Mercurial > cpython-lru_cache-weakref
annotate Doc/tutorial/classes.rst @ 87690:66c1c9f32567 default tip
Add use_weakref option to functools.lru_cache
The use_weakref option makes lru_cache create weak references to the function
arguments when creating the cache key, which prevents them from staying in the
memory forever even after all other references to them are gone.
This is a proof of concept for http://bugs.python.org/issue19859
| author | Radomir Dopieralski <devel@sheep.art.pl> |
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| date | Tue, 03 Dec 2013 16:02:48 +0100 |
| parents | 012380d57e44 |
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1 .. _tut-classes: |
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2 |
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3 ******* |
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4 Classes |
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5 ******* |
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6 |
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7 Compared with other programming languages, Python's class mechanism adds classes |
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8 with a minimum of new syntax and semantics. It is a mixture of the class |
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9 mechanisms found in C++ and Modula-3. Python classes provide all the standard |
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10 features of Object Oriented Programming: the class inheritance mechanism allows |
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11 multiple base classes, a derived class can override any methods of its base |
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12 class or classes, and a method can call the method of a base class with the same |
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13 name. Objects can contain arbitrary amounts and kinds of data. As is true for |
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14 modules, classes partake of the dynamic nature of Python: they are created at |
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15 runtime, and can be modified further after creation. |
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16 |
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17 In C++ terminology, normally class members (including the data members) are |
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18 *public* (except see below :ref:`tut-private`), and all member functions are |
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19 *virtual*. As in Modula-3, there are no shorthands for referencing the object's |
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20 members from its methods: the method function is declared with an explicit first |
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21 argument representing the object, which is provided implicitly by the call. As |
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22 in Smalltalk, classes themselves are objects. This provides semantics for |
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23 importing and renaming. Unlike C++ and Modula-3, built-in types can be used as |
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24 base classes for extension by the user. Also, like in C++, most built-in |
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25 operators with special syntax (arithmetic operators, subscripting etc.) can be |
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26 redefined for class instances. |
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27 |
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28 (Lacking universally accepted terminology to talk about classes, I will make |
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29 occasional use of Smalltalk and C++ terms. I would use Modula-3 terms, since |
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30 its object-oriented semantics are closer to those of Python than C++, but I |
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31 expect that few readers have heard of it.) |
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32 |
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33 |
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34 .. _tut-object: |
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35 |
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36 A Word About Names and Objects |
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37 ============================== |
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38 |
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39 Objects have individuality, and multiple names (in multiple scopes) can be bound |
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40 to the same object. This is known as aliasing in other languages. This is |
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41 usually not appreciated on a first glance at Python, and can be safely ignored |
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42 when dealing with immutable basic types (numbers, strings, tuples). However, |
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43 aliasing has a possibly surprising effect on the semantics of Python code |
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44 involving mutable objects such as lists, dictionaries, and most other types. |
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45 This is usually used to the benefit of the program, since aliases behave like |
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46 pointers in some respects. For example, passing an object is cheap since only a |
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47 pointer is passed by the implementation; and if a function modifies an object |
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48 passed as an argument, the caller will see the change --- this eliminates the |
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49 need for two different argument passing mechanisms as in Pascal. |
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50 |
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51 |
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52 .. _tut-scopes: |
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53 |
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54 Python Scopes and Namespaces |
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55 ============================ |
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56 |
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57 Before introducing classes, I first have to tell you something about Python's |
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58 scope rules. Class definitions play some neat tricks with namespaces, and you |
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59 need to know how scopes and namespaces work to fully understand what's going on. |
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60 Incidentally, knowledge about this subject is useful for any advanced Python |
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61 programmer. |
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62 |
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63 Let's begin with some definitions. |
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64 |
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65 A *namespace* is a mapping from names to objects. Most namespaces are currently |
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66 implemented as Python dictionaries, but that's normally not noticeable in any |
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67 way (except for performance), and it may change in the future. Examples of |
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68 namespaces are: the set of built-in names (containing functions such as :func:`abs`, and |
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69 built-in exception names); the global names in a module; and the local names in |
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70 a function invocation. In a sense the set of attributes of an object also form |
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71 a namespace. The important thing to know about namespaces is that there is |
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72 absolutely no relation between names in different namespaces; for instance, two |
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73 different modules may both define a function ``maximize`` without confusion --- |
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74 users of the modules must prefix it with the module name. |
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75 |
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76 By the way, I use the word *attribute* for any name following a dot --- for |
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77 example, in the expression ``z.real``, ``real`` is an attribute of the object |
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78 ``z``. Strictly speaking, references to names in modules are attribute |
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79 references: in the expression ``modname.funcname``, ``modname`` is a module |
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80 object and ``funcname`` is an attribute of it. In this case there happens to be |
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81 a straightforward mapping between the module's attributes and the global names |
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82 defined in the module: they share the same namespace! [#]_ |
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83 |
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84 Attributes may be read-only or writable. In the latter case, assignment to |
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85 attributes is possible. Module attributes are writable: you can write |
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86 ``modname.the_answer = 42``. Writable attributes may also be deleted with the |
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87 :keyword:`del` statement. For example, ``del modname.the_answer`` will remove |
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88 the attribute :attr:`the_answer` from the object named by ``modname``. |
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89 |
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90 Namespaces are created at different moments and have different lifetimes. The |
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91 namespace containing the built-in names is created when the Python interpreter |
