Declaring Attributes of Functions

Declaring Attributes of Functions

In GNU C, you declare certain things about functions called in your program which help the compiler optimize function calls and check your code more carefully.
The keyword __attribute__ allows you to specify special attributes when making a declaration. This keyword is followed by an attribute specification inside double parentheses. The following attributes are currently defined for functions on all targets: noreturn, noinline, always_inline, pure, const, nothrow, format, format_arg, no_instrument_function, section, constructor, destructor, used, unused, deprecated, weak, malloc, alias, and nonnull. Several other attributes are defined for functions on particular target systems. Other attributes, including section are supported for variables declarations (see Variable Attributes) and for types (see Type Attributes).
You may also specify attributes with __ preceding and following each keyword. This allows you to use them in header files without being concerned about a possible macro of the same name. For example, you may use __noreturn__ instead of noreturn.
See Attribute Syntax, for details of the exact syntax for using attributes.

noreturn

A few standard library functions, such as abort and exit, cannot return. GCC knows this automatically. Some programs define their own functions that never return. You can declare them noreturn to tell the compiler this fact. For example,

          void fatal () __attribute__ ((noreturn));
          
          void
          fatal (/* ... */)
          {
            /* ... */ /* Print error message. */ /* ... */
            exit (1);
          }
          

The noreturn keyword tells the compiler to assume that fatal cannot return. It can then optimize without regard to what would happen if fatal ever did return. This makes slightly better code. More importantly, it helps avoid spurious warnings of uninitialized variables.
Do not assume that registers saved by the calling function are restored before calling the noreturn function.
It does not make sense for a noreturn function to have a return type other than void.
The attribute noreturn is not implemented in GCC versions earlier than 2.5. An alternative way to declare that a function does not return, which works in the current version and in some older versions, is as follows:

          typedef void voidfn ();
          
          volatile voidfn fatal;
          

noinline

This function attribute prevents a function from being considered for inlining.

always_inline

Generally, functions are not inlined unless optimization is specified. For functions declared inline, this attribute inlines the function even if no optimization level was specified.

pure

Many functions have no effects except the return value and their return value depends only on the parameters and/or global variables. Such a function can be subject to common subexpression elimination and loop optimization just as an arithmetic operator would be. These functions should be declared with the attribute pure. For example,

          int square (int) __attribute__ ((pure));
          

says that the hypothetical function square is safe to call fewer times than the program says.
Some of common examples of pure functions are strlen or memcmp. Interesting non-pure functions are functions with infinite loops or those depending on volatile memory or other system resource, that may change between two consecutive calls (such as feof in a multithreading environment).
The attribute pure is not implemented in GCC versions earlier than 2.96.

const

Many functions do not examine any values except their arguments, and have no effects except the return value. Basically this is just slightly more strict class than the pure attribute above, since function is not allowed to read global memory. Note that a function that has pointer arguments and examines the data pointed to must not be declared const. Likewise, a function that calls a non-const function usually must not be const. It does not make sense for a const function to return void.
The attribute const is not implemented in GCC versions earlier than 2.5. An alternative way to declare that a function has no side effects, which works in the current version and in some older versions, is as follows:

          typedef int intfn ();
          
          extern const intfn square;
          

This approach does not work in GNU C++ from 2.6.0 on, since the language specifies that the const must be attached to the return value.

nothrow

The nothrow attribute is used to inform the compiler that a function cannot throw an exception. For example, most functions in the standard C library can be guaranteed not to throw an exception with the notable exceptions of qsort and bsearch that take function pointer arguments. The nothrow attribute is not implemented in GCC versions earlier than 3.2.

format (archetype, string-index, first-to-check)

The format attribute specifies that a function takes printf, scanf, strftime or strfmon style arguments which should be type-checked against a format string. For example, the declaration:

          extern int
          my_printf (void *my_object, const char *my_format, ...)
                __attribute__ ((format (printf, 2, 3)));
          

causes the compiler to check the arguments in calls to my_printf for consistency with the printf style format string argument my_format.
The parameter archetype determines how the format string is interpreted, and should be printf, scanf, strftime or strfmon. (You can also use __printf__, __scanf__, __strftime__ or __strfmon__.) The parameter string-index specifies which argument is the format string argument (starting from 1), while first-to-check is the number of the first argument to check against the format string. For functions where the arguments are not available to be checked (such as vprintf), specify the third parameter as zero. In this case the compiler only checks the format string for consistency. For strftime formats, the third parameter is required to be zero.
In the example above, the format string (my_format) is the second argument of the function my_print, and the arguments to check start with the third argument, so the correct parameters for the format attribute are 2 and 3.
The format attribute allows you to identify your own functions which take format strings as arguments, so that GCC can check the calls to these functions for errors. The compiler always (unless -ffreestanding is used) checks formats for the standard library functions printf, fprintf, sprintf, scanf, fscanf, sscanf, strftime, vprintf, vfprintf and vsprintf whenever such warnings are requested (using -Wformat), so there is no need to modify the header file stdio.h. In C99 mode, the functions snprintf, vsnprintf, vscanf, vfscanf and vsscanf are also checked. Except in strictly conforming C standard modes, the X/Open function strfmon is also checked as are printf_unlocked and fprintf_unlocked. See Options Controlling C Dialect.

format_arg (string-index)

The format_arg attribute specifies that a function takes a format string for a printf, scanf, strftime or strfmon style function and modifies it (for example, to translate it into another language), so the result can be passed to a printf, scanf, strftime or strfmon style function (with the remaining arguments to the format function the same as they would have been for the unmodified string). For example, the declaration:

          extern char *
          my_dgettext (char *my_domain, const char *my_format)
                __attribute__ ((format_arg (2)));
          

causes the compiler to check the arguments in calls to a printf, scanf, strftime or strfmon type function, whose format string argument is a call to the my_dgettext function, for consistency with the format string argument my_format. If the format_arg attribute had not been specified, all the compiler could tell in such calls to format functions would be that the format string argument is not constant; this would generate a warning when -Wformat-nonliteral is used, but the calls could not be checked without the attribute.
The parameter string-index specifies which argument is the format string argument (starting from 1).
The format-arg attribute allows you to identify your own functions which modify format strings, so that GCC can check the calls to printf, scanf, strftime or strfmon type function whose operands are a call to one of your own function. The compiler always treats gettext, dgettext, and dcgettext in this manner except when strict ISO C support is requested by -ansi or an appropriate -std option, or -ffreestanding is used. See Options Controlling C Dialect.

nonnull (arg-index, ...)

The nonnull attribute specifies that some function parameters should be non-null pointers. For instance, the declaration:

          extern void *
          my_memcpy (void *dest, const void *src, size_t len)
           __attribute__((nonnull (1, 2)));
          

causes the compiler to check that, in calls to my_memcpy, arguments dest and src are non-null. If the compiler determines that a null pointer is passed in an argument slot marked as non-null, and the -Wnonnull option is enabled, a warning is issued. The compiler may also choose to make optimizations based on the knowledge that certain function arguments will not be null.
If no argument index list is given to the nonnull attribute, all pointer arguments are marked as non-null. To illustrate, the following declaration is equivalent to the previous example:

          extern void *
          my_memcpy (void *dest, const void *src, size_t len)
           __attribute__((nonnull));
          

no_instrument_function

If -finstrument-functions is given, profiling function calls will be generated at entry and exit of most user-compiled functions. Functions with this attribute will not be so instrumented.

section ("section-name")

Normally, the compiler places the code it generates in the text section. Sometimes, however, you need additional sections, or you need certain particular functions to appear in special sections. The section attribute specifies that a function lives in a particular section. For example, the declaration:

          extern void foobar (void) __attribute__ ((section ("bar")));
          

puts the function foobar in the bar section.
Some file formats do not support arbitrary sections so the section attribute is not available on all platforms. If you need to map the entire contents of a module to a particular section, consider using the facilities of the linker instead.

constructor

destructor

The constructor attribute causes the function to be called automatically before execution enters main (). Similarly, the destructor attribute causes the function to be called automatically after main () has completed or exit () has been called. Functions with these attributes are useful for initializing data that will be used implicitly during the execution of the program. These attributes are not currently implemented for Objective-C.

unused

This attribute, attached to a function, means that the function is meant to be possibly unused. GCC will not produce a warning for this function. GNU C++ does not currently support this attribute as definitions without parameters are valid in C++.

used

This attribute, attached to a function, means that code must be emitted for the function even if it appears that the function is not referenced. This is useful, for example, when the function is referenced only in inline assembly.

deprecated

The deprecated attribute results in a warning if the function is used anywhere in the source file. This is useful when identifying functions that are expected to be removed in a future version of a program. The warning also includes the location of the declaration of the deprecated function, to enable users to easily find further information about why the function is deprecated, or what they should do instead. Note that the warnings only occurs for uses:

          int old_fn () __attribute__ ((deprecated));
          int old_fn ();
          int (*fn_ptr)() = old_fn;
          

results in a warning on line 3 but not line 2.
The deprecated attribute can also be used for variables and types (see Variable Attributes, see Type Attributes.)

