01_Jupyter.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working with Jupyter Notebooks and IPython"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Practical course material for the ASDM Class 09 (Text Mining) by Florian Leitner.\n",
    "\n",
    "© 2016 Florian Leitner. All rights reserved."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This lecture covers some of the basics of working with Jupyter notebooks.\n",
    "Please work through it at your own pace before class."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Help, the cell cursor, and creating, editing and moving cells"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Get a reference about the Jupter keyboard shortcuts by pressing the `H` key while in **Command Mode**. Exit the keyboard reference with `ESC`. Extended help documents can be found in the \"Help\" secion of the notebook menu."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Move the \"cell cursor\" up and down by pressing the up/down arrow buttons. The cursor currently is in **Command Mode**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Press `ENTER` on a cell to start editing that cell in **Edit Mode** and `ESC` to exit edit mode without evaluating it or `SHIFT-ENTER` to evaluate it and move to the next cell; Instead, you can use `CTRL-ENTER` to evaluate the cell and stay on the same cell in Command Mode. Try this on this cell."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To insert a new cell **a**bove the current one, press `A` in _Command Mode_, and to insert the cell **b**elow the current one, press `B`. To delete a cell (DANGER WARNING!) press `X`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Did you mistakenly delete a cell with `X` after all? The latest notebooks have you covered: Press `Z` to undo a cell deletion. Try deleting this cell and then undo that."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Another new feature in the latest notebook versions: Multi-cell selection and operation. You can hold shift and select multiple cells (either with the mouse or your cursor keys) and then delete or move them around all at once."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To move a cell up or down, either use the two arrows in the toolbar above or select \"Edit\" $\\to$ \"Move Cell Up\" (or Down). While a fairly common operation, the developers [do not want](https://github.com/jupyter/notebook/issues/21) to add a preconfigured keyboard shortcut for that, however, and the discussion on it has been closed."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we shall activate inline plotting (for Numpy and Matplotlib). This command therefore is found at the head of  any notebook that should display plots from Matplotlib, but it also is handy to properly set up Numpy."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Populating the interactive namespace from numpy and matplotlib\n"
     ]
    }
   ],
   "source": [
    "%pylab inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we can plot, for example the linear function $y=x$:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5 6 7 8 9]\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10d9d0400>]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(arange(10))\n",
    "plot(arange(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That worked because both `plot` and `arange` got imported into our namespace.\n",
    "But in reality, we are calling functions in the Mathplotlib (abbreviated as `plt`) and Numpy (abbreviated as `np`) namespace:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x10fabc080>]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.arange(10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Getting help"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here is a handy way of quickly opening help about a module, class, or function: Append a `?` to the name and evalute the cell (press `CTRL-ENTER`) to get an interactive popup window."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Alternatively, send the name to the `help` function to output the documentation directly in the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function plot in module matplotlib.pyplot:\n",
      "\n",
      "plot(*args, **kwargs)\n",
      "    Plot y versus x as lines and/or markers.\n",
      "    \n",
      "    Call signatures::\n",
      "    \n",
      "        plot([x], y, [fmt], data=None, **kwargs)\n",
      "        plot([x], y, [fmt], [x2], y2, [fmt2], ..., **kwargs)\n",
      "    \n",
      "    The coordinates of the points or line nodes are given by *x*, *y*.\n",
      "    \n",
      "    The optional parameter *fmt* is a convenient way for defining basic\n",
      "    formatting like color, marker and linestyle. It's a shortcut string\n",
      "    notation described in the *Notes* section below.\n",
      "    \n",
      "    >>> plot(x, y)        # plot x and y using default line style and color\n",
      "    >>> plot(x, y, 'bo')  # plot x and y using blue circle markers\n",
      "    >>> plot(y)           # plot y using x as index array 0..N-1\n",
      "    >>> plot(y, 'r+')     # ditto, but with red plusses\n",
      "    \n",
      "    You can use `.Line2D` properties as keyword arguments for more\n",
      "    control on the  appearance. Line properties and *fmt* can be mixed.\n",