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92 starts up, and is never deleted. The global namespace for a module is created |
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93 when the module definition is read in; normally, module namespaces also last |
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94 until the interpreter quits. The statements executed by the top-level |
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95 invocation of the interpreter, either read from a script file or interactively, |
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96 are considered part of a module called :mod:`__main__`, so they have their own |
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97 global namespace. (The built-in names actually also live in a module; this is |
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98 called :mod:`builtins`.) |
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99 |
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100 The local namespace for a function is created when the function is called, and |
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101 deleted when the function returns or raises an exception that is not handled |
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102 within the function. (Actually, forgetting would be a better way to describe |
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103 what actually happens.) Of course, recursive invocations each have their own |
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104 local namespace. |
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105 |
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106 A *scope* is a textual region of a Python program where a namespace is directly |
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107 accessible. "Directly accessible" here means that an unqualified reference to a |
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108 name attempts to find the name in the namespace. |
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109 |
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110 Although scopes are determined statically, they are used dynamically. At any |
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111 time during execution, there are at least three nested scopes whose namespaces |
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112 are directly accessible: |
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113 |
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114 * the innermost scope, which is searched first, contains the local names |
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115 * the scopes of any enclosing functions, which are searched starting with the |
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116 nearest enclosing scope, contains non-local, but also non-global names |
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117 * the next-to-last scope contains the current module's global names |
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118 * the outermost scope (searched last) is the namespace containing built-in names |
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119 |
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120 If a name is declared global, then all references and assignments go directly to |
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121 the middle scope containing the module's global names. To rebind variables |
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122 found outside of the innermost scope, the :keyword:`nonlocal` statement can be |
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123 used; if not declared nonlocal, those variable are read-only (an attempt to |
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124 write to such a variable will simply create a *new* local variable in the |
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125 innermost scope, leaving the identically named outer variable unchanged). |
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126 |
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127 Usually, the local scope references the local names of the (textually) current |
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128 function. Outside functions, the local scope references the same namespace as |
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129 the global scope: the module's namespace. Class definitions place yet another |
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130 namespace in the local scope. |
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131 |
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132 It is important to realize that scopes are determined textually: the global |
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133 scope of a function defined in a module is that module's namespace, no matter |
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134 from where or by what alias the function is called. On the other hand, the |
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135 actual search for names is done dynamically, at run time --- however, the |
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136 language definition is evolving towards static name resolution, at "compile" |
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137 time, so don't rely on dynamic name resolution! (In fact, local variables are |
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138 already determined statically.) |
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139 |
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140 A special quirk of Python is that -- if no :keyword:`global` statement is in |
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141 effect -- assignments to names always go into the innermost scope. Assignments |
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142 do not copy data --- they just bind names to objects. The same is true for |
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143 deletions: the statement ``del x`` removes the binding of ``x`` from the |
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144 namespace referenced by the local scope. In fact, all operations that introduce |
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145 new names use the local scope: in particular, :keyword:`import` statements and |
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146 function definitions bind the module or function name in the local scope. |
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147 |
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148 The :keyword:`global` statement can be used to indicate that particular |
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149 variables live in the global scope and should be rebound there; the |
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150 :keyword:`nonlocal` statement indicates that particular variables live in |
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151 an enclosing scope and should be rebound there. |
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152 |
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153 .. _tut-scopeexample: |
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154 |
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155 Scopes and Namespaces Example |
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156 ----------------------------- |
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157 |
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158 This is an example demonstrating how to reference the different scopes and |
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159 namespaces, and how :keyword:`global` and :keyword:`nonlocal` affect variable |
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160 binding:: |
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161 |
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162 def scope_test(): |
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163 def do_local(): |
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164 spam = "local spam" |
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165 def do_nonlocal(): |
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166 nonlocal spam |
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167 spam = "nonlocal spam" |
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168 def do_global(): |
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169 global spam |
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170 spam = "global spam" |
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171 spam = "test spam" |
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172 do_local() |
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173 print("After local assignment:", spam) |
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174 do_nonlocal() |
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175 print("After nonlocal assignment:", spam) |
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176 do_global() |
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177 print("After global assignment:", spam) |
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178 |
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179 scope_test() |
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180 print("In global scope:", spam) |
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181 |
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182 The output of the example code is: |
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183 |
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184 .. code-block:: none |
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185 |
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186 After local assignment: test spam |
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187 After nonlocal assignment: nonlocal spam |
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188 After global assignment: nonlocal spam |
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189 In global scope: global spam |
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190 |
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191 Note how the *local* assignment (which is default) didn't change *scope_test*\'s |
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192 binding of *spam*. The :keyword:`nonlocal` assignment changed *scope_test*\'s |
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193 binding of *spam*, and the :keyword:`global` assignment changed the module-level |
