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# 3. 定義擴展類型:已分類主題
本章節目標是提供一個各種你可以實現的類型方法及其功能的簡短介紹。
這是C類型 [`PyTypeObject`](../c-api/type.xhtml#c.PyTypeObject "PyTypeObject") 的定義,省略了只用于調試構建的字段:
```
typedef struct _typeobject {
PyObject_VAR_HEAD
const char *tp_name; /* For printing, in format "<module>.<name>" */
Py_ssize_t tp_basicsize, tp_itemsize; /* For allocation */
/* Methods to implement standard operations */
destructor tp_dealloc;
printfunc tp_print;
getattrfunc tp_getattr;
setattrfunc tp_setattr;
PyAsyncMethods *tp_as_async; /* formerly known as tp_compare (Python 2)
or tp_reserved (Python 3) */
reprfunc tp_repr;
/* Method suites for standard classes */
PyNumberMethods *tp_as_number;
PySequenceMethods *tp_as_sequence;
PyMappingMethods *tp_as_mapping;
/* More standard operations (here for binary compatibility) */
hashfunc tp_hash;
ternaryfunc tp_call;
reprfunc tp_str;
getattrofunc tp_getattro;
setattrofunc tp_setattro;
/* Functions to access object as input/output buffer */
PyBufferProcs *tp_as_buffer;
/* Flags to define presence of optional/expanded features */
unsigned long tp_flags;
const char *tp_doc; /* Documentation string */
/* call function for all accessible objects */
traverseproc tp_traverse;
/* delete references to contained objects */
inquiry tp_clear;
/* rich comparisons */
richcmpfunc tp_richcompare;
/* weak reference enabler */
Py_ssize_t tp_weaklistoffset;
/* Iterators */
getiterfunc tp_iter;
iternextfunc tp_iternext;
/* Attribute descriptor and subclassing stuff */
struct PyMethodDef *tp_methods;
struct PyMemberDef *tp_members;
struct PyGetSetDef *tp_getset;
struct _typeobject *tp_base;
PyObject *tp_dict;
descrgetfunc tp_descr_get;
descrsetfunc tp_descr_set;
Py_ssize_t tp_dictoffset;
initproc tp_init;
allocfunc tp_alloc;
newfunc tp_new;
freefunc tp_free; /* Low-level free-memory routine */
inquiry tp_is_gc; /* For PyObject_IS_GC */
PyObject *tp_bases;
PyObject *tp_mro; /* method resolution order */
PyObject *tp_cache;
PyObject *tp_subclasses;
PyObject *tp_weaklist;
destructor tp_del;
/* Type attribute cache version tag. Added in version 2.6 */
unsigned int tp_version_tag;
destructor tp_finalize;
} PyTypeObject;
```
這里有 *很多* 方法。但是不要太擔心,如果你要定義一個類型,通常只需要實現少量的方法。
正如你猜到的一樣,我們正要一步一步詳細介紹各種處理程序。因為有大量的歷史包袱影響字段的排序,所以我們不會根據它們在結構體里定義的順序講解。通常非常容易找到一個包含你需要的字段的例子,然后改變值去適應你新的類型。
```
const char *tp_name; /* For printing */
```
類型的名字 - 上一章提到過的,會出現在很多地方,幾乎全部都是為了診斷目的。嘗試選擇一個好名字,對于診斷很有幫助。
```
Py_ssize_t tp_basicsize, tp_itemsize; /* For allocation */
```
這些字段告訴運行時在創造這個類型的新對象時需要分配多少內存。Python為了可變長度的結構(想下:字符串,元組)有些內置支持,這是 [`tp_itemsize`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_itemsize "PyTypeObject.tp_itemsize") 字段存在的原由。這部分稍后解釋。
```
const char *tp_doc;
```
這里你可以放置一段字符串(或者它的地址),當你想在Python腳本引用 `obj.__doc__` 時返回這段文檔字符串。
現在我們來看一下基本類型方法 - 大多數擴展類型將實現的方法。
## 3.1. 終結和內存釋放
```
destructor tp_dealloc;
```
當您的類型實例的引用計數減少為零并且Python解釋器想要回收它時,將調用此函數。如果你的類型有內存可供釋放或執行其他清理,你可以把它放在這里。 對象本身也需要在這里釋放。 以下是此函數的示例:
```
static void
newdatatype_dealloc(newdatatypeobject *obj)
{
free(obj->obj_UnderlyingDatatypePtr);
Py_TYPE(obj)->tp_free(obj);
}
```
One important requirement of the deallocator function is that it leaves any pending exceptions alone. This is important since deallocators are frequently called as the interpreter unwinds the Python stack; when the stack is unwound due to an exception (rather than normal returns), nothing is done to protect the deallocators from seeing that an exception has already been set. Any actions which a deallocator performs which may cause additional Python code to be executed may detect that an exception has been set. This can lead to misleading errors from the interpreter. The proper way to protect against this is to save a pending exception before performing the unsafe action, and restoring it when done. This can be done using the [`PyErr_Fetch()`](../c-api/exceptions.xhtml#c.PyErr_Fetch "PyErr_Fetch") and [`PyErr_Restore()`](../c-api/exceptions.xhtml#c.PyErr_Restore "PyErr_Restore") functions:
```
static void
my_dealloc(PyObject *obj)
{
MyObject *self = (MyObject *) obj;
PyObject *cbresult;
if (self->my_callback != NULL) {
PyObject *err_type, *err_value, *err_traceback;
/* This saves the current exception state */
PyErr_Fetch(&err_type, &err_value, &err_traceback);
cbresult = PyObject_CallObject(self->my_callback, NULL);
if (cbresult == NULL)
PyErr_WriteUnraisable(self->my_callback);
else
Py_DECREF(cbresult);
/* This restores the saved exception state */
PyErr_Restore(err_type, err_value, err_traceback);
Py_DECREF(self->my_callback);
}
Py_TYPE(obj)->tp_free((PyObject*)self);
}
```
注解
There are limitations to what you can safely do in a deallocator function. First, if your type supports garbage collection (using [`tp_traverse`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_traverse "PyTypeObject.tp_traverse")and/or [`tp_clear`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_clear "PyTypeObject.tp_clear")), some of the object's members can have been cleared or finalized by the time [`tp_dealloc`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_dealloc "PyTypeObject.tp_dealloc") is called. Second, in [`tp_dealloc`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_dealloc "PyTypeObject.tp_dealloc"), your object is in an unstable state: its reference count is equal to zero. Any call to a non-trivial object or API (as in the example above) might end up calling [`tp_dealloc`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_dealloc "PyTypeObject.tp_dealloc") again, causing a double free and a crash.
