import pytest from docstring_to_markdown.rst import looks_like_rst, rst_to_markdown SEE_ALSO = """ See Also -------- DataFrame.from_records : Constructor from tuples, also record arrays. read_table : Read general delimited file into DataFrame. read_clipboard : Read text from clipboard into DataFrame. """ SEE_ALSO_MARKDOWN = """ #### See Also - `DataFrame.from_records`: Constructor from tuples, also record arrays. - `read_table`: Read general delimited file into DataFrame. - `read_clipboard`: Read text from clipboard into DataFrame. """ CODE_MULTI_LINE_CODE_OUTPUT = """ To enforce a single dtype: >>> df = pd.DataFrame(data=d, dtype=np.int8) >>> df.dtypes col1 int8 col2 int8 dtype: object Constructing DataFrame from numpy ndarray: >>> df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), ... columns=['a', 'b', 'c']) >>> df2 a b c 0 1 2 3 1 4 5 6 2 7 8 9 """ CODE_MULTI_LINE_CODE_OUTPUT_MARKDOWN = """ To enforce a single dtype: ```python df = pd.DataFrame(data=d, dtype=np.int8) df.dtypes ``` ``` col1 int8 col2 int8 dtype: object ``` Constructing DataFrame from numpy ndarray: ```python df2 = pd.DataFrame(np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]), columns=['a', 'b', 'c']) df2 ``` ``` a b c 0 1 2 3 1 4 5 6 2 7 8 9 ``` """ RST_LINK_EXAMPLE = """To learn more about the frequency strings, please see `this link `__.""" RST_LINK_EXAMPLE_MARKDOWN = ( "To learn more about the frequency strings, please see " "[this link](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases)." ) RST_LINK_MULTILINE_EXAMPLE = """ See `strftime documentation `_ for more. """ RST_LINK_MULTILINE_MARKDOWN = """ See [strftime documentation](https://docs.python.org/3/library/datetime.html#strftime-and-strptime-behavior) for more. """ RST_REF_EXAMPLE = """See :ref:`here ` for a list of frequency aliases.""" RST_REF_MARKDOWN = """See here: `timeseries.offset_aliases` for a list of frequency aliases.""" RST_PRODUCTION_LIST_EXAMPLE = """ A function definition defines a user-defined function object: .. productionlist:: python-grammar funcdef: [`decorators`] "def" `funcname` "(" [`parameter_list`] ")" : ["->" `expression`] ":" `suite` decorators: `decorator`+ defparameter: `parameter` ["=" `expression`] funcname: `identifier` A function definition is an executable statement. """ RST_PRODUCTION_LIST_EXAMPLE_MARKDOWN = """ A function definition defines a user-defined function object: ```python-grammar funcdef: [`decorators`] "def" `funcname` "(" [`parameter_list`] ")" : ["->" `expression`] ":" `suite` decorators: `decorator`+ defparameter: `parameter` ["=" `expression`] funcname: `identifier` ``` A function definition is an executable statement. """ RST_COLON_CODE_BLOCK = """ For example, the following code :: @f1(arg) @f2 def func(): pass is roughly equivalent to (.. seealso:: exact_conversion) :: def func(): pass func = f1(arg)(f2(func)) except that the original function is not temporarily bound to the name func. """ RST_COLON_CODE_BLOCK_MARKDOWN = """ For example, the following code ```python @f1(arg) @f2 def func(): pass ``` is roughly equivalent to (*See also* exact_conversion) ```python def func(): pass func = f1(arg)(f2(func)) ``` except that the original function is not temporarily bound to the name func. """ # note: two spaces indent NUMPY_EXAMPLE = """ The docstring examples assume that `numpy` has been imported as `np`:: >>> import numpy as np Code snippets are indicated by three greater-than signs:: >>> x = 42 >>> x = x + 1 """ NUMPY_EXAMPLE_MARKDOWN = """ The docstring examples assume that `numpy` has been imported as `np` ```python >>> import numpy as np ``` Code snippets are indicated by three greater-than signs ```python >>> x = 42 >>> x = x + 1 ``` """ NUMPY_MATH_EXAMPLE = """ single-frequency component at linear frequency :math:`f` is represented by a complex exponential :math:`a_m = \\exp\\{2\\pi i\\,f m\\Delta t\\}`, where :math:`\\Delta t` is the sampling interval. """ NUMPY_MATH_EXAMPLE_MARKDOWN = """ single-frequency component at linear frequency $f$ is represented by a complex exponential $a_m = \\exp\\{2\\pi i\\,f m\\Delta t\\}$, where $\\Delta t$ is the sampling interval. """ PEP_287_CODE_BLOCK = """ Here's a doctest block: >>> print 'Python-specific usage examples begun with ">>>"' Python-specific usage examples begun with ">>>" >>> print '(cut and pasted from interactive sessions)' (cut and pasted from interactive sessions)""" PEP_287_CODE_BLOCK_MARKDOWN = """ Here's a doctest block: ```python print 'Python-specific usage examples begun with ">>>"' ``` ``` Python-specific usage examples begun with ">>>" ``` ```python print '(cut and pasted from interactive sessions)' ``` ``` (cut and pasted from interactive sessions) ``` """ RST_HIGHLIGHTED_BLOCK = """ .. highlight:: R Code block :: data.frame() """ RST_HIGHLIGHTED_BLOCK_MARKDOWN = """ Code block ```R data.frame() ``` """ NUMPY_NOTE = """ operations and methods. .. note:: The `chararray` class exists for backwards compatibility with Numarray, it is not recommended for new development. Some methods will only be available if the corresponding string method is """ NUMPY_NOTE_MARKDOWN = """ operations and methods. --- 🛈 **Note** The `chararray` class exists for backwards compatibility with Numarray, it is not recommended for new development. --- Some methods will only be available if the corresponding string method is """ RST_MATH_EXAMPLE = """ In two dimensions, the DFT is defined as .. math:: A_{kl} = \\\\sum_{m=0}^{M-1} \\\\sum_{n=0}^{N-1} a_{mn}\\\\exp\\\\left\\\\{-2\\\\pi i \\\\left({mk\\\\over M}+{nl\\\\over N}\\\\right)\\\\right\\\\} \\\\qquad k = 0, \\\\ldots, M-1\\\\quad l = 0, \\\\ldots, N-1, which extends in the obvious way to higher dimensions, and the inverses """ RST_MATH_EXAMPLE_MARKDOWN = """ In two dimensions, the DFT is defined as $$ A_{kl} = \\\\sum_{m=0}^{M-1} \\\\sum_{n=0}^{N-1} a_{mn}\\\\exp\\\\left\\\\{-2\\\\pi i \\\\left({mk\\\\over M}+{nl\\\\over N}\\\\right)\\\\right\\\\} \\\\qquad k = 0, \\\\ldots, M-1\\\\quad l = 0, \\\\ldots, N-1, $$ which extends in the obvious way to higher dimensions, and the inverses """ MATH_INLINE_BLOCK = """ covariance matrix, `C`, is .. math:: R_{ij} = \\frac{ C_{ij} } { \\sqrt{ C_{ii} * C_{jj} } } The values of `R` are between -1 and 1, inclusive. """ MATH_INLINE_BLOCK_MARKDOWN = """ covariance matrix, `C`, is $$R_{ij} = \\frac{ C_{ij} } { \\sqrt{ C_{ii} * C_{jj} } }$$ The values of `R` are between -1 and 1, inclusive. """ KWARGS_PARAMETERS = """ Parameters ---------- x : array_like Input array. **kwargs For other keyword-only arguments, see the ufunc docs. """ KWARGS_PARAMETERS_MARKDOWN = """ #### Parameters - `x`: array_like Input array. - `**kwargs` For other keyword-only arguments, see the ufunc docs. """ NUMPY_ARGS_PARAMETERS = """ Parameters ---------- arys1, arys2, ... : array_like One or more input arrays. """ NUMPY_ARGS_PARAMETERS_MARKDOWN = """ #### Parameters - `arys1`, `arys2`, `...