Fix test requirements (#919)

* Require pandoc==2.16.2 for testing
* Regenerate the pandoc versions of the sample notebooks
the representation for code cells has changed from ` ``` {.python}` to ` ``` python`
* Some tests require a python kernel

docs/CHANGELOG.md

@@ -13,6 +13,7 @@ Jupytext ChangeLog
 
 **Changed**
 - We have updated the pre-commit hooks and in particular we switched to the first stable version of `black==22.1.0`.
+- We require `pandoc==2.16.2` for testing. The representation for code cells changed from ` ``` {.python}` to ` ``` python` in that version of Pandoc ([#906](https://github.com/mwouts/jupytext/issues/906)). We don't use `pandoc>=2.17` in tests at the moment because of the introduction of cell ids that cannot be filtered.
 
 
 1.13.6 (2022-01-11)

environment-ci.yml

@@ -22,7 +22,7 @@ dependencies:
   - autopep8
   - black
   - isort>=5.3.0
-  - pandoc>=2.11.4
+  - pandoc==2.16.2
   - sphinx-gallery<0.8
   - pre-commit
   - gitpython

environment.yml

@@ -29,7 +29,7 @@ dependencies:
   - pip
   - setuptools
   - twine
-  - pandoc>=2.11.4
+  - pandoc==2.16.2
   # make html in docs folder
   - sphinx
   - tox-conda

jupytext/pandoc.py

@@ -35,16 +35,18 @@ def pandoc(args, filein=None, fileout=None):
     return out.decode("utf-8")
 
 
-def is_pandoc_available(min_version="2.7.2"):
+def is_pandoc_available(min_version="2.7.2", max_version=None):
     """Is Pandoc>=2.7.2 available?"""
     try:
-        raise_if_pandoc_is_not_available(min_version=min_version)
+        raise_if_pandoc_is_not_available(
+            min_version=min_version, max_version=max_version
+        )
         return True
     except PandocError:
         return False
 
 
-def raise_if_pandoc_is_not_available(min_version="2.7.2"):
+def raise_if_pandoc_is_not_available(min_version="2.7.2", max_version=None):
     """Raise with an informative error message if pandoc is not available"""
     try:
         from pkg_resources import parse_version
@@ -61,7 +63,13 @@ def raise_if_pandoc_is_not_available(min_version="2.7.2"):
     if parse_version(version) < parse_version(min_version):
         raise PandocError(
             f"The Pandoc Markdown format requires 'pandoc>={min_version}', "
-            f"but pandoc version {version} was not found"
+            f"but pandoc version {version} was found"
+        )
+
+    if max_version and parse_version(version) > parse_version(max_version):
+        raise PandocError(
+            f"The Pandoc Markdown format requires 'pandoc<={max_version}', "
+            f"but pandoc version {version} was found"
         )
 
     return version

tests/notebooks/mirror/ipynb_to_pandoc/Notebook_with_R_magic.md

@@ -15,20 +15,20 @@ This notebook shows the use of R cells to generate plots
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 %load_ext rpy2.ipython
 ```
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 %%R
 suppressMessages(require(tidyverse))
 ```
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 %%R
 ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point()
 ```
@@ -39,7 +39,7 @@ The default plot dimensions are not good for us, so we use the -w and -h paramet
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 %%R -w 400 -h 240
 ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point()
 ```

tests/notebooks/mirror/ipynb_to_pandoc/Notebook_with_more_R_magic_111.md

@@ -9,7 +9,7 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.python}
+``` python
 %load_ext rpy2.ipython
 import pandas as pd
 
@@ -25,7 +25,7 @@ df = pd.DataFrame(
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 %%R -i df
 library("ggplot2")
 ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z))

tests/notebooks/mirror/ipynb_to_pandoc/World population.md

@@ -19,7 +19,7 @@ using the [wbdata](https://github.com/OliverSherouse/wbdata) python package
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 import pandas as pd
 import wbdata as wb
 
