Python List vs Array - when to use

Question

If you are creating a 1d array  you can implement it as a List  or else use the  array  module in the standard library   I have always used Lists for 1d arrays   What is the reason or circumstance where I would want to use the array module instead   Is it for performance and memory optimization  or am I missing something obvious

User · Answer

The standard library arrays are useful for binary I O  such as translating a list of ints to a string to write to  say  a wave file   That said  as many have already noted  if you re going to do any real work then you should consider using NumPy

User · Answer

It s a trade off     pros of each one    list   flexible can be heterogeneous   array  ex  numpy array    array of uniform values homogeneous compact  in size  efficient  functionality and speed  convenient

User · Answer

For almost all cases the normal list is the right choice  The arrays module is more like a thin wrapper over C arrays  which give you kind of strongly typed containers  see docs   with access to more C-like types such as signed unsigned short or double  which are not part of the built-in types  I d say use the arrays module only if you really need it  in all other cases stick with lists

User · Answer

Array can only be used for specific types  whereas lists can be used for any object   Arrays can also only data of one type  whereas a list can have entries of various object types   Arrays are also more efficient for some numerical computation

User · Answer

For almost all cases the normal list is the right choice  The arrays module is more like a thin wrapper over C arrays  which give you kind of strongly typed containers  see docs   with access to more C-like types such as signed unsigned short or double  which are not part of the built-in types  I d say use the arrays module only if you really need it  in all other cases stick with lists

User · Answer

The standard library arrays are useful for binary I O  such as translating a list of ints to a string to write to  say  a wave file   That said  as many have already noted  if you re going to do any real work then you should consider using NumPy

User · Answer

An important difference between numpy array and list is that array slices are views on the original array  This means that the data is not copied  and any modifications to the view will be reflected in the source array

User · Answer

This answer will sum up almost all the queries about when to use List and Array    The main difference between these two data types is the operations you can perform on them  For example  you can divide an array by 3 and it will divide each element of array by 3  Same can not be done with the list  The list is the part of python s syntax so it doesn t need to be declared whereas you have to declare the array before using it  You can store values of different data-types in a list  heterogeneous   whereas in Array you can only store values of only the same data-type  homogeneous   Arrays being rich in functionalities and fast  it is widely used for arithmetic operations and for storing a large amount of data - compared to list  Arrays take less memory compared to lists

User · Answer

For almost all cases the normal list is the right choice  The arrays module is more like a thin wrapper over C arrays  which give you kind of strongly typed containers  see docs   with access to more C-like types such as signed unsigned short or double  which are not part of the built-in types  I d say use the arrays module only if you really need it  in all other cases stick with lists

User · Answer

My understanding is that arrays are stored more efficiently  i e  as contiguous blocks of memory vs  pointers to Python objects   but I am not aware of any performance benefit   Additionally  with arrays you must store primitives of the same type  whereas lists can store anything

User · Answer

The array module is kind of one of those things that you probably don t have a need for if you don t know why you would use it  and take note that I m not trying to say that in a condescending manner     Most of the time  the array module is used to interface with C code   To give you a more direct answer to your question about performance   Arrays are more efficient than lists for some uses   If you need to allocate an array that you KNOW will not change  then arrays can be faster and use less memory   GvR has an optimization anecdote in which the array module comes out to be the winner  long read  but worth it    On the other hand  part of the reason why lists eat up more memory than arrays is because python will allocate a few extra elements when all allocated elements get used   This means that appending items to lists is faster   So if you plan on adding items  a list is the way to go   TL DR I d only use an array if you had an exceptional optimization need or you need to interface with C code  and can t use pyrex

User · Answer

If you re going to be using arrays  consider the numpy or scipy packages  which give you arrays with a lot more flexibility

User · Answer

It s a trade off     pros of each one    list   flexible can be heterogeneous   array  ex  numpy array    array of uniform values homogeneous compact  in size  efficient  functionality and speed  convenient

