{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"![](\"https://camo.githubusercontent.com/e7501c5948d48f88dad8ab2ab6bd448e1cfd6c79/68747470733a2f2f64726976652e676f6f676c652e636f6d2f75633f6578706f72743d646f776e6c6f61642669643d3135414b51365f2d42697857344b366d4c36525070684635454b58715946327a6a\")
\n",
"\n",
"Day 14 Modules and Packages in Python
"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Recap\n",
"\n",
"- Call by value\n",
"- Call by reference\n",
"- Variable length arguments\n",
"- Modules and Packages\n",
"\n",
"### Day Objectives\n",
"\n",
"\n",
"- Modules and Packages\n",
" - Pre-defined/ in-built\n",
" - User-Defined/ 3rd party"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import random"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.5371613768087516\n"
]
}
],
"source": [
"print(random.random())"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.8227023481261443\n"
]
}
],
"source": [
"print(random.random())"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0.74\n"
]
}
],
"source": [
"print(round(random.random(), 2))"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6 5\n"
]
}
],
"source": [
"a = 5.5\n",
"\n",
"ceil = 6\n",
"floor = 5\n",
"\n",
"import math\n",
"\n",
"print(math.ceil(5.5), math.floor(5.5))"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9027255381595464"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"random.random()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.09033985426934954"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"random.seed(55)\n",
"\n",
"random.random()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.1456692551041303"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"random.seed(100)\n",
"\n",
"random.random()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"0.9241408041681706"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"random.seed(1000000)\n",
"\n",
"random.random()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Return random integer in range [a, b], including both end points.\\n '"
]
},
"execution_count": 17,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"random.randint.__doc__"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n"
]
}
],
"source": [
"print(random.randint(0, 100))"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6\n"
]
}
],
"source": [
"print(random.randint(0, 6))"
]
},
{
"cell_type": "code",
"execution_count": 27,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n",
"1\n",
"1\n",
"1\n",
"5\n",
"0\n"
]
}
],
"source": [
"for i in range(6):\n",
" print(random.randint(0, 6))"
]
},
{
"cell_type": "code",
"execution_count": 28,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"65 90\n"
]
}
],
"source": [
"print(ord('A'), ord('Z'))"
]
},
{
"cell_type": "code",
"execution_count": 29,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"M\n",
"C\n",
"M\n",
"J\n",
"X\n",
"W\n",
"J\n",
"F\n",
"Q\n",
"O\n"
]
}
],
"source": [
"for i in range(10):\n",
" print(chr(random.randint(65, 90)))"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"head\n"
]
}
],
"source": [
"li = ['head', 'tail']\n",
"\n",
"print(random.choice(li))"
]
},
{
"cell_type": "code",
"execution_count": 35,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"tail\n",
"tail\n",
"head\n",
"head\n",
"tail\n",
"head\n"
]
}
],
"source": [
"li = ['head', 'tail']\n",
"for i in range(6):\n",
" print(random.choice(li))"
]
},
{
"cell_type": "code",
"execution_count": 36,
"metadata": {},
"outputs": [],
"source": [
"li = [1,2,3,4,5,6,7]\n",
"random.shuffle(li)"
]
},
{
"cell_type": "code",
"execution_count": 39,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[7, 6, 2, 1, 4, 3, 5]\n"
]
}
],
"source": [
"random.shuffle(li)\n",
"print(li)"
]
},
{
"cell_type": "code",
