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 <div class="section" id="introduction">
<h1>Introduction<a class="headerlink" href="#introduction" title="Permalink to this headline">¶</a></h1>
The Application Programmer&#8217;s Interface to Python gives C and C++ programmers
access to the Python interpreter at a variety of levels. The API is equally
usable from C++, but for brevity it is generally referred to as the Python/C
API. There are two fundamentally different reasons for using the Python/C API.
The first reason is to write extension modules for specific purposes; these
are C modules that extend the Python interpreter. This is probably the most
common use. The second reason is to use Python as a component in a larger
application; this technique is generally referred to as embedding Python
in an application.
Writing an extension module is a relatively well-understood process, where a
&#8220;cookbook&#8221; approach works well. There are several tools that automate the
process to some extent. While people have embedded Python in other
applications since its early existence, the process of embedding Python is less
straightforward than writing an extension.
Many API functions are useful independent of whether you&#8217;re embedding or
extending Python; moreover, most applications that embed Python will need to
provide a custom extension as well, so it&#8217;s probably a good idea to become
familiar with writing an extension before attempting to embed Python in a real
application.
<div class="section" id="include-files">
<h2>Include Files<a class="headerlink" href="#include-files" title="Permalink to this headline">¶</a></h2>
All function, type and macro definitions needed to use the Python/C API are
included in your code by the following line:
<div class="highlight-c"><div class="highlight"><pre>#include &quot;Python.h&quot;
</pre></div>
</div>
This implies inclusion of the following standard headers: <tt class="docutils literal">&lt;stdio.h&gt;</tt>,
<tt class="docutils literal">&lt;string.h&gt;</tt>, <tt class="docutils literal">&lt;errno.h&gt;</tt>, <tt class="docutils literal">&lt;limits.h&gt;</tt>, <tt class="docutils literal">&lt;assert.h&gt;</tt> and <tt class="docutils literal">&lt;stdlib.h&gt;</tt>
(if available).
<div class="admonition note">
Note
Since Python may define some pre-processor definitions which affect the standard
headers on some systems, you must include <tt class="file docutils literal">Python.h</tt> before any standard
headers are included.
</div>
All user visible names defined by Python.h (except those defined by the included
standard headers) have one of the prefixes <tt class="docutils literal">Py</tt> or <tt class="docutils literal">_Py</tt>. Names beginning
with <tt class="docutils literal">_Py</tt> are for internal use by the Python implementation and should not be
used by extension writers. Structure member names do not have a reserved prefix.
Important: user code should never define names that begin with <tt class="docutils literal">Py</tt> or
<tt class="docutils literal">_Py</tt>. This confuses the reader, and jeopardizes the portability of the user
code to future Python versions, which may define additional names beginning with
one of these prefixes.
The header files are typically installed with Python. On Unix, these are
located in the directories <tt class="file docutils literal">prefix/include/pythonversion/</tt> and
<tt class="file docutils literal">exec_prefix/include/pythonversion/</tt>, where <tt class="xref std std-envvar docutils literal">prefix</tt> and
<tt class="xref std std-envvar docutils literal">exec_prefix</tt> are defined by the corresponding parameters to Python&#8217;s
configure script and version is <tt class="docutils literal">sys.version[:3]</tt>. On Windows,
the headers are installed in <tt class="file docutils literal">prefix/include</tt>, where <tt class="xref std std-envvar docutils literal">prefix</tt> is
the installation directory specified to the installer.
To include the headers, place both directories (if different) on your compiler&#8217;s
search path for includes. Do not place the parent directories on the search
path and then use <tt class="docutils literal">#include &lt;pythonX.Y/Python.h&gt;</tt>; this will break on
multi-platform builds since the platform independent headers under
<tt class="xref std std-envvar docutils literal">prefix</tt> include the platform specific headers from
<tt class="xref std std-envvar docutils literal">exec_prefix</tt>.
C++ users should note that though the API is defined entirely using C, the
header files do properly declare the entry points to be <tt class="docutils literal">extern &quot;C&quot;</tt>, so there
is no need to do anything special to use the API from C++.