User · Answer

My understanding is that arrays are stored more efficiently  i e  as contiguous blocks of memory vs  pointers to Python objects   but I am not aware of any performance benefit   Additionally  with arrays you must store primitives of the same type  whereas lists can store anything

User · Answer

The array module is kind of one of those things that you probably don t have a need for if you don t know why you would use it  and take note that I m not trying to say that in a condescending manner     Most of the time  the array module is used to interface with C code   To give you a more direct answer to your question about performance   Arrays are more efficient than lists for some uses   If you need to allocate an array that you KNOW will not change  then arrays can be faster and use less memory   GvR has an optimization anecdote in which the array module comes out to be the winner  long read  but worth it    On the other hand  part of the reason why lists eat up more memory than arrays is because python will allocate a few extra elements when all allocated elements get used   This means that appending items to lists is faster   So if you plan on adding items  a list is the way to go   TL DR I d only use an array if you had an exceptional optimization need or you need to interface with C code  and can t use pyrex

User · Answer

With regard to performance  here are some numbers comparing python lists  arrays and numpy arrays  all with Python 3 7 on a 2017 Macbook Pro   The end result is that the python list is fastest for these operations     Python list with append   np mean timeit repeat setup  a        stmt  a append 1 0    number 1000  repeat 5000     1000   0 054   - 0 025 msec    Python array with append   np mean timeit repeat setup  import array  a   array array  f     stmt  a append 1 0    number 1000  repeat 5000     1000   0 104   - 0 025 msec    Numpy array with append   np mean timeit repeat setup  import numpy as np  a   np array       stmt  np append a   1 0     number 1000  repeat 5000     1000   5 183   - 0 950 msec    Python list using    np mean timeit repeat setup  a        stmt  a     1 0    number 1000  repeat 5000     1000   0 062   - 0 021 msec    Python array using     np mean timeit repeat setup  import array  a   array array  f     stmt  a    array array  f    1 0      number 1000  repeat 5000     1000   0 289   - 0 043 msec    Python list using extend   np mean timeit repeat setup  a        stmt  a extend  1 0     number 1000  repeat 5000     1000   0 083   - 0 020 msec    Python array using extend   np mean timeit repeat setup  import array  a   array array  f     stmt  a extend  1 0      number 1000  repeat 5000     1000   0 169   - 0 034

User · Answer

This answer will sum up almost all the queries about when to use List and Array    The main difference between these two data types is the operations you can perform on them  For example  you can divide an array by 3 and it will divide each element of array by 3  Same can not be done with the list  The list is the part of python s syntax so it doesn t need to be declared whereas you have to declare the array before using it  You can store values of different data-types in a list  heterogeneous   whereas in Array you can only store values of only the same data-type  homogeneous   Arrays being rich in functionalities and fast  it is widely used for arithmetic operations and for storing a large amount of data - compared to list  Arrays take less memory compared to lists

User · Answer

My understanding is that arrays are stored more efficiently  i e  as contiguous blocks of memory vs  pointers to Python objects   but I am not aware of any performance benefit   Additionally  with arrays you must store primitives of the same type  whereas lists can store anything

User · Answer

Basically  Python lists are very flexible and can hold completely heterogeneous  arbitrary data  and they can be appended to very efficiently  in amortized constant time   If you need to shrink and grow your list time-efficiently and without hassle  they are the way to go   But they use a lot more space than C arrays  in part because each item in the list requires the construction of an individual Python object  even for data that could be represented with simple C types  e g  float or uint64 t   The array array type  on the other hand  is just a thin wrapper on C arrays   It can hold only homogeneous data  that is to say  all of the same type  and so it uses only sizeof one object    length bytes of memory   Mostly  you should use it when you need to expose a C array to an extension or a system call  for example  ioctl or fctnl   array array is also a reasonable way to represent a mutable string in Python 2 x  array  B   bytes    However  Python 2 6  and 3 x offer a mutable byte string as bytearray  However  if you want to do math on a homogeneous array of numeric data  then you re much better off using NumPy  which can automatically vectorize operations on complex multi-dimensional arrays  To make a long story short  array array is useful when you need a homogeneous C array of data for reasons other than doing math