"execution_count": 43,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[2, 5, 1, 7, 3, 6, 4]\n"
]
}
],
"source": [
"random.shuffle(li)\n",
"print(li)"
]
},
{
"cell_type": "code",
"execution_count": 44,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.7774591305763382\n"
]
}
],
"source": [
"# random.gauss(mu, sigma) -> mu = mean, sigma = std\n",
"\n",
"print(random.gauss(0, 1))"
]
},
{
"cell_type": "code",
"execution_count": 47,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"7.144456058349938\n",
"7.670983477419868\n",
"8.154743166289004\n",
"8.162593217836559\n",
"5.2051290853667975\n",
"6.153058019018136\n",
"8.528796621208931\n",
"7.851741517503576\n",
"9.189532854547217\n",
"5.262431441942137\n"
]
}
],
"source": [
"for i in range(10):\n",
" print(random.uniform(5, 10))"
]
},
{
"cell_type": "code",
"execution_count": 51,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"11"
]
},
"execution_count": 51,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"random.randrange(1, 15)"
]
},
{
"cell_type": "code",
"execution_count": 52,
"metadata": {},
"outputs": [],
"source": [
"import calendar"
]
},
{
"cell_type": "code",
"execution_count": 53,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" June 2021\n",
"Mo Tu We Th Fr Sa Su\n",
" 1 2 3 4 5 6\n",
" 7 8 9 10 11 12 13\n",
"14 15 16 17 18 19 20\n",
"21 22 23 24 25 26 27\n",
"28 29 30\n",
"\n"
]
}
],
"source": [
"print(calendar.month(2021, 6))"
]
},
{
"cell_type": "code",
"execution_count": 54,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" June 2035\n",
"Mo Tu We Th Fr Sa Su\n",
" 1 2 3\n",
" 4 5 6 7 8 9 10\n",
"11 12 13 14 15 16 17\n",
"18 19 20 21 22 23 24\n",
"25 26 27 28 29 30\n",
"\n"
]
}
],
"source": [
"print(calendar.month(2035, 6))"
]
},
{
"cell_type": "code",
"execution_count": 55,
"metadata": {},
"outputs": [],
"source": [
"import calendar as cal"
]
},
{
"cell_type": "code",
"execution_count": 56,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" June 2035\n",
"Mo Tu We Th Fr Sa Su\n",
" 1 2 3\n",
" 4 5 6 7 8 9 10\n",
"11 12 13 14 15 16 17\n",
"18 19 20 21 22 23 24\n",
"25 26 27 28 29 30\n",
"\n"
]
}
],
"source": [
"print(cal.month(2035, 6))"
]
},
{
"cell_type": "code",
"execution_count": 60,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Calendar',\n",
" 'EPOCH',\n",
" 'FRIDAY',\n",
" 'February',\n",
" 'HTMLCalendar',\n",
" 'IllegalMonthError',\n",
" 'IllegalWeekdayError',\n",
" 'January',\n",
" 'LocaleHTMLCalendar',\n",
" 'LocaleTextCalendar',\n",
" 'MONDAY',\n",
" 'SATURDAY',\n",
" 'SUNDAY',\n",
" 'THURSDAY',\n",
" 'TUESDAY',\n",
" 'TextCalendar',\n",
" 'WEDNESDAY',\n",
" '_EPOCH_ORD',\n",
" '__all__',\n",
" '__builtins__',\n",
" '__cached__',\n",
" '__doc__',\n",
" '__file__',\n",
" '__loader__',\n",
" '__name__',\n",
" '__package__',\n",
" '__spec__',\n",
" '_colwidth',\n",
" '_locale',\n",
" '_localized_day',\n",
" '_localized_month',\n",
" '_monthlen',\n",
" '_nextmonth',\n",
" '_prevmonth',\n",
" '_spacing',\n",
" 'c',\n",
" 'calendar',\n",
" 'datetime',\n",
" 'day_abbr',\n",
" 'day_name',\n",
" 'different_locale',\n",
" 'error',\n",
" 'firstweekday',\n",
" 'format',\n",
" 'formatstring',\n",
" 'isleap',\n",
" 'leapdays',\n",
" 'main',\n",
" 'mdays',\n",
" 'month',\n",
" 'month_abbr',\n",
" 'month_name',\n",
" 'monthcalendar',\n",
" 'monthrange',\n",
" 'prcal',\n",
" 'prmonth',\n",
" 'prweek',\n",
" 'repeat',\n",
" 'setfirstweekday',\n",
" 'sys',\n",
" 'timegm',\n",
" 'week',\n",
" 'weekday',\n",
" 'weekheader']"
]
},
"execution_count": 60,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dir(cal)"
]
},
{
"cell_type": "code",
"execution_count": 61,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Return weekday (0-6 ~ Mon-Sun) for year, month (1-12), day (1-31).'"