`: array_like One or more input arrays. """ INITIAL_SIGNATURE = """\ absolute1(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) Calculate the absolute value element-wise. """ INITIAL_SIGNATURE_MARKDOWN = """\ ```python absolute1(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj]) ``` Calculate the absolute value element-wise. """ CODE_BLOCK_BUT_NOT_OUTPUT = """ Plot the function over ``[-10, 10]``: >>> import matplotlib.pyplot as plt >>> x = np.linspace(start=-10, stop=10, num=101) >>> plt.plot(x, np.absolute(x)) >>> plt.show() Plot the function over the complex plane: >>> xx = x + 1j * x[:, np.newaxis] >>> plt.imshow(np.abs(xx), extent=[-10, 10, -10, 10], cmap='gray') >>> plt.show() """ CODE_BLOCK_BUT_NOT_OUTPUT_MD = """ Plot the function over ``[-10, 10]``: ```python import matplotlib.pyplot as plt ``` ```python x = np.linspace(start=-10, stop=10, num=101) plt.plot(x, np.absolute(x)) plt.show() ``` Plot the function over the complex plane: ```python xx = x + 1j * x[:, np.newaxis] plt.imshow(np.abs(xx), extent=[-10, 10, -10, 10], cmap='gray') plt.show() ``` """ WARNING_BLOCK = """ Load pickled object from file. .. warning:: Loading pickled data received from untrusted sources can be unsafe. Parameters """ WARNING_BLOCK_MARKDOWN = """ Load pickled object from file. --- ⚠️ **Warning** Loading pickled data received from untrusted sources can be unsafe. --- Parameters """ LINE_WARNING = """ Create a view into the array with the given shape and strides. .. warning:: This function has to be used with extreme care, see notes. Parameters """ LINE_WARNING_MARKDOWN = """ Create a view into the array with the given shape and strides. ⚠️ **Warning**: This function has to be used with extreme care, see notes. Parameters """ REFERENCES = """ References ---------- .. [1] M.S. Bartlett, "Periodogram Analysis and Continuous Spectra", Biometrika 37, 1-16, 1950. .. [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics", The University of Alberta Press, 1975, pp. 109-110. .. [3] Wikipedia, "Window function", https://en.wikipedia.org/wiki/Window_function """ REFERENCES_MARKDOWN = """ #### References - [1] M.S. Bartlett, "Periodogram Analysis and Continuous Spectra", Biometrika 37, 1-16, 1950. - [2] E.R. Kanasewich, "Time Sequence Analysis in Geophysics", The University of Alberta Press, 1975, pp. 109-110. - [3] Wikipedia, "Window function", https://en.wikipedia.org/wiki/Window_function """ SIMPLE_TABLE = """ .. warning:: This is not a standard simple table ========= =============================================================== Character Meaning --------- --------------------------------------------------------------- 'r' open for reading (default) 'a' open for writing, appending to the end of the file if it exists ========= =============================================================== """ SIMPLE_TABLE_MARKDOWN = """ ⚠️ **Warning**: This is not a standard simple table | Character | Meaning | | --------- | --------------------------------------------------------------- | | 'r' | open for reading (default) | | 'a' | open for writing, appending to the end of the file if it exists | """ SIMPLE_TABLE_WITH_MARKUP = """ ============================== ======================================= Scalar Type Array Type ============================== ======================================= :class:`pandas.Interval` :class:`pandas.arrays.IntervalArray` :class:`bool` :class:`pandas.arrays.BooleanArray` ============================== ======================================= """ SIMPLE_TABLE_WITH_MARKUP_MARKDOWN = """ | Scalar Type | Array Type | | ----------------- | ----------------------------- | | `pandas.Interval` | `pandas.arrays.IntervalArray` | | `bool` | `pandas.arrays.BooleanArray` | """ SIMPLE_TABLE_2 = """ .. warning:: This is a standard simple table ===== ===== ======= A B A and B ===== ===== ======= False False False True False False ===== ===== ======= """ SIMPLE_TABLE_2_MARKDOWN = """ ⚠️ **Warning**: This is a standard simple table | A | B | A and B | | ----- | ----- | ------- | | False | False | False | | True | False | False | """ SIMPLE_TABLE_IN_PARAMS = """ Create an array. Parameters ---------- object : array_like An array, any object exposing the array interface, an object whose __array__ method returns an array, or any (nested) sequence. order : {'K', 'A', 'C', 'F'}, optional Specify the memory layout of the array. If object is an array the following holds. ===== ========= =================================================== order no copy copy=True ===== ========= =================================================== 'K' unchanged F & C order preserved, otherwise most similar order 'F' F order F order ===== ========= =================================================== When ``copy=False`` and a copy is made for other reasons... subok : bool, optional If True, then sub-classes will be passed-through, otherwise """ SIMPLE_TABLE_IN_PARAMS_MARKDOWN = r""" Create an array. #### Parameters - `object`: array_like An array, any object exposing the array interface, an object whose \_\_array\_\_ method returns an array, or any (nested) sequence. - `order`: {'K', 'A', 'C', 'F'}, optional Specify the memory layout of the array. If object is an array the following holds. | order | no copy | copy=True | | ----- | --------- | --------------------------------------------------- | | 'K' | unchanged | F & C order preserved, otherwise most similar order | | 'F' | F order | F order | When ``copy=False`` and a copy is made for other reasons... - `subok`: bool, optional If True, then sub-classes will be passed-through, otherwise """ GRID_TABLE_IN_SKLEARN = """ Attributes ---------- cv_results_ : dict of numpy (masked) ndarrays A dict with keys as column headers and values as columns, that can be imported into a pandas ``DataFrame``. For instance the below given table +------------+-----------+------------+-----------------+---+---------+ |param_kernel|param_gamma|param_degree|split0_test_score|...|rank_t...| +============+===========+============+=================+===+=========+ | 'poly' | -- | 2 | 0.80 |...| 2 | +------------+-----------+------------+-----------------+---+---------+ | 'poly' | -- | 3 | 0.70 |...| 4 | +------------+-----------+------------+-----------------+---+---------+ | 'rbf' | 0.1 | -- | 0.80 |...| 3 | +------------+-----------+------------+-----------------+---+---------+ | 'rbf' | 0.2 | -- | 0.93 |...| 1 | +------------+-----------+------------+-----------------+---+---------+ will be represented by a ``cv_results_`` dict """ GRID_TABLE_IN_SKLEARN_MARKDOWN = """ #### Attributes - `cv_results_`: dict of numpy (masked) ndarrays A dict with keys as column headers and values as columns, that can be imported into a pandas ``DataFrame``. For instance the below given table | param_kernel | param_gamma | param_degree | split0_test_score | ... | rank_t... | | ------------ | ----------- | ------------ | ----------------- | --- | --------- | | 'poly' | -- | 2 | 0.80 | ... | 2 | | 'poly' | -- | 3 | 0.70 | ... | 4 | | 'rbf' | 0.1 | -- | 0.80 | ... | 3 | | 'rbf' | 0.2 | -- | 0.93 | ... | 1 | will be represented by a ``cv_results_`` dict """ NESTED_PARAMETERS = """ Parameters ---------- transformers : list of tuples List of (name, transformer, columns) tuples. name : str Like in Pipeline and FeatureUnion, this allows the transformer and search. transformer : {'drop', 'passthrough'} or estimator Estimator must support :term:`fit` and :term:`transform`. columns : str, array-like of str, int, array-like of int, \ array-like of bool, slice or callable Indexes the data on its second axis. Integers are interpreted as above. To select multiple columns by name or dtype, you can use :obj:`make_column_selector`. remainder : {'drop', 'passthrough'} or estimator, default='drop' By default, only the specified columns in `transformers` are """ NESTED_PARAMETERS_MARKDOWN = """ #### Parameters - `transformers`: list of tuples List of (name, transformer, columns) tuples. - `name`: str Like in Pipeline and FeatureUnion, this allows the transformer and search. - `transformer`: {'drop', 'passthrough'} or estimator Estimator must support `fit` and `transform`. - `columns`: str, array-like of str, int, array-like of int, \ array-like of bool, slice or callable Indexes the data on its second axis. Integers are interpreted as above. To select multiple columns by name or dtype, you can use `make_column_selector`. - `remainder`: {'drop', 'passthrough'} or estimator, default='drop' By default, only the specified columns in `transformers` are """ INTEGRATION = """ Return a fixed frequency DatetimeIndex. Parameters ---------- start : str or datetime-like, optional Frequency strings can have multiples, e.g. '5H'. See :ref:`here ` for a list of frequency aliases. tz : str or tzinfo, optional To learn more about the frequency strings, please see `this link `__. """ # https://www.sphinx-doc.org/en/master/usage/restructuredtext/domains.html#info-field-lists SPHINX_SIGNATURE = """ :param str sender: The person sending the message :param str recipient: The recipient of the message :param str message_body: The body of the message :param priority: The priority of the message, can be a number 1-5 :type priority: integer or None :return: the message id :rtype: int :raises ValueError: if the message_body exceeds 160 characters """ SPHINX_SIGNATURE_MARKDOWN = """\ - `sender` (`str`): The person sending the message - `recipient` (`str`): The recipient of the message - `message_body` (`str`): The body of the message - `priority` (integer or None): The priority of the message, can be a number 1-5 - returns: the message id - return type: `int` - raises `ValueError`: if the message_body exceeds 160 characters """ SPHINX_NESTED = """\ .. code-block:: python def foo(): ''':param str message_body: blah blah''' """ SPHINX_NESTED_MARKDOWN = """\ ```python def foo(): ''':param str message_body: blah blah''' ``` """ RST_CASES = { 'handles prompt continuation and multi-line output': { 'rst': CODE_MULTI_LINE_CODE_OUTPUT, 'md': CODE_MULTI_LINE_CODE_OUTPUT_MARKDOWN }, 'converts links': { 'rst': RST_LINK_EXAMPLE, 'md': RST_LINK_EXAMPLE_MARKDOWN }, 'converts multi-line links': { 'rst': RST_LINK_MULTILINE_EXAMPLE, 'md': RST_LINK_MULTILINE_MARKDOWN }, 'changes highlight': { 'rst': RST_HIGHLIGHTED_BLOCK, 'md': RST_HIGHLIGHTED_BLOCK_MARKDOWN }, 'converts production list': { 'rst': RST_PRODUCTION_LIST_EXAMPLE, 'md': RST_PRODUCTION_LIST_EXAMPLE_MARKDOWN }, 'converts inline math': { 'rst': NUMPY_MATH_EXAMPLE, 'md': NUMPY_MATH_EXAMPLE_MARKDOWN }, 'converts math blocks': { 'rst': RST_MATH_EXAMPLE, 'md': RST_MATH_EXAMPLE_MARKDOWN }, 'converts inline-block math': { 'rst': MATH_INLINE_BLOCK, 'md': MATH_INLINE_BLOCK_MARKDOWN }, 'converts refs': { 'rst': RST_REF_EXAMPLE, 'md': RST_REF_MARKDOWN }, 'converts double colon-initiated code block and the preceding lines': { 'rst': RST_COLON_CODE_BLOCK, 'md': RST_COLON_CODE_BLOCK_MARKDOWN }, 'converts double colon-initiated code block with different indent and Python prompt': { 'rst': NUMPY_EXAMPLE, 'md': NUMPY_EXAMPLE_MARKDOWN }, 'converts version changed': { 'rst': '.. versionchanged:: 0.23.0', 'md': '*Changed in 0.23.0*' }, 'converts "see also" section': { 'rst': SEE_ALSO, 'md': SEE_ALSO_MARKDOWN }, 'converts module': { 'rst': 'Discrete Fourier Transform (:mod:`numpy.fft`)', 'md': 'Discrete Fourier Transform (`numpy.fft`)' }, 'converts note': { 'rst': NUMPY_NOTE, 'md': NUMPY_NOTE_MARKDOWN }, 'includes kwargs in parameters list': { 'rst': KWARGS_PARAMETERS, 'md': KWARGS_PARAMETERS_MARKDOWN }, 'converts numpy-style *args parameters': { 'rst': NUMPY_ARGS_PARAMETERS, 'md': NUMPY_ARGS_PARAMETERS_MARKDOWN }, 'converts signature in the first