python

Matplotlib Graphs in Research Papers

When you write a scientific paper, one of the most common tasks is to analyze the obtained results and design beautiful graphs explaining them. Currently, in the research community, Python’s ecosystem is the most popular for achieving these goals. It provides web-based interactive computational environments (e.g., Jupyter Notebook/Lab) to write code and describe the results, and pandas and matplotlib libraries to analyze data and produce graphs correspondingly. Unfortunately due to the rich functionality, it is hard to start using them effectively in your everyday research activities when you initiate your path as a researcher. In this article, I would like to share some tips and tricks on how to employ the matplotlib library to produce nice graphs for research papers.

Introducing Pyenv pip-upgrade Plugin

In my previous articles (Configuring Python Workspace and Configuring Python Workspace: Poetry), I have described how I use pyenv to create several virtual environments. With the lapse of time, the tools that you install in these environments become outdated and you need a tool to update them. I develop a pyenv plugin that updates all packages in all or particular pyenv environments and in this post I describe how to use it.

Outdated Pytest Version in Poetry

Problem

Recently, I have updated my operating system, and as a part of this process I have installed the latest poetry version (a tool for Python dependency management). When I have started a new project using my typical routine, I have discovered that poetry cannot install development dependencies exiting with a weird SolverProblemError error.

Clearing Output Data in Jupyter Notebooks using Pre-commit Framework

Recently, I have participated in a project at AI Superior aimed at the analysis of a dataset with sensitive data. So as the data have to remain private, initially we shared the dataset through a secure channel and took measures to prevent its accidental distribution (we put the dataset in a separate directory and configured git to ignore this folder and other directories containing intermediate processing results). However, working on this project I have noticed that Jupyter notebook, that is a kind of standard tool used for data analysis, may be a source of sensitive data leakage.

Starting New Python Project in VSCode

In the previous article, I have described how poetry can be used to configure Python workspace and to create a new Python package project. Although poetry creates the structure of a package and adds some boilerplate code, in order to develop this package in VSCode we need to do some additional configurations. In this post, I describe how to start developing a new Python package project in VSCode.

Configuring Python Workspace: Poetry

In the previous article, I have described my approach to configure Python workspace. I mentioned there that I do not use poetry because it “cannot be used to specify dependencies when you work with Jupyter notebooks”. However, people (@BasicWolf and @iroln) from the Russian tech website Habr recommended me to look at poetry closer, as it apparently can fulfil all my requirements. “Two heads are better than one”, and I started to explore this tool deeper. Indeed, I have managed to fulfil all my requirements with this tool but with some configurations. In this post, I describe how to configure it to meet my requirements and how to use it.