Tools to manage problem packages using the Kattis problem package format.
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README.md

Kattis Problem Tools

master: Master Build Status. develop: Develop Build Status

These are tools to manage problem packages using the Kattis problem package format.

Programs Provided

The problem tools provide the following three programs:

  • verifyproblem: run a complete check on a problem
  • problem2pdf: convert a problem statement to pdf
  • problem2html: convert a problem statement to html

Running any of them with command-line option -h gives documentation on what arguments they accept.

Example Problems

A few examples of problem packages can be found in examples.

Installing problemtools

There are four recommended ways of installing and running problemtools. (For non-Linux users, "Method 2" below, to use Docker, is probably the least painful.)

Method 1: Install the Python package

Run

pip install git+https://github.com/kattis/problemtools

Or if you don't want a system-wide installation,

pip install --user git+https://github.com/kattis/problemtools

With this second option, in order to get the command line scripts, you need to make sure that the local user bin path used (e.g., on Linux, $HOME/.local/bin) is in your $PATH.

In order for problemtools to build and run properly, you also need to have LaTeX and various LaTeX packages installed. See Requirements and compatbility below for details on which packages are needed.

Method 2: Use Docker

This method allows you to run the Kattis problemtools inside a Docker container. This method is supported on any system for which Docker exists, including macOS and Windows 10.

We maintain three official problemtools Docker images on Docker Hub:

  • problemtools/full: this image contains problemtools along with compilers/interpreters for all supported programming languages.

  • problemtools/icpc: this image contains problemtools along with compilers/interpreters for the programming languages allowed in the International Collegiate Programming Contest (ICPC): C, C++, Java, Python 2+3, and Kotlin.

  • problemtools/minimal: this image only contains problemtools, no additional programming languages. As such as it is not particularly useful on its own, but if you are organizing a contest and want to set up a problemtools environment containing exactly the right set of compilers/interpreters for your contest, this is the recommended starting point.

For example, suppose you want to use the problemtools/icpc image. To get started, install the Docker CLI, and then pull the image:

docker pull problemtools/icpc

Once the image has finished downloading, you can check that it exists on your system using docker images. To launch an interactive container and play around with verifyproblem, problem2pdf, and problem2html run:

docker run --rm -it problemtools/icpc

By default, docker containers do NOT persist storage between runs, so any files you create or modify will be lost when the container stops running. Two common ways of dealing with this are:

  1. Use a bind mount to mount a directory on your machine into the docker container. This can be done as follows (see Docker documentation for further details):
    docker run --rm -it -v ${FULL_PATH_TO_MOUNT}:/kattis_work_dir problemtools/icpc
    
  2. Persist any changes you want to keep to a remote file system/source control (e.g. a remote Git repository, note however that you would first need to install Git in the image).

Building your own images

If you want a more complete environment in the Docker images (e.g. if you want to install git or your favorite editor), feel free to extend them in whichever way you like.

The problemtools/{minimal,icpc,full} images point to the latest release versions of problemtools. If for some reason you want an image containing the latest development version, you have to build it yourself from scratch (while there are problemtools/{minimal,icpc,full}:develop Docker images on Docker Hub, these are only updated sporadically for testing purposes and not kept up to date).

Method 3: Run directly from the repository.

If you intend to help develop problemtools, or if you just want a bare-bones way of running them, this is your option.

For this method, you need to clone the repository (just downloading a zip archive of it does not work, because the project has submodules that are not included in that zip archive).

In order for the tools to work, you first have to compile the various support programs, which can be done by running make in the root directory of problemtools.

When this is done, you can run the three programs bin/verifyproblem.sh, bin/problem2pdf.sh, and bin/problem2html.sh directly from the repository.

See Requirements and compatibility below for what other software needs to be installed on your machine in order for problemtools to work correctly.

Method 4: Build and install the Debian package

This applies if you are running on Debian or a Debian derivative such as Ubuntu.

As with method 3, you need to clone the repository (just downloading a zip archive of it does not work, because the project has submodules that are not included in that zip archive).

Run make builddeb in the root of the problemtools repository to build the package. It will be found as kattis-problemtools_X.Y.deb in the directory containing problemtools (i.e., one level up from the root of the repository).

To see which packages are required in order to be able to do this, see the "Build-Depends" line of the file debian/control. Note that the dependencies needed to build the Debian package are not the same as the depencies listed below, which are the dependencies for running problemtools.

The package can then be installed using (replace <version> as appropriate):

sudo gdebi kattis-problemtools_<version>.deb

This installs the three provided programs in your path and they should now be ready to use.

Configuration

(NOTE: this feature so far only exists on the develop branch and not in any release, and therefore does not yet exist in the problemtools Docker images.)

System-wide problemtools configuration files are placed in /etc/problemtools/, and user-specific configuration files are placed in $HOME/.config/problemtools/ (or in $XDG_CONFIG_HOME if this is defined). The following files can be used to change problemtools' configuration:

  1. languages.yaml. Use it to override problemtools' default programming language configuration. For instance, while the problemtools default is to use the CPython /usr/bin/python2 interpreter for Python 2, many contests, as well as the Kattis online judge, use Pypy as the interpreter for Python 2. To change this on your machine, you can simply place a file /etc/problemtools/languages.yaml (or ~/.config/problemtools/languages.yaml if you only want to make the change for your user) containing the following:

    python2:
       name: 'Python 2 w/Pypy'
       run: '/usr/bin/pypy "{mainfile}"'

    Here, overriding the name of the language is not strictly necessary, but it is often helpful to clearly indicate that Pypy is being used.

    For more details on the format of the language specifications and what the default settings are, see the default version of languages.yaml

  2. problem.yaml. For most users, this should not be edited. If you are not sure whether you should use it, then you probably shouldn't. This file can be used to specify the system defaults for those problem limits which are not given a fixed default value in the problem format specification. The system defaults assumed by problemtools can be found in (problemtools/config/problem.yaml). For instance, if you are primarily working against a system with a default memory limit of 2 GiB, you can place a file ~/.config/problemtools/problem.yaml containing:

    limits:
        memory: 2048 # (unit is MiB)

    (In principle it is possible to override the defaults of other values than the system-dependent defaults in the problem.yaml metadata files this way, but such usage is very strongly discouraged.)

Requirements and compatibility

To build and run the tools, you need Python 2 with the YAML and PlasTeX libraries, and a LaTeX installation.

Ubuntu

In Ubuntu, the precise dependencies are as follows:

libboost-regex1.54.0, libc6 (>= 2.14), libgcc1 (>= 1:4.1.1), automake, libgmp-dev, libgmp10, libgmpxx4ldbl, libstdc++6 (>= 4.4.0), python (>= 2.7), python (<< 2.8), python:any (>= 2.7.1-0ubuntu2), python-yaml, python-plastex, texlive-latex-recommended, texlive-fonts-recommended, texlive-latex-extra, texlive-lang-cyrillic, tidy, ghostscript

Fedora

On Fedora, these dependencies can be installed with:

sudo dnf install boost-regex gcc gmp-devel gmp-c++ python2 python2-pyyaml texlive-latex texlive-collection-fontsrecommended texlive-fancyhdr texlive-subfigure texlive-wrapfig texlive-import texlive-ulem texlive-xifthen texlive-overpic texlive-pbox tidy ghostscript

Followed by:

pip2 install --user plastex

Other platforms

The problem tools have not been tested on other platforms. If you do test on another platform, we would be happy to hear what worked and what did not work, so that we can write proper instructions (and try to figure out how to make the non-working stuff work).