„Batteries included“

In Python, a library can consist of several components, including built-in data types and constants that can be used without an import statement, such as Numbers and Lists, as well as some built-in Functions and Exceptions. The largest part of the library is an extensive collection of Modules. If you have Python installed, there are also several libraries available for you to use.

• Managing data types

• Changing files

• Interacting with the operating system

• Use of Internet protocols

• Developing and debugging

Managing data types

The standard library naturally contains support for the types built into Python. In addition, there are three categories in the standard library that deal with different data types: Modules for strings, datatypes and numbers.

String modules

:

Module	Description
string	compares with constants such as string.digits or string.whitespace
re	searches and replaces text with regular expressions
struct	interprets bytes as packed binary data
difflib	helps to calculate deltas, find differences between strings or sequences and create patches and diff files
textwrap	wraps and fills text, formats text with line breaks or spaces

See also

• Manipulation of strings with pandas

Modules for data types

Module	Description
datetime, calendar	Time and calendar operations
collections	Container data types
enum	allows the creation of enumeration classes that bind symbolic names to constant values
array	Efficient arrays of numeric values
sched	Event scheduler
queue	Synchronised queue class
copy	Shallow and deep copy operations
pprint	prints Python data structures „pretty“.
typing	supports commenting code with hints about the types of objects, especially function parameters and return values

Modules for numbers

:

Module	Description
numbers	for numeric abstract base classes
math, cmath	for mathematical functions for real and complex numbers
decimal	for decimal fixed-point and floating-point arithmetic
statistics	for functions for calculating mathematical statistics
fractions	for rational numbers
random	for generating pseudo-random numbers and selections and for shuffling sequences
itertools	for functions that create iterators for efficient loops
functools	for higher-order functions and operations on callable objects
operator	for standard operators as functions

Changing files

:

Module	Description
os.path	performs common pathname manipulations
pathlib	manipulates pathnames
fileinput	iterates over multiple input files
filecmp	compares files and directories
tempfile	creates temporary files and directories
glob, fnmatch	use UNIX-like path and file name patterns
linecache	randomly accesses lines of text
shutil	performs higher level file operations
mimetypes	Assignment of file names to MIME types
pickle, shelve	enable Python object serialisation and persistence, see also The pickle module
csv	reads and writes CSV files
json	JSON encoder and decoder
sqlite3	provides a DB-API 2.0 interface for SQLite databases, see also The sqlite module
xml, xml.parsers.expat, xml.dom, xml.sax, xml.etree.ElementTree	reads and writes XML files, see also R:doc:../save-data/xml
html.parser, html.entities	Parsing HTML and XHTML
configparser	reads and writes Windows-like configuration files (.ini)
base64, binhex, binascii, quopri, uu	encodes/decodes files or streams
struct	reads and writes structured data to and from files
zlib, gzip, bz2, zipfile, tarfile	for working with archive files and compressions

See also

• pandas IO tools

• Examples of serialisation formats CSV, JSON, Excel, XML/HTML, YAML, TOML und Pickle.

Interacting with the operating system

Module	Description
os	Various operating system interfaces
platform	Access to the identification data of the underlying platform
time	Time access and conversions
io	Tools for working with data streams
select	Waiting for I/O completion
optparse	Parser for command line options
curses	Terminal handling for character cell displays
getpass	Portable password entry
ctypes	provides C-compatible data types
threading	high-level threading interface
multiprocessing	Process-based threading interface
subprocess	Management of subprocesses

Use of Internet protocols

Module	descriptiong
socket, ssl	Low-level network interface and SSL wrapper for socket objects
email	Email and MIME processing package
mailbox	Manipulation of mailboxes in various formats
cgi, cgitb	Common Gateway Interface support
wsgiref	WSGI utilities and reference implementation
urllib.request, urllib.parse	Open and parse URLs
ftplib, poplib, imaplib, nntplib, smtplib, telnetlib	Clients for various Internet protocols
socketserver	Framework for network servers
http.server	HTTP server
xmlrpc.client, xmlrpc.server	XML-RPC client and server

Developing and debugging

Module	Description
pydoc	Documentation generator and online help system
doctest	Test examples from Python docstrings
unittest	Framework for unittests, see also Unittest
test.support	Utility functions for tests
trace	traces the execution of Python statements
pdb	Python debugger
logging	logging function for Python
timeit	measures the execution time of small code snippets
profile, cProfile	Python profiler
sys	System-specific parameters and functions
gc	Functions of the Python garbage collector
inspect	inspects objects live
atexit	exit handler
__future__	Future statement definitions
imp	allows access to the import internals
zipimport	imports modules from zip archives
modulefinder	finds modules used by a script