從 Python 3.4 開始,推薦不要在 [`tp_dealloc`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_dealloc "PyTypeObject.tp_dealloc") 放復雜的終結代碼,而是使用新的 [`tp_finalize`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_finalize "PyTypeObject.tp_finalize") 類型方法。
參見
[**PEP 442**](https://www.python.org/dev/peps/pep-0442) \[https://www.python.org/dev/peps/pep-0442\] 解釋了新的終結方案。
## 3.2. 對象展示
In Python, there are two ways to generate a textual representation of an object: the [`repr()`](../library/functions.xhtml#repr "repr") function, and the [`str()`](../library/stdtypes.xhtml#str "str") function. (The [`print()`](../library/functions.xhtml#print "print")function just calls [`str()`](../library/stdtypes.xhtml#str "str").) These handlers are both optional.
```
reprfunc tp_repr;
reprfunc tp_str;
```
The [`tp_repr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_repr "PyTypeObject.tp_repr") handler should return a string object containing a representation of the instance for which it is called. Here is a simple example:
```
static PyObject *
newdatatype_repr(newdatatypeobject * obj)
{
return PyUnicode_FromFormat("Repr-ified_newdatatype{{size:%d}}",
obj->obj_UnderlyingDatatypePtr->size);
}
```
If no [`tp_repr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_repr "PyTypeObject.tp_repr") handler is specified, the interpreter will supply a representation that uses the type's [`tp_name`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_name "PyTypeObject.tp_name") and a uniquely-identifying value for the object.
The [`tp_str`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_str "PyTypeObject.tp_str") handler is to [`str()`](../library/stdtypes.xhtml#str "str") what the [`tp_repr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_repr "PyTypeObject.tp_repr") handler described above is to [`repr()`](../library/functions.xhtml#repr "repr"); that is, it is called when Python code calls [`str()`](../library/stdtypes.xhtml#str "str") on an instance of your object. Its implementation is very similar to the [`tp_repr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_repr "PyTypeObject.tp_repr") function, but the resulting string is intended for human consumption. If [`tp_str`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_str "PyTypeObject.tp_str") is not specified, the [`tp_repr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_repr "PyTypeObject.tp_repr") handler is used instead.
Here is a simple example:
```
static PyObject *
newdatatype_str(newdatatypeobject * obj)
{
return PyUnicode_FromFormat("Stringified_newdatatype{{size:%d}}",
obj->obj_UnderlyingDatatypePtr->size);
}
```
## 3.3. Attribute Management
For every object which can support attributes, the corresponding type must provide the functions that control how the attributes are resolved. There needs to be a function which can retrieve attributes (if any are defined), and another to set attributes (if setting attributes is allowed). Removing an attribute is a special case, for which the new value passed to the handler is *NULL*.
Python supports two pairs of attribute handlers; a type that supports attributes only needs to implement the functions for one pair. The difference is that one pair takes the name of the attribute as a `char*`, while the other accepts a [`PyObject*`](../c-api/structures.xhtml#c.PyObject "PyObject"). Each type can use whichever pair makes more sense for the implementation's convenience.
```
getattrfunc tp_getattr; /* char * version */
setattrfunc tp_setattr;
/* ... */
getattrofunc tp_getattro; /* PyObject * version */
setattrofunc tp_setattro;
```
If accessing attributes of an object is always a simple operation (this will be explained shortly), there are generic implementations which can be used to provide the [`PyObject*`](../c-api/structures.xhtml#c.PyObject "PyObject") version of the attribute management functions. The actual need for type-specific attribute handlers almost completely disappeared starting with Python 2.2, though there are many examples which have not been updated to use some of the new generic mechanism that is available.
### 3.3.1. Generic Attribute Management
Most extension types only use *simple* attributes. So, what makes the attributes simple? There are only a couple of conditions that must be met:
1. The name of the attributes must be known when [`PyType_Ready()`](../c-api/type.xhtml#c.PyType_Ready "PyType_Ready") is called.
2. No special processing is needed to record that an attribute was looked up or set, nor do actions need to be taken based on the value.
Note that this list does not place any restrictions on the values of the attributes, when the values are computed, or how relevant data is stored.
When [`PyType_Ready()`](../c-api/type.xhtml#c.PyType_Ready "PyType_Ready") is called, it uses three tables referenced by the type object to create [descriptor](../glossary.xhtml#term-descriptor)s which are placed in the dictionary of the type object. Each descriptor controls access to one attribute of the instance object. Each of the tables is optional; if all three are *NULL*, instances of the type will only have attributes that are inherited from their base type, and should leave the [`tp_getattro`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_getattro "PyTypeObject.tp_getattro") and [`tp_setattro`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_setattro "PyTypeObject.tp_setattro") fields *NULL* as well, allowing the base type to handle attributes.
The tables are declared as three fields of the type object:
```
struct PyMethodDef *tp_methods;
struct PyMemberDef *tp_members;
struct PyGetSetDef *tp_getset;
```
If [`tp_methods`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_methods "PyTypeObject.tp_methods") is not *NULL*, it must refer to an array of [`PyMethodDef`](../c-api/structures.xhtml#c.PyMethodDef "PyMethodDef") structures. Each entry in the table is an instance of this structure:
```
typedef struct PyMethodDef {
const char *ml_name; /* method name */
PyCFunction ml_meth; /* implementation function */
int ml_flags; /* flags */
const char *ml_doc; /* docstring */
} PyMethodDef;
```
One entry should be defined for each method provided by the type; no entries are needed for methods inherited from a base type. One additional entry is needed at the end; it is a sentinel that marks the end of the array. The `ml_name` field of the sentinel must be *NULL*.
