Results 4,151–4,160 of 5,623 for /devel/.(0.003 seconds)
Enables code to run as a daemon process on Unix-like systems
daemonize is a library for writing system daemons in Python.
Resource library for Python developers to create daemon processes
Daemons is a resource library for Python developers that want to create daemon
processes. The idea is to provide the basic daemon functionality while still
giving the developer the ability to customize their daemon for any purpose.
Database abstraction layer for Python
PyDal is a database abstraction layer for Python. It provides a DBAPI 2.0
wrapper for DBAPI 2.0 drivers. Sounds strange, but even drivers that fully
conform to the DBAPI can differ enough to make building database independent
applications difficult. Two major abstractions handled by PyDal are
paramstyles and datetime objects. PyDal makes it possible to use the same
paramstyle and datetime types with any module that conforms to DBAPI 2.0.
In addition, paramstyles and datetime types are configurable.
Tools to analyze security characteristics of MS OLE2 files
Python tools to analyze security characteristics of MS OLE2 files (also called
Structured Storage, Compound File Binary Format or Compound Document File
Format), such as Microsoft Office documents, for Malware Analysis and Incident
Response.
Simple dictionary with LRU behaviour in Python
A LRUDict is basically a simple dictionary, which has a defined
maximum capacity, that may be supplied at construction time, or
modified at run-time via the capacity property:
>>> cache = LRUDict(1)
>>> cache.capacity
1
Extensions to the standard Python datetime module
The dateutil module provides powerful extensions to the standard
datetime module.
Collection of Python deprecation patterns and strategies
A collection of Python deprecation patterns and strategies that help you
collect your technical debt in a non-destructive manner.
The goal of this library is to provide well documented developer facing
deprecation patterns that start of with a basic set and can expand into
a larger set of patterns as time goes on. The desired output of these
patterns is to apply the warnings module to emit DeprecationWarning or
PendingDeprecationWarning or similar derivative to developers using
libraries (or potentially applications) about future deprecations.
Python bindings for ORBit2
To paraphrase the README:
This is a Python language binding for the ORBit2 CORBA implementation.
It aims to take advantage of new features found in ORBit2 to make
language bindings more efficient. This includes:
- Use of ORBit2 type libraries to generate stubs
- use of the ORBit_small_invoke_stub() call for operation
invocation, which allows for short circuited invocation on local
objects.
Drop-in substitute for Py2.7's new collections
Drop-in substitute for Py2.7's new collections.OrderedDict. The
recipe has big-oh performance that matches regular dictionaries
(amortized O(1) insertion/deletion/lookup and O(n)
iteration/repr/copy/equality_testing).
Better living through Python with decorators
As of now, writing custom decorators correctly requires some
experience and it is not as easy as it could be. For instance, typical
implementations of decorators involve nested functions, and we all
know that flat is better than nested. Moreover, typical
implementations of decorators do not preserve the signature of
decorated functions, thus confusing both documentation tools and
developers.
The aim of the decorator module it to simplify the usage of decorators
for the average programmer, and to popularize decorators usage giving
examples of useful decorators, such as memoize, tracing,
redirecting_stdout, locked, etc.