Py_lectures_07_A_small_project.ipynb

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   "source": [
    "# How to structure a working code: a small example\n",
    "\n",
    "This simple script plots the info about the students of a classroom, the real students of the course itself.\n",
    "\n",
    "In particular, we limit to the info about the Departments (cds) they belong to."
   ]
  },
  {
   "cell_type": "markdown",
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   "source": [
    "## Structure\n",
    "\n",
    "To make the code simple to use and read, let's divide into three scripts having different scopes\n",
    "\n",
    "1. classroom.py : load the students' database and estract info by using the id_code (matricola) or the surname\n",
    "1. customplots.py : prepare the plot as pie or bar to show the info graphically\n",
    "1. stats_on_cds.py : print the info about the cds of the students"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## classroom.py"
   ]
  },
  {
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   "execution_count": 2,
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     "output_type": "stream",
     "text": [
      "There are 3 students from Aerospace Engineering\n",
      "There are 3 students from Bioengineering and Medical-Surgical sciences\n",
      "There are 2 students from Chemical Engineering\n",
      "There are 14 students from Electrical, Electronics and Communications Engineering\n",
      "There are 4 students from Energetics\n",
      "There are 3 students from Physics\n",
      "There is 1 student from Civil and Environmental Engineering\n",
      "There are 15 students from Computer and Control Engineering\n",
      "There are 3 students from Mechanical Engineering\n",
      "There are 4 students from Metrology\n",
      "There are 2 students from Materials Science and Technology\n",
      "There is 1 student from Urban and Regional Development\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "Script to load info\n",
    "of students from a cvs database\n",
    "\"\"\"\n",
    "import os\n",
    "import pandas as pd\n",
    "from PIL import Image\n",
    "import requests\n",
    "from io import BytesIO\n",
    "import webbrowser\n",
    "\n",
    "def cds_polito(fname):\n",
    "    \"\"\"\n",
    "    get the Names of the Departments at polito\n",
    "    given as short name, long name\n",
    "    \"\"\"\n",
    "    cds = dict()\n",
    "    with open(fname) as f:\n",
    "        data = f.readlines()\n",
    "    for row in data:\n",
    "        # Split only using the first comma\n",
    "        s, l = row.split(\",\", 1)\n",
    "        # Populate the dict\n",
    "        cds[s] = l.strip() # Clean the spaces\n",
    "    return cds\n",
    "\n",
    "class Classroom:\n",
    "    \"\"\"\n",
    "    class to load a csv file\n",
    "    containing a table of students\n",
    "    \n",
    "    It is a combination of semi-private methods like\n",
    "    _get_student_info_by_*\n",
    "    and a public one \n",
    "        get_student_info(tag)\n",
    "    which accepts a tag as a number (id_code, matricola)\n",
    "    and as a string (surname)\n",
    "    \"\"\"\n",
    "    def __init__(self, mainDir, csv_filename, cds_filename):\n",
    "        filename = os.path.join(mainDir, csv_filename)\n",
    "        self.students = pd.read_csv(filename, index_col=0)\n",
    "        self.surnames = list(self.students['COGNOME'])\n",
    "        self._id_codes = list(self.students.index)\n",
    "        self._cds_polito = cds_polito(os.path.join(mainDir, cds_filename))\n",
    "        \n",
    "    def _get_student_info_by_surname(self, surname):\n",
    "        \"\"\"\n",
    "        returns a pandas dataframe\n",
    "        with the students' infos\n",
    "        based on the surname\n",
    "        \"\"\"\n",
    "        # Surname are saves as Capital, so let's transform\n",
    "        surname = surname.upper()\n",
    "        if surname in self.surnames:\n",
    "            # extract the student as a dataframe of pandas\n",
    "            df = self.students[self.students['COGNOME'] == surname]\n",
    "            return df\n",
    "        else:\n",
    "            print(\"Surname %s not in the list\" % surname)\n",
    "            return None\n",
    "        # Can be done with try ... except ...\n",
    "\n",
    "    def _get_student_info_by_id(self, id_code):\n",
    "        \"\"\"\n",
    "        returns a pandas dataframe\n",
    "        with the students' info\n",
    "        based on id_code (Matricola)\n",
    "        \"\"\"\n",
    "        return self.students.loc[id_code]\n",
    "\n",
