quotechar = '"'
doublequote = True
skipinitialspace = False
lineterminator = '\\n'
quoting = QUOTE_ALL
Usage in Robot Framework®
.. code :: robotframework
*** Settings ***
Library DataDriver my_data_file.csv dialect=excel
.. code :: robotframework
*** Settings ***
Library DataDriver my_data_file.csv dialect=excel_tab
.. code :: robotframework
*** 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®
.. code :: robotframework
*** Settings ***
Library DataDriver my_data_file.csv
... dialect=UserDefined
... delimiter=.
... lineterminator=\\n