User · Answer

With regard to performance  here are some numbers comparing python lists  arrays and numpy arrays  all with Python 3 7 on a 2017 Macbook Pro   The end result is that the python list is fastest for these operations     Python list with append   np mean timeit repeat setup  a        stmt  a append 1 0    number 1000  repeat 5000     1000   0 054   - 0 025 msec    Python array with append   np mean timeit repeat setup  import array  a   array array  f     stmt  a append 1 0    number 1000  repeat 5000     1000   0 104   - 0 025 msec    Numpy array with append   np mean timeit repeat setup  import numpy as np  a   np array       stmt  np append a   1 0     number 1000  repeat 5000     1000   5 183   - 0 950 msec    Python list using    np mean timeit repeat setup  a        stmt  a     1 0    number 1000  repeat 5000     1000   0 062   - 0 021 msec    Python array using     np mean timeit repeat setup  import array  a   array array  f     stmt  a    array array  f    1 0      number 1000  repeat 5000     1000   0 289   - 0 043 msec    Python list using extend   np mean timeit repeat setup  a        stmt  a extend  1 0     number 1000  repeat 5000     1000   0 083   - 0 020 msec    Python array using extend   np mean timeit repeat setup  import array  a   array array  f     stmt  a extend  1 0      number 1000  repeat 5000     1000   0 169   - 0 034

User · Answer

The standard library arrays are useful for binary I O  such as translating a list of ints to a string to write to  say  a wave file   That said  as many have already noted  if you re going to do any real work then you should consider using NumPy

User · Answer

The array module is kind of one of those things that you probably don t have a need for if you don t know why you would use it  and take note that I m not trying to say that in a condescending manner     Most of the time  the array module is used to interface with C code   To give you a more direct answer to your question about performance   Arrays are more efficient than lists for some uses   If you need to allocate an array that you KNOW will not change  then arrays can be faster and use less memory   GvR has an optimization anecdote in which the array module comes out to be the winner  long read  but worth it    On the other hand  part of the reason why lists eat up more memory than arrays is because python will allocate a few extra elements when all allocated elements get used   This means that appending items to lists is faster   So if you plan on adding items  a list is the way to go   TL DR I d only use an array if you had an exceptional optimization need or you need to interface with C code  and can t use pyrex

User · Answer

Array can only be used for specific types  whereas lists can be used for any object   Arrays can also only data of one type  whereas a list can have entries of various object types   Arrays are also more efficient for some numerical computation

User · Answer

An important difference between numpy array and list is that array slices are views on the original array  This means that the data is not copied  and any modifications to the view will be reflected in the source array

User · Answer

My understanding is that arrays are stored more efficiently  i e  as contiguous blocks of memory vs  pointers to Python objects   but I am not aware of any performance benefit   Additionally  with arrays you must store primitives of the same type  whereas lists can store anything

User · Answer

If you re going to be using arrays  consider the numpy or scipy packages  which give you arrays with a lot more flexibility

User · Answer

Basically  Python lists are very flexible and can hold completely heterogeneous  arbitrary data  and they can be appended to very efficiently  in amortized constant time   If you need to shrink and grow your list time-efficiently and without hassle  they are the way to go   But they use a lot more space than C arrays  in part because each item in the list requires the construction of an individual Python object  even for data that could be represented with simple C types  e g  float or uint64 t   The array array type  on the other hand  is just a thin wrapper on C arrays   It can hold only homogeneous data  that is to say  all of the same type  and so it uses only sizeof one object    length bytes of memory   Mostly  you should use it when you need to expose a C array to an extension or a system call  for example  ioctl or fctnl   array array is also a reasonable way to represent a mutable string in Python 2 x  array  B   bytes    However  Python 2 6  and 3 x offer a mutable byte string as bytearray  However  if you want to do math on a homogeneous array of numeric data  then you re much better off using NumPy  which can automatically vectorize operations on complex multi-dimensional arrays  To make a long story short  array array is useful when you need a homogeneous C array of data for reasons other than doing math

