text: // TODO: Add Athletic Skills, Office Skills,
  // Data Engineering, Data Science, ML Engineering, ... ?
  // soft skills?
  
  const levels = [
    {
      level: 1,
      title: 'Very Limited Exposure',
      description: 'This is just a baseline - I have only used the technology in a very limited capacity.',
    },
    {
      level: 2,
      title: 'Limited Exposure',
      description: 'I have used it before, either briefly or in a limited capacity, but am somewhat familiar.',
    },
    {
      level: 3,
      title: 'Significant Exposure',
      description: 'I have used it either academically or for a non-trivial project, but may not be familiar with more advanced features.',
    },
    {
      level: 4,
      title: 'Proficiency',
      description: 'I have used it almost daily for at least 6 months, either academically or for work/personal projects.',
    },
    {
      level: 5,
      title: 'Mastery',
      description: 'I am reserving this level for skills I have honed to near perfection; hopefully more to come soon!',
    },
  ];
  
  const skills = [
    {
      title: 'Javascript',
      competency: 2,
      category: ['Web Development', 'Languages', 'Javascript'],
    },
    {
      title: 'Node.JS',
      competency: 2,
      category: ['Web Development', 'Javascript'],
    },
    {
      title: 'React',
      competency: 2,
      category: ['Web Development', 'Javascript'],
    },
    {
      title: 'Bash',
      competency: 2,
      category: ['Tools', 'Languages'],
    },
    {
      title: 'Amazon Web Services',
      competency: 3,
      category: ['Web Development', 'Tools'],
    },
    {
      title: 'SQL',
      competency: 2,
      category: ['Databases', 'Languages'],
    },
    {
      title: 'ElasticSearch',
      competency: 1,
      category: ['Web Development', 'Databases'],
    },
    {
      title: 'Data Mining',
      competency: 1,
      category: ['Data Science'],
    },
    {
      title: 'Flask',
      competency: 1,
      category: ['Web Development', 'Python'],
    },
    {
      title: 'Git',
      competency: 3,
      category: ['Tools'],
    },
    {
      title: 'NumPy',
      competency: 3,
      category: ['Data Science', 'Data Engineering', 'Python'],
    },
    {
      title: 'Jupyter',
      competency: 3,
      category: ['Data Science', 'Python'],
    },
    {
      title: 'Typescript',
      competency: 2,
      category: ['Web Development', 'Languages', 'Javascript'],
    },
    {
      title: 'HTML/CSS',
      competency: 3,
      category: ['Web Development', 'Languages'],
    },
    {
      title: 'Python',
      competency: 3,
      category: ['Languages', 'Python'],
    },
    {
      title: 'C++',
      competency: 3,
      category: ['Languages'],
    },
    {
      title: 'R',
      competency: 3,
      category: ['Languages'],
    },
    {
      title: 'Java',
      competency: 4,
      category: ['Languages', 'Javascript'],
    },
    {
      title: 'Pandas',
      competency: 2,
      category: ['Data Engineering', 'Data Science', 'Python'],
    },
    {
      title: 'C',
      competency: 2,
      category: ['Languages'],
    },
    {
      title: 'C#',
      competency: 2,
      category: ['Languages'],
    },
    {
      title: 'Machine learning',
      competency: 1,
      category: ['Data Engineering', 'Data Science'],
    },
  ].map((skill) => ({ ...skill, category: skill.category.sort() }));
  
  // this is a list of colors that I like. The length should be == to the
  // number of categories. Re-arrange this list until you find a pattern you like.
  const colors = [
    '#6968b3',
    '#37b1f5',
    '#40494e',
    '#515dd4',
    '#e47272',
    '#cc7b94',
    '#3896e2',
    '#c3423f',
    '#d75858',
    '#747fff',
    '#64cb7b',
  ];
  
  const categories = [
    ...new Set(skills.reduce((acc, { category }) => acc.concat(category), [])),
  ]
    .sort()
    .map((category, index) => ({
      name: category,
      color: colors[index],
    }));
  
  export { levels, categories, skills };
  