</div>
<div class="section" id="objects-types-and-reference-counts">
<h2>Objects, Types and Reference Counts<a class="headerlink" href="#objects-types-and-reference-counts" title="Permalink to this headline">¶</a></h2>
Most Python/C API functions have one or more arguments as well as a return value
of type <a class="reference internal" href="structures.html#PyObject" title="PyObject"><tt class="xref c c-type docutils literal">PyObject*</tt></a>. This type is a pointer to an opaque data type
representing an arbitrary Python object. Since all Python object types are
treated the same way by the Python language in most situations (e.g.,
assignments, scope rules, and argument passing), it is only fitting that they
should be represented by a single C type. Almost all Python objects live on the
heap: you never declare an automatic or static variable of type
<a class="reference internal" href="structures.html#PyObject" title="PyObject"><tt class="xref c c-type docutils literal">PyObject</tt></a>, only pointer variables of type <a class="reference internal" href="structures.html#PyObject" title="PyObject"><tt class="xref c c-type docutils literal">PyObject*</tt></a> can be
declared. The sole exception are the type objects; since these must never be
deallocated, they are typically static <a class="reference internal" href="type.html#PyTypeObject" title="PyTypeObject"><tt class="xref c c-type docutils literal">PyTypeObject</tt></a> objects.
All Python objects (even Python integers) have a type and a
reference count. An object&#8217;s type determines what kind of object it is
(e.g., an integer, a list, or a user-defined function; there are many more as
explained in <a class="reference internal" href="../reference/datamodel.html#types">The standard type hierarchy</a>). For each of the well-known types there is a macro
to check whether an object is of that type; for instance, <tt class="docutils literal">PyList_Check(a)</tt> is
true if (and only if) the object pointed to by a is a Python list.
<div class="section" id="reference-counts">
<h3>Reference Counts<a class="headerlink" href="#reference-counts" title="Permalink to this headline">¶</a></h3>
The reference count is important because today&#8217;s computers have a finite (and
often severely limited) memory size; it counts how many different places there
are that have a reference to an object. Such a place could be another object,
or a global (or static) C variable, or a local variable in some C function.
When an object&#8217;s reference count becomes zero, the object is deallocated. If
it contains references to other objects, their reference count is decremented.
Those other objects may be deallocated in turn, if this decrement makes their
reference count become zero, and so on. (There&#8217;s an obvious problem with
objects that reference each other here; for now, the solution is &#8220;don&#8217;t do
that.&#8221;)
Reference counts are always manipulated explicitly. The normal way is to use
the macro <a class="reference internal" href="refcounting.html#Py_INCREF" title="Py_INCREF"><tt class="xref c c-func docutils literal">Py_INCREF()</tt></a> to increment an object&#8217;s reference count by one,
and <a class="reference internal" href="refcounting.html#Py_DECREF" title="Py_DECREF"><tt class="xref c c-func docutils literal">Py_DECREF()</tt></a> to decrement it by one. The <a class="reference internal" href="refcounting.html#Py_DECREF" title="Py_DECREF"><tt class="xref c c-func docutils literal">Py_DECREF()</tt></a> macro
is considerably more complex than the incref one, since it must check whether
the reference count becomes zero and then cause the object&#8217;s deallocator to be
called. The deallocator is a function pointer contained in the object&#8217;s type
structure. The type-specific deallocator takes care of decrementing the
reference counts for other objects contained in the object if this is a compound
object type, such as a list, as well as performing any additional finalization
that&#8217;s needed. There&#8217;s no chance that the reference count can overflow; at
least as many bits are used to hold the reference count as there are distinct
memory locations in virtual memory (assuming <tt class="docutils literal">sizeof(Py_ssize_t) &gt;= sizeof(void*)</tt>).
Thus, the reference count increment is a simple operation.
It is not necessary to increment an object&#8217;s reference count for every local
variable that contains a pointer to an object. In theory, the object&#8217;s
reference count goes up by one when the variable is made to point to it and it
goes down by one when the variable goes out of scope. However, these two
cancel each other out, so at the end the reference count hasn&#8217;t changed. The
only real reason to use the reference count is to prevent the object from being
deallocated as long as our variable is pointing to it. If we know that there
is at least one other reference to the object that lives at least as long as
our variable, there is no need to increment the reference count temporarily.
An important situation where this arises is in objects that are passed as
arguments to C functions in an extension module that are called from Python;
the call mechanism guarantees to hold a reference to every argument for the
duration of the call.
However, a common pitfall is to extract an object from a list and hold on to it
for a while without incrementing its reference count. Some other operation might
conceivably remove the object from the list, decrementing its reference count
and possible deallocating it. The real danger is that innocent-looking
operations may invoke arbitrary Python code which could do this; there is a code
path which allows control to flow back to the user from a <a class="reference internal" href="refcounting.html#Py_DECREF" title="Py_DECREF"><tt class="xref c c-func docutils literal">Py_DECREF()</tt></a>, so
almost any operation is potentially dangerous.
A safe approach is to always use the generic operations (functions whose name
begins with <tt class="docutils literal">PyObject_</tt>, <tt class="docutils literal">PyNumber_</tt>, <tt class="docutils literal">PySequence_</tt> or <tt class="docutils literal">PyMapping_</tt>).