The second table is used to define attributes which map directly to data stored in the instance. A variety of primitive C types are supported, and access may be read-only or read-write. The structures in the table are defined as:
```
typedef struct PyMemberDef {
const char *name;
int type;
int offset;
int flags;
const char *doc;
} PyMemberDef;
```
For each entry in the table, a [descriptor](../glossary.xhtml#term-descriptor) will be constructed and added to the type which will be able to extract a value from the instance structure. The [`type`](../library/functions.xhtml#type "type") field should contain one of the type codes defined in the `structmember.h` header; the value will be used to determine how to convert Python values to and from C values. The `flags` field is used to store flags which control how the attribute can be accessed.
The following flag constants are defined in `structmember.h`; they may be combined using bitwise-OR.
常數
意義
`READONLY`
Never writable.
`READ_RESTRICTED`
Not readable in restricted mode.
`WRITE_RESTRICTED`
Not writable in restricted mode.
`RESTRICTED`
Not readable or writable in restricted mode.
An interesting advantage of using the [`tp_members`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_members "PyTypeObject.tp_members") table to build descriptors that are used at runtime is that any attribute defined this way can have an associated doc string simply by providing the text in the table. An application can use the introspection API to retrieve the descriptor from the class object, and get the doc string using its `__doc__` attribute.
As with the [`tp_methods`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_methods "PyTypeObject.tp_methods") table, a sentinel entry with a `name` value of *NULL* is required.
### 3.3.2. Type-specific Attribute Management
For simplicity, only the `char*` version will be demonstrated here; the type of the name parameter is the only difference between the `char*`and [`PyObject*`](../c-api/structures.xhtml#c.PyObject "PyObject") flavors of the interface. This example effectively does the same thing as the generic example above, but does not use the generic support added in Python 2.2. It explains how the handler functions are called, so that if you do need to extend their functionality, you'll understand what needs to be done.
The [`tp_getattr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_getattr "PyTypeObject.tp_getattr") handler is called when the object requires an attribute look-up. It is called in the same situations where the [`__getattr__()`](../reference/datamodel.xhtml#object.__getattr__ "object.__getattr__")method of a class would be called.
Here is an example:
```
static PyObject *
newdatatype_getattr(newdatatypeobject *obj, char *name)
{
if (strcmp(name, "data") == 0)
{
return PyLong_FromLong(obj->data);
}
PyErr_Format(PyExc_AttributeError,
"'%.50s' object has no attribute '%.400s'",
tp->tp_name, name);
return NULL;
}
```
The [`tp_setattr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_setattr "PyTypeObject.tp_setattr") handler is called when the [`__setattr__()`](../reference/datamodel.xhtml#object.__setattr__ "object.__setattr__") or [`__delattr__()`](../reference/datamodel.xhtml#object.__delattr__ "object.__delattr__") method of a class instance would be called. When an attribute should be deleted, the third parameter will be *NULL*. Here is an example that simply raises an exception; if this were really all you wanted, the [`tp_setattr`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_setattr "PyTypeObject.tp_setattr") handler should be set to *NULL*.
```
static int
newdatatype_setattr(newdatatypeobject *obj, char *name, PyObject *v)
{
PyErr_Format(PyExc_RuntimeError, "Read-only attribute: %s", name);
return -1;
}
```
## 3.4. Object Comparison
```
richcmpfunc tp_richcompare;
```
The [`tp_richcompare`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_richcompare "PyTypeObject.tp_richcompare") handler is called when comparisons are needed. It is analogous to the [rich comparison methods](../reference/datamodel.xhtml#richcmpfuncs), like [`__lt__()`](../reference/datamodel.xhtml#object.__lt__ "object.__lt__"), and also called by [`PyObject_RichCompare()`](../c-api/object.xhtml#c.PyObject_RichCompare "PyObject_RichCompare") and [`PyObject_RichCompareBool()`](../c-api/object.xhtml#c.PyObject_RichCompareBool "PyObject_RichCompareBool").
This function is called with two Python objects and the operator as arguments, where the operator is one of `Py_EQ`, `Py_NE`, `Py_LE`, `Py_GT`, `Py_LT` or `Py_GT`. It should compare the two objects with respect to the specified operator and return `Py_True` or `Py_False` if the comparison is successful, `Py_NotImplemented` to indicate that comparison is not implemented and the other object's comparison method should be tried, or *NULL*if an exception was set.
Here is a sample implementation, for a datatype that is considered equal if the size of an internal pointer is equal:
```
static PyObject *
newdatatype_richcmp(PyObject *obj1, PyObject *obj2, int op)
{
PyObject *result;
int c, size1, size2;
/* code to make sure that both arguments are of type
newdatatype omitted */
size1 = obj1->obj_UnderlyingDatatypePtr->size;
size2 = obj2->obj_UnderlyingDatatypePtr->size;
switch (op) {
case Py_LT: c = size1 < size2; break;
case Py_LE: c = size1 <= size2; break;
case Py_EQ: c = size1 == size2; break;
case Py_NE: c = size1 != size2; break;
case Py_GT: c = size1 > size2; break;
case Py_GE: c = size1 >= size2; break;
}
result = c ? Py_True : Py_False;
Py_INCREF(result);
return result;
}
```
## 3.5. Abstract Protocol Support
Python supports a variety of *abstract* 'protocols;' the specific interfaces provided to use these interfaces are documented in [抽象對象層](../c-api/abstract.xhtml#abstract).
A number of these abstract interfaces were defined early in the development of the Python implementation. In particular, the number, mapping, and sequence protocols have been part of Python since the beginning. Other protocols have been added over time. For protocols which depend on several handler routines from the type implementation, the older protocols have been defined as optional blocks of handlers referenced by the type object. For newer protocols there are additional slots in the main type object, with a flag bit being set to indicate that the slots are present and should be checked by the interpreter. (The flag bit does not indicate that the slot values are non-*NULL*. The flag may be set to indicate the presence of a slot, but a slot may still be unfilled.)