weak

The weak attribute causes the declaration to be emitted as a weak symbol rather than a global. This is primarily useful in defining library functions which can be overridden in user code, though it can also be used with non-function declarations. Weak symbols are supported for ELF targets, and also for a.out targets when using the GNU assembler and linker.

malloc

The malloc attribute is used to tell the compiler that a function may be treated as if it were the malloc function. The compiler assumes that calls to malloc result in a pointers that cannot alias anything. This will often improve optimization.

alias ("target")

The alias attribute causes the declaration to be emitted as an alias for another symbol, which must be specified. For instance,

          void __f () { /* Do something. */; }
          void f () __attribute__ ((weak, alias ("__f")));
          

declares f to be a weak alias for __f. In C++, the mangled name for the target must be used.
Not all target machines support this attribute.

visibility ("visibility_type")

The visibility attribute on ELF targets causes the declaration to be emitted with default, hidden, protected or internal visibility.

          void __attribute__ ((visibility ("protected")))
          f () { /* Do something. */; }
          int i __attribute__ ((visibility ("hidden")));
          

See the ELF gABI for complete details, but the short story is

default

Default visibility is the normal case for ELF. This value is available for the visibility attribute to override other options that may change the assumed visibility of symbols.

hidden

Hidden visibility indicates that the symbol will not be placed into the dynamic symbol table, so no other module (executable or shared library) can reference it directly.

protected

Protected visibility indicates that the symbol will be placed in the dynamic symbol table, but that references within the defining module will bind to the local symbol. That is, the symbol cannot be overridden by another module.

internal

Internal visibility is like hidden visibility, but with additional processor specific semantics. Unless otherwise specified by the psABI, gcc defines internal visibility to mean that the function is never called from another module. Note that hidden symbols, while then cannot be referenced directly by other modules, can be referenced indirectly via function pointers. By indicating that a symbol cannot be called from outside the module, gcc may for instance omit the load of a PIC register since it is known that the calling function loaded the correct value.

Not all ELF targets support this attribute.

tls_model ("tls_model")

The tls_model attribute sets thread-local storage model (see Thread-Local) of a particular __thread variable, overriding -ftls-model= command line switch on a per-variable basis. The tls_model argument should be one of global-dynamic, local-dynamic, initial-exec or local-exec.

regparm (number)

On the Intel 386, the regparm attribute causes the compiler to pass up to number integer arguments in registers EAX, EDX, and ECX instead of on the stack. Functions that take a variable number of arguments will continue to be passed all of their arguments on the stack.

stdcall

On the Intel 386, the stdcall attribute causes the compiler to assume that the called function will pop off the stack space used to pass arguments, unless it takes a variable number of arguments. The PowerPC compiler for Windows NT currently ignores the stdcall attribute.

cdecl

On the Intel 386, the cdecl attribute causes the compiler to assume that the calling function will pop off the stack space used to pass arguments. This is useful to override the effects of the -mrtd switch. The PowerPC compiler for Windows NT currently ignores the cdecl attribute.

longcall/shortcall

On the RS/6000 and PowerPC, the longcall attribute causes the compiler to always call this function via a pointer, just as it would if the -mlongcall option had been specified. The shortcall attribute causes the compiler not to do this. These attributes override both the -mlongcall switch and the #pragma longcall setting. See RS/6000 and PowerPC Options, for more information on when long calls are and are not necessary.

long_call/short_call

This attribute allows to specify how to call a particular function on ARM. Both attributes override the -mlong-calls (see ARM Options) command line switch and #pragma long_calls settings. The long_call attribute causes the compiler to always call the function by first loading its address into a register and then using the contents of that register. The short_call attribute always places the offset to the function from the call site into the BL instruction directly.

dllimport

On the PowerPC running Windows NT, the dllimport attribute causes the compiler to call the function via a global pointer to the function pointer that is set up by the Windows NT dll library. The pointer name is formed by combining __imp_ and the function name.

dllexport

On the PowerPC running Windows NT, the dllexport attribute causes the compiler to provide a global pointer to the function pointer, so that it can be called with the dllimport attribute. The pointer name is formed by combining __imp_ and the function name.

exception (except-func [, except-arg])

On the PowerPC running Windows NT, the exception attribute causes the compiler to modify the structured exception table entry it emits for the declared function. The string or identifier except-func is placed in the third entry of the structured exception table. It represents a function, which is called by the exception handling mechanism if an exception occurs. If it was specified, the string or identifier except-arg is placed in the fourth entry of the structured exception table.

function_vector

Use this attribute on the H8/300 and H8/300H to indicate that the specified function should be called through the function vector. Calling a function through the function vector will reduce code size, however; the function vector has a limited size (maximum 128 entries on the H8/300 and 64 entries on the H8/300H) and shares space with the interrupt vector. You must use GAS and GLD from GNU binutils version 2.7 or later for this attribute to work correctly.

interrupt

Use this attribute on the ARM, AVR, M32R/D and Xstormy16 ports to indicate that the specified function is an interrupt handler. The compiler will generate function entry and exit sequences suitable for use in an interrupt handler when this attribute is present. Note, interrupt handlers for the H8/300, H8/300H and SH processors can be specified via the interrupt_handler attribute.
Note, on the AVR interrupts will be enabled inside the function.
Note, for the ARM you can specify the kind of interrupt to be handled by adding an optional parameter to the interrupt attribute like this:

          void f () __attribute__ ((interrupt ("IRQ")));
          

Permissible values for this parameter are: IRQ, FIQ, SWI, ABORT and UNDEF.

interrupt_handler

Use this attribute on the H8/300, H8/300H and SH to indicate that the specified function is an interrupt handler. The compiler will generate function entry and exit sequences suitable for use in an interrupt handler when this attribute is present.

sp_switch

Use this attribute on the SH to indicate an interrupt_handler function should switch to an alternate stack. It expects a string argument that names a global variable holding the address of the alternate stack.

          void *alt_stack;
          void f () __attribute__ ((interrupt_handler,
                                    sp_switch ("alt_stack")));
          

trap_exit

Use this attribute on the SH for an interrupt_handle to return using trapa instead of rte. This attribute expects an integer argument specifying the trap number to be used.

eightbit_data

Use this attribute on the H8/300 and H8/300H to indicate that the specified variable should be placed into the eight bit data section. The compiler will generate more efficient code for certain operations on data in the eight bit data area. Note the eight bit data area is limited to 256 bytes of data. You must use GAS and GLD from GNU binutils version 2.7 or later for this attribute to work correctly.

tiny_data

Use this attribute on the H8/300H to indicate that the specified variable should be placed into the tiny data section. The compiler will generate more efficient code for loads and stores on data in the tiny data section. Note the tiny data area is limited to slightly under 32kbytes of data.

signal

Use this attribute on the AVR to indicate that the specified function is an signal handler. The compiler will generate function entry and exit sequences suitable for use in an signal handler when this attribute is present. Interrupts will be disabled inside function.

naked

Use this attribute on the ARM, AVR and IP2K ports to indicate that the specified function do not need prologue/epilogue sequences generated by the compiler. It is up to the programmer to provide these sequences.

model (model-name)

Use this attribute on the M32R/D to set the addressability of an object, and the code generated for a function. The identifier model-name is one of small, medium, or large, representing each of the code models. Small model objects live in the lower 16MB of memory (so that their addresses can be loaded with the ld24 instruction), and are callable with the bl instruction.
Medium model objects may live anywhere in the 32-bit address space (the compiler will generate seth/add3 instructions to load their addresses), and are callable with the bl instruction.
Large model objects may live anywhere in the 32-bit address space (the compiler will generate seth/add3 instructions to load their addresses), and may not be reachable with the bl instruction (the compiler will generate the much slower seth/add3/jl instruction sequence).

far

On 68HC11 and 68HC12 the far attribute causes the compiler to use a calling convention that takes care of switching memory banks when entering and leaving a function. This calling convention is also the default when using the -mlong-calls option. On 68HC12 the compiler will use the call and rtc instructions to call and return from a function.
On 68HC11 the compiler will generate a sequence of instructions to invoke a board-specific routine to switch the memory bank and call the real function. The board-specific routine simulates a call. At the end of a function, it will jump to a board-specific routine instead of using rts. The board-specific return routine simulates the rtc.

near

On 68HC11 and 68HC12 the near attribute causes the compiler to use the normal calling convention based on jsr and rts. This attribute can be used to cancel the effect of the -mlong-calls option.