These operations always increment the reference count of the object they return.
This leaves the caller with the responsibility to call <a class="reference internal" href="refcounting.html#Py_DECREF" title="Py_DECREF"><tt class="xref c c-func docutils literal">Py_DECREF()</tt></a> when
they are done with the result; this soon becomes second nature.
<div class="section" id="reference-count-details">
<h4>Reference Count Details<a class="headerlink" href="#reference-count-details" title="Permalink to this headline">¶</a></h4>
The reference count behavior of functions in the Python/C API is best explained
in terms of ownership of references. Ownership pertains to references, never
to objects (objects are not owned: they are always shared). &#8220;Owning a
reference&#8221; means being responsible for calling Py_DECREF on it when the
reference is no longer needed. Ownership can also be transferred, meaning that
the code that receives ownership of the reference then becomes responsible for
eventually decref&#8217;ing it by calling <a class="reference internal" href="refcounting.html#Py_DECREF" title="Py_DECREF"><tt class="xref c c-func docutils literal">Py_DECREF()</tt></a> or <a class="reference internal" href="refcounting.html#Py_XDECREF" title="Py_XDECREF"><tt class="xref c c-func docutils literal">Py_XDECREF()</tt></a>
when it&#8217;s no longer needed&#8212;or passing on this responsibility (usually to its
caller). When a function passes ownership of a reference on to its caller, the
caller is said to receive a new reference. When no ownership is transferred,
the caller is said to borrow the reference. Nothing needs to be done for a
borrowed reference.
Conversely, when a calling function passes in a reference to an object, there
are two possibilities: the function steals a reference to the object, or it
does not. Stealing a reference means that when you pass a reference to a
function, that function assumes that it now owns that reference, and you are not
responsible for it any longer.
Few functions steal references; the two notable exceptions are
<a class="reference internal" href="list.html#PyList_SetItem" title="PyList_SetItem"><tt class="xref c c-func docutils literal">PyList_SetItem()</tt></a> and <a class="reference internal" href="tuple.html#PyTuple_SetItem" title="PyTuple_SetItem"><tt class="xref c c-func docutils literal">PyTuple_SetItem()</tt></a>, which steal a reference
to the item (but not to the tuple or list into which the item is put!). These
functions were designed to steal a reference because of a common idiom for
populating a tuple or list with newly created objects; for example, the code to
create the tuple <tt class="docutils literal">(1, 2, &quot;three&quot;)</tt> could look like this (forgetting about
error handling for the moment; a better way to code this is shown below):
<div class="highlight-c"><div class="highlight"><pre>PyObject *t;

t = PyTuple_New(3);
PyTuple_SetItem(t, 0, PyInt_FromLong(1L));
PyTuple_SetItem(t, 1, PyInt_FromLong(2L));
PyTuple_SetItem(t, 2, PyString_FromString(&quot;three&quot;));
</pre></div>
</div>
Here, <a class="reference internal" href="int.html#PyInt_FromLong" title="PyInt_FromLong"><tt class="xref c c-func docutils literal">PyInt_FromLong()</tt></a> returns a new reference which is immediately
stolen by <a class="reference internal" href="tuple.html#PyTuple_SetItem" title="PyTuple_SetItem"><tt class="xref c c-func docutils literal">PyTuple_SetItem()</tt></a>. When you want to keep using an object
although the reference to it will be stolen, use <a class="reference internal" href="refcounting.html#Py_INCREF" title="Py_INCREF"><tt class="xref c c-func docutils literal">Py_INCREF()</tt></a> to grab
another reference before calling the reference-stealing function.
Incidentally, <a class="reference internal" href="tuple.html#PyTuple_SetItem" title="PyTuple_SetItem"><tt class="xref c c-func docutils literal">PyTuple_SetItem()</tt></a> is the only way to set tuple items;
<a class="reference internal" href="sequence.html#PySequence_SetItem" title="PySequence_SetItem"><tt class="xref c c-func docutils literal">PySequence_SetItem()</tt></a> and <a class="reference internal" href="object.html#PyObject_SetItem" title="PyObject_SetItem"><tt class="xref c c-func docutils literal">PyObject_SetItem()</tt></a> refuse to do this
since tuples are an immutable data type. You should only use
<a class="reference internal" href="tuple.html#PyTuple_SetItem" title="PyTuple_SetItem"><tt class="xref c c-func docutils literal">PyTuple_SetItem()</tt></a> for tuples that you are creating yourself.
