test_rst.py

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
<https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__."""
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_REF_EXAMPLE = """See :ref:`here <timeseries.offset_aliases>` 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_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 <timeseries.offset_aliases>` for a list of
    frequency aliases.
tz : str or tzinfo, optional

To learn more about the frequency strings, please see `this link
<https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases>`__.
"""


# 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
    },
    '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\_\_'
    },
    '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 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')


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