PltPack
Bind your matplotlib functions with data
PltPack is a lightweight packaging tool for storing and exchanging data & code bound in a single file. It is mainly created to accelerate scientific work and is focused on supporting matplotlib package for exchanging scientific figures. Integrated with Jupyter Notebook.
Install from PyPi with pip:
pip install plt_pack
Usage
PltPack saves minimal atomic part of your code and the data required to run a function and plot a figure:
- arguments
- imports
- function code
- called sub-functions
- global variables
- used module versions
- non-default matplotlib rcParams
The most convenient way to use PltPack is to define a project with a folder where all the .plt files will be saved, and register the entry functions you would like to save. The alternative is to decorate a function with 'auto_save' method to save it with new arguments on every call.
Below is a self-explanatory example:
# imports
from matplotlib import pyplot as plt
import numpy as np
from plt_pack import PltProject
# define your project with directory for figures
plt_project = PltProject('FiguresDir')
# define your functions
# decorate them with 'register' or 'auto_save' method
@plt_project.register
def plot(x, y_list, label_list):
for y, label in zip(y_list, label_list):
plot_line(x, y, label)
add_legend()
@plt_project.auto_save(rewrite=False, datefmt='%H-%M-%S')
def plot_hist(y, bins: int = 10):
plt.hist(y, bins=bins)
# some util functions & globals defined somewhere in your
# file or Jupyter Notebook
COLOR = 'red'
def plot_line(x, y, label: str = None, ls: str = '--'):
plt.plot(x, y, ls=ls, lw=2, c=COLOR, label=label)
def add_legend():
plt.legend()
# Registered function can be saved with context parameters:
x = np.arange(10)
y_list = [np.arange(10) * i for i in range(5)]
label_list = [f'Curve #{i}' for i in range(5)]
with plt_project(rewrite=True, name='my_function'):
plot(x, y_list, label_list)
# function will be executed but also saved to my_function.plt
# file to your project folder:
assert plt_project.list_files() == ['my_function']Now you can upload this file later (non necessarily on the same machine) and reproduce the result with one call.
from plt_pack import read_plt_file
file = read_plt_file('my_function')
# or using plt_project:
# file = plt_project.load_file('path/to/file')
file.exec() # that will re-run the function
print(file.get_code_str()) # that will show all the code to reproduce itExpected output:
# Imports:
import matplotlib.pyplot as plt
# Global variables:
COLOR = 'red'
# Main function:
def plot(x, y_list, label_list):
for y, label in zip(y_list, label_list):
plot_line(x, y, label)
add_legend()
# Sub-functions:
def add_legend():
plt.legend()
def plot_line(x, y, label: str = None, ls: str = '--'):
plt.plot(x, y, ls=ls, lw=2, c=COLOR, label=label)
LICENSE
MIT
