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Pexpect — Python module for controlling interactive programs in a pseudo-terminal; winpexpect — port of pexpect to the Windows platform; paramiko-expect — A Python expect-like extension for the Paramiko SSH library which also supports tailing logs.
Python (programming language) scientific libraries (36 P) Pages in category "Python (programming language) libraries" The following 43 pages are in this category, out of 43 total.
Construct, a python library for the declarative construction and deconstruction of data structures; Genshi, a template engine for XML-based vocabularies; IPython, a development shell both written in and designed for Python; Jinja, a Python-powered template engine, inspired by Django's template engine; Kid, simple template engine for XML-based ...
Pygame was originally written by Pete Shinners to replace PySDL after its development stalled. [2] [8] It has been a community project since 2000 [9] and is released under the free software GNU Lesser General Public License [5] (which "provides for Pygame to be distributed with open source and commercial software" [10]).
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
Scapy is a packet manipulation tool for computer networks, [3] [4] originally written in Python by Philippe Biondi. It can forge or decode packets, send them on the wire, capture them, and match requests and replies. It can also handle tasks like scanning, tracerouting, probing, unit tests, attacks, and network discovery.
Requests is an HTTP client library for the Python programming language. [2] [3] Requests is one of the most downloaded Python libraries, [2] with over 300 million monthly downloads. [4] It maps the HTTP protocol onto Python's object-oriented semantics. Requests's design has inspired and been copied by HTTP client libraries for other programming ...
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.