eLife assement.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 236
        },
        "id": "MMaPOpxctLyB",
        "outputId": "3ff90e45-c20c-4fab-b5d0-baa1fdc21a60"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "  9%|▉         | 21/223 [00:28<04:32,  1.35s/it]\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "KeyboardInterrupt",
          "evalue": "ignored",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-18-8481193c242f>\u001b[0m in \u001b[0;36m<cell line: 46>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     46\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mid\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtqdm\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtqdm\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_ids\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     47\u001b[0m     \u001b[0mterm_counts\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mid\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcount_highlighted_terms\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mid\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 48\u001b[0;31m     \u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msleep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# to prevent flooding the server with requests\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     49\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ],
      "source": [
        "import requests\n",
        "from bs4 import BeautifulSoup\n",
        "from collections import defaultdict\n",
        "import time, tqdm\n",
        "\n",
        "base_url = 'https://api.elifesciences.org/reviewed-preprints?page={}&per-page=100&order=desc'\n",
        "reviewed_preprints_url = 'https://elifesciences.org/reviewed-preprints/{}'\n",
        "\n",
        "def get_all_ids():\n",
        "    page = 1\n",
        "    all_ids = []\n",
        "\n",
        "    while True:\n",
        "        response = requests.get(base_url.format(page))\n",
        "        data = response.json()\n",
        "\n",
        "        if not data['items']:\n",
        "            break\n",
        "\n",
        "        all_ids.extend([item['id'] for item in data['items']])\n",
        "        page += 1\n",
        "        time.sleep(0.1)  # to prevent flooding the server with requests\n",
        "\n",
        "    return all_ids\n",
        "\n",
        "def count_highlighted_terms(id):\n",
        "    response = requests.get(reviewed_preprints_url.format(id))\n",
        "    soup = BeautifulSoup(response.text, 'html.parser')\n",
        "\n",
        "    review_body = soup.find('div', class_='review-content_body')\n",
        "    if review_body is None:\n",
        "        return {}\n",
        "\n",
        "    highlights = review_body.find_all('strong', class_='highlighted-term')\n",
        "    \n",
        "    term_count = defaultdict(int)\n",
        "    for highlight in highlights:\n",
        "        term_count[highlight.text] += 1\n",
        "\n",
        "    return term_count\n",
        "\n",
        "\n",
        "all_ids = get_all_ids()\n",
        "term_counts = {}\n",
        "\n",
        "for id in tqdm.tqdm(all_ids):\n",
        "    term_counts[id] = count_highlighted_terms(id)\n",
        "    time.sleep(1)  # to prevent flooding the server with requests\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# define the categories\n",
        "significance_terms = ['landmark', 'fundamental', 'important', 'valuable', 'useful']\n",
        "strength_of_support_terms = ['exceptional', 'compelling', 'convincing', 'solid', 'incomplete', 'inadequate']\n",
        "\n",
        "# create dictionaries for the total counts\n",
        "total_significance_counts = defaultdict(int)\n",
        "total_strength_counts = defaultdict(int)\n",
        "other = defaultdict(int)\n",
        "\n",
        "# iterate through the term counts and add to the total counts\n",
        "for id, counts in term_counts.items():\n",
        "    for term, count in counts.items():\n",
        "        term_lower = term.lower().replace(\"ly\",\"\")\n",
        "        if term_lower in significance_terms:\n",
        "            total_significance_counts[term_lower] += count\n",
        "        elif term_lower in strength_of_support_terms:\n",
        "            total_strength_counts[term_lower] += count\n",
        "        else:\n",
        "          other[term_lower] += count\n",
        "\n",
        "# function to plot bar charts\n",
        "def plot_counts(counts, title, order):\n",
        "    # create a sorted dictionary based on the order list\n",
        "    sorted_counts = {term: counts.get(term, 0) for term in order}\n",
        "    \n",
        "    plt.bar(range(len(sorted_counts)), list(sorted_counts.values()), align='center')\n",
        "    plt.xticks(range(len(sorted_counts)), [k.title() for k in sorted_counts.keys()], rotation=25)  # Rotate labels and make them title case\n",
        "    plt.title(title)\n",
        "    plt.ylabel(\"Times used\")\n",
        "    \n",
        "    plt.show()\n",
        "\n",
        "# plot the counts\n",
        "plot_counts(total_significance_counts, 'Significance terms', significance_terms[::-1])\n",
        "plot_counts(total_strength_counts, 'Strength of Support terms', strength_of_support_terms[::-1])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 957
        },
        "id": "htzETrDTtUAd",
        "outputId": "137433f2-9b22-4e68-861e-4d5e994c5b03"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "E5iHWrRWxIA7"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}