]
},
"execution_count": 61,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cal.weekday.__doc__"
]
},
{
"cell_type": "code",
"execution_count": 62,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on function weekday in module calendar:\n",
"\n",
"weekday(year, month, day)\n",
" Return weekday (0-6 ~ Mon-Sun) for year, month (1-12), day (1-31).\n",
"\n"
]
}
],
"source": [
"help(cal.weekday)"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"6\n"
]
}
],
"source": [
"print(cal.weekday(2021, 6, 6))"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Help on method formatweek in module calendar:\n",
"\n",
"formatweek(theweek, width) method of calendar.TextCalendar instance\n",
" Returns a single week in a string (no newline).\n",
"\n"
]
}
],
"source": [
"help(cal.week)"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" 2021\n",
"\n",
" January February March\n",
"Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su\n",
" 1 2 3 1 2 3 4 5 6 7 1 2 3 4 5 6 7\n",
" 4 5 6 7 8 9 10 8 9 10 11 12 13 14 8 9 10 11 12 13 14\n",
"11 12 13 14 15 16 17 15 16 17 18 19 20 21 15 16 17 18 19 20 21\n",
"18 19 20 21 22 23 24 22 23 24 25 26 27 28 22 23 24 25 26 27 28\n",
"25 26 27 28 29 30 31 29 30 31\n",
"\n",
" April May June\n",
"Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su\n",
" 1 2 3 4 1 2 1 2 3 4 5 6\n",
" 5 6 7 8 9 10 11 3 4 5 6 7 8 9 7 8 9 10 11 12 13\n",
"12 13 14 15 16 17 18 10 11 12 13 14 15 16 14 15 16 17 18 19 20\n",
"19 20 21 22 23 24 25 17 18 19 20 21 22 23 21 22 23 24 25 26 27\n",
"26 27 28 29 30 24 25 26 27 28 29 30 28 29 30\n",
" 31\n",
"\n",
" July August September\n",
"Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su\n",
" 1 2 3 4 1 1 2 3 4 5\n",
" 5 6 7 8 9 10 11 2 3 4 5 6 7 8 6 7 8 9 10 11 12\n",
"12 13 14 15 16 17 18 9 10 11 12 13 14 15 13 14 15 16 17 18 19\n",
"19 20 21 22 23 24 25 16 17 18 19 20 21 22 20 21 22 23 24 25 26\n",
"26 27 28 29 30 31 23 24 25 26 27 28 29 27 28 29 30\n",
" 30 31\n",
"\n",
" October November December\n",
"Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su Mo Tu We Th Fr Sa Su\n",
" 1 2 3 1 2 3 4 5 6 7 1 2 3 4 5\n",
" 4 5 6 7 8 9 10 8 9 10 11 12 13 14 6 7 8 9 10 11 12\n",
"11 12 13 14 15 16 17 15 16 17 18 19 20 21 13 14 15 16 17 18 19\n",
"18 19 20 21 22 23 24 22 23 24 25 26 27 28 20 21 22 23 24 25 26\n",
"25 26 27 28 29 30 31 29 30 27 28 29 30 31\n",
"\n"
]
}
],
"source": [
"print(cal.calendar(2021))"
]
},
{
"cell_type": "code",
"execution_count": 81,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"datetime.date(2021, 6, 8)"
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"cal.datetime.date(2021, 6, 8)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- from package import module \n",
"- from package import module as alias\n",
"- import package.module as alias"
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [],
"source": [
"import os"
]
},
{
"cell_type": "code",
"execution_count": 82,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Volume in drive C has no label.\n",
" Volume Serial Number is 7866-1790\n",
"\n",
" Directory of C:\\Users\\Jesus\\Desktop\\Data Science Internship May-2021\n",
"\n",
"08-Jun-21 05:26 PM .\n",