    "    def _get_student_info(self, tag=None):\n",
    "        if not tag:\n",
    "            print(\"Please give a id code or his/her surname\")\n",
    "            return\n",
    "        else:\n",
    "            return self._get_df_from_tag(tag)\n",
    "\n",
    "    def get_student_info(self, tag=None):\n",
    "        \"\"\"\n",
    "        Why two methods with the same name\n",
    "        just one private?\n",
    "        If we return a dataframe,\n",
    "        pandas will plot it, \n",
    "        and this is what we do not want to\n",
    "        \"\"\"\n",
    "        df = self._get_student_info(tag)\n",
    "        if df is not None:\n",
    "            print(df.to_string())\n",
    "        return\n",
    "\n",
    "    def _get_df_from_tag(self, tag):\n",
    "        \"\"\"\n",
    "        get the pandas dataframe\n",
    "        corresponding a tag (id_code or surname)\n",
    "\n",
    "        tag: int or string (also as 'ALL')\n",
    "        \"\"\"\n",
    "        if type(tag) == int and tag in self._id_codes:\n",
    "            df = self._get_student_info_by_id(tag)\n",
    "        elif type(tag) == str:\n",
    "            tag = tag.upper() \n",
    "            if tag in self.surnames:\n",
    "                df = self._get_student_info_by_surname(tag)\n",
    "            elif tag == 'ALL':\n",
    "                df = self.students\n",
    "            else:\n",
    "                df = None\n",
    "                print(\"%s surname does not exist\" % tag)\n",
    "        else:\n",
    "            print(\"There is a problem, check your input\")\n",
    "            df = None\n",
    "        return df\n",
    "\n",
    "\n",
    "    def get_students_cds(self, cds):\n",
    "        cds_short = cds[:3]\n",
    "        cds_long = self._cds_polito[cds_short]\n",
    "        locations = self.students['CDS STUDENTE'] == cds\n",
    "        st = sum(locations)\n",
    "        # Can we adjust plural and singular?\n",
    "        if st == 1:\n",
    "            verb, stud = \"is\", \"\"\n",
    "        else:\n",
    "            verb, stud = \"are\", \"s\"\n",
    "        print(\"There %s %i student%s from %s\" % (verb, st, stud, cds_long))\n",
    "        return st\n",
    "\n",
    "    def get_student_photo(self, tag=None):\n",
    "        \"\"\"\n",
    "        This method unfortunately works\n",
    "        only if connected to the polito network\n",
    "        \"\"\"\n",
    "        df = self._get_student_info(tag)\n",
    "        code = df.index.tolist()[0]\n",
    "        try: \n",
    "            url = \"https://didattica.polito.it/pls/portal30/sviluppo.foto_studente?p_matricola=%s\" % code\n",
    "            response = requests.get(url)\n",
    "            cnt = response.content\n",
    "            img = Image.open(BytesIO(cnt))\n",
    "        except OSError:\n",
    "            cnt = cnt.decode(\"utf-8\")\n",
    "            if 'ACCESS DENIED' in cnt:\n",
    "                 webbrowser.open(url)\n",
    "        except:\n",
    "            print(\"Impossible to connect to the Polito site\")\n",
    "\n",
    "    @property\n",
    "    def cds(self):\n",
    "        return set(self.students['CDS STUDENTE'])\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    mainDir = \"/home/gf/src/Python/Python-in-the-lab/project\"\n",
    "    csv_file = \"01RONKG_2017.csv\"\n",
    "    cds_file ='phds.txt'\n",
    "    filename = os.path.join(mainDir, csv_file)\n",
    "    cl = Classroom(mainDir, csv_file, cds_file)\n",
    "    for c in sorted(cl.cds):\n",
    "        cl.get_students_cds(c)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## customplots.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
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    "\"\"\"\n",
    "custom plots of pie and bar\n",
    "\"\"\"\n",
    "\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "class CustomPlots:\n",
    "    def __init__(self, ax):\n",
    "        self.ax = ax\n",
    "\n",
    "    def plot_xy(self, x, y, marker='o', color='r'):\n",
    "        self.ax.plot(x, y, mk=marker, cl=color)\n",
    "\n",
    "    def plot_pie(self, size, labels, explode=None, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90):\n",
    "        patches, texts, autotext = self.ax.pie(size, labels=labels, \n",
    "            explode=explode, autopct=autopct, shadow=shadow, \n",
    "            startangle=startangle)\n",
    "        self.ax.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle.\n",
    "        [t.set_fontsize(22) for t in texts]\n",
    "    \n",
    "    def plot_bar(self, size, labels, width=0.4):\n",
    "        x = np.arange(1, len(labels)+1)\n",
    "        self.ax.bar(x, size, width)\n",
    "        self.ax.set_ylabel('Students')\n",
    "        self.ax.set_xticks(x + width / 2)\n",
    "        self.ax.set_xticklabels(tuple(labels))\n",
    "\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    import matplotlib.pyplot as plt\n",
    "    # Pie chart, where the slices will be ordered and plotted counter-clockwise:\n",
    "    labels = 'Frogs', 'Hogs', 'Dogs', 'Logs'\n",
    "    sizes = [15, 30, 45, 10]\n",
    "    explode = (0, 0.1, 0, 0)  # only \"explode\" the 2nd slice (i.e. 'Hogs')\n",
    "    fig1, ax1 = plt.subplots()\n",
    "    cp = CustomPlots(ax1)\n",
    "    cp.plot_pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',\n",
    "        shadow=True, startangle=90)\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## stats_on_cds.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
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     "text": [
      "There are 3 students from Aerospace Engineering\n",
      "There are 3 students from Bioengineering and Medical-Surgical sciences\n",
      "There are 2 students from Chemical Engineering\n",
      "There are 14 students from Electrical, Electronics and Communications Engineering\n",
      "There are 4 students from Energetics\n",
      "There are 3 students from Physics\n",
      "There is 1 student from Civil and Environmental Engineering\n",
      "There are 15 students from Computer and Control Engineering\n",
      "There are 3 students from Mechanical Engineering\n",
      "There are 4 students from Metrology\n",
      "There are 2 students from Materials Science and Technology\n",
      "There is 1 student from Urban and Regional Development\n"
     ]
    }
   ],
   "source": [
    "\"\"\"\n",
    "This is a demo \n",
    "for the Python-in-the-lab course\n",
    "to illustrate how a simple project\n",
    "can be structured\n",
    "\n",
    "The final goal is to plot the different Departments\n",
    "to which the students of the Python course\n",
    "belong to.\n",
    "This is done calling the class\n",
    "Plot_cds_stats twice,\n",
    "using pie and bar plots\n",
    "\"\"\"\n",
    "import os\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "# The lines below are adapted to work inside a notebook, \n",
    "# with the two files in the cells above.\n",
    "try:\n",
    "    import classroom as cl \n",
    "    import customplots as cp\n",
    "except:\n",
    "    import __main__ as cl\n",
    "    import __main__ as cp\n",
    "\n",
    "class Plot_cds_stats:\n",
    "    \"\"\"\n",
    "    class to print the data about the students\n",
    "    \"\"\"\n",
    "    def __init__(self, mainDir, csv_filename, cds_filename):\n",
    "        # Call the Classroom class from classroom.py\n",
    "        my_class = cl.Classroom(mainDir, csv_filename, cds_filename)\n",
    "        # cds: codes of Polito Departments\n",
    "        cds = sorted(my_class.cds)\n",
    "        self.students = [my_class.get_students_cds(c) for c in cds]\n",
    "        # Only the first 3 elements of the Departments code are needed\n",
    "        self.labels = [c[:3] for c in cds]\n",
    "    \n",
    "    def pie(self, ax, explode=0.03):\n",
    "        \"\"\"\n",
    "        plot a pie plot using axis ax\n",
    "        \"\"\"\n",
    "        this_plot = cp.CustomPlots(ax)\n",
    "        if explode is not None:\n",
    "            if type(explode)  == float:\n",
    "                # Let's explode all the pies with the same value\n",
    "                explode = explode * np.ones(len(self.students))\n",
    "        # Draw the plot\n",
    "        this_plot.plot_pie(size=self.students, labels=self.labels, explode=explode)\n",
    "    \n",
    "    def bar(self, ax):\n",
    "        \"\"\"\n",
    "        plot a bar plot using axis ax\n",
    "        \"\"\"\n",
    "        this_plot = cp.CustomPlots(ax)\n",
    "        # Draw the plot\n",
    "        this_plot.plot_bar(size=self.students, labels=self.labels)\n",
    "\n",
    "\n",
    "if __name__ == \"__main__\":\n",
    "    # The plot is setup here, and not in the classes \n",
    "    fig, ax = plt.subplots(1,2, figsize=(18,8))\n",
    "    # Load the file with the students' info\n",
    "    mainDir = \"/home/gf/src/Python/Python-in-the-lab/project\"\n",
    "    csv_file = \"01RONKG_2017.csv\"\n",
    "    cds_file = \"phds.txt\"\n",
    "    # Initialize the class to plot\n",
    "    plot = Plot_cds_stats(mainDir, csv_file, cds_file)\n",
    "    plot.pie(ax[0], explode=0.03)\n",
    "    plot.bar(ax[1])\n",
    "    plt.show()"
   ]
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