```
PyNumberMethods *tp_as_number;
PySequenceMethods *tp_as_sequence;
PyMappingMethods *tp_as_mapping;
```
If you wish your object to be able to act like a number, a sequence, or a mapping object, then you place the address of a structure that implements the C type [`PyNumberMethods`](../c-api/typeobj.xhtml#c.PyNumberMethods "PyNumberMethods"), [`PySequenceMethods`](../c-api/typeobj.xhtml#c.PySequenceMethods "PySequenceMethods"), or [`PyMappingMethods`](../c-api/typeobj.xhtml#c.PyMappingMethods "PyMappingMethods"), respectively. It is up to you to fill in this structure with appropriate values. You can find examples of the use of each of these in the `Objects` directory of the Python source distribution.
```
hashfunc tp_hash;
```
This function, if you choose to provide it, should return a hash number for an instance of your data type. Here is a simple example:
```
static Py_hash_t
newdatatype_hash(newdatatypeobject *obj)
{
Py_hash_t result;
result = obj->some_size + 32767 * obj->some_number;
if (result == -1)
result = -2;
return result;
}
```
`Py_hash_t` is a signed integer type with a platform-varying width. Returning `-1` from [`tp_hash`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_hash "PyTypeObject.tp_hash") indicates an error, which is why you should be careful to avoid returning it when hash computation is successful, as seen above.
```
ternaryfunc tp_call;
```
This function is called when an instance of your data type is "called", for example, if `obj1` is an instance of your data type and the Python script contains `obj1('hello')`, the [`tp_call`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_call "PyTypeObject.tp_call") handler is invoked.
This function takes three arguments:
1. *self* is the instance of the data type which is the subject of the call. If the call is `obj1('hello')`, then *self* is `obj1`.
2. *args* is a tuple containing the arguments to the call. You can use [`PyArg_ParseTuple()`](../c-api/arg.xhtml#c.PyArg_ParseTuple "PyArg_ParseTuple") to extract the arguments.
3. *kwds* is a dictionary of keyword arguments that were passed. If this is non-*NULL* and you support keyword arguments, use [`PyArg_ParseTupleAndKeywords()`](../c-api/arg.xhtml#c.PyArg_ParseTupleAndKeywords "PyArg_ParseTupleAndKeywords") to extract the arguments. If you do not want to support keyword arguments and this is non-*NULL*, raise a [`TypeError`](../library/exceptions.xhtml#TypeError "TypeError") with a message saying that keyword arguments are not supported.
Here is a toy `tp_call` implementation:
```
static PyObject *
newdatatype_call(newdatatypeobject *self, PyObject *args, PyObject *kwds)
{
PyObject *result;
const char *arg1;
const char *arg2;
const char *arg3;
if (!PyArg_ParseTuple(args, "sss:call", &arg1, &arg2, &arg3)) {
return NULL;
}
result = PyUnicode_FromFormat(
"Returning -- value: [%d] arg1: [%s] arg2: [%s] arg3: [%s]\n",
obj->obj_UnderlyingDatatypePtr->size,
arg1, arg2, arg3);
return result;
}
```
```
/* Iterators */
getiterfunc tp_iter;
iternextfunc tp_iternext;
```
These functions provide support for the iterator protocol. Both handlers take exactly one parameter, the instance for which they are being called, and return a new reference. In the case of an error, they should set an exception and return *NULL*. [`tp_iter`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iter "PyTypeObject.tp_iter") corresponds to the Python [`__iter__()`](../reference/datamodel.xhtml#object.__iter__ "object.__iter__") method, while [`tp_iternext`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iternext "PyTypeObject.tp_iternext")corresponds to the Python [`__next__()`](../library/stdtypes.xhtml#iterator.__next__ "iterator.__next__") method.
Any [iterable](../glossary.xhtml#term-iterable) object must implement the [`tp_iter`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iter "PyTypeObject.tp_iter")handler, which must return an [iterator](../glossary.xhtml#term-iterator) object. Here the same guidelines apply as for Python classes:
- For collections (such as lists and tuples) which can support multiple independent iterators, a new iterator should be created and returned by each call to [`tp_iter`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iter "PyTypeObject.tp_iter").
- Objects which can only be iterated over once (usually due to side effects of iteration, such as file objects) can implement [`tp_iter`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iter "PyTypeObject.tp_iter")by returning a new reference to themselves -- and should also therefore implement the [`tp_iternext`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iternext "PyTypeObject.tp_iternext") handler.
Any [iterator](../glossary.xhtml#term-iterator) object should implement both [`tp_iter`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iter "PyTypeObject.tp_iter")and [`tp_iternext`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iternext "PyTypeObject.tp_iternext"). An iterator's [`tp_iter`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iter "PyTypeObject.tp_iter") handler should return a new reference to the iterator. Its [`tp_iternext`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iternext "PyTypeObject.tp_iternext") handler should return a new reference to the next object in the iteration, if there is one. If the iteration has reached the end, [`tp_iternext`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iternext "PyTypeObject.tp_iternext")may return *NULL* without setting an exception, or it may set [`StopIteration`](../library/exceptions.xhtml#StopIteration "StopIteration") *in addition* to returning *NULL*; avoiding the exception can yield slightly better performance. If an actual error occurs, [`tp_iternext`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_iternext "PyTypeObject.tp_iternext") should always set an exception and return *NULL*.
## 3.6. Weak Reference Support
One of the goals of Python's weak reference implementation is to allow any type to participate in the weak reference mechanism without incurring the overhead on performance-critical objects (such as numbers).
參見
Documentation for the [`weakref`](../library/weakref.xhtml#module-weakref "weakref: Support for weak references and weak dictionaries.") module.
For an object to be weakly referencable, the extension type must do two things:
1. Include a [`PyObject*`](../c-api/structures.xhtml#c.PyObject "PyObject") field in the C object structure dedicated to the weak reference mechanism. The object's constructor should leave it *NULL* (which is automatic when using the default [`tp_alloc`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_alloc "PyTypeObject.tp_alloc")).
2. Set the [`tp_weaklistoffset`](../c-api/typeobj.xhtml#c.PyTypeObject.tp_weaklistoffset "PyTypeObject.tp_weaklistoffset") type member to the offset of the aforementioned field in the C object structure, so that the interpreter knows how to access and modify that field.