      "    The following two calls yield identical results:\n",
      "    \n",
      "    >>> plot(x, y, 'go--', linewidth=2, markersize=12)\n",
      "    >>> plot(x, y, color='green', marker='o', linestyle='dashed',\n",
      "            linewidth=2, markersize=12)\n",
      "    \n",
      "    When conflicting with *fmt*, keyword arguments take precedence.\n",
      "    \n",
      "    **Plotting labelled data**\n",
      "    \n",
      "    There's a convenient way for plotting objects with labelled data (i.e.\n",
      "    data that can be accessed by index ``obj['y']``). Instead of giving\n",
      "    the data in *x* and *y*, you can provide the object in the *data*\n",
      "    parameter and just give the labels for *x* and *y*::\n",
      "    \n",
      "    >>> plot('xlabel', 'ylabel', data=obj)\n",
      "    \n",
      "    All indexable objects are supported. This could e.g. be a `dict`, a\n",
      "    `pandas.DataFame` or a structured numpy array.\n",
      "    \n",
      "    \n",
      "    **Plotting multiple sets of data**\n",
      "    \n",
      "    There are various ways to plot multiple sets of data.\n",
      "    \n",
      "    - The most straight forward way is just to call `plot` multiple times.\n",
      "      Example:\n",
      "    \n",
      "      >>> plot(x1, y1, 'bo')\n",
      "      >>> plot(x2, y2, 'go')\n",
      "    \n",
      "    - Alternatively, if your data is already a 2d array, you can pass it\n",
      "      directly to *x*, *y*. A separate data set will be drawn for every\n",
      "      column.\n",
      "    \n",
      "      Example: an array ``a`` where the first column represents the *x*\n",
      "      values and the other columns are the *y* columns::\n",
      "    \n",
      "      >>> plot(a[0], a[1:])\n",
      "    \n",
      "    - The third way is to specify multiple sets of *[x]*, *y*, *[fmt]*\n",
      "      groups::\n",
      "    \n",
      "      >>> plot(x1, y1, 'g^', x2, y2, 'g-')\n",
      "    \n",
      "      In this case, any additional keyword argument applies to all\n",
      "      datasets. Also this syntax cannot be combined with the *data*\n",
      "      parameter.\n",
      "    \n",
      "    By default, each line is assigned a different style specified by a\n",
      "    'style cycle'. The *fmt* and line property parameters are only\n",
      "    necessary if you want explicit deviations from these defaults.\n",
      "    Alternatively, you can also change the style cycle using the\n",
      "    'axes.prop_cycle' rcParam.\n",
      "    \n",
      "    Parameters\n",
      "    ----------\n",
      "    x, y : array-like or scalar\n",
      "        The horizontal / vertical coordinates of the data points.\n",
      "        *x* values are optional. If not given, they default to\n",
      "        ``[0, ..., N-1]``.\n",
      "    \n",
      "        Commonly, these parameters are arrays of length N. However,\n",
      "        scalars are supported as well (equivalent to an array with\n",
      "        constant value).\n",
      "    \n",
      "        The parameters can also be 2-dimensional. Then, the columns\n",
      "        represent separate data sets.\n",
      "    \n",
      "    fmt : str, optional\n",
      "        A format string, e.g. 'ro' for red circles. See the *Notes*\n",
      "        section for a full description of the format strings.\n",
      "    \n",
      "        Format strings are just an abbreviation for quickly setting\n",
      "        basic line properties. All of these and more can also be\n",
      "        controlled by keyword arguments.\n",
      "    \n",
      "    data : indexable object, optional\n",
      "        An object with labelled data. If given, provide the label names to\n",
      "        plot in *x* and *y*.\n",
      "    \n",
      "        .. note::\n",
      "            Technically there's a slight ambiguity in calls where the\n",
      "            second label is a valid *fmt*. `plot('n', 'o', data=obj)`\n",
      "            could be `plt(x, y)` or `plt(y, fmt)`. In such cases,\n",
      "            the former interpretation is chosen, but a warning is issued.\n",
      "            You may suppress the warning by adding an empty format string\n",
      "            `plot('n', 'o', '', data=obj)`.\n",
      "    \n",
      "    \n",
      "    Other Parameters\n",
      "    ----------------\n",
      "    scalex, scaley : bool, optional, default: True\n",
      "        These parameters determined if the view limits are adapted to\n",
      "        the data limits. The values are passed on to `autoscale_view`.\n",
      "    \n",
      "    **kwargs : `.Line2D` properties, optional\n",
      "        *kwargs* are used to specify properties like a line label (for\n",
      "        auto legends), linewidth, antialiasing, marker face color.\n",
      "        Example::\n",
      "    \n",
      "        >>> plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)\n",
      "        >>> plot([1,2,3], [1,4,9], 'rs',  label='line 2')\n",
      "    \n",
      "        If you make multiple lines with one plot command, the kwargs\n",
      "        apply to all those lines.\n",
      "    \n",
      "        Here is a list of available `.Line2D` properties:\n",
      "    \n",