Equivalent code for populating a list can be written using <a class="reference internal" href="list.html#PyList_New" title="PyList_New"><tt class="xref c c-func docutils literal">PyList_New()</tt></a>
and <a class="reference internal" href="list.html#PyList_SetItem" title="PyList_SetItem"><tt class="xref c c-func docutils literal">PyList_SetItem()</tt></a>.
However, in practice, you will rarely use these ways of creating and populating
a tuple or list. There&#8217;s a generic function, <a class="reference internal" href="arg.html#Py_BuildValue" title="Py_BuildValue"><tt class="xref c c-func docutils literal">Py_BuildValue()</tt></a>, that can
create most common objects from C values, directed by a format string.
For example, the above two blocks of code could be replaced by the following
(which also takes care of the error checking):
<div class="highlight-c"><div class="highlight"><pre>PyObject *tuple, *list;

tuple = Py_BuildValue(&quot;(iis)&quot;, 1, 2, &quot;three&quot;);
list = Py_BuildValue(&quot;[iis]&quot;, 1, 2, &quot;three&quot;);
</pre></div>
</div>
It is much more common to use <a class="reference internal" href="object.html#PyObject_SetItem" title="PyObject_SetItem"><tt class="xref c c-func docutils literal">PyObject_SetItem()</tt></a> and friends with items
whose references you are only borrowing, like arguments that were passed in to
the function you are writing. In that case, their behaviour regarding reference
counts is much saner, since you don&#8217;t have to increment a reference count so you
can give a reference away (&#8220;have it be stolen&#8221;). For example, this function
sets all items of a list (actually, any mutable sequence) to a given item:
<div class="highlight-c"><div class="highlight"><pre>int
set_all(PyObject *target, PyObject *item)
{
 int i, n;

n = PyObject_Length(target);
 if (n &lt; 0)
 return -1;
 for (i = 0; i &lt; n; i++) {
 PyObject *index = PyInt_FromLong(i);
 if (!index)
 return -1;
 if (PyObject_SetItem(target, index, item) &lt; 0) {
 Py_DECREF(index);
 return -1;
 }
 Py_DECREF(index);
 }
 return 0;
}
</pre></div>
</div>
The situation is slightly different for function return values. While passing
a reference to most functions does not change your ownership responsibilities
for that reference, many functions that return a reference to an object give
you ownership of the reference. The reason is simple: in many cases, the
returned object is created on the fly, and the reference you get is the only
reference to the object. Therefore, the generic functions that return object
references, like <a class="reference internal" href="object.html#PyObject_GetItem" title="PyObject_GetItem"><tt class="xref c c-func docutils literal">PyObject_GetItem()</tt></a> and <a class="reference internal" href="sequence.html#PySequence_GetItem" title="PySequence_GetItem"><tt class="xref c c-func docutils literal">PySequence_GetItem()</tt></a>,
always return a new reference (the caller becomes the owner of the reference).
It is important to realize that whether you own a reference returned by a
function depends on which function you call only &#8212; the plumage (the type of
the object passed as an argument to the function) doesn&#8217;t enter into it!
Thus, if you extract an item from a list using <a class="reference internal" href="list.html#PyList_GetItem" title="PyList_GetItem"><tt class="xref c c-func docutils literal">PyList_GetItem()</tt></a>, you
don&#8217;t own the reference &#8212; but if you obtain the same item from the same list
using <a class="reference internal" href="sequence.html#PySequence_GetItem" title="PySequence_GetItem"><tt class="xref c c-func docutils literal">PySequence_GetItem()</tt></a> (which happens to take exactly the same
arguments), you do own a reference to the returned object.
Here is an example of how you could write a function that computes the sum of
the items in a list of integers; once using <a class="reference internal" href="list.html#PyList_GetItem" title="PyList_GetItem"><tt class="xref c c-func docutils literal">PyList_GetItem()</tt></a>, and once
using <a class="reference internal" href="sequence.html#PySequence_GetItem" title="PySequence_GetItem"><tt class="xref c c-func docutils literal">PySequence_GetItem()</tt></a>.
