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Home
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At DataCamp we build tools to [learn data science](https://www.datacamp.com) interactively. See e.g. our online [R tutorial](https://www.datacamp.com/courses/free-introduction-to-r) to learn R Programming and our Python For Data Science tutorial to [learn Python](https://www.datacamp.com/courses/intro-to-python-for-data-science).
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pythonwhat?
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If, during execution of the SCT, a test function notices a mistake, an appropriate feedback will be generated and presented to the student. It is always possible to override these feedback messages with your own messages. Defining custom feedback will make your SCTs longer and they may be error prone (typos, etc.), but they typically give the exercise a more natural and personalized feel.
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If all test functions pass, a success message is presented to the student. `pytonwhat` has some messages in store from which it can choose randomly, but you can override this with the `success_msg()` function.
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If all test functions pass, a success message is presented to the student. `pythonwhat` has some messages in store from which it can choose randomly, but you can override this with the `success_msg()` function.
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Overview
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To get started, make sure to check out the [Quickstart Guide](https://www.github.com/datacamp/pythonwhat/wiki/Quickstart_Guide).
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To get started, make sure to check out the [Quickstart Guide](quickstart_guide.md).
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To robustly test the equality of objects, and results of evaluations, it has to fetch the information from the respective processes, i.e. the student and solution processes. By default, this is done through a process of 'dilling' and 'undilling', but it's also possible to define your own converters to customize the way objects and results are compared. For more background on this, check out the [Processes article](https://github.com/datacamp/pythonwhat/wiki/Processes). For some more background on the principle of 'sub-SCTs', i.e. sets of tests to be called on a particular part or a particular state of a student's submission, have a look at the [Sub-SCTs article](https://github.com/datacamp/pythonwhat/wiki/Sub-SCTs).
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To robustly test the equality of objects, and results of evaluations, it has to fetch the information from the respective processes, i.e. the student and solution processes. By default, this is done through a process of 'dilling' and 'undilling', but it's also possible to define your own converters to customize the way objects and results are compared. For more background on this, check out the [Processes article](expression_tests.md). For some more background on the principle of 'sub-SCTs', i.e. sets of tests to be called on a particular part or a particular state of a student's submission, have a look at the [Part Checks article](part_checks.rst).
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The remainder of the wiki goes over every test function that `pythonwhat` features, explaining all arguments and covering different use cases. They will give you an idea of how, why and when to use them.
- If some tests fail, do other tests to pinpoint the problem: [test_correct()](https://www.github.com/datacamp/pythonwhat/wiki/test_correct)
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- Specify several tests, only one of which should pass: [test_or()](https://www.github.com/datacamp/pythonwhat/wiki/test_or)
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**Advanced functions**
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- Value of data frame: [test_data_frame()](https://github.com/datacamp/pythonwhat/wiki/test_data_frame)
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- Value of dictionary: [test_dictionary()](https://github.com/datacamp/pythonwhat/wiki/test_dictionary)
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- If ... else ... constructs: [test_if_else()](https://github.com/datacamp/pythonwhat/wiki/test_if_else)
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- For loops: [test_for_loop()](https://github.com/datacamp/pythonwhat/wiki/test_for_loop)
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- While loops: [test_while_loop()](https://github.com/datacamp/pythonwhat/wiki/test_while_loop)
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- Test value of object after expression: [test_object_after_expression()](https://github.com/datacamp/pythonwhat/wiki/test_object_after_expression)
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- Test output of an expression: [test_expression_output()](https://github.com/datacamp/pythonwhat/wiki/test_expression_output)
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- Test result of an expression: [test_expression_result()](https://github.com/datacamp/pythonwhat/wiki/test_expression_result)
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- Context managers, the with statement: [test_with()](https://github.com/datacamp/pythonwhat/wiki/test_with)
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- Test user-defined functions: [test_function_definition()](https://github.com/datacamp/pythonwhat/wiki/test_function_definition)
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- Test lambda function definitions: [test_lambda_function()](https://github.com/datacamp/pythonwhat/wiki/test_lambda_function)
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- Test comprehensions: [test_list_comp(), test_dict_comp() and test_generator_exp()](https://github.com/datacamp/pythonwhat/wiki/test_comprehension)
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- Test try except blcoks: [test_try_except()](https://github.com/datacamp/pythonwhat/test_try_except)
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All these functions are also documented inside the `pythonwhat` source code itself. The documentation there goes into the tiny details of all functions' implementations. Follow the steps in the README of this repository to generate a PDF version of the documentation.
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For more full examples of SCTs for Python exercises on DataCamp, check out the [source files of the introduction to Python course](http://www.github.com/datacamp/courses-intro-to-python). In the chapter files there, you can can see the SCTs that have been written for several exercises.
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To test your understanding of writing SCTs for Python exercises on the DataCamp platform, you can take the course [Writing SCTs with pythonwhat](https://www.datacamp.com/courses/writing-scts-with-pythonwhat) course.
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