"08-Jun-21 05:26 PM ..\n",
"08-Jun-21 04:29 PM .ipynb_checkpoints\n",
"08-Jun-21 05:26 PM 17,063 Day 14 Modules and Packages in Python.ipynb\n",
"26-May-21 06:59 PM 5,605 Day03_Markdown_Syntax.ipynb\n",
"26-May-21 07:09 PM 286,289 Day03_Markdown_Syntax.slides.html\n",
"26-May-21 07:09 PM 286,289 Day03_Markdown_Syntax.slidesa.html\n",
"29-May-21 09:54 PM 17,953 Day06_Python_Basics.ipynb\n",
"31-May-21 07:46 PM 29,748 Day07_Conditional_Statements_Loops_Strings.ipynb\n",
"01-Jun-21 06:46 PM 39,036 Day08_Strings_and_StringMethods.ipynb\n",
"02-Jun-21 08:00 PM 52,775 Day09_Lists_and_Tuples_in_Python.ipynb\n",
"04-Jun-21 04:35 PM 32,065 Day10_Dictionary_in_Python.ipynb\n",
"07-Jun-21 04:07 PM 66,708 Day11_Sets_and_Functions_in_Python.ipynb\n",
"05-Jun-21 10:30 PM Day12_File_Handling_in_Python\n",
"07-Jun-21 09:09 PM Day13_Files_and_Functions_Contd\n",
"28-May-21 04:26 PM dummy\n",
"05-Jun-21 06:34 PM 78,620 File Handing in Python.ipynb\n",
"05-Jun-21 06:32 PM 32 file.txt\n",
"05-Jun-21 06:27 PM 38,944 file1.txt\n",
"05-Jun-21 05:56 PM 0 file10.txt\n",
"05-Jun-21 06:27 PM 38,944 file2.txt\n",
"05-Jun-21 06:27 PM 38,944 file3.txt\n",
"05-Jun-21 06:27 PM 38,944 file4.txt\n",
"05-Jun-21 06:27 PM 38,944 file5.txt\n",
"05-Jun-21 06:27 PM 38,944 file6.txt\n",
"05-Jun-21 06:27 PM 38,944 file7.txt\n",
"05-Jun-21 06:27 PM 38,944 file8.txt\n",
"05-Jun-21 06:27 PM 38,944 file9.txt\n",
"26-May-21 06:37 PM 11,155 python-logo-master-v3-TM-flattened.png\n",
"31-May-21 03:50 PM 17,803 Sample_Projects.ipynb\n",
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" 25 File(s) 1,681,374 bytes\n",
" 6 Dir(s) 65,374,728,192 bytes free\n"
]
}
],
"source": [
"ls"
]
},
{
"cell_type": "code",
"execution_count": 83,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'C:\\\\Users\\\\Jesus\\\\Desktop\\\\Data Science Internship May-2021'"
]
},
"execution_count": 83,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pwd"
]
},
{
"cell_type": "code",
"execution_count": 84,
"metadata": {},
"outputs": [],
"source": [
"mkdir newFolder"
]
},
{
"cell_type": "code",
"execution_count": 85,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
" Volume in drive C has no label.\n",
" Volume Serial Number is 7866-1790\n",
"\n",
" Directory of C:\\Users\\Jesus\\Desktop\\Data Science Internship May-2021\n",
"\n",
"08-Jun-21 05:29 PM .\n",
"08-Jun-21 05:29 PM ..\n",
"08-Jun-21 04:29 PM .ipynb_checkpoints\n",
"08-Jun-21 05:29 PM 19,945 Day 14 Modules and Packages in Python.ipynb\n",
"26-May-21 06:59 PM 5,605 Day03_Markdown_Syntax.ipynb\n",
"26-May-21 07:09 PM 286,289 Day03_Markdown_Syntax.slides.html\n",
"26-May-21 07:09 PM 286,289 Day03_Markdown_Syntax.slidesa.html\n",
"29-May-21 09:54 PM 17,953 Day06_Python_Basics.ipynb\n",
"31-May-21 07:46 PM 29,748 Day07_Conditional_Statements_Loops_Strings.ipynb\n",
"01-Jun-21 06:46 PM 39,036 Day08_Strings_and_StringMethods.ipynb\n",
"02-Jun-21 08:00 PM 52,775 Day09_Lists_and_Tuples_in_Python.ipynb\n",
"04-Jun-21 04:35 PM 32,065 Day10_Dictionary_in_Python.ipynb\n",
"07-Jun-21 04:07 PM 66,708 Day11_Sets_and_Functions_in_Python.ipynb\n",
"05-Jun-21 10:30 PM Day12_File_Handling_in_Python\n",
"07-Jun-21 09:09 PM Day13_Files_and_Functions_Contd\n",
