1 Pheasant 2.2.19

1.1 Overview

Welcome to Pheasant. Pheasant is a Markdown converter which is designed to work with MkDocs as a plugin.

Highlights include:

  • Auto generation of outputs for a fenced code block or inline code in Markdown source using Jupyter client. The code language is not restricted to Python.
  • Auto numbering of headers, figures, and tables, and etc. Numbered objects can be linked from other Markdown sources.

1.2 Installation

You can install Pheasant from PyPI.

$ pip install pheasant

If you use Pheasant as a plugin of MkDocs, you also need to install it.

$ pip install mkdocs

In your mkdocs.yml, add lines below to register Pheasant as a MkDocs plugin.

  - pheasant

1.3 Getting Started

1.3.1 Auto generation of the executed outputs with Jupyter client

In a markdown fenced code below,


a print function is executed via Jupyter client and converted into HTML source:

<div class="input"><pre><code class="python">print(1)</code></pre></div>
<div class="stdout"><pre><code class="text">1</code></pre></div>

Then, finally rendered as:


[3] 2019-04-24 22:14:35 (10.0ms) python3 (23.0ms)


Other language code can be executed if a kernel for the language has been installed. For example,

console.log("Hello Javascript")

You can check the kernel name and its total execution count during the conversion process at the right side of input cells.

1.3.2 Inline code embeded in a Markdown source

"Inline code" is a powerful feature of Pheasant. Any python codes surrounded by {{ and }} are automatically executed and the result remains there. For example, {{3*5}} becomes 15. Variables can be assigned in an inline code like this: {{name='Pheasant'}}. Then, "I'm {{name}}." becomes "I'm Pheasant."

1.3.3 Visualization

Pheasant supports various output formats other than the standard stream (sys.stdout/sys.stderr) or a plain text output. For example, you can create a PNG image using Matplotlib. First, import Matplotlib plotting library.

import matplotlib.pyplot as plt
import matplotlib.pyplot as plt

[7] 2019-04-24 22:14:35 (128ms) python3 (177ms)

Plot a line.

plt.plot([1, 3])
plt.plot([1, 3])

[8] 2019-04-24 22:14:35 (127ms) python3 (304ms)

[<matplotlib.lines.Line2D at 0x18d89db4748>]


Execution of the above Markdown source on a Jupyter client creates a plain text output as an execute result and a PNG image as display data. You may want to display only the image. You can set inline option to a fenced code after a language identifier:

```python inline
plt.plot([1, 2])


Pheasant also supports Bokeh's HTML output.

from bokeh.plotting import figure
plot = figure(plot_width=250, plot_height=250)
plot.circle([1, 2, 3, 4, 5], [1, 2, 3, 4, 5], size=10)

[10] 2019-04-24 22:14:35 (28.0ms) python3 (444ms)

As well as a fenced code style, we can choose inline code style: {{plot}}

Furthermore, Pheasant supports HoloViews objects as well as interactive HoloMap.

import holoviews as hv
hv.Curve(((1, 2), (2, 3)))

[12] 2019-04-24 22:14:36 (256ms) python3 (723ms)

HoloMap can work as in a Jupyter Notebook.

import numpy as np

def sine_curve(phase, freq):
    xvals = [0.1* i for i in range(100)]
    return hv.Curve((xvals, [np.sin(phase+freq*x) for x in xvals]))

frequencies = [0.5, 0.75, 1.0]
curve_dict = {f: sine_curve(0, f) for f in frequencies}
hv.HoloMap(curve_dict, kdims='Frequency')

[13] 2019-04-24 22:14:36 (99.0ms) python3 (822ms)

Finally, Altair plots from official Example Gallery,

import altair as alt
import pandas as pd

source = pd.DataFrame({
    'a': ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I'],
    'b': [30, 55, 43, 91, 81, 53, 19, 87, 52]

alt.Chart(source).mark_bar().encode(x='a', y='b')

[14] 2019-04-24 22:14:36 (26.0ms) python3 (848ms)

import altair as alt
from vega_datasets import data

source = data.seattle_weather()
brush = alt.selection(type='interval', encodings=['x'])

bars = alt.Chart().mark_bar().encode(
    opacity=alt.condition(brush, alt.OpacityValue(1), alt.OpacityValue(0.7))

line = alt.Chart().mark_rule(color='firebrick').encode(

alt.layer(bars, line, data=source)

[15] 2019-04-24 22:14:36 (196ms) python3 (1.04s)

1.3.4 Auto numbering of headers, figures, tables, etc.

As you can see, all of headers are numbered in this document. This numbering has done by Pheasant automatically. In addition, Pheasant can count the number of figures, tables, etc. and give the identical number to each object.

You can use a special "header" statement for figure, table, etc. to number them like below:

#Fig Markdown link for an image can be numbered. {#cat#}


Figure 1 Markdown link for an image can be numbered.

Supported numbered headers are shown in Table 1:

Table 1 Supported numbered headers

Type Markdown
Header # (title)
Figure #Figure (title), #Fig (title)
Table #Table (title), #Tab (title)
Equation #Eq (equation), #Eq* (equation)
[other] #[other] (title)

In the above Markdown source, {#<tag>#} is an ID tag for hyperlink described below. Off course, you can use any code to create a figure.

#Figure A Matplotlib figure
plt.plot([2, 4])


Figure 2 A Matplotlib figure

Like figures, tables can be numbered.

#Table A Markdown table
a | b
0 | 1
2 | 3

Table 2 A Markdown table

a b
0 1
2 3

Pandas's DataFarme is useful to create a table programmatically.

#Table A Pandas's DataFrame
import pandas as pd
pd.DataFrame([[1, 2], [3, 4]], index=list('XY'), columns=list('ab'))

Table 3 A Pandas's DataFrame

a b
X 1 2
Y 3 4

A plain Markdown source which is not processed by Pheasant has to be separated by a blank line from the following Markdown source which is not a part of the figure or table. If a figure or table has blank lines within it, you have to write the content in a fenced code with tilde (~~~).

#Fig A figure with a blank line




Figure 3 A figure with a blank line

In addition, Pheasant provides an easy way to number figures, tables, etc. regardless of whether they actually have any blank lines or not. Try this:

#Figure {{plot}} Inline numbering method.

Figure 4 Inline numbering method.

Numbered objects are linked from Markdown source using {#<tag>#}:

For example, go to Fig. {#cat#}

For example, go to Fig. 1

You can add external link from section headers.

#### MkDocs (https://www.mkdocs.org/) MkDocs