Installation

The main CV Creator tool is created in Python and can be install through pip. See this guide for help to get pip working on your system.

With this repository cloned to disk, and Python and pip in place, install CV Creator through:

pip install cvcreator

The tool depend on a working installation of Latex:

• Windows – Install Miktex.

• Debian/Ubuntu – run sudo apt-get install texlive-latex-extra texlive-lang-european.

• Arch – run sudo pacman -Syu texlive-latexextra texlive-lang.

• Mac OSX – Install Homebrew and run brew install --cask mactex.

Basic usage

Start by creating a simple example:

cv example example.toml

Edit the resulting example.toml file with your favorite text editor. This is the content file which will be inserted into the final CV output. The different sections should be self-explanatory.

With the content ready, create a CV with:

cv create example.toml my_new_cv.pdf

It will look something like this:

Projects and publications

To include projects/publications use the flag --publications/--projects. These flags must be followed by specific tags present in the toml content file:

cv create example.yaml --projects "A1,A2"
cv create example.yaml --publications "P1,P2"

The projects/publications will be added in selected order. Alternatively, use a colon : to include all entries.

cv create example.yaml --publications :

Custom logo

There are currently two components that are Expert Analytic:

• The logo image in the upper right corner of the first document.

• The footer image on each page.

These two elements can be overridden through the .toml content file. Add the following two lines to the top of the file (outside a title scope):

logo_image = "path/to/image.png"
footer_image = "path/to/image.png"

These can be any images, but it perhaps makes sense that the logo_image is a personal photo when using the tool privately.

Technology skills

To be able to do statistics on various skills, the list of allowed skills is limited to a predefined list. To quickly list what skills are allowed, and their spelling, see:

cv skills

In addition, some skills have badges that can be activated during document creation using the --badges flag with e.g. cv create and cv latex. To list which skill can produce an icon, see:

cv skills --badges

Developer Guide

The project uses poetry to manage its development installation. Assuming poetry installed on your system, installing cvcreator for development can be done from the repository root with the command:

poetry install

This will install all required dependencies and cvcreator into a virtual environment. To enter the create environment, run:

poetry shell

Afterwards exit with:

exit

poetry run pytest --doctest-modules cvcreator/ test/

Deployment

Releases to PyPI (the repository used when using pip install) is created and deployed automatically when making a tagged released. To do so you need to:

• Update and push a new version number in pyproject.toml to branch master.

After merging to master, the workflow creates the tag and Github release for this version and uploads its wheel file to Pypi.

Docker

Cvcreator can also be run in a docker container. To build the container image, run the following command from the repository root:

docker build -t cvcreator .

Example usage of running cvcreator in the docker container:

docker run --rm -v $(pwd):/data cvcreator create /data/example.toml /data/my_cv.pdf

This will mount the current working directory into the container at /data, and run the cvcreator command to create a CV from example.toml to my_cv.pdf.

If you want it even simpler (and always have to stand in the directory where your files are located), you can create an alias in your shell configuration file like this:

alias cvcreator='docker run --rm -v $(pwd):/data cvcreator'

Then you can run cvcreator commands as if it was installed on your system, e.g.:

cvcreator create /data/example.toml /data/my_cv.pdf