"28-May-21 04:26 PM dummy\n",
"05-Jun-21 06:34 PM 78,620 File Handing in Python.ipynb\n",
"05-Jun-21 06:32 PM 32 file.txt\n",
"05-Jun-21 06:27 PM 38,944 file1.txt\n",
"05-Jun-21 05:56 PM 0 file10.txt\n",
"05-Jun-21 06:27 PM 38,944 file2.txt\n",
"05-Jun-21 06:27 PM 38,944 file3.txt\n",
"05-Jun-21 06:27 PM 38,944 file4.txt\n",
"05-Jun-21 06:27 PM 38,944 file5.txt\n",
"05-Jun-21 06:27 PM 38,944 file6.txt\n",
"05-Jun-21 06:27 PM 38,944 file7.txt\n",
"05-Jun-21 06:27 PM 38,944 file8.txt\n",
"05-Jun-21 06:27 PM 38,944 file9.txt\n",
"08-Jun-21 05:29 PM newFolder\n",
"26-May-21 06:37 PM 11,155 python-logo-master-v3-TM-flattened.png\n",
"31-May-21 03:50 PM 17,803 Sample_Projects.ipynb\n",
"31-May-21 09:33 PM 389,737 Untitled.ipynb\n",
" 25 File(s) 1,684,256 bytes\n",
" 7 Dir(s) 65,378,168,832 bytes free\n"
]
}
],
"source": [
"ls"
]
},
{
"cell_type": "code",
"execution_count": 88,
"metadata": {},
"outputs": [],
"source": [
"os.mkdir('folderFromPython')"
]
},
{
"cell_type": "code",
"execution_count": 90,
"metadata": {},
"outputs": [],
"source": [
"os.remove('file9.txt')"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['.ipynb_checkpoints',\n",
" 'Day 14 Modules and Packages in Python.ipynb',\n",
" 'Day03_Markdown_Syntax.ipynb',\n",
" 'Day03_Markdown_Syntax.slides.html',\n",
" 'Day03_Markdown_Syntax.slidesa.html',\n",
" 'Day06_Python_Basics.ipynb',\n",
" 'Day07_Conditional_Statements_Loops_Strings.ipynb',\n",
" 'Day08_Strings_and_StringMethods.ipynb',\n",
" 'Day09_Lists_and_Tuples_in_Python.ipynb',\n",
" 'Day10_Dictionary_in_Python.ipynb',\n",
" 'Day11_Sets_and_Functions_in_Python.ipynb',\n",
" 'Day12_File_Handling_in_Python',\n",
" 'Day13_Files_and_Functions_Contd',\n",
" 'dummy',\n",
" 'File Handing in Python.ipynb',\n",
" 'file.txt',\n",
" 'file1.txt',\n",
" 'file10.txt',\n",
" 'file2.txt',\n",
" 'file3.txt',\n",
" 'file4.txt',\n",
" 'file5.txt',\n",
" 'file6.txt',\n",
" 'file7.txt',\n",
" 'file8.txt',\n",
" 'folderFromPython',\n",
" 'newFolder',\n",
" 'python-logo-master-v3-TM-flattened.png',\n",
" 'Sample_Projects.ipynb',\n",
" 'Untitled.ipynb']"
]
},
"execution_count": 91,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.listdir()"
]
},
{
"cell_type": "code",
"execution_count": 92,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'C:\\\\Users\\\\Jesus\\\\Desktop\\\\Data Science Internship May-2021'"
]
},
"execution_count": 92,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.getcwd()"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'C:\\\\Users\\\\Jesus\\\\Desktop\\\\Data Science Internship May-2021\\\\newFolder'"
]
},
"execution_count": 93,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.chdir('newFolder')\n",
"\n",
"\n",
"os.getcwd()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"- import module/package -> all the functions/classes/attr will be import\n",
"- from package import module -> all the functions/classes/attr which are avaliable in that module\n",
"- from package.module import method -> only functions/class/attri will be imported from package/module\n",
"- from module import method -> module"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [],
