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Named (and numeric) HTML entities to/from each other or Unicode

Project description

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When reading HTML, named entities are neater and often easier to comprehend than numeric entities (whether in decimal or hexidecimal notation), Unicode characters, or a mixture. The ⊕ character, for example, is easier to recognize and remember as ⊕ than ⊕ or ⊕ or \u2295.

Because they use only pure ASCII characters, entities are safer to use in databases, files, emails, and other contexts, especially given the many encodings (UTF-8 and such) required to fit Unicode into byte-oriented storage–and the many platform variations and quirks seen along the way.

This module helps convert from whatever mixture of characters and/or entities you have into named HTML entities. Or, if you prefer, into numeric HTML entities (either decimal or hexadecimal). It will even help you go the other way, mapping entities into Unicode.

Usage

Python 2:

from namedentities import *

u = u'both em\u2014and–dashes…'

print "named:  ", repr(named_entities(u))
print "numeric:", repr(numeric_entities(u))
print "hex:"   ", repr(hex_entities(u))
print "unicode:", repr(unicode_entities(u))

yields:

named:   'both em—and–dashes…'
numeric: 'both em—and–dashes…'
hex:     'both em—and–dashes…'
unicode: u'both em\u2014and\u2013dashes\u2026'

You can do just about the same thing in Python 3, but you have to use a print function rather than a print statement, and prior to 3.3, you have to skip the u prefix that in Python 2 marks string literals as being Unicode literals. In Python 3.3 and following, however, you can start using the u marker again, if you like. While all Python 3 strings are Unicode, it helps with cross-version code compatibility. (You can use the six cross-version compatibility library, as the tests do.)

One good use for unicode_entities is to create cross-platform, cross-Python-version strings that conceptually contain Unicode characters, but spelled out as named (or numeric) HTML entities. For example:

unicode_entities('This ’thing” is great!')

This has the advantage of using only ASCII characters and common string encoding mechanisms, yet rendering full Unicode strings upon reconstitution. You can use the other functions, say named_entities(), to go from Unicode characters to named entities.

Other APIs

entities(text, kind) takes text and the kind of entities you’d like returned. kind can be 'named' (the default), 'numeric', 'hex', 'unicode', or 'none'. It’s an alternative to the more explicit individual functions such as named_entities.

unescape(text) changes all entities into Unicode characters. It has an alias, unicode_entities(text) for parallelism with the other APIs.

Encodings Akimbo

This module helps map string between HTML entities (named, numeric, or hex) and Unicode characters. It makes those mappings–previously somewhat obscure and nitsy–easy. Yay us! It will not, however, specifically help you with “encodings” of Unicode characters such as UTF-8; for these, use Python’s built-in features.

Python 3 tends to handle encoding/decoding pretty transparently. Python 2, however, does not. Use the decode string method to get (byte) strings including UTF-8 into Unicode; use encode to convert true unicode strings into UTF-8. Please convert them to Unicode before processing with namedentities:

s = "String with some UTF-8 characters..."
print named_entities(s.decode("utf-8"))

The best strategy is to convert data to full Unicode as soon as possible after ingesting it. Process everything uniformly in Unicode. Then encode back to UTF-8 etc. as you write the data out. This strategy is baked-in to Python 3, but must be manually accomplished in Python 2.

Notes

  • Version 1.8.1 starts automatic test branch coverage with 96% coverage.

  • Version 1.8 acheives 100% test line coverage.

  • See CHANGES.yml for more historical changes.

  • Doesn’t attempt to encode <, >, or & (or their numerical equivalents) to avoid interfering with HTML escaping.

  • Automated multi-version testing managed with the wonderful pytest, pytest-cov, coverage, and tox. Continuous integration testing with Travis-CI. Packaging linting with pyroma.

    Successfully packaged for, and tested against, all late-model versions of Python: 2.6, 2.7, 3.2, 3.3, 3.4, and 3.5 pre-release (3.5.0b3) as well as PyPy 2.6.0 (based on 2.7.9) and PyPy3 2.4.0 (based on 3.2.5).

  • This module started as basically a packaging of Ian Beck’s recipe. While it’s moved forward since then, Ian’s contribution to the core remains key. Thank you, Ian!

  • The author, Jonathan Eunice or @jeunice on Twitter welcomes your comments and suggestions.

Installation

To install or upgrade to the latest version:

pip install -U namedentities

To easy_install under a specific Python version (3.3 in this example):

python3.3 -m easy_install --upgrade namedentities

(You may need to prefix these with sudo to authorize installation. In environments without super-user privileges, you may want to use pip’s --user option, to install only for a single user, rather than system-wide.)

Testing

To run the module tests, use one of these commands:

tox                # normal run - speed optimized
tox -e py27        # run for a specific version only (e.g. py27, py34)
tox -c toxcov.ini  # run full coverage tests

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