line': { 'rst': INITIAL_SIGNATURE, 'md': INITIAL_SIGNATURE_MARKDOWN }, 'separates following paragraph after a code blocks without output': { 'rst': CODE_BLOCK_BUT_NOT_OUTPUT, 'md': CODE_BLOCK_BUT_NOT_OUTPUT_MD }, 'converts block warnings': { 'rst': WARNING_BLOCK, 'md': WARNING_BLOCK_MARKDOWN }, 'converts inline-block warnings': { 'rst': LINE_WARNING, 'md': LINE_WARNING_MARKDOWN }, 'escapes double dunders': { # this is guaranteed to not be any rst markup as per # https://docutils.sourceforge.io/docs/ref/rst/restructuredtext.html#inline-markup-recognition-rules 'rst': '__init__', 'md': r'\_\_init\_\_' }, 'does not escape dunders in code': { 'rst': '`__init__`', 'md': '`__init__`' }, 'converts bibliographic references': { 'rst': REFERENCES, 'md': REFERENCES_MARKDOWN }, 'converts sphinx cross-references to func, meth, class, etc.': { 'rst': ':func:`function1`, :meth:`.Script.inline`, :class:`.Environment`', 'md': '`function1`, `Script.inline`, `Environment`' }, 'converts sphinx cross-references in Python domain': { 'rst': ':py:func:`function1`, :py:meth:`.Script.inline`, :py:class:`.Environment`', 'md': '`function1`, `Script.inline`, `Environment`' }, 'converts sphinx cross-references in C domain': { 'rst': ':c:func:`function1`, :c:struct:`Data`', 'md': '`function1`, `Data`' }, 'converts sphinx cross-references in C++ domain': { 'rst': ':cpp:func:`function1`, :cpp:var:`data`', 'md': '`function1`, `data`' }, 'converts sphinx cross-references in JS domain': { 'rst': ':js:func:`function1`, :js:class:`Math`', 'md': '`function1`, `Math`' }, 'converts sphinx params': { 'rst': ':param x: test arg', 'md': '- `x`: test arg' }, 'converts indented sphinx params': { 'rst': '\t:param x: test arg', 'md': '- `x`: test arg' }, 'converts non-standard simple table': { 'rst': SIMPLE_TABLE, 'md': SIMPLE_TABLE_MARKDOWN }, 'converts syntax within table': { 'rst': SIMPLE_TABLE_WITH_MARKUP, 'md': SIMPLE_TABLE_WITH_MARKUP_MARKDOWN }, 'converts standard simple table': { 'rst': SIMPLE_TABLE_2, 'md': SIMPLE_TABLE_2_MARKDOWN }, 'converts indented simple table': { 'rst': SIMPLE_TABLE_IN_PARAMS, 'md': SIMPLE_TABLE_IN_PARAMS_MARKDOWN }, 'converts indented grid table': { 'rst': GRID_TABLE_IN_SKLEARN, 'md': GRID_TABLE_IN_SKLEARN_MARKDOWN }, 'converts nested parameter lists': { 'rst': NESTED_PARAMETERS, 'md': NESTED_PARAMETERS_MARKDOWN }, 'converts sphinx signatures': { 'rst': SPHINX_SIGNATURE, 'md': SPHINX_SIGNATURE_MARKDOWN }, 'keeps params intact in code blocks': { 'rst': SPHINX_NESTED, 'md': SPHINX_NESTED_MARKDOWN } } def test_looks_like_rst_recognises_rst(): assert looks_like_rst(PEP_287_CODE_BLOCK) assert looks_like_rst('the following code ::\n\n\tcode') assert looks_like_rst('the following code::\n\n\tcode') assert looks_like_rst('See Also\n--------\n') assert looks_like_rst('.. versionadded:: 0.1') assert looks_like_rst('Description.\n\n:param spam: eggs.\n') def test_looks_like_rst_ignores_plain_text(): assert not looks_like_rst('this is plain text') assert not looks_like_rst('this might be **markdown**') assert not looks_like_rst('::::::\n\n\tcode') assert not looks_like_rst('::') assert not looks_like_rst('See Also: Interesting Topic') def test_rst_to_markdown_pep287(): # Converts PEP 287 examples correctly # https://www.python.org/dev/peps/pep-0287/ converted = rst_to_markdown(PEP_287_CODE_BLOCK) assert converted == PEP_287_CODE_BLOCK_MARKDOWN def test_integration(): converted = rst_to_markdown(INTEGRATION) assert RST_LINK_EXAMPLE_MARKDOWN in converted @pytest.mark.parametrize( 'rst,markdown', [[case['rst'], case['md']] for case in RST_CASES.values()], ids=RST_CASES.keys() ) def test_rst_to_markdown(rst, markdown): converted = rst_to_markdown(rst) print(converted) assert converted == markdown