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      <h1>Code Metrics</h1>
<p>Code metrics can be produced by static code analysis tools to determine 
complexity and non-standard practices.</p>
<h2>Why are code metrics important?</h2>
<p>Code metrics allow developers to find problematic codebase areas that may
need refactoring. In addition, some metrics such as technical debt assist 
developers in communicating to non-technical audiences why issues with a
system are occurring.</p>
<h2>Open source code metrics projects</h2>
<ul>
<li>
<p><a href="http://radon.readthedocs.org/en/latest/index.html">Radon</a> is a tool for
  obtaining raw metrics on line counts, Cyclomatic Complexity, Halstead
  metrics and maintainability metrics.</p>
</li>
<li>
<p><a href="http://www.pylint.org/">Pylint</a> contains checkers for PEP8 code 
  style compliance, design, exceptions and many other source code analysis
  tools.</p>
</li>
<li>
<p><a href="https://pypi.python.org/pypi/pyflakes">PyFlakes</a> parses source files for
  errors and reports on them.</p>
</li>
<li>
<p><a href="http://www.unixuser.org/~euske/python/pyntch/index.html">Pyntch</a> is a
  static code analyzer that attempts to detect runtime errors. It does not
  perform code style checking.</p>
</li>
</ul>
<h2>Hosted code metrics services</h2>
<ul>
<li><a href="https://landscape.io/">Landscape</a> provides free code metrics for open 
  source Python projects. Pricing is available for analyzing private 
  repositories as well.</li>
</ul>
<h2>Code metrics resources</h2>
<ul>
<li>
<p><a href="http://doughellmann.com/2008/03/01/static-code-analizers-for-python.html">Static Code Analizers for Python</a>
  is an older article but goes over the basics of what Python static code
  analyzers do.</p>
</li>
<li>
<p>This <a href="http://stackoverflow.com/questions/1428872/pylint-pychecker-or-pyflakes">Stack Overflow question on Python static code analysis tools</a>
  contains comparison discussions of PyLint, PyChecker and PyFlakes.</p>
</li>
</ul>
<h3>What's next after obtaining code metrics?</h3>
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