User · Answer

The array module is kind of one of those things that you probably don t have a need for if you don t know why you would use it  and take note that I m not trying to say that in a condescending manner     Most of the time  the array module is used to interface with C code   To give you a more direct answer to your question about performance   Arrays are more efficient than lists for some uses   If you need to allocate an array that you KNOW will not change  then arrays can be faster and use less memory   GvR has an optimization anecdote in which the array module comes out to be the winner  long read  but worth it    On the other hand  part of the reason why lists eat up more memory than arrays is because python will allocate a few extra elements when all allocated elements get used   This means that appending items to lists is faster   So if you plan on adding items  a list is the way to go   TL DR I d only use an array if you had an exceptional optimization need or you need to interface with C code  and can t use pyrex

User · Answer

If you re going to be using arrays  consider the numpy or scipy packages  which give you arrays with a lot more flexibility

User · Answer

The standard library arrays are useful for binary I O  such as translating a list of ints to a string to write to  say  a wave file   That said  as many have already noted  if you re going to do any real work then you should consider using NumPy

User · Answer

If you re going to be using arrays  consider the numpy or scipy packages  which give you arrays with a lot more flexibility

User · Answer

Array can only be used for specific types  whereas lists can be used for any object   Arrays can also only data of one type  whereas a list can have entries of various object types   Arrays are also more efficient for some numerical computation

User · Answer

Basically  Python lists are very flexible and can hold completely heterogeneous  arbitrary data  and they can be appended to very efficiently  in amortized constant time   If you need to shrink and grow your list time-efficiently and without hassle  they are the way to go   But they use a lot more space than C arrays  in part because each item in the list requires the construction of an individual Python object  even for data that could be represented with simple C types  e g  float or uint64 t   The array array type  on the other hand  is just a thin wrapper on C arrays   It can hold only homogeneous data  that is to say  all of the same type  and so it uses only sizeof one object    length bytes of memory   Mostly  you should use it when you need to expose a C array to an extension or a system call  for example  ioctl or fctnl   array array is also a reasonable way to represent a mutable string in Python 2 x  array  B   bytes    However  Python 2 6  and 3 x offer a mutable byte string as bytearray  However  if you want to do math on a homogeneous array of numeric data  then you re much better off using NumPy  which can automatically vectorize operations on complex multi-dimensional arrays  To make a long story short  array array is useful when you need a homogeneous C array of data for reasons other than doing math

User · Answer

Array can only be used for specific types  whereas lists can be used for any object   Arrays can also only data of one type  whereas a list can have entries of various object types   Arrays are also more efficient for some numerical computation

User · Answer

For almost all cases the normal list is the right choice  The arrays module is more like a thin wrapper over C arrays  which give you kind of strongly typed containers  see docs   with access to more C-like types such as signed unsigned short or double  which are not part of the built-in types  I d say use the arrays module only if you really need it  in all other cases stick with lists

User · Answer

Basically  Python lists are very flexible and can hold completely heterogeneous  arbitrary data  and they can be appended to very efficiently  in amortized constant time   If you need to shrink and grow your list time-efficiently and without hassle  they are the way to go   But they use a lot more space than C arrays  in part because each item in the list requires the construction of an individual Python object  even for data that could be represented with simple C types  e g  float or uint64 t   The array array type  on the other hand  is just a thin wrapper on C arrays   It can hold only homogeneous data  that is to say  all of the same type  and so it uses only sizeof one object    length bytes of memory   Mostly  you should use it when you need to expose a C array to an extension or a system call  for example  ioctl or fctnl   array array is also a reasonable way to represent a mutable string in Python 2 x  array  B   bytes    However  Python 2 6  and 3 x offer a mutable byte string as bytearray  However  if you want to do math on a homogeneous array of numeric data  then you re much better off using NumPy  which can automatically vectorize operations on complex multi-dimensional arrays  To make a long story short  array array is useful when you need a homogeneous C array of data for reasons other than doing math

[python] Python List vs. Array - when to use?

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