gemeint hatte ich es etwa so:
Code: Alles auswählen
for i in range(len(buffer)):
run = False
if buffer[i].find('!') is not -1:
else if (buffer[i].find('<') is not -1):
wenn das nicht geht die Zeile:
durch das ersetzen:
wegen dem Bezeichner, bin mir nicht so sicher ob du wirklich einen Buffer benötigst, eigentlich könntest du auch jeden anderen Bezeichner verwenden um einfach eine Liste zu generieren. buffer ist ja ein Bezeichner für ein Buffer Object:
Python objects implemented in C can export a group of functions called the ``buffer interface.'' These functions can be used by an object to expose its data in a raw, byte-oriented format. Clients of the object can use the buffer interface to access the object data directly, without needing to copy it first.
Two examples of objects that support the buffer interface are strings and arrays. The string object exposes the character contents in the buffer interface's byte-oriented form. An array can also expose its contents, but it should be noted that array elements may be multi-byte values.
An example user of the buffer interface is the file object's write() method. Any object that can export a series of bytes through the buffer interface can be written to a file. There are a number of format codes to PyArg_ParseTuple() that operate against an object's buffer interface, returning data from the target object.
More information on the buffer interface is provided in the section ``Buffer Object Structures'' (section 10.7), under the description for PyBufferProcs .
A ``buffer object'' is defined in the bufferobject.h header (included by Python.h). These objects look very similar to string objects at the Python programming level: they support slicing, indexing, concatenation, and some other standard string operations. However, their data can come from one of two sources: from a block of memory, or from another object which exports the buffer interface.
Buffer objects are useful as a way to expose the data from another object's buffer interface to the Python programmer. They can also be used as a zero-copy slicing mechanism. Using their ability to reference a block of memory, it is possible to expose any data to the Python programmer quite easily. The memory could be a large, constant array in a C extension, it could be a raw block of memory for manipulation before passing to an operating system library, or it could be used to pass around structured data in its native, in-memory format.