Concretely, here is how a trivial object structure would be augmented with the required field:
```
typedef struct {
PyObject_HEAD
PyObject *weakreflist; /* List of weak references */
} TrivialObject;
```
And the corresponding member in the statically-declared type object:
```
static PyTypeObject TrivialType = {
PyVarObject_HEAD_INIT(NULL, 0)
/* ... other members omitted for brevity ... */
.tp_weaklistoffset = offsetof(TrivialObject, weakreflist),
};
```
The only further addition is that `tp_dealloc` needs to clear any weak references (by calling `PyObject_ClearWeakRefs()`) if the field is non-*NULL*:
```
static void
Trivial_dealloc(TrivialObject *self)
{
/* Clear weakrefs first before calling any destructors */
if (self->weakreflist != NULL)
PyObject_ClearWeakRefs((PyObject *) self);
/* ... remainder of destruction code omitted for brevity ... */
Py_TYPE(self)->tp_free((PyObject *) self);
}
```
## 3.7. 更多建議
In order to learn how to implement any specific method for your new data type, get the [CPython](../glossary.xhtml#term-cpython) source code. Go to the `Objects` directory, then search the C source files for `tp_` plus the function you want (for example, `tp_richcompare`). You will find examples of the function you want to implement.
When you need to verify that an object is a concrete instance of the type you are implementing, use the [`PyObject_TypeCheck()`](../c-api/object.xhtml#c.PyObject_TypeCheck "PyObject_TypeCheck") function. A sample of its use might be something like the following:
```
if (!PyObject_TypeCheck(some_object, &MyType)) {
PyErr_SetString(PyExc_TypeError, "arg #1 not a mything");
return NULL;
}
```
參見
下載CPython源代碼版本。<https://www.python.org/downloads/source/>
GitHub上開發CPython源代碼的CPython項目。<https://github.com/python/cpython>
### 導航
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- Python 教程
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- stringprep — Internet String Preparation
- readline — GNU readline interface
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- 二進制數據服務
- struct — Interpret bytes as packed binary data
- codecs — Codec registry and base classes
- 數據類型
- datetime — 基礎日期/時間數據類型
- calendar — General calendar-related functions
- collections — 容器數據類型
- collections.abc — 容器的抽象基類
- heapq — 堆隊列算法
- bisect — Array bisection algorithm
- array — Efficient arrays of numeric values
- weakref — 弱引用
- types — Dynamic type creation and names for built-in types
- copy — 淺層 (shallow) 和深層 (deep) 復制操作
- pprint — 數據美化輸出
- reprlib — Alternate repr() implementation
- enum — Support for enumerations
- 數字和數學模塊
- numbers — 數字的抽象基類
- math — 數學函數
- cmath — Mathematical functions for complex numbers
- decimal — 十進制定點和浮點運算
- fractions — 分數
- random — 生成偽隨機數
- statistics — Mathematical statistics functions
- 函數式編程模塊
- itertools — 為高效循環而創建迭代器的函數
- functools — 高階函數和可調用對象上的操作
- operator — 標準運算符替代函數
- 文件和目錄訪問
- pathlib — 面向對象的文件系統路徑
- os.path — 常見路徑操作
- fileinput — Iterate over lines from multiple input streams
- stat — Interpreting stat() results
- filecmp — File and Directory Comparisons
- tempfile — Generate temporary files and directories
- glob — Unix style pathname pattern expansion
- fnmatch — Unix filename pattern matching
- linecache — Random access to text lines
- shutil — High-level file operations
- macpath — Mac OS 9 路徑操作函數
- 數據持久化
- pickle —— Python 對象序列化
- copyreg — Register pickle support functions
- shelve — Python object persistence
- marshal — Internal Python object serialization
- dbm — Interfaces to Unix “databases”
- sqlite3 — SQLite 數據庫 DB-API 2.0 接口模塊
- 數據壓縮和存檔
- zlib — 與 gzip 兼容的壓縮
- gzip — 對 gzip 格式的支持
- bz2 — 對 bzip2 壓縮算法的支持
- lzma — 用 LZMA 算法壓縮
- zipfile — 在 ZIP 歸檔中工作
- tarfile — Read and write tar archive files
- 文件格式
- csv — CSV 文件讀寫
- configparser — Configuration file parser
- netrc — netrc file processing
- xdrlib — Encode and decode XDR data
- plistlib — Generate and parse Mac OS X .plist files
- 加密服務
- hashlib — 安全哈希與消息摘要
- hmac — 基于密鑰的消息驗證
- secrets — Generate secure random numbers for managing secrets
- 通用操作系統服務
- os — 操作系統接口模塊
- io — 處理流的核心工具
- time — 時間的訪問和轉換
- argparse — 命令行選項、參數和子命令解析器
- getopt — C-style parser for command line options
- 模塊 logging — Python 的日志記錄工具
- logging.config — 日志記錄配置
- logging.handlers — Logging handlers
- getpass — 便攜式密碼輸入工具
- curses — 終端字符單元顯示的處理
- curses.textpad — Text input widget for curses programs
- curses.ascii — Utilities for ASCII characters
- curses.panel — A panel stack extension for curses
- platform — Access to underlying platform's identifying data
- errno — Standard errno system symbols
- ctypes — Python 的外部函數庫
- 并發執行
- threading — 基于線程的并行
- multiprocessing — 基于進程的并行
- concurrent 包
- concurrent.futures — 啟動并行任務
- subprocess — 子進程管理
- sched — 事件調度器
- queue — 一個同步的隊列類
- _thread — 底層多線程 API
- _dummy_thread — _thread 的替代模塊
- dummy_threading — 可直接替代 threading 模塊。
- contextvars — Context Variables
- Context Variables
- Manual Context Management
- asyncio support
- 網絡和進程間通信
- asyncio — 異步 I/O
- socket — 底層網絡接口
- ssl — TLS/SSL wrapper for socket objects
- select — Waiting for I/O completion
- selectors — 高級 I/O 復用庫