You can specify multiple attributes in a declaration by separating them by commas within the double parentheses or by immediately following an attribute declaration with another attribute declaration.
Some people object to the __attribute__ feature, suggesting that ISO C's #pragma should be used instead. At the time __attribute__ was designed, there were two reasons for not doing this.

1. It is impossible to generate #pragma commands from a macro.
2. There is no telling what the same #pragma might mean in another compiler.

These two reasons applied to almost any application that might have been proposed for #pragma. It was basically a mistake to use #pragma for anything.
The ISO C99 standard includes _Pragma, which now allows pragmas to be generated from macros. In addition, a #pragma GCC namespace is now in use for GCC-specific pragmas. However, it has been found convenient to use __attribute__ to achieve a natural attachment of attributes to their corresponding declarations, whereas #pragma GCC is of use for constructs that do not naturally form part of the grammar. See Miscellaneous Preprocessing Directives.

Reference:

https://gcc.gnu.org/onlinedocs/gcc-3.3/gcc/Function-Attributes.html

Specifying Attributes of Variables

Specifying Attributes of Variables

The keyword __attribute__ allows you to specify special attributes of variables or structure fields. This keyword is followed by an attribute specification inside double parentheses. Ten attributes are currently defined for variables: aligned, mode, nocommon, packed, section, transparent_union, unused, deprecated, vector_size, and weak. Some other attributes are defined for variables on particular target systems. Other attributes are available for functions (see Function Attributes) and for types (see Type Attributes). Other front ends might define more attributes (see Extensions to the C++ Language).
You may also specify attributes with __ preceding and following each keyword. This allows you to use them in header files without being concerned about a possible macro of the same name. For example, you may use __aligned__ instead of aligned.
See Attribute Syntax, for details of the exact syntax for using attributes.

aligned (alignment)

This attribute specifies a minimum alignment for the variable or structure field, measured in bytes. For example, the declaration:

          int x __attribute__ ((aligned (16))) = 0;
          

causes the compiler to allocate the global variable x on a 16-byte boundary. On a 68040, this could be used in conjunction with an asm expression to access the move16 instruction which requires 16-byte aligned operands.
You can also specify the alignment of structure fields. For example, to create a double-word aligned int pair, you could write:

          struct foo { int x[2] __attribute__ ((aligned (8))); };
          

This is an alternative to creating a union with a double member that forces the union to be double-word aligned.
As in the preceding examples, you can explicitly specify the alignment (in bytes) that you wish the compiler to use for a given variable or structure field. Alternatively, you can leave out the alignment factor and just ask the compiler to align a variable or field to the maximum useful alignment for the target machine you are compiling for. For example, you could write:

          short array[3] __attribute__ ((aligned));
          

Whenever you leave out the alignment factor in an aligned attribute specification, the compiler automatically sets the alignment for the declared variable or field to the largest alignment which is ever used for any data type on the target machine you are compiling for. Doing this can often make copy operations more efficient, because the compiler can use whatever instructions copy the biggest chunks of memory when performing copies to or from the variables or fields that you have aligned this way.
The aligned attribute can only increase the alignment; but you can decrease it by specifying packed as well. See below.
Note that the effectiveness of aligned attributes may be limited by inherent limitations in your linker. On many systems, the linker is only able to arrange for variables to be aligned up to a certain maximum alignment. (For some linkers, the maximum supported alignment may be very very small.) If your linker is only able to align variables up to a maximum of 8 byte alignment, then specifying aligned(16) in an __attribute__ will still only provide you with 8 byte alignment. See your linker documentation for further information.

mode (mode)

This attribute specifies the data type for the declaration--whichever type corresponds to the mode mode. This in effect lets you request an integer or floating point type according to its width. You may also specify a mode of byte or __byte__ to indicate the mode corresponding to a one-byte integer, word or __word__ for the mode of a one-word integer, and pointer or __pointer__ for the mode used to represent pointers.

nocommon

This attribute specifies requests GCC not to place a variable "common" but instead to allocate space for it directly. If you specify the -fno-common flag, GCC will do this for all variables. Specifying the nocommon attribute for a variable provides an initialization of zeros. A variable may only be initialized in one source file.

packed

The packed attribute specifies that a variable or structure field should have the smallest possible alignment--one byte for a variable, and one bit for a field, unless you specify a larger value with the aligned attribute. Here is a structure in which the field x is packed, so that it immediately follows a:

          struct foo
          {
            char a;
            int x[2] __attribute__ ((packed));
          };
          

section ("section-name")

Normally, the compiler places the objects it generates in sections like data and bss. Sometimes, however, you need additional sections, or you need certain particular variables to appear in special sections, for example to map to special hardware. The section attribute specifies that a variable (or function) lives in a particular section. For example, this small program uses several specific section names:

          struct duart a __attribute__ ((section ("DUART_A"))) = { 0 };
          struct duart b __attribute__ ((section ("DUART_B"))) = { 0 };
          char stack[10000] __attribute__ ((section ("STACK"))) = { 0 };
          int init_data __attribute__ ((section ("INITDATA"))) = 0;
          
          main()
          {
            /* Initialize stack pointer */
            init_sp (stack + sizeof (stack));
          
            /* Initialize initialized data */
            memcpy (&init_data, &data, &edata - &data);
          
            /* Turn on the serial ports */
            init_duart (&a);
            init_duart (&b);
          }
          

Use the section attribute with an initialized definition of a global variable, as shown in the example. GCC issues a warning and otherwise ignores the section attribute in uninitialized variable declarations.
You may only use the section attribute with a fully initialized global definition because of the way linkers work. The linker requires each object be defined once, with the exception that uninitialized variables tentatively go in the common (or bss) section and can be multiply "defined". You can force a variable to be initialized with the -fno-common flag or the nocommon attribute.
Some file formats do not support arbitrary sections so the section attribute is not available on all platforms. If you need to map the entire contents of a module to a particular section, consider using the facilities of the linker instead.

shared

On Windows NT, in addition to putting variable definitions in a named section, the section can also be shared among all running copies of an executable or DLL. For example, this small program defines shared data by putting it in a named section shared and marking the section shareable:

          int foo __attribute__((section ("shared"), shared)) = 0;
          
          int
          main()
          {
            /* Read and write foo.  All running
               copies see the same value.  */
            return 0;
          }
          

You may only use the shared attribute along with section attribute with a fully initialized global definition because of the way linkers work. See section attribute for more information.
The shared attribute is only available on Windows NT.

transparent_union

This attribute, attached to a function parameter which is a union, means that the corresponding argument may have the type of any union member, but the argument is passed as if its type were that of the first union member. For more details see See Type Attributes. You can also use this attribute on a typedef for a union data type; then it applies to all function parameters with that type.

unused

This attribute, attached to a variable, means that the variable is meant to be possibly unused. GCC will not produce a warning for this variable.

deprecated

The deprecated attribute results in a warning if the variable is used anywhere in the source file. This is useful when identifying variables that are expected to be removed in a future version of a program. The warning also includes the location of the declaration of the deprecated variable, to enable users to easily find further information about why the variable is deprecated, or what they should do instead. Note that the warnings only occurs for uses:

          extern int old_var __attribute__ ((deprecated));
          extern int old_var;
          int new_fn () { return old_var; }
          

results in a warning on line 3 but not line 2.
The deprecated attribute can also be used for functions and types (see Function Attributes, see Type Attributes.)

vector_size (bytes)

This attribute specifies the vector size for the variable, measured in bytes. For example, the declaration:

          int foo __attribute__ ((vector_size (16)));
          

causes the compiler to set the mode for foo, to be 16 bytes, divided into int sized units. Assuming a 32-bit int (a vector of 4 units of 4 bytes), the corresponding mode of foo will be V4SI.
This attribute is only applicable to integral and float scalars, although arrays, pointers, and function return values are allowed in conjunction with this construct.
Aggregates with this attribute are invalid, even if they are of the same size as a corresponding scalar. For example, the declaration:

          struct S { int a; };
          struct S  __attribute__ ((vector_size (16))) foo;
          

is invalid even if the size of the structure is the same as the size of the int.

weak

The weak attribute is described in See Function Attributes.

model (model-name)

Use this attribute on the M32R/D to set the addressability of an object. The identifier model-name is one of small, medium, or large, representing each of the code models. Small model objects live in the lower 16MB of memory (so that their addresses can be loaded with the ld24 instruction).
Medium and large model objects may live anywhere in the 32-bit address space (the compiler will generate seth/add3 instructions to load their addresses).

To specify multiple attributes, separate them by commas within the double parentheses: for example, __attribute__ ((aligned (16), packed)).