      "          agg_filter: a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array \n",
      "      alpha: float (0.0 transparent through 1.0 opaque) \n",
      "      animated: bool \n",
      "      antialiased or aa: bool \n",
      "      clip_box: a `.Bbox` instance \n",
      "      clip_on: bool \n",
      "      clip_path: [(`~matplotlib.path.Path`, `.Transform`) | `.Patch` | None] \n",
      "      color or c: any matplotlib color \n",
      "      contains: a callable function \n",
      "      dash_capstyle: ['butt' | 'round' | 'projecting'] \n",
      "      dash_joinstyle: ['miter' | 'round' | 'bevel'] \n",
      "      dashes: sequence of on/off ink in points \n",
      "      drawstyle: ['default' | 'steps' | 'steps-pre' | 'steps-mid' | 'steps-post'] \n",
      "      figure: a `.Figure` instance \n",
      "      fillstyle: ['full' | 'left' | 'right' | 'bottom' | 'top' | 'none'] \n",
      "      gid: an id string \n",
      "      label: object \n",
      "      linestyle or ls: ['solid' | 'dashed', 'dashdot', 'dotted' | (offset, on-off-dash-seq) | ``'-'`` | ``'--'`` | ``'-.'`` | ``':'`` | ``'None'`` | ``' '`` | ``''``]\n",
      "      linewidth or lw: float value in points \n",
      "      marker: :mod:`A valid marker style <matplotlib.markers>`\n",
      "      markeredgecolor or mec: any matplotlib color \n",
      "      markeredgewidth or mew: float value in points \n",
      "      markerfacecolor or mfc: any matplotlib color \n",
      "      markerfacecoloralt or mfcalt: any matplotlib color \n",
      "      markersize or ms: float \n",
      "      markevery: [None | int | length-2 tuple of int | slice | list/array of int | float | length-2 tuple of float]\n",
      "      path_effects: `.AbstractPathEffect` \n",
      "      picker: float distance in points or callable pick function ``fn(artist, event)`` \n",
      "      pickradius: float distance in points\n",
      "      rasterized: bool or None \n",
      "      sketch_params: (scale: float, length: float, randomness: float) \n",
      "      snap: bool or None \n",
      "      solid_capstyle: ['butt' | 'round' |  'projecting'] \n",
      "      solid_joinstyle: ['miter' | 'round' | 'bevel'] \n",
      "      transform: a :class:`matplotlib.transforms.Transform` instance \n",
      "      url: a url string \n",
      "      visible: bool \n",
      "      xdata: 1D array \n",
      "      ydata: 1D array \n",
      "      zorder: float \n",
      "    \n",
      "    Returns\n",
      "    -------\n",
      "    lines\n",
      "        A list of `.Line2D` objects representing the plotted data.\n",
      "    \n",
      "    \n",
      "    See Also\n",
      "    --------\n",
      "    scatter : XY scatter plot with markers of variing size and/or color (\n",
      "        sometimes also called bubble chart).\n",
      "    \n",
      "    \n",
      "    Notes\n",
      "    -----\n",
      "    **Format Strings**\n",
      "    \n",
      "    A format string consists of a part for color, marker and line::\n",
      "    \n",
      "        fmt = '[color][marker][line]'\n",
      "    \n",
      "    Each of them is optional. If not provided, the value from the style\n",
      "    cycle is used. Exception: If ``line`` is given, but no ``marker``,\n",
      "    the data will be a line without markers.\n",
      "    \n",
      "    **Colors**\n",
      "    \n",
      "    The following color abbreviations are supported:\n",
      "    \n",
      "    =============    ===============================\n",
      "    character        color\n",
      "    =============    ===============================\n",
      "    ``'b'``          blue\n",
      "    ``'g'``          green\n",
      "    ``'r'``          red\n",
      "    ``'c'``          cyan\n",
      "    ``'m'``          magenta\n",
      "    ``'y'``          yellow\n",
      "    ``'k'``          black\n",
      "    ``'w'``          white\n",
      "    =============    ===============================\n",
      "    \n",
      "    If the color is the only part of the format string, you can\n",
      "    additionally use any  `matplotlib.colors` spec, e.g. full names\n",
      "    (``'green'``) or hex strings (``'#008000'``).\n",
      "    \n",
      "    **Markers**\n",
      "    \n",
      "    =============    ===============================\n",
      "    character        description\n",
      "    =============    ===============================\n",
      "    ``'.'``          point marker\n",
      "    ``','``          pixel marker\n",
      "    ``'o'``          circle marker\n",
      "    ``'v'``          triangle_down marker\n",
      "    ``'^'``          triangle_up marker\n",
      "    ``'<'``          triangle_left marker\n",
      "    ``'>'``          triangle_right marker\n",
      "    ``'1'``          tri_down marker\n",
      "    ``'2'``          tri_up marker\n",
      "    ``'3'``          tri_left marker\n",
      "    ``'4'``          tri_right marker\n",
      "    ``'s'``          square marker\n",
      "    ``'p'``          pentagon marker\n",
      "    ``'*'``          star marker\n",
      "    ``'h'``          hexagon1 marker\n",
      "    ``'H'``          hexagon2 marker\n",
      "    ``'+'``          plus marker\n",
      "    ``'x'``          x marker\n",
      "    ``'D'``          diamond marker\n",