<div class="highlight-c"><div class="highlight"><pre>long
sum_list(PyObject *list)
{
 int i, n;
 long total = 0;
 PyObject *item;

n = PyList_Size(list);
 if (n &lt; 0)
 return -1; /* Not a list */
 for (i = 0; i &lt; n; i++) {
 item = PyList_GetItem(list, i); /* Can&#39;t fail */
 if (!PyInt_Check(item)) continue; /* Skip non-integers */
 total += PyInt_AsLong(item);
 }
 return total;
}
</pre></div>
</div>
<div class="highlight-c" id="index-10"><div class="highlight"><pre>long
sum_sequence(PyObject *sequence)
{
 int i, n;
 long total = 0;
 PyObject *item;
 n = PySequence_Length(sequence);
 if (n &lt; 0)
 return -1; /* Has no length */
 for (i = 0; i &lt; n; i++) {
 item = PySequence_GetItem(sequence, i);
 if (item == NULL)
 return -1; /* Not a sequence, or other failure */
 if (PyInt_Check(item))
 total += PyInt_AsLong(item);
 Py_DECREF(item); /* Discard reference ownership */
 }
 return total;
}
</pre></div>
</div>
</div>
</div>
<div class="section" id="types">
<h3>Types<a class="headerlink" href="#types" title="Permalink to this headline">¶</a></h3>
There are few other data types that play a significant role in the Python/C
API; most are simple C types such as <tt class="xref c c-type docutils literal">int</tt>, <tt class="xref c c-type docutils literal">long</tt>,
<tt class="xref c c-type docutils literal">double</tt> and <tt class="xref c c-type docutils literal">char*</tt>. A few structure types are used to
describe static tables used to list the functions exported by a module or the
data attributes of a new object type, and another is used to describe the value
of a complex number. These will be discussed together with the functions that
use them.
</div>
</div>
<div class="section" id="exceptions">
<h2>Exceptions<a class="headerlink" href="#exceptions" title="Permalink to this headline">¶</a></h2>
The Python programmer only needs to deal with exceptions if specific error
handling is required; unhandled exceptions are automatically propagated to the
caller, then to the caller&#8217;s caller, and so on, until they reach the top-level
interpreter, where they are reported to the user accompanied by a stack
traceback.
For C programmers, however, error checking always has to be explicit. All
functions in the Python/C API can raise exceptions, unless an explicit claim is
made otherwise in a function&#8217;s documentation. In general, when a function
encounters an error, it sets an exception, discards any object references that
it owns, and returns an error indicator. If not documented otherwise, this
indicator is either NULL or <tt class="docutils literal">-1</tt>, depending on the function&#8217;s return type.
A few functions return a Boolean true/false result, with false indicating an
error. Very few functions return no explicit error indicator or have an
ambiguous return value, and require explicit testing for errors with
<a class="reference internal" href="exceptions.html#PyErr_Occurred" title="PyErr_Occurred"><tt class="xref c c-func docutils literal">PyErr_Occurred()</tt></a>. These exceptions are always explicitly documented.
Exception state is maintained in per-thread storage (this is equivalent to
using global storage in an unthreaded application). A thread can be in one of
two states: an exception has occurred, or not. The function
<a class="reference internal" href="exceptions.html#PyErr_Occurred" title="PyErr_Occurred"><tt class="xref c c-func docutils literal">PyErr_Occurred()</tt></a> can be used to check for this: it returns a borrowed
reference to the exception type object when an exception has occurred, and
NULL otherwise. There are a number of functions to set the exception state:
<a class="reference internal" href="exceptions.html#PyErr_SetString" title="PyErr_SetString"><tt class="xref c c-func docutils literal">PyErr_SetString()</tt></a> is the most common (though not the most general)
function to set the exception state, and <a class="reference internal" href="exceptions.html#PyErr_Clear" title="PyErr_Clear"><tt class="xref c c-func docutils literal">PyErr_Clear()</tt></a> clears the
exception state.
The full exception state consists of three objects (all of which can be
NULL): the exception type, the corresponding exception value, and the
traceback. These have the same meanings as the Python objects
<tt class="docutils literal">sys.exc_type</tt>, <tt class="docutils literal">sys.exc_value</tt>, and <tt class="docutils literal">sys.exc_traceback</tt>; however, they
are not the same: the Python objects represent the last exception being handled
by a Python <a class="reference internal" href="../reference/compound_stmts.html#try"><tt class="xref std std-keyword docutils literal">try</tt></a> ... <a class="reference internal" href="../reference/compound_stmts.html#except"><tt class="xref std std-keyword docutils literal">except</tt></a> statement, while the C level
exception state only exists while an exception is being passed on between C
functions until it reaches the Python bytecode interpreter&#8217;s main loop, which
takes care of transferring it to <tt class="docutils literal">sys.exc_type</tt> and friends.
Note that starting with Python 1.5, the preferred, thread-safe way to access the
exception state from Python code is to call the function <a class="reference internal" href="../library/sys.html#sys.exc_info" title="sys.exc_info"><tt class="xref py py-func docutils literal">sys.exc_info()</tt></a>,
which returns the per-thread exception state for Python code. Also, the
semantics of both ways to access the exception state have changed so that a
function which catches an exception will save and restore its thread&#8217;s exception
state so as to preserve the exception state of its caller. This prevents common
bugs in exception handling code caused by an innocent-looking function
overwriting the exception being handled; it also reduces the often unwanted
lifetime extension for objects that are referenced by the stack frames in the
traceback.
