Rename nb-cell/nb-raw to code-cell/raw-cell

demo/World population.mystnb

@@ -15,7 +15,7 @@ In the below we retrieve population data from the
 [World Bank](http://www.worldbank.org/)
 using the [wbdata](https://github.com/OliverSherouse/wbdata) python package
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 import pandas as pd
 import wbdata as wb
 
@@ -26,15 +26,15 @@ pd.options.display.max_columns = 20
 Corresponding indicator is found using search method - or, directly,
 the World Bank site.
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 wb.search_indicators('Population, total')  # SP.POP.TOTL
 # wb.search_indicators('area')
 # => https://data.worldbank.org/indicator is easier to use
 ```
 
 Now we download the population data
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 indicators = {'SP.POP.TOTL': 'Population, total',
               'AG.SRF.TOTL.K2': 'Surface area (sq. km)',
               'AG.LND.TOTL.K2': 'Land area (sq. km)',
@@ -45,20 +45,20 @@ data
 
 World is one of the countries
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 data.loc['World']
 ```
 
 Can we classify over continents?
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 data.loc[(slice(None), '2017-01-01'), :]['Population, total'].dropna(
 ).sort_values().tail(60).index.get_level_values('country')
 ```
 
 Extract zones manually (in order of increasing population)
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 zones = ['North America', 'Middle East & North Africa',
          'Latin America & Caribbean', 'Europe & Central Asia',
          'Sub-Saharan Africa', 'South Asia',
@@ -67,19 +67,19 @@ zones = ['North America', 'Middle East & North Africa',
 
 And extract population information (and check total is right)
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 population = data.loc[zones]['Population, total'].swaplevel().unstack()
 population = population[zones]
 assert all(data.loc['World']['Population, total'] == population.sum(axis=1))
 ```
 
 ## Stacked area plot with matplotlib
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 import matplotlib.pyplot as plt
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 plt.clf()
 plt.figure(figsize=(10, 5), dpi=100)
 plt.stackplot(population.index, population.values.T / 1e9)
@@ -97,14 +97,14 @@ selected legends) are
 [on their way](https://github.com/plotly/plotly.js/pull/2960) at Plotly. For
 now we just do a stacked bar plot.
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 import plotly.offline as offline
 import plotly.graph_objs as go
 
 offline.init_notebook_mode()
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 bars = [go.Bar(x=population.index, y=population[zone], name=zone)
         for zone in zones]
 fig = go.Figure(data=bars,

docs/formats.md

@@ -93,7 +93,7 @@ Similar to the Markdown format, MyST-NB uses code blocks to contain code cells.
 The difference though, is that the metadata is contained in a YAML block:
 
 ````md
-```{nb-code} ipython3
+```{code-cell} ipython3
 ---
 other:
   more: true
@@ -111,7 +111,7 @@ Also, where possible the conversion will use the short-hand metadata format
 (see the [MyST guide](https://myst-parser.readthedocs.io/en/latest/using/syntax.html#parameterizing-directives)):
 
 ````md
-```{nb-code} ipython3
+```{code-cell} ipython3
 :tags: [hide-output, show-input]
 
 print("Hallo!")
@@ -121,7 +121,7 @@ print("Hallo!")
 Raw cells are also represented in a similare fashion:
 
 ````md
-```{nb-raw}
+```{raw-cell}
 :raw_mimetype: text/html
 
 <b>Bold text<b>

jupytext/myst.py

@@ -8,8 +8,8 @@
 import yaml
 
 MYST_FORMAT_NAME = "mystnb"
-CODE_DIRECTIVE = "nb-code"
-RAW_DIRECTIVE = "nb-raw"
+CODE_DIRECTIVE = "code-cell"
+RAW_DIRECTIVE = "raw-cell"
 
 
 class CompactDumper(yaml.SafeDumper):

tests/notebooks/mirror/ipynb_to_myst/Notebook with function and cell metadata 164.mystnb

@@ -7,14 +7,14 @@ nbformat: 4
 nbformat_minor: 2
 ---
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 1 + 1
 ```
 
 A markdown cell
 And below, the cell for function f has non trivial cell metadata. And the next cell as well.
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 ---
 attributes:
   classes: []
@@ -25,7 +25,7 @@ def f(x):
     return x
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 ---
 attributes:
   classes: []
@@ -37,6 +37,6 @@ f(5)
 