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194 binding. |
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195 |
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196 You can also see that there was no previous binding for *spam* before the |
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197 :keyword:`global` assignment. |
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198 |
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199 |
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200 .. _tut-firstclasses: |
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201 |
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202 A First Look at Classes |
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203 ======================= |
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204 |
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205 Classes introduce a little bit of new syntax, three new object types, and some |
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206 new semantics. |
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207 |
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208 |
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209 .. _tut-classdefinition: |
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210 |
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211 Class Definition Syntax |
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212 ----------------------- |
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213 |
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214 The simplest form of class definition looks like this:: |
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215 |
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216 class ClassName: |
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217 <statement-1> |
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218 . |
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219 . |
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220 . |
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221 <statement-N> |
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222 |
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223 Class definitions, like function definitions (:keyword:`def` statements) must be |
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224 executed before they have any effect. (You could conceivably place a class |
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225 definition in a branch of an :keyword:`if` statement, or inside a function.) |
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226 |
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227 In practice, the statements inside a class definition will usually be function |
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228 definitions, but other statements are allowed, and sometimes useful --- we'll |
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229 come back to this later. The function definitions inside a class normally have |
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230 a peculiar form of argument list, dictated by the calling conventions for |
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231 methods --- again, this is explained later. |
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232 |
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233 When a class definition is entered, a new namespace is created, and used as the |
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234 local scope --- thus, all assignments to local variables go into this new |
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235 namespace. In particular, function definitions bind the name of the new |
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236 function here. |
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237 |
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238 When a class definition is left normally (via the end), a *class object* is |
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239 created. This is basically a wrapper around the contents of the namespace |
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240 created by the class definition; we'll learn more about class objects in the |
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241 next section. The original local scope (the one in effect just before the class |
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242 definition was entered) is reinstated, and the class object is bound here to the |
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243 class name given in the class definition header (:class:`ClassName` in the |
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244 example). |
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245 |
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246 |
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247 .. _tut-classobjects: |
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248 |
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249 Class Objects |
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250 ------------- |
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251 |
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252 Class objects support two kinds of operations: attribute references and |
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253 instantiation. |
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254 |
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255 *Attribute references* use the standard syntax used for all attribute references |
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256 in Python: ``obj.name``. Valid attribute names are all the names that were in |
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257 the class's namespace when the class object was created. So, if the class |
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258 definition looked like this:: |
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259 |
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260 class MyClass: |
| 49180 | 261 """A simple example class""" |
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262 i = 12345 |
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263 def f(self): |
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264 return 'hello world' |
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265 |
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266 then ``MyClass.i`` and ``MyClass.f`` are valid attribute references, returning |
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267 an integer and a function object, respectively. Class attributes can also be |
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268 assigned to, so you can change the value of ``MyClass.i`` by assignment. |
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269 :attr:`__doc__` is also a valid attribute, returning the docstring belonging to |
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270 the class: ``"A simple example class"``. |
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271 |
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272 Class *instantiation* uses function notation. Just pretend that the class |
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273 object is a parameterless function that returns a new instance of the class. |
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274 For example (assuming the above class):: |
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275 |
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276 x = MyClass() |
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277 |
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278 creates a new *instance* of the class and assigns this object to the local |
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279 variable ``x``. |
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280 |
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281 The instantiation operation ("calling" a class object) creates an empty object. |
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282 Many classes like to create objects with instances customized to a specific |
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283 initial state. Therefore a class may define a special method named |
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284 :meth:`__init__`, like this:: |
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285 |
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286 def __init__(self): |
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287 self.data = [] |
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288 |
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289 When a class defines an :meth:`__init__` method, class instantiation |
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290 automatically invokes :meth:`__init__` for the newly-created class instance. So |
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291 in this example, a new, initialized instance can be obtained by:: |
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292 |
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293 x = MyClass() |
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294 |
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295 Of course, the :meth:`__init__` method may have arguments for greater |
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296 flexibility. In that case, arguments given to the class instantiation operator |
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297 are passed on to :meth:`__init__`. For example, :: |
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298 |
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299 >>> class Complex: |
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300 ... def __init__(self, realpart, imagpart): |
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301 ... self.r = realpart |
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302 ... self.i = imagpart |
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303 ... |
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304 >>> x = Complex(3.0, -4.5) |
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305 >>> x.r, x.i |
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306 (3.0, -4.5) |
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307 |
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308 |
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309 .. _tut-instanceobjects: |
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310 |
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311 Instance Objects |
