graphs from conda repodata.json

DependencyGraphs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "adapted from https://gist.github.com/ericdill/9942ac55c2c9f6a550973dd2dc3653a4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import copy\n",
    "import json\n",
    "import glob\n",
    "from os.path import join, basename, isfile\n",
    "from matplotlib import pyplot as plt\n",
    "import networkx as nx\n",
    "%matplotlib inline\n",
    "\n",
    "if not isfile('repodata.json'):\n",
    "    from six.moves import urllib\n",
    "    urllib.request.urlretrieve(\"https://repo.anaconda.com/pkgs/main/linux-64/repodata.json\", \"repodata.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dg = nx.DiGraph()\n",
    "\n",
    "for rec, meta in json.load(open('repodata.json'))['packages'].items():\n",
    "    dg.add_node(meta['name'])\n",
    "    for dep in meta.get('depends', []):\n",
    "        dg.add_edge(meta['name'], dep.split(' ')[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "dg.number_of_nodes()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.draw_networkx(dg, pos, node_color='#A0CBE2', edge_color='#FFCBE2', with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def neighbor_subgraph(G, center_node, steps):\n",
    "    neighbors = set([center_node])\n",
    "    for n in range(steps):\n",
    "        immediate_neighbors = copy.copy(neighbors)\n",
    "        for neighbor in immediate_neighbors:\n",
    "            neighbors.update(nx.all_neighbors(G, neighbor))\n",
    "    return nx.subgraph(G, neighbors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sg = neighbor_subgraph(dg, 'scikit-learn', 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.draw_kamada_kawai(sg, with_labels=True, node_color='#A0CBE2', edge_color='#FFCBE2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.draw_shell(sg, with_labels=True, node_color='#A0CBE2', edge_color='#FFCBE2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.draw_random(sg, with_labels=True, node_color='#A0CBE2', edge_color='#FFCBE2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.draw_spring(sg, with_labels=True, node_color='#A0CBE2', edge_color='#FFCBE2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "nx.draw_circular(sg, with_labels=True, node_color='#A0CBE2', edge_color='#FFCBE2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://ocefpaf.github.io/python4oceanographers/blog/2014/11/17/networkX/\n",
    "def trim_nodes(G, d):\n",
    "    \"\"\"Returns a copy of G without the nodes with a degree less than d.\n",
    "    http://glowingpython.blogspot.com/2012/11/first-steps-with-networx.html\n",
    "    \"\"\"\n",
    "    Gt = G.copy()\n",
    "    dn = nx.degree(Gt)\n",
    "    for n in G.nodes():\n",
    "        if dn[n] <= d:\n",
    "            Gt.remove_node(n)\n",
    "    return Gt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "trim_graph = trim_nodes(dg, 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pos = nx.shell_layout(trim_graph)\n",
    "nx.draw_networkx(trim_graph, pos, node_color='#A0CBE2', edge_color='#FFCBE2', with_labels=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.6.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}

Thanks for the example, @msarahan! What is pos in the 4th cell?

For those not wanting to fire up notebooks to check dependencies, I wrote a CLI utility that more or less does the same thing: https://github.com/omegacen/conda-depgraph.