paper-per-year 0.2.0

Generate publication per year plots for academic authors

Paper Per Year

A command-line tool to visualize an academic author's publications per year using data from Google Scholar.

Note

Numbers are not everything and number of published papers is certainly no metric for academic success.

Installation

You can run this using uvx without installation.

uvx paper-per-year [OPTIONS] AUTHOR_NAME

Alternatively, you can install it using pip.

[uv] pip install paper-per-year

Usage

paper-per-year [OPTIONS] AUTHOR_NAME

For example:

# Save plot in current directory with default style
paper-per-year "Adam Dziedzic"

# Save plot in a specific directory with custom style
paper-per-year "Adam Dziedzic" -o ~/Documents/plots --style whitegrid --context poster

The command will:

1. Search for authors matching the provided name
2. Display a list of found authors with their affiliations
3. Prompt you to select the correct author
4. Generate a beautiful PDF plot showing the number of publications per year
5. Save the plot as Author_Name.pdf in the specified directory
6. Output year-count data to stdout for potential piping

Options

• -o, --output-dir: Directory to save the output PDF (default: current directory)
• --style: Plot style (choices: darkgrid, whitegrid, dark, white, ticks; default: darkgrid)
• --context: Plot scaling context (choices: paper, notebook, talk, poster; default: talk)

Plot Features

• Beautiful Seaborn-styled visualizations
• Publication counts displayed on top of each bar
• Automatically adjusted layout and spacing
• High-resolution output (300 DPI)
• Multiple style options for different use cases

Output Format

The command outputs the year-count data to stdout in a tab-separated format:

YEAR    COUNT
2020    5
2021    3
2022    7
...

This allows for easy piping to other commands, for example:

# Get total publication count
paper-per-year "Adam Dziedzic" | awk '{sum += $2} END {print sum}'

# Find the most productive year
paper-per-year "Adam Dziedzic" | sort -k2 -nr | head -n1

Requirements

• Python 3.13 or higher
• scholarly
• numpy
• matplotlib
• seaborn
• click