- asyncore — 異步socket處理器
- asynchat — 異步 socket 指令/響應 處理器
- signal — Set handlers for asynchronous events
- mmap — Memory-mapped file support
- 互聯網數據處理
- email — 電子郵件與 MIME 處理包
- json — JSON 編碼和解碼器
- mailcap — Mailcap file handling
- mailbox — Manipulate mailboxes in various formats
- mimetypes — Map filenames to MIME types
- base64 — Base16, Base32, Base64, Base85 數據編碼
- binhex — 對binhex4文件進行編碼和解碼
- binascii — 二進制和 ASCII 碼互轉
- quopri — Encode and decode MIME quoted-printable data
- uu — Encode and decode uuencode files
- 結構化標記處理工具
- html — 超文本標記語言支持
- html.parser — 簡單的 HTML 和 XHTML 解析器
- html.entities — HTML 一般實體的定義
- XML處理模塊
- xml.etree.ElementTree — The ElementTree XML API
- xml.dom — The Document Object Model API
- xml.dom.minidom — Minimal DOM implementation
- xml.dom.pulldom — Support for building partial DOM trees
- xml.sax — Support for SAX2 parsers
- xml.sax.handler — Base classes for SAX handlers
- xml.sax.saxutils — SAX Utilities
- xml.sax.xmlreader — Interface for XML parsers
- xml.parsers.expat — Fast XML parsing using Expat
- 互聯網協議和支持
- webbrowser — 方便的Web瀏覽器控制器
- cgi — Common Gateway Interface support
- cgitb — Traceback manager for CGI scripts
- wsgiref — WSGI Utilities and Reference Implementation
- urllib — URL 處理模塊
- urllib.request — 用于打開 URL 的可擴展庫
- urllib.response — Response classes used by urllib
- urllib.parse — Parse URLs into components
- urllib.error — Exception classes raised by urllib.request
- urllib.robotparser — Parser for robots.txt
- http — HTTP 模塊
- http.client — HTTP協議客戶端
- ftplib — FTP protocol client
- poplib — POP3 protocol client
- imaplib — IMAP4 protocol client
- nntplib — NNTP protocol client
- smtplib —SMTP協議客戶端
- smtpd — SMTP Server
- telnetlib — Telnet client
- uuid — UUID objects according to RFC 4122
- socketserver — A framework for network servers
- http.server — HTTP 服務器
- http.cookies — HTTP state management
- http.cookiejar — Cookie handling for HTTP clients
- xmlrpc — XMLRPC 服務端與客戶端模塊
- xmlrpc.client — XML-RPC client access
- xmlrpc.server — Basic XML-RPC servers
- ipaddress — IPv4/IPv6 manipulation library
- 多媒體服務
- audioop — Manipulate raw audio data
- aifc — Read and write AIFF and AIFC files
- sunau — 讀寫 Sun AU 文件
- wave — 讀寫WAV格式文件
- chunk — Read IFF chunked data
- colorsys — Conversions between color systems
- imghdr — 推測圖像類型
- sndhdr — 推測聲音文件的類型
- ossaudiodev — Access to OSS-compatible audio devices
- 國際化
- gettext — 多語種國際化服務
- locale — 國際化服務
- 程序框架
- turtle — 海龜繪圖
- cmd — 支持面向行的命令解釋器
- shlex — Simple lexical analysis
- Tk圖形用戶界面(GUI)
- tkinter — Tcl/Tk的Python接口
- tkinter.ttk — Tk themed widgets
- tkinter.tix — Extension widgets for Tk
- tkinter.scrolledtext — 滾動文字控件
- IDLE
- 其他圖形用戶界面(GUI)包
- 開發工具
- typing — 類型標注支持
- pydoc — Documentation generator and online help system
- doctest — Test interactive Python examples
- unittest — 單元測試框架
- unittest.mock — mock object library
- unittest.mock 上手指南
- 2to3 - 自動將 Python 2 代碼轉為 Python 3 代碼
- test — Regression tests package for Python
- test.support — Utilities for the Python test suite
- test.support.script_helper — Utilities for the Python execution tests
- 調試和分析
- bdb — Debugger framework
- faulthandler — Dump the Python traceback
- pdb — The Python Debugger
- The Python Profilers
- timeit — 測量小代碼片段的執行時間
- trace — Trace or track Python statement execution
- tracemalloc — Trace memory allocations
- 軟件打包和分發
- distutils — 構建和安裝 Python 模塊
- ensurepip — Bootstrapping the pip installer
- venv — 創建虛擬環境
- zipapp — Manage executable Python zip archives
- Python運行時服務
- sys — 系統相關的參數和函數
- sysconfig — Provide access to Python's configuration information
- builtins — 內建對象
- main — 頂層腳本環境
- warnings — Warning control
- dataclasses — 數據類
- contextlib — Utilities for with-statement contexts
- abc — 抽象基類
- atexit — 退出處理器
- traceback — Print or retrieve a stack traceback
- future — Future 語句定義
- gc — 垃圾回收器接口
- inspect — 檢查對象
- site — Site-specific configuration hook
- 自定義 Python 解釋器
- code — Interpreter base classes
- codeop — Compile Python code
- 導入模塊
- zipimport — Import modules from Zip archives
- pkgutil — Package extension utility
- modulefinder — 查找腳本使用的模塊
- runpy — Locating and executing Python modules
- importlib — The implementation of import
- Python 語言服務
- parser — Access Python parse trees
- ast — 抽象語法樹
- symtable — Access to the compiler's symbol tables
- symbol — 與 Python 解析樹一起使用的常量
- token — 與Python解析樹一起使用的常量
- keyword — 檢驗Python關鍵字
- tokenize — Tokenizer for Python source
- tabnanny — 模糊縮進檢測
- pyclbr — Python class browser support
- py_compile — Compile Python source files
- compileall — Byte-compile Python libraries
- dis — Python 字節碼反匯編器
- pickletools — Tools for pickle developers
- 雜項服務
- formatter — Generic output formatting
- Windows系統相關模塊
- msilib — Read and write Microsoft Installer files
- msvcrt — Useful routines from the MS VC++ runtime
- winreg — Windows 注冊表訪問
- winsound — Sound-playing interface for Windows
- Unix 專有服務
- posix — The most common POSIX system calls
- pwd — 用戶密碼數據庫
- spwd — The shadow password database
- grp — The group database
- crypt — Function to check Unix passwords
