Why tuples use less space in memory than lists in Python?

Small tutorial on basic classes in Python with code examples 
17 October 2017   1000

Let's create a Python tuple:

>>> a = (1,2,3)
>>> a.__sizeof__()
48

and list

>>> b = [1,2,3]
>>> b.__sizeof__()
64

Tuple will use less memory than list. Let's figure out why.

 lists are variable-sized while tuples are fixed-size.

So tuples can store the elements directly inside the struct, lists on the other hand need a layer of indirection (it stores a pointer to the elements). This layer of indirection is a pointer, on 64bit systems that's 64bit, hence 8bytes.

But there's another thing that lists do: They over-allocate. Otherwise list.append would be an O(n) operation always - to make it amortized O(1) (much faster) it over-allocates. But now it has to keep track of the allocated size and the filled size (tuples only need to store one size, because allocated and filled size are always identical). That means each list has to store another "size" which on 64bit systems is a 64bit integer, again 8 bytes.

So lists need at least 16 bytes more memory than tuples. Because of the over-allocation. Over-allocation means it allocates more space than needed. However, the amount of over-allocation depends on "how" you create the list and the append/deletion history:

>>> l = [1,2,3]
>>> l.__sizeof__()
64
>>> l.append(4)  # triggers re-allocation (with over-allocation), because the original list is full
>>> l.__sizeof__()
96

>>> l = []
>>> l.__sizeof__()
40
>>> l.append(1)  # re-allocation with over-allocation
>>> l.__sizeof__()
72
>>> l.append(2)  # no re-alloc
>>> l.append(3)  # no re-alloc
>>> l.__sizeof__()
72
>>> l.append(4)  # still has room, so no over-allocation needed (yet)
>>> l.__sizeof__()
72

Some handy links on this topic:

  • tuple struct
  • list struct

NGINX to Release Unit 1.3 Beta

Developers expanded the ability to run web applications in Python, PHP, Perl, Ruby and Go
16 July 2018   104

In open access, a beta version of the NGINX Unit 1.3 application server was released. Developers continued to expand the ability to run web applications in Python, PHP, Perl, Ruby and Go. The project code is written in C and is distributed under the Apache 2.0 license.

Features

Version 1.3 eliminates the problems with handling errors when installing HTTP connections.

Among other changes:

  • parameter max_body_size to limit the size of the body of the request;
  • new parameters for setting timeouts when setting up an HTTP connection:
         "settings": {
              "http": {
                  "header_read_timeout": 30,
                  "body_read_timeout": 30,
                  "send_timeout": 30,
                  "idle_timeout": 180,
                  "max_body_size": 8388608
              }
          },
  • automatic use of the Bundler where possible in the Ruby module;
  • http.Flusher interface in the module for the Go language;
  • The possibility of using characters in the UTF-8 encoding in the request headers.

The first version of the NGINX 1.1 application server was released in mid-April 2018. Under the control of NGINX Unit, several applications can be executed simultaneously in different programming languages, the startup parameters of which can be changed dynamically without the need to edit the configuration files and restart.