As a general principle, a function that calls another function to perform some
task should check whether the called function raised an exception, and if so,
pass the exception state on to its caller. It should discard any object
references that it owns, and return an error indicator, but it should not set
another exception &#8212; that would overwrite the exception that was just raised,
and lose important information about the exact cause of the error.
A simple example of detecting exceptions and passing them on is shown in the
<tt class="xref c c-func docutils literal">sum_sequence()</tt> example above. It so happens that this example doesn&#8217;t
need to clean up any owned references when it detects an error. The following
example function shows some error cleanup. First, to remind you why you like
Python, we show the equivalent Python code:
<div class="highlight-c"><div class="highlight"><pre>def incr_item(dict, key):
 try:
 item = dict[key]
 except KeyError:
 item = 0
 dict[key] = item + 1
</pre></div>
</div>
Here is the corresponding C code, in all its glory:
<div class="highlight-c"><div class="highlight"><pre>int
incr_item(PyObject *dict, PyObject *key)
{
 /* Objects all initialized to NULL for Py_XDECREF */
 PyObject *item = NULL, *const_one = NULL, *incremented_item = NULL;
 int rv = -1; /* Return value initialized to -1 (failure) */

item = PyObject_GetItem(dict, key);
 if (item == NULL) {
 /* Handle KeyError only: */
 if (!PyErr_ExceptionMatches(PyExc_KeyError))
 goto error;

/* Clear the error and use zero: */
 PyErr_Clear();
 item = PyInt_FromLong(0L);
 if (item == NULL)
 goto error;
 }
 const_one = PyInt_FromLong(1L);
 if (const_one == NULL)
 goto error;

incremented_item = PyNumber_Add(item, const_one);
 if (incremented_item == NULL)
 goto error;

if (PyObject_SetItem(dict, key, incremented_item) &lt; 0)
 goto error;
 rv = 0; /* Success */
 /* Continue with cleanup code */

error:
 /* Cleanup code, shared by success and failure path */

/* Use Py_XDECREF() to ignore NULL references */
 Py_XDECREF(item);
 Py_XDECREF(const_one);
 Py_XDECREF(incremented_item);

return rv; /* -1 for error, 0 for success */
}
</pre></div>
</div>
This example represents an endorsed use of the <tt class="docutils literal">goto</tt> statement in C!
It illustrates the use of <a class="reference internal" href="exceptions.html#PyErr_ExceptionMatches" title="PyErr_ExceptionMatches"><tt class="xref c c-func docutils literal">PyErr_ExceptionMatches()</tt></a> and
<a class="reference internal" href="exceptions.html#PyErr_Clear" title="PyErr_Clear"><tt class="xref c c-func docutils literal">PyErr_Clear()</tt></a> to handle specific exceptions, and the use of
<a class="reference internal" href="refcounting.html#Py_XDECREF" title="Py_XDECREF"><tt class="xref c c-func docutils literal">Py_XDECREF()</tt></a> to dispose of owned references that may be NULL (note the
<tt class="docutils literal">'X'</tt> in the name; <a class="reference internal" href="refcounting.html#Py_DECREF" title="Py_DECREF"><tt class="xref c c-func docutils literal">Py_DECREF()</tt></a> would crash when confronted with a
NULL reference). It is important that the variables used to hold owned
references are initialized to NULL for this to work; likewise, the proposed
return value is initialized to <tt class="docutils literal">-1</tt> (failure) and only set to success after
the final call made is successful.
</div>
<div class="section" id="embedding-python">
<h2>Embedding Python<a class="headerlink" href="#embedding-python" title="Permalink to this headline">¶</a></h2>
The one important task that only embedders (as opposed to extension writers) of
the Python interpreter have to worry about is the initialization, and possibly
the finalization, of the Python interpreter. Most functionality of the
interpreter can only be used after the interpreter has been initialized.