Reference:

https://gcc.gnu.org/onlinedocs/gcc-3.3/gcc/Variable-Attributes.html#Variable%20Attributes

wxPython: Send event manually (v2.8.x)

#!/usr/bin/env python
# vim: tabstop=8 shiftwidth=4 softtabstop=4
# python version: 2.7.5 final, serial: 0

import sys
import wxversion
wxversion.select('2.8')
import wx


class DemoApp(wx.App):
    def OnInit(self):
        self._frame = DemoMainFrame(None, title='Send Event Demo')
        self.SetTopWindow(self._frame)
        self._frame.Show()
        return True
    # end of OnInit
# end of DemoApp


class DemoMainFrame(wx.Frame):
    def __init__(self, parent, id_=wx.ID_ANY, title='Main', \
                      pos=wx.DefaultPosition, size=wx.DefaultSize, \
                      style=wx.DEFAULT_FRAME_STYLE, name='Main'):
        super(DemoMainFrame, self).__init__(\
            parent, id_, title, pos, size, style, name)
        self.Centre(wx.BOTH)
        self._mainMenu = wx.MenuBar()
        self._fileMenu = wx.Menu()
        self._checkItem = self._fileMenu.AppendCheckItem(\
            wx.ID_ANY, 'Check Item')
        self.Bind(wx.EVT_MENU, self._onCheckItemClick, self._checkItem)
        self._mainMenu.Append(self._fileMenu, 'File(&F)')
        self.SetMenuBar(self._mainMenu)
        self._panel = wx.Panel(self, wx.ID_ANY)
        self._button = wx.Button(self._panel, wx.ID_ANY, 'Send Event')
        self._button.SetPosition((10, 10))
        self._button.Bind(wx.EVT_BUTTON, self._onButtonClick)
    # end of __init__

    def _onCheckItemClick(self, event):
        style = wx.OK | wx.ICON_INFORMATION | wx.STAY_ON_TOP | wx.CENTRE
        dialog = wx.MessageDialog(self, 'Check Item Clicked!', 'Check Item', style)
        dialog.ShowModal()
        if dialog:
            dialog.Destroy()
    # end of _onCheckItemClick

    def _onButtonClick(self, event):
        sendEvent(wx.wxEVT_COMMAND_MENU_SELECTED, self._checkItem.Id, \
                          self._fileMenu, self.GetEventHandler())
        self._checkItem.Check(not self._checkItem.IsChecked())
    # end of _onButtonClick

def sendEvent(eventType, targetID, eventObj, eventHandler, isSetInt=True, \
              eventClass=wx.CommandEvent):
    """Send a event manually."""
    event = eventClass(eventType, targetID)
    if isSetInt:
        event.SetInt(1)
    event.SetEventObject(eventObj)
    #wx.PostEvent(eventHandler, event)
    assert eventHandler.ProcessEvent(event), 'Send event fail!'
# end of sendEvent

def _main():
    try:
        app = DemoApp(False)
        app.SetAppName('Send Event Demo')
        app.MainLoop()
    except KeyboardInterrupt:
        sys.exit(0)
# end of _main

if __name__ == '__main__':
    _main()
# end of __main__

C++: vector v.s. deque

std::vector

template < class T, class Alloc = allocator<T> > class vector; // generic template

Vector

Vectors are sequence containers representing arrays that can change in size.

Just like arrays, vectors use contiguous storage locations for their elements, which means that their elements can also be accessed using offsets on regular pointers to its elements, and just as efficiently as in arrays. But unlike arrays, their size can change dynamically, with their storage being handled automatically by the container.

Internally, vectors use a dynamically allocated array to store their elements. This array may need to be reallocated in order to grow in size when new elements are inserted, which implies allocating a new array and moving all elements to it. This is a relatively expensive task in terms of processing time, and thus, vectors do not reallocate each time an element is added to the container.

Instead, vector containers may allocate some extra storage to accommodate for possible growth, and thus the container may have an actual capacity greater than the storage strictly needed to contain its elements (i.e., its size). Libraries can implement different strategies for growth to balance between memory usage and reallocations, but in any case, reallocations should only happen at logarithmically growing intervals of size so that the insertion of individual elements at the end of the vector can be provided with amortized constant time complexity (see push_back).

Therefore, compared to arrays, vectors consume more memory in exchange for the ability to manage storage and grow dynamically in an efficient way.

Compared to the other dynamic sequence containers (deques, lists and forward_lists), vectors are very efficient accessing its elements (just like arrays) and relatively efficient adding or removing elements from its end. For operations that involve inserting or removing elements at positions other than the end, they perform worse than the others, and have less consistent iterators and references than lists and forward_lists.

std::deque

template < class T, class Alloc = allocator<T> > class deque;

Double ended queue

deque (usually pronounced like "deck") is an irregular acronym of double-ended queue. Double-ended queues are sequence containers with dynamic sizes that can be expanded or contracted on both ends (either its front or its back).

Specific libraries may implement deques in different ways, generally as some form of dynamic array. But in any case, they allow for the individual elements to be accessed directly through random access iterators, with storage handled automatically by expanding and contracting the container as needed.

Therefore, they provide a functionality similar to vectors, but with efficient insertion and deletion of elements also at the beginning of the sequence, and not only at its end. But, unlike vectors, deques are not guaranteed to store all its elements in contiguous storage locations: accessing elements in a deque by offsetting a pointer to another element causes undefined behavior.

Both vectors and deques provide a very similar interface and can be used for similar purposes, but internally both work in quite different ways: While vectors use a single array that needs to be occasionally reallocated for growth, the elements of a deque can be scattered in different chunks of storage, with the container keeping the necessary information internally to provide direct access to any of its elements in constant time and with a uniform sequential interface (through iterators). Therefore, deques are a little more complex internally than vectors, but this allows them to grow more efficiently under certain circumstances, especially with very long sequences, where reallocations become more expensive.

For operations that involve frequent insertion or removals of elements at positions other than the beginning or the end, deques perform worse and have less consistent iterators and references than lists and forward lists.

 

Reference:

http://www.cplusplus.com/reference/vector/vector/?kw=vector

http://www.cplusplus.com/reference/deque/deque/?kw=deque

GotW #54: Using Vector and Deque

Python OrderedDict

https://docs.python.org/2/library/collections.html#collections.OrderedDict
New in version 2.7.

See also: Equivalent OrderedDict recipe that runs on Python 2.4 or later.

cURL: VERSIONS -- the version numbering scheme in curl

Version Numbers and Releases
Curl is not only curl. Curl is also libcurl. They're actually individually versioned, but they mostly follow each other rather closely.
The version numbering is always built up using the same system:
X.Y[.Z]
Where
X is main version number
Y is release number
Z is patch number
One of these numbers will get bumped in each new release. The numbers to the right of a bumped number will be reset to zero. If Z is zero, it may not be included in the version number.
The main version number will get bumped when *really* big, world colliding changes are made. The release number is bumped when changes are performed or things/features are added. The patch number is bumped when the changes are mere bugfixes.
It means that after release 1.2.3, we can release 2.0 if something really big has been made, 1.3 if not that big changes were made or 1.2.4 if mostly bugs were fixed.
Bumping, as in increasing the number with 1, is unconditionally only affecting one of the numbers (except the ones to the right of it, that may be set to zero). 1 becomes 2, 3 becomes 4, 9 becomes 10, 88 becomes 89 and 99 becomes 100. So, after 1.2.9 comes 1.2.10. After 3.99.3, 3.100 might come.
All original curl source release archives are named according to the libcurl version (not according to the curl client version that, as said before, might differ).
As a service to any application that might want to support new libcurl features while still being able to build with older versions, all releases have the libcurl version stored in the curl/curlver.h file using a static numbering scheme that can be used for comparison. The version number is defined as:
Where XX, YY and ZZ are the main version, release and patch numbers in hexadecimal. All three number fields are always represented using two digits (eight bits each). 1.2 would appear as "0x010200" while version 9.11.7 appears as "0x090b07".
This 6-digit hexadecimal number is always a greater number in a more recent release. It makes comparisons with greater than and less than work.
This number is also available as three separate defines: LIBCURL_VERSION_MAJOR, LIBCURL_VERSION_MINOR and LIBCURL_VERSION_PATCH.

The library name may always be "libcurl.so.4.1.1". So check the actually version number in "curl/curlver.h" or use the curl-config tool:
$ sh curl-config --version

Reference:
http://curl.haxx.se/docs/versions.html
http://curl.haxx.se/libcurl/using/

Windows PowerShell "Pause"

Write-Host "Press any key to continue ..."
$x = $host.UI.RawUI.ReadKey("NoEcho, IncludeKeyDown")

In this line we’re using PowerShell’s automatic variable $host (which is actually an instance of the .NET Framework class System.Management.Automation.Host) and the ReadKey method. (Which is actually a method of the RawUI property, which is a property of the UI property, which is a property of $host. And the leg bone’s connected to the knee bone, the knee bone’s connected to the ankle bone, the ….) The ReadKey method enables us to get information about the key that has just been pressed. Of course, in this case the only information we care about is the fact that a key has been pressed. Therefore, we pass ReadKey two parameters:

NoEcho. This prevents any information from appearing on screen when the user presses a key. If you leave out this parameter the pressed key will be echoed back to the screen.