"source": [
"import math"
]
},
{
"cell_type": "code",
"execution_count": 95,
"metadata": {
"collapsed": true
},
"outputs": [
{
"data": {
"text/plain": [
"['__doc__',\n",
" '__loader__',\n",
" '__name__',\n",
" '__package__',\n",
" '__spec__',\n",
" 'acos',\n",
" 'acosh',\n",
" 'asin',\n",
" 'asinh',\n",
" 'atan',\n",
" 'atan2',\n",
" 'atanh',\n",
" 'ceil',\n",
" 'comb',\n",
" 'copysign',\n",
" 'cos',\n",
" 'cosh',\n",
" 'degrees',\n",
" 'dist',\n",
" 'e',\n",
" 'erf',\n",
" 'erfc',\n",
" 'exp',\n",
" 'expm1',\n",
" 'fabs',\n",
" 'factorial',\n",
" 'floor',\n",
" 'fmod',\n",
" 'frexp',\n",
" 'fsum',\n",
" 'gamma',\n",
" 'gcd',\n",
" 'hypot',\n",
" 'inf',\n",
" 'isclose',\n",
" 'isfinite',\n",
" 'isinf',\n",
" 'isnan',\n",
" 'isqrt',\n",
" 'ldexp',\n",
" 'lgamma',\n",
" 'log',\n",
" 'log10',\n",
" 'log1p',\n",
" 'log2',\n",
" 'modf',\n",
" 'nan',\n",
" 'perm',\n",
" 'pi',\n",
" 'pow',\n",
" 'prod',\n",
" 'radians',\n",
" 'remainder',\n",
" 'sin',\n",
" 'sinh',\n",
" 'sqrt',\n",
" 'tan',\n",
" 'tanh',\n",
" 'tau',\n",
" 'trunc']"
]
},
"execution_count": 95,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dir(math)"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"['__doc__', '__loader__', '__name__', '__package__', '__spec__', 'acos', 'acosh', 'asin', 'asinh', 'atan', 'atan2', 'atanh', 'ceil', 'comb', 'copysign', 'cos', 'cosh', 'degrees', 'dist', 'e', 'erf', 'erfc', 'exp', 'expm1', 'fabs', 'factorial', 'floor', 'fmod', 'frexp', 'fsum', 'gamma', 'gcd', 'hypot', 'inf', 'isclose', 'isfinite', 'isinf', 'isnan', 'isqrt', 'ldexp', 'lgamma', 'log', 'log10', 'log1p', 'log2', 'modf', 'nan', 'perm', 'pi', 'pow', 'prod', 'radians', 'remainder', 'sin', 'sinh', 'sqrt', 'tan', 'tanh', 'tau', 'trunc']\n"
]
}
],
"source": [
"import math as m\n",
"\n",
"print(dir(m))"
]
},
{
"cell_type": "code",
"execution_count": 97,
"metadata": {},
"outputs": [],
"source": [
"from math import ceil, floor"
]
},
{
"cell_type": "code",
"execution_count": 98,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"56 66\n"
]
}
],
"source": [
"print(ceil(55.66), floor(66.66))"
]
},
{
"cell_type": "code",
"execution_count": 99,
"metadata": {},
"outputs": [],
"source": [
"from math import *"
]
},
{
"cell_type": "code",
"execution_count": 100,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.3048106211022167 120\n"
]
}
],
"source": [
"print(sin(60), factorial(5))"
]
},
{
"cell_type": "code",
"execution_count": 101,
"metadata": {},
"outputs": [],
"source": [
"from math import * # floor\n",
"from random import * # floor"
]
},
{
"cell_type": "code",
"execution_count": 102,
"metadata": {},
"outputs": [],
"source": [
"os.chdir('../')"
]
},
{
"cell_type": "code",
"execution_count": 103,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'C:\\\\Users\\\\Jesus\\\\Desktop\\\\Data Science Internship May-2021'"
]
},
"execution_count": 103,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.getcwd()"
]
},
{
"cell_type": "code",
"execution_count": 104,
"metadata": {},
"outputs": [],
"source": [
"import anil"
]
},
{
"cell_type": "code",
"execution_count": 105,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Hey welcome to my module called anil...'"