The basic initialization function is <a class="reference internal" href="init.html#Py_Initialize" title="Py_Initialize"><tt class="xref c c-func docutils literal">Py_Initialize()</tt></a>. This initializes
the table of loaded modules, and creates the fundamental modules
<a class="reference internal" href="../library/__builtin__.html#module-__builtin__" title="__builtin__: The module that provides the built-in namespace."><tt class="xref py py-mod docutils literal">__builtin__</tt></a>, <a class="reference internal" href="../library/__main__.html#module-__main__" title="__main__: The environment where the top-level script is run."><tt class="xref py py-mod docutils literal">__main__</tt></a>, <a class="reference internal" href="../library/sys.html#module-sys" title="sys: Access system-specific parameters and functions."><tt class="xref py py-mod docutils literal">sys</tt></a>, and <a class="reference internal" href="../library/exceptions.html#module-exceptions" title="exceptions: Standard exception classes."><tt class="xref py py-mod docutils literal">exceptions</tt></a>. It also
initializes the module search path (<tt class="docutils literal">sys.path</tt>).
<a class="reference internal" href="init.html#Py_Initialize" title="Py_Initialize"><tt class="xref c c-func docutils literal">Py_Initialize()</tt></a> does not set the &#8220;script argument list&#8221; (<tt class="docutils literal">sys.argv</tt>).
If this variable is needed by Python code that will be executed later, it must
be set explicitly with a call to <tt class="docutils literal">PySys_SetArgvEx(argc, argv, updatepath)</tt>
after the call to <a class="reference internal" href="init.html#Py_Initialize" title="Py_Initialize"><tt class="xref c c-func docutils literal">Py_Initialize()</tt></a>.
On most systems (in particular, on Unix and Windows, although the details are
slightly different), <a class="reference internal" href="init.html#Py_Initialize" title="Py_Initialize"><tt class="xref c c-func docutils literal">Py_Initialize()</tt></a> calculates the module search path
based upon its best guess for the location of the standard Python interpreter
executable, assuming that the Python library is found in a fixed location
relative to the Python interpreter executable. In particular, it looks for a
directory named <tt class="file docutils literal">lib/pythonX.Y</tt> relative to the parent directory
where the executable named <tt class="file docutils literal">python</tt> is found on the shell command search
path (the environment variable <tt class="xref std std-envvar docutils literal">PATH</tt>).
For instance, if the Python executable is found in
<tt class="file docutils literal">/usr/local/bin/python</tt>, it will assume that the libraries are in
<tt class="file docutils literal">/usr/local/lib/pythonX.Y</tt>. (In fact, this particular path is also
the &#8220;fallback&#8221; location, used when no executable file named <tt class="file docutils literal">python</tt> is
found along <tt class="xref std std-envvar docutils literal">PATH</tt>.) The user can override this behavior by setting the
environment variable <a class="reference internal" href="../using/cmdline.html#envvar-PYTHONHOME"><tt class="xref std std-envvar docutils literal">PYTHONHOME</tt></a>, or insert additional directories in
front of the standard path by setting <a class="reference internal" href="../using/cmdline.html#envvar-PYTHONPATH"><tt class="xref std std-envvar docutils literal">PYTHONPATH</tt></a>.
The embedding application can steer the search by calling
<tt class="docutils literal">Py_SetProgramName(file)</tt> before calling <a class="reference internal" href="init.html#Py_Initialize" title="Py_Initialize"><tt class="xref c c-func docutils literal">Py_Initialize()</tt></a>. Note that
<a class="reference internal" href="../using/cmdline.html#envvar-PYTHONHOME"><tt class="xref std std-envvar docutils literal">PYTHONHOME</tt></a> still overrides this and <a class="reference internal" href="../using/cmdline.html#envvar-PYTHONPATH"><tt class="xref std std-envvar docutils literal">PYTHONPATH</tt></a> is still
inserted in front of the standard path. An application that requires total
control has to provide its own implementation of <a class="reference internal" href="init.html#Py_GetPath" title="Py_GetPath"><tt class="xref c c-func docutils literal">Py_GetPath()</tt></a>,
<a class="reference internal" href="init.html#Py_GetPrefix" title="Py_GetPrefix"><tt class="xref c c-func docutils literal">Py_GetPrefix()</tt></a>, <a class="reference internal" href="init.html#Py_GetExecPrefix" title="Py_GetExecPrefix"><tt class="xref c c-func docutils literal">Py_GetExecPrefix()</tt></a>, and
<a class="reference internal" href="init.html#Py_GetProgramFullPath" title="Py_GetProgramFullPath"><tt class="xref c c-func docutils literal">Py_GetProgramFullPath()</tt></a> (all defined in <tt class="file docutils literal">Modules/getpath.c</tt>).