IncludeKeyDown. This tells the script to continue as soon as a key has been pressed; that means the script will continue even if the user presses and holds a key down. If you’d prefer to wait until the user has released the key, then use this parameter instead: IncludeKeyUp.

There’s one more parameter that we can add to the ReadKey method: AllowCtrlC. In Windows PowerShell, pressing Ctrl+C typically causes the script to terminate. If you add the AllowCtrlC parameter to the ReadKey method, however, the user can choose to press Ctrl+C instead of pressing any other key. If they do that, the script will not terminate, but instead continue on as if the user had pressed any other key on the keyboard. (But only in conjunction with the ReadKey method. If the user presses Ctrl+C somewhere else the script will terminate.)

Reference:
Pausing a Script Until the User Presses a Key
How do you do a ‘Pause’ with PowerShell 2.0?
How to Properly Pause a PowerShell Script

Style Guide for Python Code

PEP 8 - Style Guide for Python Code

PEP:	8
Title:	Style Guide for Python Code
Author:	Guido van Rossum <guido at python.org>, Barry Warsaw <barry at python.org>, Nick Coghlan <ncoghlan at gmail.com>
Status:	Active
Type:	Process
Created:	05-Jul-2001
Post-History:	05-Jul-2001, 01-Aug-2013

---

Contents

• Introduction
• A Foolish Consistency is the Hobgoblin of Little Minds
• Code lay-out
  • Indentation
  • Tabs or Spaces?
  • Maximum Line Length
  • Blank Lines
  • Source File Encoding
  • Imports
• String Quotes
• Whitespace in Expressions and Statements
  • Pet Peeves
  • Other Recommendations
• Comments
  • Block Comments
  • Inline Comments
  • Documentation Strings
• Version Bookkeeping
• Naming Conventions
  • Overriding Principle
  • Descriptive: Naming Styles
  • Prescriptive: Naming Conventions
    • Names to Avoid
    • Package and Module Names
    • Class Names
    • Exception Names
    • Global Variable Names
    • Function Names
    • Function and method arguments
    • Method Names and Instance Variables
    • Constants
    • Designing for inheritance
  • Public and internal interfaces
• Programming Recommendations
• References
• Copyright

Introduction

This document gives coding conventions for the Python code comprising the standard library in the main Python distribution. Please see the companion informational PEP describing style guidelines for the C code in the C implementation of Python [1] .
This document and PEP 257 (Docstring Conventions) were adapted from Guido's original Python Style Guide essay, with some additions from Barry's style guide [2] .
This style guide evolves over time as additional conventions are identified and past conventions are rendered obsolete by changes in the language itself.
Many projects have their own coding style guidelines. In the event of any conflicts, such project-specific guides take precedence for that project.

A Foolish Consistency is the Hobgoblin of Little Minds

One of Guido's key insights is that code is read much more often than it is written. The guidelines provided here are intended to improve the readability of code and make it consistent across the wide spectrum of Python code. As PEP 20 says, "Readability counts".
A style guide is about consistency. Consistency with this style guide is important. Consistency within a project is more important. Consistency within one module or function is most important.
But most importantly: know when to be inconsistent -- sometimes the style guide just doesn't apply. When in doubt, use your best judgment. Look at other examples and decide what looks best. And don't hesitate to ask!
In particular: do not break backwards compatibility just to comply with this PEP!
Some other good reasons to ignore a particular guideline:

1. When applying the guideline would make the code less readable, even for someone who is used to reading code that follows this PEP.
2. To be consistent with surrounding code that also breaks it (maybe for historic reasons) -- although this is also an opportunity to clean up someone else's mess (in true XP style).
3. Because the code in question predates the introduction of the guideline and there is no other reason to be modifying that code.
4. When the code needs to remain compatible with older versions of Python that don't support the feature recommended by the style guide.

Code lay-out

Indentation

Use 4 spaces per indentation level.
Continuation lines should align wrapped elements either vertically using Python's implicit line joining inside parentheses, brackets and braces, or using a hanging indent [5] . When using a hanging indent the following considerations should be applied; there should be no arguments on the first line and further indentation should be used to clearly distinguish itself as a continuation line.
Yes:

# Aligned with opening delimiter.
foo = long_function_name(var_one, var_two,
                         var_three, var_four)

# More indentation included to distinguish this from the rest.
def long_function_name(
        var_one, var_two, var_three,
        var_four):
    print(var_one)

# Hanging indents should add a level.
foo = long_function_name(
    var_one, var_two,
    var_three, var_four)

No:

# Arguments on first line forbidden when not using vertical alignment.
foo = long_function_name(var_one, var_two,
    var_three, var_four)

# Further indentation required as indentation is not distinguishable.
def long_function_name(
    var_one, var_two, var_three,
    var_four):
    print(var_one)

The 4-space rule is optional for continuation lines.
Optional:

# Hanging indents *may* be indented to other than 4 spaces.
foo = long_function_name(
  var_one, var_two,
  var_three, var_four)

When the conditional part of an if -statement is long enough to require that it be written across multiple lines, it's worth noting that the combination of a two character keyword (i.e. if ), plus a single space, plus an opening parenthesis creates a natural 4-space indent for the subsequent lines of the multiline conditional. This can produce a visual conflict with the indented suite of code nested inside the if -statement, which would also naturally be indented to 4 spaces. This PEP takes no explicit position on how (or whether) to further visually distinguish such conditional lines from the nested suite inside the if -statement. Acceptable options in this situation include, but are not limited to:

# No extra indentation.
if (this_is_one_thing and
    that_is_another_thing):
    do_something()

# Add a comment, which will provide some distinction in editors
# supporting syntax highlighting.
if (this_is_one_thing and
    that_is_another_thing):
    # Since both conditions are true, we can frobnicate.
    do_something()

# Add some extra indentation on the conditional continuation line.
if (this_is_one_thing
        and that_is_another_thing):
    do_something()

The closing brace/bracket/parenthesis on multi-line constructs may either line up under the first non-whitespace character of the last line of list, as in:

my_list = [
    1, 2, 3,
    4, 5, 6,
    ]
result = some_function_that_takes_arguments(
    'a', 'b', 'c',
    'd', 'e', 'f',
    )

or it may be lined up under the first character of the line that starts the multi-line construct, as in:

my_list = [
    1, 2, 3,
    4, 5, 6,
]
result = some_function_that_takes_arguments(
    'a', 'b', 'c',
    'd', 'e', 'f',
)

Tabs or Spaces?

Spaces are the preferred indentation method.
Tabs should be used solely to remain consistent with code that is already indented with tabs.
Python 3 disallows mixing the use of tabs and spaces for indentation.
Python 2 code indented with a mixture of tabs and spaces should be converted to using spaces exclusively.
When invoking the Python 2 command line interpreter with the -t option, it issues warnings about code that illegally mixes tabs and spaces. When using -tt these warnings become errors. These options are highly recommended!

Maximum Line Length

Limit all lines to a maximum of 79 characters.
For flowing long blocks of text with fewer structural restrictions (docstrings or comments), the line length should be limited to 72 characters.
Limiting the required editor window width makes it possible to have several files open side-by-side, and works well when using code review tools that present the two versions in adjacent columns.
The default wrapping in most tools disrupts the visual structure of the code, making it more difficult to understand. The limits are chosen to avoid wrapping in editors with the window width set to 80, even if the tool places a marker glyph in the final column when wrapping lines. Some web based tools may not offer dynamic line wrapping at all.
Some teams strongly prefer a longer line length. For code maintained exclusively or primarily by a team that can reach agreement on this issue, it is okay to increase the nominal line length from 80 to 100 characters (effectively increasing the maximum length to 99 characters), provided that comments and docstrings are still wrapped at 72 characters.
The Python standard library is conservative and requires limiting lines to 79 characters (and docstrings/comments to 72).
The preferred way of wrapping long lines is by using Python's implied line continuation inside parentheses, brackets and braces. Long lines can be broken over multiple lines by wrapping expressions in parentheses. These should be used in preference to using a backslash for line continuation.
Backslashes may still be appropriate at times. For example, long, multiple with -statements cannot use implicit continuation, so backslashes are acceptable:

with open('/path/to/some/file/you/want/to/read') as file_1, \
     open('/path/to/some/file/being/written', 'w') as file_2:
    file_2.write(file_1.read())

(See the previous discussion on multiline if-statements for further thoughts on the indentation of such multiline with -statements.)
Another such case is with assert statements.
Make sure to indent the continued line appropriately. The preferred place to break around a binary operator is after the operator, not before it. Some examples:

class Rectangle(Blob):

    def __init__(self, width, height,
                 color='black', emphasis=None, highlight=0):
        if (width == 0 and height == 0 and
                color == 'red' and emphasis == 'strong' or
                highlight > 100):
            raise ValueError("sorry, you lose")
        if width == 0 and height == 0 and (color == 'red' or
                                           emphasis is None):
            raise ValueError("I don't think so -- values are %s, %s" %
                             (width, height))
        Blob.__init__(self, width, height,
                      color, emphasis, highlight)

Blank Lines

Separate top-level function and class definitions with two blank lines.
Method definitions inside a class are separated by a single blank line.
Extra blank lines may be used (sparingly) to separate groups of related functions. Blank lines may be omitted between a bunch of related one-liners (e.g. a set of dummy implementations).
Use blank lines in functions, sparingly, to indicate logical sections.
Python accepts the control-L (i.e. ^L) form feed character as whitespace; Many tools treat these characters as page separators, so you may use them to separate pages of related sections of your file. Note, some editors and web-based code viewers may not recognize control-L as a form feed and will show another glyph in its place.

