The Nextjournal Python Environment
Default environments for Python 3 and Python 2
Nexjournal's Python 3 environment runs version nil↩ while Python 2 runs version nil↩.
Learn more about environments on Nextjournal.
1. Showcase
These packages are included in Nextjournal's Python 3 environment.
1.1. Package Management
Packages are installed using conda
or pip
version nil↩. setuptools
version nil↩ is also included for convenience. Please refer to How to Install Python Packages for more detailed information.
1.2. Plotting
The default environment comes with plotly
version nil↩ and matplotlib
version nil↩. Here are some examples of how they are used in Nextjournal:
1.2.1. Plotly
Plot a histogram of 500 values using plotly
, a plotting library for making interactive graphs online.
import plotly.graph_objs as go import numpy as np x0 = np.random.randn(quiet-butterfly↩) x1 = np.random.randn(quiet-butterfly↩)+1 trace1 = go.Histogram(x=x0, opacity=0.75) trace2 = go.Histogram(x=x1, opacity=0.75) layout = go.Layout(barmode='overlay') go.Figure(data=[trace1, trace2], layout=layout)
1.2.2. Matplotlib
Plot a 5 hertz sine wave using matplotlib
, a Python plotting library.
import matplotlib.pyplot as plt # Data for plotting t = np.arange(0.0, 2.0, 0.01) s = 1 + np.sin((sine-cycles↩ * 2)* np.pi * t) # Note that using plt.subplots below is equivalent to using # fig = plt.figure() and then ax = fig.add_subplot(111) fig, ax = plt.subplots() ax.plot(t, s) ax.set(xlabel='time (s)', ylabel='voltage (mV)', title='Sine Wave') ax.grid() fig
1.3. Data Structures
Nextjournal's default Python environment contains several packages for data manipulation and parsing.
- The SciPy ecosystem is available, including
scipy
version nil↩,numpy
version nil↩, andpandas
version nil↩. simplejson
version nil↩ makes it easy to encode/decode JSON data structures.six
version nil↩ is included to help smooth differences between Python 2 and 3.
1.3.1. Numpy
Numpy
's main object is a N-dimensional array useful for linear algebra, Fourier transforms, and random number capabilities. Here it is used to create a Mandelbrot set which is ultimately plotted using matplotlib
.
def mandelbrot( h,w, maxit=10): y,x = np.ogrid[ -1.4:1.4:h*1j, -2:0.8:w*1j ] c = x+y*1j z = c divtime = maxit + np.zeros(z.shape, dtype=int) for i in range(maxit): z = z**2 + c diverge = z * np.conj(z) > 2**2 # who is diverging div_now = diverge & (divtime==maxit) # who is diverging now divtime[div_now] = i + 100 # note when z[diverge] = 2 # avoid diverging too much return divtime fig = plt.subplots(1,figsize=(20,20)) plt.imshow(mandelbrot(1000,1000)) plt.axis('off') plt.savefig("/results/temp.png")
1.3.2. Pandas
Pandas
makes data analysis easier with Python. For example, a single instantiation of pandas
' Series
class can include all label and data information. 996 random values are generated by numpy
and the final graph is plotted with matplotlib
.
import pandas as pd ts = pd.Series(np.random.randn(pandas↩), index=pd.date_range('1/1/2000', periods=pandas↩)) ts = ts.cumsum() fig, ax = plt.subplots() ax = ts.plot() fig
1.3.3. Simplejson
Import and export JSON on Nextjournal using simplejson
. In the example below, a Python data structure input results in JSON output. The change from None
to null
is a clear indicator.
import simplejson as json json.dumps(['foo', {'bar': ('baz', None, 1.0, 2)}])
1.3.4. Six
Six
makes it easy to write Python code that is compatible with both Python 2 and Python 3.
For example, Python 2's urllib
, urllib2
, and urlparse
modules have been combined in the urllib
package in Python 3. The six.moves.urllib
package is a version-independent location for this functionality.
Python 2:
from six.moves.urllib.request import urlopen url = urlopen("http://nextjournal.com") print url.read()
Python 3:
from six.moves.urllib.request import urlopen url = urlopen("http://nextjournal.com") print(url.read())
2. Setup
2.1. Build a Minimal Python 3 Environment
Download and install conda
.
CONDA_VER="4.5.4" curl -sSL -o ~/anaconda.sh \ https://repo.continuum.io/miniconda/Miniconda3-${CONDA_VER}-Linux-x86_64.sh /bin/bash ~/anaconda.sh -b -p /opt/conda rm ~/anaconda.sh
Add conda
's library directory so ldconfig
will pick it up, set conda config
, and ensure pip
is reasonably updated. We also pin Python to the installed minor version, allowing only patch-version up/downgrades.
echo "/opt/conda/lib" >> /etc/ld.so.conf.d/conda.conf conda config --set always_yes True printf "[global]\ndisable-pip-version-check = True\n" > /etc/pip.conf echo 'pip >=18.1' > /opt/conda/conda-meta/pinned # prevent pip downgrade # upgrade Python within minor version PYTHON_MINOR=`python --version 2>&1 | sed 's/Python //;s/.[0-9] ::.*//;'` echo "python =$PYTHON_MINOR" >> /opt/conda/conda-meta/pinned conda update python conda clean -tipsy ldconfig python -V pip -V
2.2. Build the Default Python 3 Environment
2.2.1. Install
We'll install gcc
and other build tools, since some pip
installs require compilation.
apt-get -qq update apt-get install \ build-essential gfortran cmake automake libtool libltdl-dev pkg-config apt-get clean rm -r /var/lib/apt/lists/* # Clear package list so it isn't stale
This default image has support for pandas
, scipy
, matplotlib
, and plotly
. We'll also install some basic utilities, as well as setuptools
to make any additional installs less difficult. We're installing Jedi to have code completions for Python.
Some version interactions in conda centered on openssl
currently make it better to install matplotlib 2.2 here, lest we be forced to downgrade to Python 3.6.6.
conda install \ setuptools six simplejson \ plotly 'matplotlib>=2,<3.0' \ numpy scipy pandas cython jedi conda clean -tipsy ldconfig python -V pip -V
Now we can upgrade matplotlib with pip
.
pip install --upgrade matplotlib pyqt5
2.2.2. Test
python --version
import sys; sys.version
import pip; pip.__version__
import plotly; plotly.__version__
np.__version__
import matplotlib; matplotlib.__version__
import setuptools; setuptools.__version__
import six; six.__version__
import simplejson; simplejson.__version__
import pandas; pandas.__version__
import scipy; scipy.__version__
2.3. Minimal Python 2
Download and install conda
.
CONDA_VER="4.5.4" curl -sSL -o ~/anaconda.sh \ https://repo.continuum.io/miniconda/Miniconda2-${CONDA_VER}-Linux-x86_64.sh /bin/bash ~/anaconda.sh -b -p /opt/conda rm ~/anaconda.sh
Setup conda
, ld
, and pip
.
2.4. Default Python 2
2.4.1. Install
2.4.2. Test
python --version
import sys import jedi import numpy import scipy sys.version