- termios — POSIX style tty control
- tty — 終端控制功能
- pty — Pseudo-terminal utilities
- fcntl — The fcntl and ioctl system calls
- pipes — Interface to shell pipelines
- resource — Resource usage information
- nis — Interface to Sun's NIS (Yellow Pages)
- Unix syslog 庫例程
- 被取代的模塊
- optparse — Parser for command line options
- imp — Access the import internals
- 未創建文檔的模塊
- 平臺特定模塊
- 擴展和嵌入 Python 解釋器
- 推薦的第三方工具
- 不使用第三方工具創建擴展
- 使用 C 或 C++ 擴展 Python
- 自定義擴展類型:教程
- 定義擴展類型:已分類主題
- 構建C/C++擴展
- 在Windows平臺編譯C和C++擴展
- 在更大的應用程序中嵌入 CPython 運行時
- Embedding Python in Another Application
- Python/C API 參考手冊
- 概述
- 代碼標準
- 包含文件
- 有用的宏
- 對象、類型和引用計數
- 異常
- 嵌入Python
- 調試構建
- 穩定的應用程序二進制接口
- The Very High Level Layer
- Reference Counting
- 異常處理
- Printing and clearing
- 拋出異常
- Issuing warnings
- Querying the error indicator
- Signal Handling
- Exception Classes
- Exception Objects
- Unicode Exception Objects
- Recursion Control
- 標準異常
- 標準警告類別
- 工具
- 操作系統實用程序
- 系統功能
- 過程控制
- 導入模塊
- Data marshalling support
- 語句解釋及變量編譯
- 字符串轉換與格式化
- 反射
- 編解碼器注冊與支持功能
- 抽象對象層
- Object Protocol
- 數字協議
- Sequence Protocol
- Mapping Protocol
- 迭代器協議
- 緩沖協議
- Old Buffer Protocol
- 具體的對象層
- 基本對象
- 數值對象
- 序列對象
- 容器對象
- 函數對象
- 其他對象
- Initialization, Finalization, and Threads
- 在Python初始化之前
- 全局配置變量
- Initializing and finalizing the interpreter
- Process-wide parameters
- Thread State and the Global Interpreter Lock
- Sub-interpreter support
- Asynchronous Notifications
- Profiling and Tracing
- Advanced Debugger Support
- Thread Local Storage Support
- 內存管理
- 概述
- 原始內存接口
- Memory Interface
- 對象分配器
- 默認內存分配器
- Customize Memory Allocators
- The pymalloc allocator
- tracemalloc C API
- 示例
- 對象實現支持
- 在堆中分配對象
- Common Object Structures
- Type 對象
- Number Object Structures
- Mapping Object Structures
- Sequence Object Structures
- Buffer Object Structures
- Async Object Structures
- 使對象類型支持循環垃圾回收
- API 和 ABI 版本管理
- 分發 Python 模塊
- 關鍵術語
- 開源許可與協作
- 安裝工具
- 閱讀指南
- 我該如何...?
- ...為我的項目選擇一個名字?
- ...創建和分發二進制擴展?
- 安裝 Python 模塊
- 關鍵術語
- 基本使用
- 我應如何 ...?
- ... 在 Python 3.4 之前的 Python 版本中安裝 pip ?
- ... 只為當前用戶安裝軟件包?
- ... 安裝科學計算類 Python 軟件包?
- ... 使用并行安裝的多個 Python 版本?
- 常見的安裝問題
- 在 Linux 的系統 Python 版本上安裝
- 未安裝 pip
- 安裝二進制編譯擴展
- Python 常用指引
- 將 Python 2 代碼遷移到 Python 3
- 簡要說明
- 詳情
- 將擴展模塊移植到 Python 3
- 條件編譯
- 對象API的更改
- 模塊初始化和狀態
- CObject 替換為 Capsule
- 其他選項
- Curses Programming with Python
- What is curses?
- Starting and ending a curses application
- Windows and Pads
- Displaying Text
- User Input
- For More Information
- 實現描述器
- 摘要
- 定義和簡介
- 描述器協議
- 發起調用描述符
- 描述符示例
- Properties
- 函數和方法
- Static Methods and Class Methods
- 函數式編程指引
- 概述
- 迭代器
- 生成器表達式和列表推導式
- 生成器
- 內置函數
- itertools 模塊
- The functools module
- Small functions and the lambda expression
- Revision History and Acknowledgements
- 引用文獻
- 日志 HOWTO
- 日志基礎教程
- 進階日志教程
- 日志級別
- 有用的處理程序
- 記錄日志中引發的異常
- 使用任意對象作為消息
- 優化
- 日志操作手冊
- 在多個模塊中使用日志
- 在多線程中使用日志
- 使用多個日志處理器和多種格式化
- 在多個地方記錄日志
- 日志服務器配置示例
- 處理日志處理器的阻塞
- Sending and receiving logging events across a network
- Adding contextual information to your logging output
- Logging to a single file from multiple processes
- Using file rotation
- Use of alternative formatting styles
- Customizing LogRecord
- Subclassing QueueHandler - a ZeroMQ example
- Subclassing QueueListener - a ZeroMQ example
- An example dictionary-based configuration
- Using a rotator and namer to customize log rotation processing
- A more elaborate multiprocessing example
- Inserting a BOM into messages sent to a SysLogHandler
- Implementing structured logging
- Customizing handlers with dictConfig()
- Using particular formatting styles throughout your application
- Configuring filters with dictConfig()
- Customized exception formatting
- Speaking logging messages
- Buffering logging messages and outputting them conditionally
- Formatting times using UTC (GMT) via configuration
- Using a context manager for selective logging
- 正則表達式HOWTO
- 概述
- 簡單模式
- 使用正則表達式
- 更多模式能力
- 修改字符串
- 常見問題
- 反饋
- 套接字編程指南
- 套接字
- 創建套接字
- 使用一個套接字
- 斷開連接
- 非阻塞的套接字
- 排序指南
- 基本排序
- 關鍵函數
- Operator 模塊函數
- 升序和降序
- 排序穩定性和排序復雜度
- 使用裝飾-排序-去裝飾的舊方法
- 使用 cmp 參數的舊方法
- 其它
- Unicode 指南
- Unicode 概述
- Python's Unicode Support
- Reading and Writing Unicode Data
- Acknowledgements
- 如何使用urllib包獲取網絡資源
- 概述
- Fetching URLs
- 處理異常
- info and geturl
- Openers and Handlers
- Basic Authentication
- Proxies
- Sockets and Layers
- 腳注
- Argparse 教程
- 概念
- 基礎
- 位置參數介紹
- Introducing Optional arguments
- Combining Positional and Optional arguments
- Getting a little more advanced
- Conclusion
- ipaddress模塊介紹
- 創建 Address/Network/Interface 對象
- 審查 Address/Network/Interface 對象
- Network 作為 Address 列表
- 比較
- 將IP地址與其他模塊一起使用
- 實例創建失敗時獲取更多詳細信息
- Argument Clinic How-To
- The Goals Of Argument Clinic
- Basic Concepts And Usage
- Converting Your First Function
- Advanced Topics
- 使用 DTrace 和 SystemTap 檢測CPython
- Enabling the static markers
- Static DTrace probes
- Static SystemTap markers
- Available static markers
- SystemTap Tapsets
- 示例
- Python 常見問題
- Python常見問題
- 一般信息
- 現實世界中的 Python
- 編程常見問題
- 一般問題
- 核心語言
- 數字和字符串
- 性能
- 序列(元組/列表)
- 對象
- 模塊
- 設計和歷史常見問題
- 為什么Python使用縮進來分組語句?