 More text
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 2 + 2
 ```

tests/notebooks/mirror/ipynb_to_myst/Notebook with html and latex cells.mystnb

@@ -7,27 +7,27 @@ nbformat: 4
 nbformat_minor: 2
 ---
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 %%html
 <p><a href="https://github.com/mwouts/jupytext", style="color: rgb(0,0,255)">Jupytext</a> on GitHub</p>
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 %%latex
 $\frac{\pi}{2}$
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 %load_ext rpy2.ipython
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 %%R
 library(ggplot2)
 ggplot(data=data.frame(x=c('A', 'B'), y=c(5, 2)), aes(x,weight=y)) + geom_bar()
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 %matplotlib inline
 import pandas as pd
 pd.Series({'A':5, 'B':2}).plot(figsize=(3,2), kind='bar')

tests/notebooks/mirror/ipynb_to_myst/Notebook with many hash signs.mystnb

@@ -12,7 +12,7 @@ This is a notebook that contains many hash signs.
 Hopefully its python representation is not recognized as a Sphinx Gallery script...
 ##################################################################
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 some = 1
 code = 2
 some+code

tests/notebooks/mirror/ipynb_to_myst/Notebook with metadata and long cells.mystnb

@@ -27,7 +27,7 @@ with a code block inside it
 
 After that cell we'll have a code cell
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 2 + 2
 
 
@@ -36,7 +36,7 @@ After that cell we'll have a code cell
 
 Followed by a raw cell
 
-```{nb-raw}
+```{raw-cell}
 This is 
 the content
 of the raw cell
@@ -48,15 +48,15 @@ of the raw cell
 
 This is a markdown cell with cell metadata `{"key": "value"}`
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 ---
 .class: null
 tags: [parameters]
 ---
 """This is a code cell with metadata `{"tags":["parameters"], ".class":null}`"""
 ```
 
-```{nb-raw}
+```{raw-cell}
 :key: value
 
 This is a raw cell with cell metadata `{"key": "value"}`

tests/notebooks/mirror/ipynb_to_myst/Notebook_with_R_magic.mystnb

@@ -11,23 +11,23 @@ nbformat_minor: 2
 
 This notebook shows the use of R cells to generate plots
 
-```{nb-code} ipython2
+```{code-cell} ipython2
 %load_ext rpy2.ipython
 ```
 
-```{nb-code} ipython2
+```{code-cell} ipython2
 %%R
 suppressMessages(require(tidyverse))
 ```
 
-```{nb-code} ipython2
+```{code-cell} ipython2
 %%R
 ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point()
 ```
 
 The default plot dimensions are not good for us, so we use the -w and -h parameters in %%R magic to set the plot size
 
-```{nb-code} ipython2
+```{code-cell} ipython2
 %%R -w 400 -h 240
 ggplot(iris, aes(x = Sepal.Length, y = Petal.Length, color=Species)) + geom_point()
 ```

tests/notebooks/mirror/ipynb_to_myst/Notebook_with_more_R_magic_111.mystnb

@@ -7,7 +7,7 @@ nbformat: 4
 nbformat_minor: 2
 ---
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 %load_ext rpy2.ipython
 import pandas as pd
 
@@ -21,7 +21,7 @@ df = pd.DataFrame(
 )
 ```
 
-```{nb-code} ipython3
+```{code-cell} ipython3
 %%R -i df
 library("ggplot2")
 ggplot(data = df) + geom_point(aes(x = X, y = Y, color = Letter, size = Z))

tests/notebooks/mirror/ipynb_to_myst/R notebook with invalid cell keys.mystnb

@@ -9,7 +9,7 @@ nbformat_minor: 2
 
 This notebook was created with IRKernel 0.8.12, and is not completely valid, as the code cell below contains an unexpected 'source' entry. This did cause https://github.com/mwouts/jupytext/issues/234. Note that the problem is solved when one upgrades to IRKernel 1.0.0.
 
-```{nb-code} r
+```{code-cell} r
 library("ggplot2")
 ggplot(mtcars, aes(mpg)) + stat_ecdf()
 ```