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312 ---------------- |
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313 |
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314 Now what can we do with instance objects? The only operations understood by |
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315 instance objects are attribute references. There are two kinds of valid |
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316 attribute names, data attributes and methods. |
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317 |
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318 *data attributes* correspond to "instance variables" in Smalltalk, and to "data |
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319 members" in C++. Data attributes need not be declared; like local variables, |
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320 they spring into existence when they are first assigned to. For example, if |
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321 ``x`` is the instance of :class:`MyClass` created above, the following piece of |
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322 code will print the value ``16``, without leaving a trace:: |
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323 |
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324 x.counter = 1 |
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325 while x.counter < 10: |
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326 x.counter = x.counter * 2 |
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327 print(x.counter) |
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328 del x.counter |
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329 |
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330 The other kind of instance attribute reference is a *method*. A method is a |
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331 function that "belongs to" an object. (In Python, the term method is not unique |
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332 to class instances: other object types can have methods as well. For example, |
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333 list objects have methods called append, insert, remove, sort, and so on. |
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334 However, in the following discussion, we'll use the term method exclusively to |
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335 mean methods of class instance objects, unless explicitly stated otherwise.) |
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336 |
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337 .. index:: object: method |
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338 |
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339 Valid method names of an instance object depend on its class. By definition, |
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340 all attributes of a class that are function objects define corresponding |
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341 methods of its instances. So in our example, ``x.f`` is a valid method |
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342 reference, since ``MyClass.f`` is a function, but ``x.i`` is not, since |
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343 ``MyClass.i`` is not. But ``x.f`` is not the same thing as ``MyClass.f`` --- it |
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344 is a *method object*, not a function object. |
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345 |
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346 |
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347 .. _tut-methodobjects: |
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348 |
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349 Method Objects |
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350 -------------- |
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351 |
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352 Usually, a method is called right after it is bound:: |
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353 |
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354 x.f() |
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355 |
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356 In the :class:`MyClass` example, this will return the string ``'hello world'``. |
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357 However, it is not necessary to call a method right away: ``x.f`` is a method |
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358 object, and can be stored away and called at a later time. For example:: |
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359 |
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360 xf = x.f |
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361 while True: |
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362 print(xf()) |
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363 |
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364 will continue to print ``hello world`` until the end of time. |
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365 |
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366 What exactly happens when a method is called? You may have noticed that |
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367 ``x.f()`` was called without an argument above, even though the function |
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368 definition for :meth:`f` specified an argument. What happened to the argument? |
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369 Surely Python raises an exception when a function that requires an argument is |
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370 called without any --- even if the argument isn't actually used... |
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371 |
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372 Actually, you may have guessed the answer: the special thing about methods is |
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373 that the object is passed as the first argument of the function. In our |
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374 example, the call ``x.f()`` is exactly equivalent to ``MyClass.f(x)``. In |
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375 general, calling a method with a list of *n* arguments is equivalent to calling |
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376 the corresponding function with an argument list that is created by inserting |
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377 the method's object before the first argument. |
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378 |
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379 If you still don't understand how methods work, a look at the implementation can |
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380 perhaps clarify matters. When an instance attribute is referenced that isn't a |
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381 data attribute, its class is searched. If the name denotes a valid class |
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382 attribute that is a function object, a method object is created by packing |
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383 (pointers to) the instance object and the function object just found together in |
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384 an abstract object: this is the method object. When the method object is called |
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385 with an argument list, a new argument list is constructed from the instance |
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386 object and the argument list, and the function object is called with this new |
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387 argument list. |
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388 |
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389 |
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390 .. _tut-remarks: |
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391 |
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392 Random Remarks |
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393 ============== |
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394 |
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395 .. These should perhaps be placed more carefully... |
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396 |
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397 Data attributes override method attributes with the same name; to avoid |
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398 accidental name conflicts, which may cause hard-to-find bugs in large programs, |
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399 it is wise to use some kind of convention that minimizes the chance of |
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400 conflicts. Possible conventions include capitalizing method names, prefixing |
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401 data attribute names with a small unique string (perhaps just an underscore), or |
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402 using verbs for methods and nouns for data attributes. |
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403 |
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404 Data attributes may be referenced by methods as well as by ordinary users |
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405 ("clients") of an object. In other words, classes are not usable to implement |
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406 pure abstract data types. In fact, nothing in Python makes it possible to |
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407 enforce data hiding --- it is all based upon convention. (On the other hand, |
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408 the Python implementation, written in C, can completely hide implementation |
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409 details and control access to an object if necessary; this can be used by |
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410 extensions to Python written in C.) |
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411 |
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412 Clients should use data attributes with care --- clients may mess up invariants |
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413 maintained by the methods by stamping on their data attributes. Note that |
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414 clients may add data attributes of their own to an instance object without |
