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|
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_LINK_MULTILINE_EXAMPLE = """
See
`strftime documentation
<https://docs.python.org/3/library/datetime.html
#strftime-and-strptime-behavior>`_ 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 <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_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 <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
},
'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
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