Source File Encoding

Code in the core Python distribution should always use UTF-8 (or ASCII in Python 2).
Files using ASCII (in Python 2) or UTF-8 (in Python 3) should not have an encoding declaration.
In the standard library, non-default encodings should be used only for test purposes or when a comment or docstring needs to mention an author name that contains non-ASCII characters; otherwise, using \x , \u , \U , or \N escapes is the preferred way to include non-ASCII data in string literals.
For Python 3.0 and beyond, the following policy is prescribed for the standard library (see PEP 3131 ): All identifiers in the Python standard library MUST use ASCII-only identifiers, and SHOULD use English words wherever feasible (in many cases, abbreviations and technical terms are used which aren't English). In addition, string literals and comments must also be in ASCII. The only exceptions are (a) test cases testing the non-ASCII features, and (b) names of authors. Authors whose names are not based on the latin alphabet MUST provide a latin transliteration of their names.
Open source projects with a global audience are encouraged to adopt a similar policy.

Imports

• Imports should usually be on separate lines, e.g.:

  Yes: import os
       import sys
  
  No:  import sys, os
  

  It's okay to say this though:
  

  from subprocess import Popen, PIPE
  

• Imports are always put at the top of the file, just after any module comments and docstrings, and before module globals and constants.
  Imports should be grouped in the following order:
  
  1. standard library imports
  2. related third party imports
  3. local application/library specific imports
  You should put a blank line between each group of imports.
  Put any relevant __all__ specification after the imports.
  
• Absolute imports are recommended, as they are usually more readable and tend to be better behaved (or at least give better error messages) if the import system is incorrectly configured (such as when a directory inside a package ends up on sys.path ):

  import mypkg.sibling
  from mypkg import sibling
  from mypkg.sibling import example
  

  However, explicit relative imports are an acceptable alternative to absolute imports, especially when dealing with complex package layouts where using absolute imports would be unnecessarily verbose:
  

  from . import sibling
  from .sibling import example
  

  Standard library code should avoid complex package layouts and always use absolute imports.
  Implicit relative imports should never be used and have been removed in Python 3.
  
• When importing a class from a class-containing module, it's usually okay to spell this:

  from myclass import MyClass
  from foo.bar.yourclass import YourClass
  

  If this spelling causes local name clashes, then spell them
  

  import myclass
  import foo.bar.yourclass
  

  and use "myclass.MyClass" and "foo.bar.yourclass.YourClass".
  
• Wildcard imports ( from <module> import * ) should be avoided, as they make it unclear which names are present in the namespace, confusing both readers and many automated tools. There is one defensible use case for a wildcard import, which is to republish an internal interface as part of a public API (for example, overwriting a pure Python implementation of an interface with the definitions from an optional accelerator module and exactly which definitions will be overwritten isn't known in advance).
  When republishing names this way, the guidelines below regarding public and internal interfaces still apply.
  

String Quotes

In Python, single-quoted strings and double-quoted strings are the same. This PEP does not make a recommendation for this. Pick a rule and stick to it. When a string contains single or double quote characters, however, use the other one to avoid backslashes in the string. It improves readability.
For triple-quoted strings, always use double quote characters to be consistent with the docstring convention in PEP 257 .

Whitespace in Expressions and Statements

Pet Peeves

Avoid extraneous whitespace in the following situations:

• Immediately inside parentheses, brackets or braces.

  Yes: spam(ham[1], {eggs: 2})
  No:  spam( ham[ 1 ], { eggs: 2 } )
  

• Immediately before a comma, semicolon, or colon:

  Yes: if x == 4: print x, y; x, y = y, x
  No:  if x == 4 : print x , y ; x , y = y , x
  

• However, in a slice the colon acts like a binary operator, and should have equal amounts on either side (treating it as the operator with the lowest priority). In an extended slice, both colons must have the same amount of spacing applied. Exception: when a slice parameter is omitted, the space is omitted.
  Yes:
  

  ham[1:9], ham[1:9:3], ham[:9:3], ham[1::3], ham[1:9:]
  ham[lower:upper], ham[lower:upper:], ham[lower::step]
  ham[lower+offset : upper+offset]
  ham[: upper_fn(x) : step_fn(x)], ham[:: step_fn(x)]
  ham[lower + offset : upper + offset]
  

  No:
  

  ham[lower + offset:upper + offset]
  ham[1: 9], ham[1 :9], ham[1:9 :3]
  ham[lower : : upper]
  ham[ : upper]
  

• Immediately before the open parenthesis that starts the argument list of a function call:

  Yes: spam(1)
  No:  spam (1)
  

• Immediately before the open parenthesis that starts an indexing or slicing:

  Yes: dct['key'] = lst[index]
  No:  dct ['key'] = lst [index]
  

• More than one space around an assignment (or other) operator to align it with another.
  Yes:
  

  x = 1
  y = 2
  long_variable = 3
  

  No:
  

  x             = 1
  y             = 2
  long_variable = 3
  

Other Recommendations

• Always surround these binary operators with a single space on either side: assignment ( = ), augmented assignment ( += , -= etc.), comparisons ( == , < , > , != , <> , <= , >= , in , not in , is , is not ), Booleans ( and , or , not ).
• If operators with different priorities are used, consider adding whitespace around the operators with the lowest priority(ies). Use your own judgment; however, never use more than one space, and always have the same amount of whitespace on both sides of a binary operator.
  Yes:
  

  i = i + 1
  submitted += 1
  x = x*2 - 1
  hypot2 = x*x + y*y
  c = (a+b) * (a-b)
  

  No:
  

  i=i+1
  submitted +=1
  x = x * 2 - 1
  hypot2 = x * x + y * y
  c = (a + b) * (a - b)
  

• Don't use spaces around the = sign when used to indicate a keyword argument or a default parameter value.
  Yes:
  

  def complex(real, imag=0.0):
      return magic(r=real, i=imag)
  

  No:
  

  def complex(real, imag = 0.0):
      return magic(r = real, i = imag)
  

• Do use spaces around the = sign of an annotated function definition. Additionally, use a single space after the : , as well as a single space on either side of the -> sign representing an annotated return value.
  Yes:
  

  def munge(input: AnyStr):
  def munge(sep: AnyStr = None):
  def munge() -> AnyStr:
  def munge(input: AnyStr, sep: AnyStr = None, limit=1000):
  

  No:
  

  def munge(input: AnyStr=None):
  def munge(input:AnyStr):
  def munge(input: AnyStr)->PosInt:
  

• Compound statements (multiple statements on the same line) are generally discouraged.
  Yes:
  

  if foo == 'blah':
      do_blah_thing()
  do_one()
  do_two()
  do_three()
  

  Rather not:
  

  if foo == 'blah': do_blah_thing()
  do_one(); do_two(); do_three()
  

• While sometimes it's okay to put an if/for/while with a small body on the same line, never do this for multi-clause statements. Also avoid folding such long lines!
  Rather not:
  

  if foo == 'blah': do_blah_thing()
  for x in lst: total += x
  while t < 10: t = delay()
  

  Definitely not:
  

  if foo == 'blah': do_blah_thing()
  else: do_non_blah_thing()
  
  try: something()
  finally: cleanup()
  
  do_one(); do_two(); do_three(long, argument,
                               list, like, this)
  
  if foo == 'blah': one(); two(); three()
  

Version Bookkeeping

If you have to have Subversion, CVS, or RCS crud in your source file, do it as follows.

__version__ = "$Revision$"
# $Source$

These lines should be included after the module's docstring, before any other code, separated by a blank line above and below.

Naming Conventions

The naming conventions of Python's library are a bit of a mess, so we'll never get this completely consistent -- nevertheless, here are the currently recommended naming standards. New modules and packages (including third party frameworks) should be written to these standards, but where an existing library has a different style, internal consistency is preferred.