@@ -34,7 +34,7 @@ the World Bank site.
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 wb.search_indicators('Population, total')  # SP.POP.TOTL
 # wb.search_indicators('area')
 # => https://data.worldbank.org/indicator is easier to use
@@ -46,7 +46,7 @@ Now we download the population data
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 indicators = {'SP.POP.TOTL': 'Population, total',
               'AG.SRF.TOTL.K2': 'Surface area (sq. km)',
               'AG.LND.TOTL.K2': 'Land area (sq. km)',
@@ -61,7 +61,7 @@ World is one of the countries
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 data.loc['World']
 ```
 :::
@@ -71,7 +71,7 @@ Can we classify over continents?
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna(
 ).sort_values().tail(60).index.get_level_values('country')
 ```
@@ -82,7 +82,7 @@ Extract zones manually (in order of increasing population)
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 zones = ['North America', 'Middle East & North Africa',
          'Latin America & Caribbean', 'Europe & Central Asia',
          'Sub-Saharan Africa', 'South Asia',
@@ -95,7 +95,7 @@ And extract population information (and check total is right)
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 population = data.loc[zones]['Population, total'].swaplevel().unstack()
 population = population[zones]
 assert all(data.loc['World']['Population, total'] == population.sum(axis=1))
@@ -107,13 +107,13 @@ assert all(data.loc['World']['Population, total'] == population.sum(axis=1))
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 import matplotlib.pyplot as plt
 ```
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 plt.clf()
 plt.figure(figsize=(10, 5), dpi=100)
 plt.stackplot(population.index, population.values.T / 1e9)
@@ -135,7 +135,7 @@ now we just do a stacked bar plot.
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 import plotly.offline as offline
 import plotly.graph_objs as go
 
@@ -144,7 +144,7 @@ offline.init_notebook_mode()
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 bars = [go.Bar(x=population.index, y=population[zone], name=zone)
         for zone in zones]
 fig = go.Figure(data=bars,

tests/notebooks/mirror/ipynb_to_pandoc/cat_variable.md

@@ -9,7 +9,7 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.python}
+``` python
 cat = 42
 ```
 :::

tests/notebooks/mirror/ipynb_to_pandoc/convert_to_py_then_test_with_update83.md

@@ -9,7 +9,7 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.python}
+``` python
 %%time
 
 print('asdf')
@@ -21,6 +21,6 @@ Thanks for jupytext!
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 ```
 :::

tests/notebooks/mirror/ipynb_to_pandoc/frozen_cell.md

@@ -9,14 +9,14 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.python}
+``` python
 # This is an unfrozen cell. Works as usual.
 print("I'm a regular cell so I run and print!")
 ```
 :::
 
 ::: {.cell .code deletable="false" editable="false" run_control="{\"frozen\":true}"}
-``` {.python}
+``` python
 # This is an frozen cell
 print("I'm frozen so Im not executed :(")
 ```

tests/notebooks/mirror/ipynb_to_pandoc/ir_notebook.md

@@ -13,18 +13,18 @@ This is a jupyter notebook that uses the IR kernel.
 :::
 
 ::: {.cell .code}
-``` {.R}
+``` R
 sum(1:10)
 ```
 :::
 
 ::: {.cell .code}
-``` {.R}
+``` R
 plot(cars)
 ```
 :::
 
 ::: {.cell .code}
-``` {.R}
+``` R
 ```
 :::

tests/notebooks/mirror/ipynb_to_pandoc/julia_benchmark_plotly_barchart.md

@@ -9,7 +9,7 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.julia}
+``` julia
 # IJulia rocks! So does Plotly. Check it out
 
 using Plotly
@@ -21,7 +21,7 @@ Plotly.signin(username, api_key)
 :::
 
 ::: {.cell .code}
-``` {.julia}
+``` julia
 # Following data taken from http://julialang.org/ frontpage 
 benchmarks = ["fib", "parse_int", "quicksort3", "mandel", "pi_sum", "rand_mat_stat", "rand_mat_mul"]
 platforms = ["Fortran", "Julia", "Python", "R", "Matlab", "Mathematica", "Javascript", "Go"]
@@ -70,7 +70,7 @@ display("text/html", s)
 :::
 
 ::: {.cell .code}
-``` {.julia}
+``` julia
 # checkout https://plot.ly/api/ for more Julia examples!
 # But to show off some other Plotly features:
 x = 1:1500

tests/notebooks/mirror/ipynb_to_pandoc/jupyter.md

@@ -15,7 +15,7 @@ This notebook is a simple jupyter notebook. It only has markdown and code cells.
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 a = 1
 b = 2
 a + b
@@ -27,13 +27,13 @@ Now we return a few tuples
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 a, b
 ```
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 a, b, a+b
 ```
 :::

tests/notebooks/mirror/ipynb_to_pandoc/jupyter_again.md

@@ -9,7 +9,7 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.python}
+``` python
 c = '''
 title: "Quick test"
 output:
@@ -23,14 +23,14 @@ editor_options:
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 import yaml
 print(yaml.dump(yaml.load(c)))
 ```
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 ?next
 ```
 :::

tests/notebooks/mirror/ipynb_to_pandoc/jupyter_with_raw_cell_in_body.md

@@ -9,7 +9,7 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.python}
+``` python
 1+2+3
 ```
 :::

tests/notebooks/mirror/ipynb_to_pandoc/jupyter_with_raw_cell_on_top.md

@@ -23,12 +23,12 @@ editor_options:
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 1+2+3
 ```
 :::
 
 ::: {.cell .code}
-``` {.python}
+``` python
 ```
 :::

tests/notebooks/mirror/ipynb_to_pandoc/notebook_with_complex_metadata.md

@@ -9,6 +9,6 @@ jupyter:
 ---
 
 ::: {.cell .code}
-``` {.python}
+``` python
 ```
 :::