Sometimes, it is desirable to &#8220;uninitialize&#8221; Python. For instance, the
application may want to start over (make another call to
<a class="reference internal" href="init.html#Py_Initialize" title="Py_Initialize"><tt class="xref c c-func docutils literal">Py_Initialize()</tt></a>) or the application is simply done with its use of
Python and wants to free memory allocated by Python. This can be accomplished
by calling <a class="reference internal" href="init.html#Py_Finalize" title="Py_Finalize"><tt class="xref c c-func docutils literal">Py_Finalize()</tt></a>. The function <a class="reference internal" href="init.html#Py_IsInitialized" title="Py_IsInitialized"><tt class="xref c c-func docutils literal">Py_IsInitialized()</tt></a> returns
true if Python is currently in the initialized state. More information about
these functions is given in a later chapter. Notice that <a class="reference internal" href="init.html#Py_Finalize" title="Py_Finalize"><tt class="xref c c-func docutils literal">Py_Finalize()</tt></a>
does not free all memory allocated by the Python interpreter, e.g. memory
allocated by extension modules currently cannot be released.
</div>
<div class="section" id="debugging-builds">
<h2>Debugging Builds<a class="headerlink" href="#debugging-builds" title="Permalink to this headline">¶</a></h2>
Python can be built with several macros to enable extra checks of the
interpreter and extension modules. These checks tend to add a large amount of
overhead to the runtime so they are not enabled by default.
A full list of the various types of debugging builds is in the file
<tt class="file docutils literal">Misc/SpecialBuilds.txt</tt> in the Python source distribution. Builds are
available that support tracing of reference counts, debugging the memory
allocator, or low-level profiling of the main interpreter loop. Only the most
frequently-used builds will be described in the remainder of this section.
Compiling the interpreter with the <tt class="xref c c-macro docutils literal">Py_DEBUG</tt> macro defined produces
what is generally meant by &#8220;a debug build&#8221; of Python. <tt class="xref c c-macro docutils literal">Py_DEBUG</tt> is
enabled in the Unix build by adding <tt class="docutils literal">--with-pydebug</tt> to the
<tt class="file docutils literal">./configure</tt> command. It is also implied by the presence of the
not-Python-specific <tt class="xref c c-macro docutils literal">_DEBUG</tt> macro. When <tt class="xref c c-macro docutils literal">Py_DEBUG</tt> is enabled
in the Unix build, compiler optimization is disabled.
In addition to the reference count debugging described below, the following
extra checks are performed:
<ul class="simple">
<li>Extra checks are added to the object allocator.</li>
<li>Extra checks are added to the parser and compiler.</li>
<li>Downcasts from wide types to narrow types are checked for loss of information.</li>
<li>A number of assertions are added to the dictionary and set implementations.
In addition, the set object acquires a <tt class="xref py py-meth docutils literal">test_c_api()</tt> method.</li>
<li>Sanity checks of the input arguments are added to frame creation.</li>
<li>The storage for long ints is initialized with a known invalid pattern to catch
reference to uninitialized digits.</li>
<li>Low-level tracing and extra exception checking are added to the runtime
virtual machine.</li>
<li>Extra checks are added to the memory arena implementation.</li>
<li>Extra debugging is added to the thread module.</li>
</ul>
There may be additional checks not mentioned here.
Defining <tt class="xref c c-macro docutils literal">Py_TRACE_REFS</tt> enables reference tracing. When defined, a
circular doubly linked list of active objects is maintained by adding two extra
fields to every <a class="reference internal" href="structures.html#PyObject" title="PyObject"><tt class="xref c c-type docutils literal">PyObject</tt></a>. Total allocations are tracked as well. Upon
exit, all existing references are printed. (In interactive mode this happens
after every statement run by the interpreter.) Implied by <tt class="xref c c-macro docutils literal">Py_DEBUG</tt>.
Please refer to <tt class="file docutils literal">Misc/SpecialBuilds.txt</tt> in the Python source distribution
for more detailed information.
</div>
</div>

</div>
 </div>
 </div>
 <div class="sphinxsidebar">
 <div class="sphinxsidebarwrapper">
 <h3><a href="../contents.html">Table Of Contents</a></h3>
 <ul>
<li><a class="reference internal" href="#">Introduction</a><ul>
<li><a class="reference internal" href="#include-files">Include Files</a></li>
<li><a class="reference internal" href="#objects-types-and-reference-counts">Objects, Types and Reference Counts</a><ul>
<li><a class="reference internal" href="#reference-counts">Reference Counts</a><ul>
<li><a class="reference internal" href="#reference-count-details">Reference Count Details</a></li>
</ul>
</li>
<li><a class="reference internal" href="#types">Types</a></li>
</ul>
</li>
<li><a class="reference internal" href="#exceptions">Exceptions</a></li>
<li><a class="reference internal" href="#embedding-python">Embedding Python</a></li>
<li><a class="reference internal" href="#debugging-builds">Debugging Builds</a></li>
</ul>
</li>
</ul>

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