- 為什么簡單的算術運算得到奇怪的結果?
- 為什么浮點計算不準確?
- 為什么Python字符串是不可變的?
- 為什么必須在方法定義和調用中顯式使用“self”?
- 為什么不能在表達式中賦值?
- 為什么Python對某些功能(例如list.index())使用方法來實現,而其他功能(例如len(List))使用函數實現?
- 為什么 join()是一個字符串方法而不是列表或元組方法?
- 異常有多快?
- 為什么Python中沒有switch或case語句?
- 難道不能在解釋器中模擬線程,而非得依賴特定于操作系統的線程實現嗎?
- 為什么lambda表達式不能包含語句?
- 可以將Python編譯為機器代碼,C或其他語言嗎?
- Python如何管理內存?
- 為什么CPython不使用更傳統的垃圾回收方案?
- CPython退出時為什么不釋放所有內存?
- 為什么有單獨的元組和列表數據類型?
- 列表是如何在CPython中實現的?
- 字典是如何在CPython中實現的?
- 為什么字典key必須是不可變的?
- 為什么 list.sort() 沒有返回排序列表?
- 如何在Python中指定和實施接口規范?
- 為什么沒有goto?
- 為什么原始字符串(r-strings)不能以反斜杠結尾?
- 為什么Python沒有屬性賦值的“with”語句?
- 為什么 if/while/def/class語句需要冒號?
- 為什么Python在列表和元組的末尾允許使用逗號?
- 代碼庫和插件 FAQ
- 通用的代碼庫問題
- 通用任務
- 線程相關
- 輸入輸出
- 網絡 / Internet 編程
- 數據庫
- 數學和數字
- 擴展/嵌入常見問題
- 可以使用C語言中創建自己的函數嗎?
- 可以使用C++語言中創建自己的函數嗎?
- C很難寫,有沒有其他選擇?
- 如何從C執行任意Python語句?
- 如何從C中評估任意Python表達式?
- 如何從Python對象中提取C的值?
- 如何使用Py_BuildValue()創建任意長度的元組?
- 如何從C調用對象的方法?
- 如何捕獲PyErr_Print()(或打印到stdout / stderr的任何內容)的輸出?
- 如何從C訪問用Python編寫的模塊?
- 如何從Python接口到C ++對象?
- 我使用Setup文件添加了一個模塊,為什么make失敗了?
- 如何調試擴展?
- 我想在Linux系統上編譯一個Python模塊,但是缺少一些文件。為什么?
- 如何區分“輸入不完整”和“輸入無效”?
- 如何找到未定義的g++符號__builtin_new或__pure_virtual?
- 能否創建一個對象類,其中部分方法在C中實現,而其他方法在Python中實現(例如通過繼承)?
- Python在Windows上的常見問題
- 我怎樣在Windows下運行一個Python程序?
- 我怎么讓 Python 腳本可執行?
- 為什么有時候 Python 程序會啟動緩慢?
- 我怎樣使用Python腳本制作可執行文件?
- *.pyd 文件和DLL文件相同嗎?
- 我怎樣將Python嵌入一個Windows程序?
- 如何讓編輯器不要在我的 Python 源代碼中插入 tab ?
- 如何在不阻塞的情況下檢查按鍵?
- 圖形用戶界面(GUI)常見問題
- 圖形界面常見問題
- Python 是否有平臺無關的圖形界面工具包?
- 有哪些Python的GUI工具是某個平臺專用的?
- 有關Tkinter的問題
- “為什么我的電腦上安裝了 Python ?”
- 什么是Python?
- 為什么我的電腦上安裝了 Python ?
- 我能刪除 Python 嗎?
- 術語對照表
- 文檔說明
- Python 文檔貢獻者
- 解決 Bug
- 文檔錯誤
- 使用 Python 的錯誤追蹤系統
- 開始為 Python 貢獻您的知識
- 版權
- 歷史和許可證
- 軟件歷史
- 訪問Python或以其他方式使用Python的條款和條件
- Python 3.7.3 的 PSF 許可協議
- Python 2.0 的 BeOpen.com 許可協議
- Python 1.6.1 的 CNRI 許可協議
- Python 0.9.0 至 1.2 的 CWI 許可協議
- 集成軟件的許可和認可
- Mersenne Twister
- 套接字
- Asynchronous socket services
- Cookie management
- Execution tracing
- UUencode and UUdecode functions
- XML Remote Procedure Calls
- test_epoll
- Select kqueue
- SipHash24
- strtod and dtoa
- OpenSSL
- expat
- libffi
- zlib
- cfuhash
- libmpdec