Skip to content

Instantly share code, notes, and snippets.

Embed
What would you like to do?
Further exploration of line lengths and PEP8
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# PEP8 Line Distributions\n",
"\n",
"A followup to http://jakevdp.github.io/blog/2017/11/09/exploring-line-lengths-in-python-packages/ with one change: it removes all comments and docstrings."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import matplotlib.pyplot as plt\n",
"import numpy as np\n",
"from scipy import stats, optimize"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"# from https://stackoverflow.com/questions/1769332/script-to-remove-python-comments-docstrings\n",
"# modified for compatibility with Python 3\n",
"\n",
"from io import StringIO\n",
"import tokenize\n",
"\n",
"def remove_comments_and_docstrings(source):\n",
" \"\"\"\n",
" Returns 'source' minus comments and docstrings.\n",
" \"\"\"\n",
" io_obj = StringIO(source)\n",
" out = \"\"\n",
" prev_toktype = tokenize.INDENT\n",
" last_lineno = -1\n",
" last_col = 0\n",
" for tok in tokenize.generate_tokens(io_obj.readline):\n",
" token_type = tok[0]\n",
" token_string = tok[1]\n",
" start_line, start_col = tok[2]\n",
" end_line, end_col = tok[3]\n",
" ltext = tok[4]\n",
" # The following two conditionals preserve indentation.\n",
" # This is necessary because we're not using tokenize.untokenize()\n",
" # (because it spits out code with copious amounts of oddly-placed\n",
" # whitespace).\n",
" if start_line > last_lineno:\n",
" last_col = 0\n",
" if start_col > last_col:\n",
" out += (\" \" * (start_col - last_col))\n",
" # Remove comments:\n",
" if token_type == tokenize.COMMENT:\n",
" pass\n",
" # This series of conditionals removes docstrings:\n",
" elif token_type == tokenize.STRING:\n",
" if prev_toktype != tokenize.INDENT:\n",
" # This is likely a docstring; double-check we're not inside an operator:\n",
" if prev_toktype != tokenize.NEWLINE:\n",
" # Note regarding NEWLINE vs NL: The tokenize module\n",
" # differentiates between newlines that start a new statement\n",
" # and newlines inside of operators such as parens, brackes,\n",
" # and curly braces. Newlines inside of operators are\n",
" # NEWLINE and newlines that start new code are NL.\n",
" # Catch whole-module docstrings:\n",
" if start_col > 0:\n",
" # Unlabelled indentation means we're inside an operator\n",
" out += token_string\n",
" # Note regarding the INDENT token: The tokenize module does\n",
" # not label indentation inside of an operator (parens,\n",
" # brackets, and curly braces) as actual indentation.\n",
" # For example:\n",
" # def foo():\n",
" # \"The spaces before this docstring are tokenize.INDENT\"\n",
" # test = [\n",
" # \"The spaces before this string do not get a token\"\n",
" # ]\n",
" else:\n",
" out += token_string\n",
" prev_toktype = token_type\n",
" last_col = end_col\n",
" last_lineno = end_line\n",
" return out"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"# Python 3.X\n",
"import os\n",
"\n",
"def iter_lines(module):\n",
" \"\"\"Iterate over all lines of Python in module\"\"\"\n",
" for root, dirs, files in os.walk(module.__path__[0]):\n",
" for filename in files:\n",
" if filename.endswith('.py'):\n",
" with open(os.path.join(root, filename)) as f:\n",
" source = f.read()\n",
" source_no_comments = remove_comments_and_docstrings(source)\n",
" yield from (line for line in source_no_comments.splitlines() if line.strip())"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"def lognorm_model(x, theta):\n",
" amp, mu, sigma = theta\n",
" return amp * stats.lognorm.pdf(x, scale=np.exp(mu), s=sigma)\n",
"\n",
"def minfunc(theta, lengths, freqs):\n",
" return np.sum((freqs - lognorm_model(lengths, theta)) ** 2)\n",
"\n",
"def lognorm_mode(amp, mu, sigma):\n",
" return np.exp(mu - sigma ** 2)\n",
"\n",
"def lognorm_std(amp, mu, sigma):\n",
" var = (np.exp(sigma ** 2) - 1) * np.exp(2 * mu + sigma ** 2)\n",
" return np.sqrt(var)\n",
"\n",
"def hist_linelengths(module, ax):\n",
" \"\"\"Plot a histogram of lengths of unique lines in the given module\"\"\"\n",
" lengths = [len(line.rstrip('\\n')) for line in set(iter_lines(module))]\n",
" h = ax.hist(lengths, bins=np.arange(125) + 0.5, histtype='step', linewidth=1.5)\n",
" ax.axvline(x=79.5, linestyle=':', color='black')\n",
" ax.set(title=\"{0} {1}\".format(module.__name__, module.__version__),\n",
" xlim=(1, 100),\n",
" ylim=(0, None),\n",
" xlabel='characters in line',\n",
" ylabel='number of lines')\n",
" return h\n",
"\n",
"def hist_linelengths_with_fit(module, ax, indices=slice(50)):\n",
" counts, bins, _ = hist_linelengths(module, ax)\n",
" lengths = 0.5 * (bins[:-1] + bins[1:])\n",
" opt = optimize.minimize(minfunc, x0=[1E5, 4, 0.5],\n",
" args=(lengths[indices], counts[indices]),\n",
" method='Nelder-Mead')\n",
" model_counts = lognorm_model(lengths, opt.x)\n",
" ax.fill_between(lengths, model_counts, alpha=0.3, color='gray')\n",
" \n",
" # Add text describing mu and sigma\n",
" \n",
" A, mu, sigma = opt.x\n",
" mode = np.exp(mu - sigma ** 2)\n",
" ax.text(0.22, 0.15, 'mode = {0:.1f}'.format(lognorm_mode(*opt.x)),\n",
" transform=ax.transAxes, size=14)\n",
" ax.text(0.22, 0.05, 'stdev = {0:.1f}'.format(lognorm_std(*opt.x)),\n",
" transform=ax.transAxes, size=14)\n",
" \n",
" return opt.x"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": "iVBORw0KGgoAAAANSUhEUgAAA1MAAAGDCAYAAADOGUqaAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nD/4fFGOwceskXKAAAAAASUVORK5CYII=\n",
"text/plain": [
"<matplotlib.figure.Figure at 0x10691d4e0>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import numpy, scipy, pandas, matplotlib, sklearn, astropy\n",
"\n",
"modules = [numpy, scipy, pandas, matplotlib, sklearn, astropy]\n",
"\n",
"fig, ax = plt.subplots(2, 3, figsize=(14, 6), sharex=True)\n",
"fig.subplots_adjust(hspace=0.2, wspace=0.2)\n",
"\n",
"fits = {}\n",
"\n",
"for axi, module in zip(ax.flat, modules):\n",
" fits[module.__name__] = hist_linelengths_with_fit(module, ax=axi)\n",
"\n",
"for axi in ax[0]:\n",
" axi.set_xlabel('')\n",
"for axi in ax[:, 1:].flat:\n",
" axi.set_ylabel('')"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.6.1"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment