Notebooks/Python_Basic/05_Packages_Modules.ipynb

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    "# Introduction to Python  \n",
    "\n",
    "## [Packages](https://docs.python.org/3/tutorial/modules.html#packages) and [Modules](https://docs.python.org/3/tutorial/modules.html)\n",
    "\n",
    "#### Packages are a way of structuring Python’s module namespace by using “dotted module names”. For example, the module name A.B designates a submodule named B in a package named A. Just like the use of modules saves the authors of different modules from having to worry about each other’s global variable names, the use of dotted module names saves the authors of multi-module packages like NumPy or Pillow from having to worry about each other’s module names.  \n",
    "\n",
    "#### A module is a file containing Python definitions and statements. The file name is the module name with the suffix .py appended. Within a module, the module’s name (as a string) is available as the value of the global variable __name__. "
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      "__main__\n"
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   "source": [
    "print(__name__)"
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   "source": [
    "### We can check all the properties (attributes and methods) from an object using _dir()_"
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    "dir()"
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   "source": [
    "#### We can also access all the Python builtins introspecting the __builtins__ variable "
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       " 'IndexError',\n",
       " 'InterruptedError',\n",
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       " 'TypeError',\n",
       " 'UnboundLocalError',\n",
       " 'UnicodeDecodeError',\n",
       " 'UnicodeEncodeError',\n",
       " 'UnicodeError',\n",
       " 'UnicodeTranslateError',\n",
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       " 'UserWarning',\n",
       " 'ValueError',\n",
       " 'Warning',\n",
       " 'WindowsError',\n",
       " 'ZeroDivisionError',\n",
       " '__IPYTHON__',\n",
       " '__build_class__',\n",
       " '__debug__',\n",
       " '__doc__',\n",
       " '__import__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__spec__',\n",
       " 'abs',\n",
       " 'aiter',\n",
       " 'all',\n",
       " 'anext',\n",
       " 'any',\n",
       " 'ascii',\n",
       " 'bin',\n",
       " 'bool',\n",
       " 'breakpoint',\n",
       " 'bytearray',\n",
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       " 'callable',\n",
       " 'chr',\n",
       " 'classmethod',\n",
       " 'compile',\n",
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       " 'credits',\n",
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       " 'get_ipython',\n",
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       " 'globals',\n",
       " 'hasattr',\n",
       " 'hash',\n",
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       " 'hex',\n",
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       " 'locals',\n",
       " 'map',\n",
       " 'max',\n",
       " 'memoryview',\n",
       " 'min',\n",
       " 'next',\n",
       " 'object',\n",
       " 'oct',\n",
       " 'open',\n",
       " 'ord',\n",
       " 'pow',\n",
       " 'print',\n",
       " 'property',\n",
       " 'range',\n",
       " 'repr',\n",
       " 'reversed',\n",
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       " 'runfile',\n",
       " 'set',\n",
       " 'setattr',\n",
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       " 'sorted',\n",
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       " 'zip']"
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    "dir(__builtins__)"
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   "source": [
    "***"
   ]
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   "source": [
    "## There are 4 main ways to import Packages and Modules  \n",
    "### 1 - Importing the full package:  "
   ]
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   "execution_count": 1,
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   "source": [
    "import string\n",
    "import random\n",
    "import math\n",
    "import numpy"
   ]
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    "dir()"
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       "'!\"#$%&\\'()*+,-./:;<=>?@[\\\\]^_`{|}~'"
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     "execution_count": 4,
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   "source": [
    "random.random()"
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       "3.141592653589793"
      ]
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     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "numpy.pi"
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  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
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     "execution_count": 7,
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   ],
   "source": [
    "numpy.pi == math.pi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
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    "editable": true
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   "source": [
    "### 2 - Importing all modules from a package:  \n",
    "#### (although this is not recommended)  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "deletable": true,
    "editable": true
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   "outputs": [],
   "source": [
    "from math import *\n",
    "from numpy import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dir()"
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   "cell_type": "code",
   "execution_count": 19,
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    {
     "data": {
      "text/plain": [
       "2.718281828459045"
      ]
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     "execution_count": 19,
     "metadata": {},
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    }
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   "source": [
    "e"
   ]
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   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "deletable": true,
    "editable": true
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   "source": [
    "e = [1,2,3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[1, 2, 3]"
      ]
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     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "e"
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   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "deletable": true,
    "editable": true
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   "source": [
    "from math import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
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    {
     "data": {
      "text/plain": [
       "2.718281828459045"
      ]
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     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": [
    "e   # The original variable was overwritten after the import"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3 - Importing specific modules from a package:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "deletable": true,
    "editable": true
   },
   "outputs": [],
   "source": [
    "from numpy import mean, pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dir()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5.0"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mean([1,2,3,4,5,6,7,8,9])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
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    {
     "data": {
      "text/plain": [
       "3.141592653589793"
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     "execution_count": 27,
     "metadata": {},
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    }
   ],
   "source": [
    "pi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "math.pi == numpy.pi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
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    "editable": true
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   "source": [
    "### 4 - Importing a module and giving it a nickname:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "deletable": true,
    "editable": true
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   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'matplotlib'",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "\u001b[1;32mc:\\Users\\matte\\OneDrive\\Dokumente\\GitHub\\Python_Course\\Notebooks\\Python_Basic\\05_Packages_Modules.ipynb Cell 34\u001b[0m line \u001b[0;36m3\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/matte/OneDrive/Dokumente/GitHub/Python_Course/Notebooks/Python_Basic/05_Packages_Modules.ipynb#X45sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mpandas\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mpd\u001b[39;00m\n\u001b[0;32m      <a href='vscode-notebook-cell:/c%3A/Users/matte/OneDrive/Dokumente/GitHub/Python_Course/Notebooks/Python_Basic/05_Packages_Modules.ipynb#X45sZmlsZQ%3D%3D?line=1'>2</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mnumpy\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mnp\u001b[39;00m\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/matte/OneDrive/Dokumente/GitHub/Python_Course/Notebooks/Python_Basic/05_Packages_Modules.ipynb#X45sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mmatplotlib\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mpyplot\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mplt\u001b[39;00m\n",
      "\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'matplotlib'"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#dir()"
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   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'plt' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[1;32mc:\\Users\\matte\\OneDrive\\Dokumente\\GitHub\\Python_Course\\Notebooks\\Python_Basic\\05_Packages_Modules.ipynb Cell 36\u001b[0m line \u001b[0;36m1\n\u001b[1;32m----> <a href='vscode-notebook-cell:/c%3A/Users/matte/OneDrive/Dokumente/GitHub/Python_Course/Notebooks/Python_Basic/05_Packages_Modules.ipynb#X50sZmlsZQ%3D%3D?line=0'>1</a>\u001b[0m plt\u001b[39m.\u001b[39mplot([\u001b[39m1\u001b[39m,\u001b[39m2\u001b[39m,\u001b[39m3\u001b[39m,\u001b[39m4\u001b[39m,\u001b[39m5\u001b[39m,\u001b[39m6\u001b[39m,\u001b[39m4\u001b[39m,\u001b[39m3\u001b[39m,\u001b[39m2\u001b[39m,\u001b[39m1\u001b[39m])\n",
      "\u001b[1;31mNameError\u001b[0m: name 'plt' is not defined"
     ]
    }
   ],
   "source": [
    "plt.plot([1,2,3,4,5,6,4,3,2,1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'pandas' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn [34], line 1\u001b[0m\n\u001b[1;32m----> 1\u001b[0m pandas  \u001b[39m#NameError: name 'pandas' is not defined\u001b[39;00m\n",
      "\u001b[1;31mNameError\u001b[0m: name 'pandas' is not defined"
     ]
    }
   ],
   "source": [
    "pandas  #NameError: name 'pandas' is not defined"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5 - (Creating and) Importing your own module:  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This will be printed on import\n"
     ]
    }
   ],
   "source": [
    "import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['__builtins__',\n",
       " '__cached__',\n",
       " '__doc__',\n",
       " '__file__',\n",
       " '__loader__',\n",
       " '__name__',\n",
       " '__package__',\n",
       " '__spec__',\n",
       " 'cube',\n",
       " 'my_constant',\n",
       " 'other_property',\n",
       " 'square']"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dir(utils)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "64"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "utils.cube(4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'3.14159'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "utils.my_constant"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### And, as a curiosity, there is an \"Easter egg\" in Python\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false,
    "deletable": true,
    "editable": true,
    "jupyter": {
     "outputs_hidden": false
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The Zen of Python, by Tim Peters\n",
      "\n",
      "Beautiful is better than ugly.\n",
      "Explicit is better than implicit.\n",
      "Simple is better than complex.\n",
      "Complex is better than complicated.\n",
      "Flat is better than nested.\n",
      "Sparse is better than dense.\n",
      "Readability counts.\n",
      "Special cases aren't special enough to break the rules.\n",
      "Although practicality beats purity.\n",
      "Errors should never pass silently.\n",
      "Unless explicitly silenced.\n",
      "In the face of ambiguity, refuse the temptation to guess.\n",
      "There should be one-- and preferably only one --obvious way to do it.\n",
      "Although that way may not be obvious at first unless you're Dutch.\n",
      "Now is better than never.\n",
      "Although never is often better than *right* now.\n",
      "If the implementation is hard to explain, it's a bad idea.\n",
      "If the implementation is easy to explain, it may be a good idea.\n",
      "Namespaces are one honking great idea -- let's do more of those!\n"
     ]
    }
   ],
   "source": [
    "import this"
   ]
  }
 ],
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