Overriding Principle

Names that are visible to the user as public parts of the API should follow conventions that reflect usage rather than implementation.

Descriptive: Naming Styles

There are a lot of different naming styles. It helps to be able to recognize what naming style is being used, independently from what they are used for.
The following naming styles are commonly distinguished:

• b (single lowercase letter)
• B (single uppercase letter)
• lowercase
• lower_case_with_underscores
• UPPERCASE
• UPPER_CASE_WITH_UNDERSCORES
• CapitalizedWords (or CapWords, or CamelCase -- so named because of the bumpy look of its letters [3] ). This is also sometimes known as StudlyCaps.
  Note: When using abbreviations in CapWords, capitalize all the letters of the abbreviation. Thus HTTPServerError is better than HttpServerError.
  
• mixedCase (differs from CapitalizedWords by initial lowercase character!)
• Capitalized_Words_With_Underscores (ugly!)

There's also the style of using a short unique prefix to group related names together. This is not used much in Python, but it is mentioned for completeness. For example, the os.stat() function returns a tuple whose items traditionally have names like st_mode , st_size , st_mtime and so on. (This is done to emphasize the correspondence with the fields of the POSIX system call struct, which helps programmers familiar with that.)
The X11 library uses a leading X for all its public functions. In Python, this style is generally deemed unnecessary because attribute and method names are prefixed with an object, and function names are prefixed with a module name.
In addition, the following special forms using leading or trailing underscores are recognized (these can generally be combined with any case convention):

• _single_leading_underscore : weak "internal use" indicator. E.g. from M import * does not import objects whose name starts with an underscore.
• single_trailing_underscore_ : used by convention to avoid conflicts with Python keyword, e.g.

  Tkinter.Toplevel(master, class_='ClassName')
  

• __double_leading_underscore : when naming a class attribute, invokes name mangling (inside class FooBar, __boo becomes _FooBar__boo ; see below).
• __double_leading_and_trailing_underscore__ : "magic" objects or attributes that live in user-controlled namespaces. E.g. __init__ , __import__ or __file__ . Never invent such names; only use them as documented.

Prescriptive: Naming Conventions

Names to Avoid

Never use the characters 'l' (lowercase letter el), 'O' (uppercase letter oh), or 'I' (uppercase letter eye) as single character variable names.
In some fonts, these characters are indistinguishable from the numerals one and zero. When tempted to use 'l', use 'L' instead.

Package and Module Names

Modules should have short, all-lowercase names. Underscores can be used in the module name if it improves readability. Python packages should also have short, all-lowercase names, although the use of underscores is discouraged.
Since module names are mapped to file names, and some file systems are case insensitive and truncate long names, it is important that module names be chosen to be fairly short -- this won't be a problem on Unix, but it may be a problem when the code is transported to older Mac or Windows versions, or DOS.
When an extension module written in C or C++ has an accompanying Python module that provides a higher level (e.g. more object oriented) interface, the C/C++ module has a leading underscore (e.g. _socket ).

Class Names

Class names should normally use the CapWords convention.
The naming convention for functions may be used instead in cases where the interface is documented and used primarily as a callable.
Note that there is a separate convention for builtin names: most builtin names are single words (or two words run together), with the CapWords convention used only for exception names and builtin constants.

Exception Names

Because exceptions should be classes, the class naming convention applies here. However, you should use the suffix "Error" on your exception names (if the exception actually is an error).

Global Variable Names

(Let's hope that these variables are meant for use inside one module only.) The conventions are about the same as those for functions.
Modules that are designed for use via from M import * should use the __all__ mechanism to prevent exporting globals, or use the older convention of prefixing such globals with an underscore (which you might want to do to indicate these globals are "module non-public").

Function Names

Function names should be lowercase, with words separated by underscores as necessary to improve readability.
mixedCase is allowed only in contexts where that's already the prevailing style (e.g. threading.py), to retain backwards compatibility.

Function and method arguments

Always use self for the first argument to instance methods.
Always use cls for the first argument to class methods.
If a function argument's name clashes with a reserved keyword, it is generally better to append a single trailing underscore rather than use an abbreviation or spelling corruption. Thus class_ is better than clss . (Perhaps better is to avoid such clashes by using a synonym.)

Method Names and Instance Variables

Use the function naming rules: lowercase with words separated by underscores as necessary to improve readability.
Use one leading underscore only for non-public methods and instance variables.
To avoid name clashes with subclasses, use two leading underscores to invoke Python's name mangling rules.
Python mangles these names with the class name: if class Foo has an attribute named __a , it cannot be accessed by Foo.__a . (An insistent user could still gain access by calling Foo._Foo__a .) Generally, double leading underscores should be used only to avoid name conflicts with attributes in classes designed to be subclassed.
Note: there is some controversy about the use of __names (see below).

Constants

Constants are usually defined on a module level and written in all capital letters with underscores separating words. Examples include MAX_OVERFLOW and TOTAL .

Designing for inheritance

Always decide whether a class's methods and instance variables (collectively: "attributes") should be public or non-public. If in doubt, choose non-public; it's easier to make it public later than to make a public attribute non-public.
Public attributes are those that you expect unrelated clients of your class to use, with your commitment to avoid backward incompatible changes. Non-public attributes are those that are not intended to be used by third parties; you make no guarantees that non-public attributes won't change or even be removed.
We don't use the term "private" here, since no attribute is really private in Python (without a generally unnecessary amount of work).
Another category of attributes are those that are part of the "subclass API" (often called "protected" in other languages). Some classes are designed to be inherited from, either to extend or modify aspects of the class's behavior. When designing such a class, take care to make explicit decisions about which attributes are public, which are part of the subclass API, and which are truly only to be used by your base class.
With this in mind, here are the Pythonic guidelines:

• Public attributes should have no leading underscores.
• If your public attribute name collides with a reserved keyword, append a single trailing underscore to your attribute name. This is preferable to an abbreviation or corrupted spelling. (However, notwithstanding this rule, 'cls' is the preferred spelling for any variable or argument which is known to be a class, especially the first argument to a class method.)
  Note 1: See the argument name recommendation above for class methods.
  
• For simple public data attributes, it is best to expose just the attribute name, without complicated accessor/mutator methods. Keep in mind that Python provides an easy path to future enhancement, should you find that a simple data attribute needs to grow functional behavior. In that case, use properties to hide functional implementation behind simple data attribute access syntax.
  Note 1: Properties only work on new-style classes.
  Note 2: Try to keep the functional behavior side-effect free, although side-effects such as caching are generally fine.
  Note 3: Avoid using properties for computationally expensive operations; the attribute notation makes the caller believe that access is (relatively) cheap.
  
• If your class is intended to be subclassed, and you have attributes that you do not want subclasses to use, consider naming them with double leading underscores and no trailing underscores. This invokes Python's name mangling algorithm, where the name of the class is mangled into the attribute name. This helps avoid attribute name collisions should subclasses inadvertently contain attributes with the same name.
  Note 1: Note that only the simple class name is used in the mangled name, so if a subclass chooses both the same class name and attribute name, you can still get name collisions.
  Note 2: Name mangling can make certain uses, such as debugging and __getattr__() , less convenient. However the name mangling algorithm is well documented and easy to perform manually.
  Note 3: Not everyone likes name mangling. Try to balance the need to avoid accidental name clashes with potential use by advanced callers.
  

Public and internal interfaces

Any backwards compatibility guarantees apply only to public interfaces. Accordingly, it is important that users be able to clearly distinguish between public and internal interfaces.
Documented interfaces are considered public, unless the documentation explicitly declares them to be provisional or internal interfaces exempt from the usual backwards compatibility guarantees. All undocumented interfaces should be assumed to be internal.
To better support introspection, modules should explicitly declare the names in their public API using the __all__ attribute. Setting __all__ to an empty list indicates that the module has no public API.
Even with __all__ set appropriately, internal interfaces (packages, modules, classes, functions, attributes or other names) should still be prefixed with a single leading underscore.
An interface is also considered internal if any containing namespace (package, module or class) is considered internal.
Imported names should always be considered an implementation detail. Other modules must not rely on indirect access to such imported names unless they are an explicitly documented part of the containing module's API, such as os.path or a package's __init__ module that exposes functionality from submodules.

Programming Recommendations

• Code should be written in a way that does not disadvantage other implementations of Python (PyPy, Jython, IronPython, Cython, Psyco, and such).
  For example, do not rely on CPython's efficient implementation of in-place string concatenation for statements in the form a += b or a = a + b . This optimization is fragile even in CPython (it only works for some types) and isn't present at all in implementations that don't use refcounting. In performance sensitive parts of the library, the ''.join() form should be used instead. This will ensure that concatenation occurs in linear time across various implementations.
  