      "    ``'d'``          thin_diamond marker\n",
      "    ``'|'``          vline marker\n",
      "    ``'_'``          hline marker\n",
      "    =============    ===============================\n",
      "    \n",
      "    **Line Styles**\n",
      "    \n",
      "    =============    ===============================\n",
      "    character        description\n",
      "    =============    ===============================\n",
      "    ``'-'``          solid line style\n",
      "    ``'--'``         dashed line style\n",
      "    ``'-.'``         dash-dot line style\n",
      "    ``':'``          dotted line style\n",
      "    =============    ===============================\n",
      "    \n",
      "    Example format strings::\n",
      "    \n",
      "        'b'    # blue markers with default shape\n",
      "        'ro'   # red circles\n",
      "        'g-'   # green solid line\n",
      "        '--'   # dashed line with default color\n",
      "        'k^:'  # black triangle_up markers connected by a dotted line\n",
      "    \n",
      "    .. note::\n",
      "        In addition to the above described arguments, this function can take a\n",
      "        **data** keyword argument. If such a **data** argument is given, the\n",
      "        following arguments are replaced by **data[<arg>]**:\n",
      "    \n",
      "        * All arguments with the following names: 'x', 'y'.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(plt.plot)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If that isn't enough, you instead show the source code in the popup window by appending `??` (double questionmark)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "plot??"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tab completion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Tab completion allows you to search for the correct (module/class/funcion) name to use."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Try this by only entering the first few letters of each name and pressing tab to show the possible completions\n",
    "# \"np.li\" TAB [SELECT linalg] \".e\" TAB [SELECT eigh] \"?\"\n",
    "# np.linalg.eigh?\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Switching cell types: Code - Markdown"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you wish to add text or comments to your notebook, you have to swich the cell from *code* into *markdown* state."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "print(\"set this cell to markdown state by pressing M and to code state by pressing Y, both in Command Mode\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Markdown text formatting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Try copying this content:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```\n",
    "# Title\n",
    "\n",
    "## Subtitle\n",
    "\n",
    "...\n",
    "\n",
    "Markdown for `code`, *emphasized*, and **bold face** plus [links](http://www.google.com).\n",
    "\n",
    "1. first\n",
    "1. second\n",
    "1. third\n",
    "  * nested\n",
    "  * again\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And pasting it into here:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Syntax-colored code"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Start and end code regions with three backticks (\\`\\`\\`); To activate syntax coloring for a particular programming language, write the name of the language after the opening backticks, e.g.: \"\\`\\`\\`python\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "from sys import path\n",
    "print path\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ([La]TeX-based) Math typesetting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Simple inline math expressions should be surrounded by `$`; Complex expressions that should stand on their own (formulae, etc.) should be surrounded by `$$` (two dollar signs). The functionality is based on [MathJax](http://docs.mathjax.org/en/latest/tex.html#tex-support) and you can consult a [quick reference](http://meta.math.stackexchange.com/questions/5020/mathjax-basic-tutorial-and-quick-reference) for typesetting math expressions."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The Cauchy-Schwarz inequality:\n",
    "\n",
    "\\begin{equation*} \\left( \\sum_{k=1}^n a_k b_k \\right)^2 \\leq \\left( \\sum_{k=1}^n a_k^2 \\right) \\left( \\sum_{k=1}^n b_k^2 \\right) \\end{equation*}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "## IPython magic"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Sorry, this is a course on statistics, not heretics.... But here are some hints for the eager aprentice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "%magic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "%quickref"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Well, here's one magic function that can be useful if your workspace got too cluttered:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "%reset?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Once deleted, variables cannot be recovered. Proceed (y/[n])? y\n"
     ]
    }
   ],
   "source": [
    "%reset -s"
   ]
  }
 ],
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   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
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