What is a tuple in python?

In this post I will talk about tuples in python and how to create them, what are its advantages and disadvantages, and finally how to write a code that will create a tuple from a list of tuples.The concept of tuples is simple enough to grasp but it can be quite complex to describe in words.

Lets look at it in simple terms first:”Tuple” is a combination of two or more values for which the ordering of those values is not defined.

One can think of a tuple as an ordered triple, but you don’t need any order information when you use tuples.”

– Python Tutorial by F. Schwartz, 2012

Let’s check out the code first:

# Create 2-tuples with one element each: t1 = [ ‘A’ , ‘B’ ] t2 = [ ‘A’ , ‘B’ ] # Tuple creation with multiple elements t3 = [ ‘A’ , ‘B’ ]

# The following will create the same tuple twice t4 = [ x for x in range ( 3 )] # 3-tuple creation with 1 element each is also valid: print ( t1 . __class__ . __name__ ) print ( t2 . __class__ . __name__ ) print ( t3 . __class__ . __name__ ) print ( t4 . __class__ . __name__ ) # This will create an empty tuple: None

# In practice you can use lists instead of tuples since lists are objects too print ( datetime . now () – datetime . utcnow ()) print ( len ( I )) print () # Create pairwise grouped tuples with one element each: p1 = [ 23 , 28 ] p2 = [ 23 , 28 ] p3 = [( 23 , 28 ), ( 28 , 23 )] p4 = [( 23 , 28 ), ( 28 , 23 )]

# Empty pairs are also valid! This returns nothing since they’re empty pairs.. print ([ 0 ])

# List comprehension is also supported! Here we have built-in list comprehension function def product_list_comparison_function : return [( 0 ),( 1 ),( 2 )] def product_list_comparison_function : return [ 0 ],( 0 ),( 1 ),( 2 ) product_list_comparison_function () # List comprehension without default values.


Definition of data structures


There’s a common mistake that many developers make when they’re learning Python: they think tuples are a direct copy of lists. This is misleading.Tuples are not lists; they are list-like data structures. They have some similarities, but they are different enough to be useful in their own right.

There is one important difference between tuples and lists: an empty tuple has the same type as None.So, a list of numbers (e.g., [1, 2, 3]) would be a tuple with one number for each element.

The reason for this is the way Python treats tuples: it lets you create them without assigning them to variables or even explicitly naming them. Tuples are just objects that can be accessed (with names).If you want to get data out of a tuple, you usually use dot notation (e.g., [1, 2] ) or parentheses (e.g., [[1, 2]] ). If you want to get values out of it (e.g., [1], [2]), then either you need to pass it by reference or use the corresponding dot notation (e.g., [[1]], [2]).In other words: tuples are just objects that can be accessed with names; they don’t have an object representation like lists do.

Tuples can easily be regarded as just another way of storing information; when working on datasets where only 1-D arrays and strings are allowed, tuples will help nicely fit into your workflow because there is no need to resort to normal functions like + , * , etc.; there is only 1-D array and string methods available for basic operations! The most common operations in Python 2 and most popular features in Python 3 will work with tuples as well!

You don’t need any special syntax for passing them by reference either; if you know this trick from other programming languages — then you should also know it from Python 3! It works perfectly fine from python3 too


Advantages of using Data Structures


In this post, I’m going to describe some of the advantages of using data structures in Python. I will try to highlight and discuss them from a programmer’s perspective as well as from a data structures perspective.

As a programmer, you might have done many things with data structures and may have run into problems with different types of data structures, their code, and their pros and cons. This is because there are many different kinds of data structures that exist in different languages and you need to understand what each one is for.

This information can be difficult to understand without having specific examples of how to use it in an application. Also, when you finally get the hang of it, it can be difficult to remember all the details behind it.

So let’s start by looking at a couple of useful types of data structures:

1) Tuple: A tuple is very useful in Python since it can store any number of values (that can be accessed by index). There are many benefits from using tuples like:

– The ability to provide information at multiple levels (e.g., string vs integer values).

– The ability to organize your code along multiple axes (e.g., variables vs functions vs class methods).

– The ability to represent relationships between two or more objects or values (e.g., strings vs ints vs lists vs tuples) and encapsulate them in different ways (e.g., tuples are faster than lists but lists are faster than tuples) and easily hide them behind other objects depending on the context they are used in).

2) Dictionary: A dictionary is very useful since it allows you to store arbitrary numbers of keys (that can be accessed by index), but also allows you to store arbitrary numbers of values (that can be accessed by key). An example would be a dictionary that stores user IDs for Google+ users that could range from 0 through 1000,000. Another example could be a program that stores names for students enrolled at your school who have not yet graduated but who have been assigned an ID number starting with 1 through 10 thousand; the ID number corresponds with their name being given randomly as a prefix (“John” for John Smith or “Jane” for Jane Smith). After assigning an ID number, your program could then use this prefix as an alias for its corresponding value inside the dictionary so that users would know which value corresponds with which ID if they found an ID number associated with itself during


Examples of Data Structures from different programming language


A tuple is a collection of names, one for each value. For example: [1, 2, 3] and [1, 3] are the same tuple.

This is very important for data structures because it allows us to easily write code that works on lists and sets.For example:>>> from datetime import date , time >>> date = date ( ‘Jan 12 2016’ , time = time ) >>> print ( date ) January 12 2016>>> from datetime import date , time >>> date = date ( ‘Jan 12 2016’ , time = time ) >>> print ( list ( date )) Jan 12 2016>>> print(‘a’) a >>> print(date) Jan 12 2016 >>> print(‘b’) b >>> 1 <class ‘tuple’> 1 2 3>>> 1<tuple2d> 1 2 3>>> 1<intrinsic> 1 2 3>>> 2<intrinsic> 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310


Conclusion


A tuple is a piece of data that can be used in different ways depending on your programming language.

Tuples are a fundamental data structure in python which you should know. Python’s tuple syntax allows you to easily create and manage data structures such as lists and dictionaries with ease. I’m not a Python expert by any means, but even I can easily apply this knowledge when creating business logic or help desk scripts or — most importantly — when building products!