• Comparisons to singletons like None should always be done with is or is not , never the equality operators.
  Also, beware of writing if x when you really mean if x is not None -- e.g. when testing whether a variable or argument that defaults to None was set to some other value. The other value might have a type (such as a container) that could be false in a boolean context!
  
• Use is not operator rather than not ... is . While both expressions are functionally identical, the former is more readable and preferred.
  Yes:
  

  if foo is not None:
  

  No:
  

  if not foo is None:
  

• When implementing ordering operations with rich comparisons, it is best to implement all six operations ( __eq__ , __ne__ , __lt__ , __le__ , __gt__ , __ge__ ) rather than relying on other code to only exercise a particular comparison.
  To minimize the effort involved, the functools.total_ordering() decorator provides a tool to generate missing comparison methods.
  PEP 207 indicates that reflexivity rules are assumed by Python. Thus, the interpreter may swap y > x with x < y , y >= x with x <= y , and may swap the arguments of x == y and x != y . The sort() and min() operations are guaranteed to use the < operator and the max() function uses the > operator. However, it is best to implement all six operations so that confusion doesn't arise in other contexts.
  
• Always use a def statement instead of an assignment statement that binds a lambda expression directly to an identifier.
  Yes:
  

  def f(x): return 2*x
  

  No:
  

  f = lambda x: 2*x
  

  The first form means that the name of the resulting function object is specifically 'f' instead of the generic '<lambda>'. This is more useful for tracebacks and string representations in general. The use of the assignment statement eliminates the sole benefit a lambda expression can offer over an explicit def statement (i.e. that it can be embedded inside a larger expression)
  
• Derive exceptions from Exception rather than BaseException . Direct inheritance from BaseException is reserved for exceptions where catching them is almost always the wrong thing to do.
  Design exception hierarchies based on the distinctions that code catching the exceptions is likely to need, rather than the locations where the exceptions are raised. Aim to answer the question "What went wrong?" programmatically, rather than only stating that "A problem occurred" (see PEP 3151 for an example of this lesson being learned for the builtin exception hierarchy)
  Class naming conventions apply here, although you should add the suffix "Error" to your exception classes if the exception is an error. Non-error exceptions that are used for non-local flow control or other forms of signaling need no special suffix.
  
• Use exception chaining appropriately. In Python 3, "raise X from Y" should be used to indicate explicit replacement without losing the original traceback.
  When deliberately replacing an inner exception (using "raise X" in Python 2 or "raise X from None" in Python 3.3+), ensure that relevant details are transferred to the new exception (such as preserving the attribute name when converting KeyError to AttributeError, or embedding the text of the original exception in the new exception message).
  
• When raising an exception in Python 2, use raise ValueError('message') instead of the older form raise ValueError, 'message' .
  The latter form is not legal Python 3 syntax.
  The paren-using form also means that when the exception arguments are long or include string formatting, you don't need to use line continuation characters thanks to the containing parentheses.
  
• When catching exceptions, mention specific exceptions whenever possible instead of using a bare except: clause.
  For example, use:
  

  try:
      import platform_specific_module
  except ImportError:
      platform_specific_module = None
  

  A bare except: clause will catch SystemExit and KeyboardInterrupt exceptions, making it harder to interrupt a program with Control-C, and can disguise other problems. If you want to catch all exceptions that signal program errors, use except Exception: (bare except is equivalent to except BaseException: ).
  A good rule of thumb is to limit use of bare 'except' clauses to two cases:
  
  1. If the exception handler will be printing out or logging the traceback; at least the user will be aware that an error has occurred.
  2. If the code needs to do some cleanup work, but then lets the exception propagate upwards with raise . try...finally can be a better way to handle this case.
• When binding caught exceptions to a name, prefer the explicit name binding syntax added in Python 2.6:

  try:
      process_data()
  except Exception as exc:
      raise DataProcessingFailedError(str(exc))
  

  This is the only syntax supported in Python 3, and avoids the ambiguity problems associated with the older comma-based syntax.
  
• When catching operating system errors, prefer the explicit exception hierarchy introduced in Python 3.3 over introspection of errno values.
• Additionally, for all try/except clauses, limit the try clause to the absolute minimum amount of code necessary. Again, this avoids masking bugs.
  Yes:
  

  try:
      value = collection[key]
  except KeyError:
      return key_not_found(key)
  else:
      return handle_value(value)
  

  No:
  

  try:
      # Too broad!
      return handle_value(collection[key])
  except KeyError:
      # Will also catch KeyError raised by handle_value()
      return key_not_found(key)
  

• When a resource is local to a particular section of code, use a with statement to ensure it is cleaned up promptly and reliably after use. A try/finally statement is also acceptable.
• Context managers should be invoked through separate functions or methods whenever they do something other than acquire and release resources. For example:
  Yes:
  

  with conn.begin_transaction():
      do_stuff_in_transaction(conn)
  

  No:
  

  with conn:
      do_stuff_in_transaction(conn)
  

  The latter example doesn't provide any information to indicate that the __enter__ and __exit__ methods are doing something other than closing the connection after a transaction. Being explicit is important in this case.
  
• Use string methods instead of the string module.
  String methods are always much faster and share the same API with unicode strings. Override this rule if backward compatibility with Pythons older than 2.0 is required.
  
• Use ''.startswith() and ''.endswith() instead of string slicing to check for prefixes or suffixes.
  startswith() and endswith() are cleaner and less error prone. For example:
  

  Yes: if foo.startswith('bar'):
  No:  if foo[:3] == 'bar':
  

• Object type comparisons should always use isinstance() instead of comparing types directly.

  Yes: if isinstance(obj, int):
  
  No:  if type(obj) is type(1):
  

  When checking if an object is a string, keep in mind that it might be a unicode string too! In Python 2, str and unicode have a common base class, basestring, so you can do:
  

  if isinstance(obj, basestring):
  

  Note that in Python 3, unicode and basestring no longer exist (there is only str ) and a bytes object is no longer a kind of string (it is a sequence of integers instead)
  
• For sequences, (strings, lists, tuples), use the fact that empty sequences are false.

  Yes: if not seq:
       if seq:
  
  No: if len(seq)
      if not len(seq)
  

• Don't write string literals that rely on significant trailing whitespace. Such trailing whitespace is visually indistinguishable and some editors (or more recently, reindent.py) will trim them.
• Don't compare boolean values to True or False using == .

  Yes:   if greeting:
  No:    if greeting == True:
  Worse: if greeting is True:
  

• The Python standard library will not use function annotations as that would result in a premature commitment to a particular annotation style. Instead, the annotations are left for users to discover and experiment with useful annotation styles.
  It is recommended that third party experiments with annotations use an associated decorator to indicate how the annotation should be interpreted.
  Early core developer attempts to use function annotations revealed inconsistent, ad-hoc annotation styles. For example:
  
  • [str] was ambiguous as to whether it represented a list of strings or a value that could be either str or None .
  • The notation open(file:(str,bytes)) was used for a value that could be either bytes or str rather than a 2-tuple containing a str value followed by a bytes value.
  • The annotation seek(whence:int) exhibited a mix of over-specification and under-specification: int is too restrictive (anything with __index__ would be allowed) and it is not restrictive enough (only the values 0, 1, and 2 are allowed). Likewise, the annotation write(b: bytes) was also too restrictive (anything supporting the buffer protocol would be allowed).
  • Annotations such as read1(n: int=None) were self-contradictory since None is not an int . Annotations such as source_path(self, fullname:str) -> object were confusing about what the return type should be.
  • In addition to the above, annotations were inconsistent in the use of concrete types versus abstract types: int versus Integral and set/frozenset versus MutableSet/Set.
  • Some annotations in the abstract base classes were incorrect specifications. For example, set-to-set operations require other to be another instance of Set rather than just an Iterable .
  • A further issue was that annotations become part of the specification but weren't being tested.
  • In most cases, the docstrings already included the type specifications and did so with greater clarity than the function annotations. In the remaining cases, the docstrings were improved once the annotations were removed.
  • The observed function annotations were too ad-hoc and inconsistent to work with a coherent system of automatic type checking or argument validation. Leaving these annotations in the code would have made it more difficult to make changes later so that automated utilities could be supported.

Footnotes

[5]

Hanging indentation is a type-setting style where all the lines in a paragraph are indented except the first line. In the context of Python, the term is used to describe a style where the opening parenthesis of a parenthesized statement is the last non-whitespace character of the line, with subsequent lines being indented until the closing parenthesis.

References

[1]	PEP 7 , Style Guide for C Code, van Rossum

[2]	Barry's GNU Mailman style guide http://barry.warsaw.us/software/STYLEGUIDE.txt

[3]	http://www.wikipedia.com/wiki/CamelCase

[4]	PEP 8 modernisation, July 2013 http://bugs.python.org/issue18472

Copyright

This document has been placed in the public domain.

Source: https://hg.python.org/peps/file/tip/pep-0008.txt