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415 affecting the validity of the methods, as long as name conflicts are avoided --- |
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416 again, a naming convention can save a lot of headaches here. |
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417 |
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418 There is no shorthand for referencing data attributes (or other methods!) from |
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419 within methods. I find that this actually increases the readability of methods: |
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420 there is no chance of confusing local variables and instance variables when |
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421 glancing through a method. |
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422 |
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423 Often, the first argument of a method is called ``self``. This is nothing more |
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424 than a convention: the name ``self`` has absolutely no special meaning to |
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425 Python. Note, however, that by not following the convention your code may be |
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426 less readable to other Python programmers, and it is also conceivable that a |
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427 *class browser* program might be written that relies upon such a convention. |
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428 |
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429 Any function object that is a class attribute defines a method for instances of |
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430 that class. It is not necessary that the function definition is textually |
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431 enclosed in the class definition: assigning a function object to a local |
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432 variable in the class is also ok. For example:: |
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433 |
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434 # Function defined outside the class |
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435 def f1(self, x, y): |
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436 return min(x, x+y) |
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437 |
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438 class C: |
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439 f = f1 |
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440 def g(self): |
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441 return 'hello world' |
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442 h = g |
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443 |
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444 Now ``f``, ``g`` and ``h`` are all attributes of class :class:`C` that refer to |
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445 function objects, and consequently they are all methods of instances of |
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446 :class:`C` --- ``h`` being exactly equivalent to ``g``. Note that this practice |
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447 usually only serves to confuse the reader of a program. |
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448 |
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449 Methods may call other methods by using method attributes of the ``self`` |
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450 argument:: |
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451 |
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452 class Bag: |
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453 def __init__(self): |
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454 self.data = [] |
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455 def add(self, x): |
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456 self.data.append(x) |
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457 def addtwice(self, x): |
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458 self.add(x) |
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459 self.add(x) |
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460 |
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461 Methods may reference global names in the same way as ordinary functions. The |
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462 global scope associated with a method is the module containing its |
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463 definition. (A class is never used as a global scope.) While one |
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464 rarely encounters a good reason for using global data in a method, there are |
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465 many legitimate uses of the global scope: for one thing, functions and modules |
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466 imported into the global scope can be used by methods, as well as functions and |
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467 classes defined in it. Usually, the class containing the method is itself |
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468 defined in this global scope, and in the next section we'll find some good |
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469 reasons why a method would want to reference its own class. |
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470 |
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471 Each value is an object, and therefore has a *class* (also called its *type*). |
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472 It is stored as ``object.__class__``. |
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473 |
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474 |
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475 .. _tut-inheritance: |
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476 |
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477 Inheritance |
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478 =========== |
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479 |
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480 Of course, a language feature would not be worthy of the name "class" without |
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481 supporting inheritance. The syntax for a derived class definition looks like |
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482 this:: |
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483 |
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484 class DerivedClassName(BaseClassName): |
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485 <statement-1> |
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486 . |
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487 . |
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488 . |
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489 <statement-N> |
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490 |
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491 The name :class:`BaseClassName` must be defined in a scope containing the |
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492 derived class definition. In place of a base class name, other arbitrary |
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493 expressions are also allowed. This can be useful, for example, when the base |
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494 class is defined in another module:: |
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495 |
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496 class DerivedClassName(modname.BaseClassName): |
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497 |
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498 Execution of a derived class definition proceeds the same as for a base class. |
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499 When the class object is constructed, the base class is remembered. This is |
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500 used for resolving attribute references: if a requested attribute is not found |
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501 in the class, the search proceeds to look in the base class. This rule is |
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502 applied recursively if the base class itself is derived from some other class. |
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503 |
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504 There's nothing special about instantiation of derived classes: |
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505 ``DerivedClassName()`` creates a new instance of the class. Method references |
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506 are resolved as follows: the corresponding class attribute is searched, |
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507 descending down the chain of base classes if necessary, and the method reference |
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508 is valid if this yields a function object. |
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509 |
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510 Derived classes may override methods of their base classes. Because methods |
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511 have no special privileges when calling other methods of the same object, a |
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512 method of a base class that calls another method defined in the same base class |
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513 may end up calling a method of a derived class that overrides it. (For C++ |
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514 programmers: all methods in Python are effectively ``virtual``.) |
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515 |
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516 An overriding method in a derived class may in fact want to extend rather than |
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517 simply replace the base class method of the same name. There is a simple way to |
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518 call the base class method directly: just call ``BaseClassName.methodname(self, |
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519 arguments)``. This is occasionally useful to clients as well. (Note that this |