]
},
"execution_count": 105,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"anil.__doc__"
]
},
{
"cell_type": "code",
"execution_count": 106,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['__builtins__',\n",
" '__cached__',\n",
" '__doc__',\n",
" '__file__',\n",
" '__loader__',\n",
" '__name__',\n",
" '__package__',\n",
" '__spec__',\n",
" 'factorial',\n",
" 'gravity',\n",
" 'isEven',\n",
" 'pi']"
]
},
"execution_count": 106,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dir(anil)"
]
},
{
"cell_type": "code",
"execution_count": 107,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'Check whether a number is even or not'"
]
},
"execution_count": 107,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"anil.isEven.__doc__"
]
},
{
"cell_type": "code",
"execution_count": 108,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 108,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"anil.isEven(5)"
]
},
{
"cell_type": "code",
"execution_count": 109,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"120"
]
},
"execution_count": 109,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"anil.factorial(5)"
]
},
{
"cell_type": "code",
"execution_count": 110,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"3.14"
]
},
"execution_count": 110,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"anil.pi"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['__builtins__',\n",
" '__cached__',\n",
" '__doc__',\n",
" '__file__',\n",
" '__loader__',\n",
" '__name__',\n",
" '__package__',\n",
" '__spec__',\n",
" 'factorial',\n",
" 'gravity',\n",
" 'isEven',\n",
" 'isOdd',\n",
" 'pi']"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import anil\n",
"\n",
"dir(anil)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"ename": "AttributeError",
"evalue": "module 'anil' has no attribute 'isodd'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mAttributeError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0manil\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0misodd\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m5\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;31mAttributeError\u001b[0m: module 'anil' has no attribute 'isodd'"
]
}
],
"source": [
"anil.isodd(5)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"ename": "ModuleNotFoundError",
"evalue": "No module named 'anilkumar'",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[1;32mimport\u001b[0m \u001b[0manilkumar\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;31mModuleNotFoundError\u001b[0m: No module named 'anilkumar'"
]
}
],
"source": [
"import anilkumar"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"anil.isOdd(5)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"78.5\n"
]
}
],
"source": [
"from anil import pi\n",
"\n",
"print(pi * 5 **2)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {},
"outputs": [],
"source": [
"import package"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['__doc__',\n",
" '__file__',\n",
" '__loader__',\n",
" '__name__',\n",
" '__package__',\n",
" '__path__',\n",
" '__spec__']"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dir(package)"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [],
"source": [
"import package.module1\n",
"from package import module1 as m"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"False"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m.isEven(5)"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 14,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m.isOdd(5)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"from package import module2 as m"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 16,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"m.isOdd(5)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Task\n",
"\n",
"### Contact application `contact.py`\n",
"\n",
"Create a module with diff function\n",
"\n",
"\n",
"- createContact -> for creating the contact of the user -> name, ph, email\n",
"- DeleteContact -> Delete the contact given be the user -> name\n",
"- editContcact -> Modify the existing contact ->ph/email/name\n",
"- getContact -> show the details of the user -> name\n",
"- save the contacts into a file -> contacts.txt"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {},
"outputs": [],
"source": [
"def createContact(name, ph, email):\n",
" f = open('contacts.txt', 'a')\n",
" f.write(name + '\\t'+ ph + '\\t' + email)\n",
" f.close()"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'C:\\\\Users\\\\Jesus\\\\Desktop\\\\Data Science Internship May-2021'"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import os\n",
"os.getcwd()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['.ipynb_checkpoints',\n",
" 'anil.py',\n",
" 'Day 14 Modules and Packages in Python.ipynb',\n",
" 'Day03_Markdown_Syntax.ipynb',\n",
" 'Day03_Markdown_Syntax.slides.html',\n",
" 'Day03_Markdown_Syntax.slidesa.html',\n",
" 'Day06_Python_Basics.ipynb',\n",
" 'Day07_Conditional_Statements_Loops_Strings.ipynb',\n",
" 'Day08_Strings_and_StringMethods.ipynb',\n",
" 'Day09_Lists_and_Tuples_in_Python.ipynb',\n",
" 'Day10_Dictionary_in_Python.ipynb',\n",
" 'Day11_Sets_and_Functions_in_Python.ipynb',\n",
" 'Day12_File_Handling_in_Python',\n",
" 'Day13_Files_and_Functions_Contd',\n",
" 'dummy',\n",
" 'File Handing in Python.ipynb',\n",
" 'file.txt',\n",
" 'file1.txt',\n",
" 'file10.txt',\n",
" 'file2.txt',\n",
" 'file3.txt',\n",
" 'file4.txt',\n",
" 'file5.txt',\n",
" 'file6.txt',\n",
" 'file7.txt',\n",
" 'file8.txt',\n",
" 'folderFromPython',\n",
" 'newFolder',\n",
" 'package',\n",
" 'python-logo-master-v3-TM-flattened.png',\n",
" 'Sample_Projects.ipynb',\n",
" 'Untitled.ipynb',\n",
" '__pycache__']"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"os.listdir()"
]
},
{
"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": "3.8.3"
}
},
"nbformat": 4,
"nbformat_minor": 4
}