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List:       pypy-svn
Subject:    [pypy-svn] r78627 - pypy/extradoc/talk/pycon2011
From:       agaynor () codespeak ! net
Date:       2010-10-31 16:04:44
Message-ID: 20101031160444.94ACB282BE3 () codespeak ! net
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Author: agaynor
Date: Sun Oct 31 17:04:42 2010
New Revision: 78627

Modified:
   pypy/extradoc/talk/pycon2011/pypy-optimizations.txt
Log:
Random grammar and typo fixes.


Modified: pypy/extradoc/talk/pycon2011/pypy-optimizations.txt
==============================================================================
--- pypy/extradoc/talk/pycon2011/pypy-optimizations.txt	(original)
+++ pypy/extradoc/talk/pycon2011/pypy-optimizations.txt	Sun Oct 31 17:04:42 2010
@@ -14,17 +14,16 @@
 Classification: Discuss in depth
 Abstract:
 
-The talk will explain a bit in details how a python interpreter
-internally and why some operations are costly. We'll go through several
-python features, how the work, why they're slow in CPython and how we're
-fixing it.
+The talk will explain a bit in details how a python interpreter works
+internally and why some operations are costly. We'll go through several python
+features, how they work, why they're slow in CPython and how we're fixing it.
 
 The list of mentioned features is not exhaustive, however we will try to
 focus at least on the following:
 
-* Dynamic language - In Python code we have no known types, like a statically typed
-  language.  Even operations like "a + b" can do anything, unless we know more
-  about the code, especially associated types.
+* Dynamic language - In Python code we have no known types, like a statically
+  typed language.  Even operations like "a + b" can do anything, unless we know
+  more about the code, especially associated types.
 
 * Frame introspection - Frame objects need to be allocated for every function
   call, and all local variables are stored on the frame, and must be accessible
@@ -41,10 +40,10 @@
   (except more PyPy specific) called map dictionaries. XXX type versions?
 
 * FFI calls - calling C from Python is costly and hard to optimize. In PyPy we
-  decided to go via ctypes, this part will explain how are we going to handle
-  ctypes calls to be fast.
+  expse C APIs to Python code via ctypes, this part will explain how are we
+  going to handle ctypes calls to be fast.
 
-* `array` module - users of the CPython's array module probably know it can save
+* `array` module - users of CPython's array module probably know it can save
   them quite a bit of memory, however it's also slower than using a list, due
   to the overhead of boxing and unboxing on every operations. Here we will tie
   everything together and describe how the ``array`` module is much faster with
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