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520 only works if the base class is accessible as ``BaseClassName`` in the global |
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521 scope.) |
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522 |
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523 Python has two built-in functions that work with inheritance: |
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524 |
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525 * Use :func:`isinstance` to check an instance's type: ``isinstance(obj, int)`` |
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526 will be ``True`` only if ``obj.__class__`` is :class:`int` or some class |
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527 derived from :class:`int`. |
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528 |
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529 * Use :func:`issubclass` to check class inheritance: ``issubclass(bool, int)`` |
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530 is ``True`` since :class:`bool` is a subclass of :class:`int`. However, |
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531 ``issubclass(float, int)`` is ``False`` since :class:`float` is not a |
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532 subclass of :class:`int`. |
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533 |
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534 |
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535 |
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536 .. _tut-multiple: |
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537 |
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538 Multiple Inheritance |
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539 -------------------- |
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540 |
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541 Python supports a form of multiple inheritance as well. A class definition with |
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542 multiple base classes looks like this:: |
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543 |
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544 class DerivedClassName(Base1, Base2, Base3): |
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545 <statement-1> |
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546 . |
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547 . |
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548 . |
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549 <statement-N> |
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550 |
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551 For most purposes, in the simplest cases, you can think of the search for |
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552 attributes inherited from a parent class as depth-first, left-to-right, not |
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553 searching twice in the same class where there is an overlap in the hierarchy. |
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554 Thus, if an attribute is not found in :class:`DerivedClassName`, it is searched |
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555 for in :class:`Base1`, then (recursively) in the base classes of :class:`Base1`, |
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556 and if it was not found there, it was searched for in :class:`Base2`, and so on. |
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557 |
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558 In fact, it is slightly more complex than that; the method resolution order |
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559 changes dynamically to support cooperative calls to :func:`super`. This |
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560 approach is known in some other multiple-inheritance languages as |
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561 call-next-method and is more powerful than the super call found in |
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562 single-inheritance languages. |
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563 |
| 43155 | 564 Dynamic ordering is necessary because all cases of multiple inheritance exhibit |
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565 one or more diamond relationships (where at least one of the parent classes |
| 43155 | 566 can be accessed through multiple paths from the bottommost class). For example, |
| 567 all classes inherit from :class:`object`, so any case of multiple inheritance | |
| 568 provides more than one path to reach :class:`object`. To keep the base classes | |
| 569 from being accessed more than once, the dynamic algorithm linearizes the search | |
| 570 order in a way that preserves the left-to-right ordering specified in each | |
| 571 class, that calls each parent only once, and that is monotonic (meaning that a | |
| 572 class can be subclassed without affecting the precedence order of its parents). | |
| 573 Taken together, these properties make it possible to design reliable and | |
| 574 extensible classes with multiple inheritance. For more detail, see | |
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575 http://www.python.org/download/releases/2.3/mro/. |
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576 |
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577 |
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578 .. _tut-private: |
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579 |
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580 Private Variables |
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581 ================= |
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582 |
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583 "Private" instance variables that cannot be accessed except from inside an |
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584 object don't exist in Python. However, there is a convention that is followed |
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585 by most Python code: a name prefixed with an underscore (e.g. ``_spam``) should |
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586 be treated as a non-public part of the API (whether it is a function, a method |
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587 or a data member). It should be considered an implementation detail and subject |
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588 to change without notice. |
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589 |
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590 Since there is a valid use-case for class-private members (namely to avoid name |
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591 clashes of names with names defined by subclasses), there is limited support for |
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592 such a mechanism, called :dfn:`name mangling`. Any identifier of the form |
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593 ``__spam`` (at least two leading underscores, at most one trailing underscore) |
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594 is textually replaced with ``_classname__spam``, where ``classname`` is the |
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595 current class name with leading underscore(s) stripped. This mangling is done |
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596 without regard to the syntactic position of the identifier, as long as it |
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597 occurs within the definition of a class. |
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598 |
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599 Name mangling is helpful for letting subclasses override methods without |
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600 breaking intraclass method calls. For example:: |
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601 |
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602 class Mapping: |
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603 def __init__(self, iterable): |
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604 self.items_list = [] |
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605 self.__update(iterable) |
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606 |
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607 def update(self, iterable): |
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608 for item in iterable: |
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609 self.items_list.append(item) |
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610 |
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611 __update = update # private copy of original update() method |
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612 |
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613 class MappingSubclass(Mapping): |
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614 |
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615 def update(self, keys, values): |
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616 # provides new signature for update() |
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617 # but does not break __init__() |
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618 for item in zip(keys, values): |
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619 self.items_list.append(item) |
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620 |
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621 Note that the mangling rules are designed mostly to avoid accidents; it still is |
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622 possible to access or modify a variable that is considered private. This can |
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623 even be useful in special circumstances, such as in the debugger. |
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624 |
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625 Notice that code passed to ``exec()`` or ``eval()`` does not consider the |
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626 classname of the invoking class to be the current class; this is similar to the |
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627 effect of the ``global`` statement, the effect of which is likewise restricted |
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628 to code that is byte-compiled together. The same restriction applies to |
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629 ``getattr()``, ``setattr()`` and ``delattr()``, as well as when referencing |
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630 ``__dict__`` directly. |
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631 |
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632 |
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633 .. _tut-odds: |
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634 |
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635 Odds and Ends |
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636 ============= |
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637 |
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638 Sometimes it is useful to have a data type similar to the Pascal "record" or C |
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639 "struct", bundling together a few named data items. An empty class definition |
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640 will do nicely:: |
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642 class Employee: |
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643 pass |
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645 john = Employee() # Create an empty employee record |
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646 |
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647 # Fill the fields of the record |
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648 john.name = 'John Doe' |
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649 john.dept = 'computer lab' |
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650 john.salary = 1000 |
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651 |
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652 A piece of Python code that expects a particular abstract data type can often be |
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653 passed a class that emulates the methods of that data type instead. For |
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654 instance, if you have a function that formats some data from a file object, you |
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655 can define a class with methods :meth:`read` and :meth:`!readline` that get the |
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656 data from a string buffer instead, and pass it as an argument. |
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657 |
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658 .. (Unfortunately, this technique has its limitations: a class can't define |
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659 operations that are accessed by special syntax such as sequence subscripting |
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660 or arithmetic operators, and assigning such a "pseudo-file" to sys.stdin will |
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661 not cause the interpreter to read further input from it.) |
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662 |
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663 Instance method objects have attributes, too: ``m.__self__`` is the instance |
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664 object with the method :meth:`m`, and ``m.__func__`` is the function object |
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665 corresponding to the method. |
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666 |
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667 |
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668 .. _tut-exceptionclasses: |
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669 |
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670 Exceptions Are Classes Too |
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671 ========================== |
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672 |
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673 User-defined exceptions are identified by classes as well. Using this mechanism |
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674 it is possible to create extensible hierarchies of exceptions. |
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675 |
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676 There are two new valid (semantic) forms for the :keyword:`raise` statement:: |
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677 |
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678 raise Class |
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679 |
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680 raise Instance |
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681 |
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682 In the first form, ``Class`` must be an instance of :class:`type` or of a |
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683 class derived from it. The first form is a shorthand for:: |
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684 |
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685 raise Class() |
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686 |
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687 A class in an :keyword:`except` clause is compatible with an exception if it is |
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688 the same class or a base class thereof (but not the other way around --- an |
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689 except clause listing a derived class is not compatible with a base class). For |
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690 example, the following code will print B, C, D in that order:: |
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691 |
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692 class B(Exception): |
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693 pass |
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694 class C(B): |
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695 pass |
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696 class D(C): |
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697 pass |
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698 |
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699 for cls in [B, C, D]: |
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700 try: |
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701 raise cls() |
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702 except D: |
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703 print("D") |
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704 except C: |
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705 print("C") |
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706 except B: |
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707 print("B") |
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708 |
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709 Note that if the except clauses were reversed (with ``except B`` first), it |
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710 would have printed B, B, B --- the first matching except clause is triggered. |
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711 |
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712 When an error message is printed for an unhandled exception, the exception's |
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713 class name is printed, then a colon and a space, and finally the instance |
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714 converted to a string using the built-in function :func:`str`. |
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715 |
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716 |
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717 .. _tut-iterators: |
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718 |
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719 Iterators |
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720 ========= |
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721 |
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722 By now you have probably noticed that most container objects can be looped over |
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723 using a :keyword:`for` statement:: |
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724 |
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725 for element in [1, 2, 3]: |
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726 print(element) |
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727 for element in (1, 2, 3): |
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728 print(element) |
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729 for key in {'one':1, 'two':2}: |
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730 print(key) |
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731 for char in "123": |
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732 print(char) |
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733 for line in open("myfile.txt"): |
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734 print(line) |
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735 |
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736 This style of access is clear, concise, and convenient. The use of iterators |
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737 pervades and unifies Python. Behind the scenes, the :keyword:`for` statement |
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738 calls :func:`iter` on the container object. The function returns an iterator |
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739 object that defines the method :meth:`~iterator.__next__` which accesses |
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740 elements in the container one at a time. When there are no more elements, |
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741 :meth:`~iterator.__next__` raises a :exc:`StopIteration` exception which tells the |
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742 :keyword:`for` loop to terminate. You can call the :meth:`~iterator.__next__` method |
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743 using the :func:`next` built-in function; this example shows how it all works:: |
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744 |
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745 >>> s = 'abc' |
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746 >>> it = iter(s) |
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747 >>> it |
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748 <iterator object at 0x00A1DB50> |
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749 >>> next(it) |
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750 'a' |
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751 >>> next(it) |
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752 'b' |
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753 >>> next(it) |
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754 'c' |
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755 >>> next(it) |
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756 Traceback (most recent call last): |
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757 File "<stdin>", line 1, in ? |
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758 next(it) |
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759 StopIteration |
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760 |
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761 Having seen the mechanics behind the iterator protocol, it is easy to add |
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762 iterator behavior to your classes. Define an :meth:`__iter__` method which |
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763 returns an object with a :meth:`~iterator.__next__` method. If the class |
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764 defines :meth:`__next__`, then :meth:`__iter__` can just return ``self``:: |
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765 |
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766 class Reverse: |
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767 """Iterator for looping over a sequence backwards.""" |
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768 def __init__(self, data): |
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769 self.data = data |
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770 self.index = len(data) |
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771 def __iter__(self): |
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772 return self |
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773 def __next__(self): |
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774 if self.index == 0: |
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775 raise StopIteration |
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776 self.index = self.index - 1 |
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777 return self.data[self.index] |
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778 |
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779 :: |
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780 |
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781 >>> rev = Reverse('spam') |
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782 >>> iter(rev) |
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783 <__main__.Reverse object at 0x00A1DB50> |
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784 >>> for char in rev: |
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785 ... print(char) |
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786 ... |
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791 |
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792 |
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793 .. _tut-generators: |
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794 |
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795 Generators |
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796 ========== |
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797 |
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798 :term:`Generator`\s are a simple and powerful tool for creating iterators. They |
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799 are written like regular functions but use the :keyword:`yield` statement |
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800 whenever they want to return data. Each time :func:`next` is called on it, the |
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801 generator resumes where it left-off (it remembers all the data values and which |
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802 statement was last executed). An example shows that generators can be trivially |
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803 easy to create:: |
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804 |
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805 def reverse(data): |
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806 for index in range(len(data)-1, -1, -1): |
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807 yield data[index] |
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808 |
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809 :: |
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810 |
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811 >>> for char in reverse('golf'): |
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812 ... print(char) |
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813 ... |
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814 f |
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815 l |
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816 o |
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817 g |
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818 |
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819 Anything that can be done with generators can also be done with class based |
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820 iterators as described in the previous section. What makes generators so |
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821 compact is that the :meth:`__iter__` and :meth:`~generator.__next__` methods |
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822 are created automatically. |
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823 |
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824 Another key feature is that the local variables and execution state are |
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825 automatically saved between calls. This made the function easier to write and |
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826 much more clear than an approach using instance variables like ``self.index`` |
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827 and ``self.data``. |
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828 |
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829 In addition to automatic method creation and saving program state, when |
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830 generators terminate, they automatically raise :exc:`StopIteration`. In |
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831 combination, these features make it easy to create iterators with no more effort |
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832 than writing a regular function. |
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833 |
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834 |
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835 .. _tut-genexps: |
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836 |
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837 Generator Expressions |
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838 ===================== |
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839 |
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840 Some simple generators can be coded succinctly as expressions using a syntax |
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841 similar to list comprehensions but with parentheses instead of brackets. These |
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842 expressions are designed for situations where the generator is used right away |
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843 by an enclosing function. Generator expressions are more compact but less |
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844 versatile than full generator definitions and tend to be more memory friendly |
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845 than equivalent list comprehensions. |
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846 |
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847 Examples:: |
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848 |
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849 >>> sum(i*i for i in range(10)) # sum of squares |
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850 285 |
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851 |
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852 >>> xvec = [10, 20, 30] |
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853 >>> yvec = [7, 5, 3] |
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854 >>> sum(x*y for x,y in zip(xvec, yvec)) # dot product |
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855 260 |
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856 |
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857 >>> from math import pi, sin |
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858 >>> sine_table = {x: sin(x*pi/180) for x in range(0, 91)} |
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859 |
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860 >>> unique_words = set(word for line in page for word in line.split()) |
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861 |
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862 >>> valedictorian = max((student.gpa, student.name) for student in graduates) |
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863 |
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864 >>> data = 'golf' |
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865 >>> list(data[i] for i in range(len(data)-1, -1, -1)) |
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866 ['f', 'l', 'o', 'g'] |
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867 |
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868 |
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869 |
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870 .. rubric:: Footnotes |
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871 |
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872 .. [#] Except for one thing. Module objects have a secret read-only attribute called |
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873 :attr:`__dict__` which returns the dictionary used to implement the module's |
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874 namespace; the name :attr:`__dict__` is an attribute but not a global name. |
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875 Obviously, using this violates the abstraction of namespace implementation, and |
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876 should be restricted to things like post-mortem debuggers. |
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877 |
