Skip to main content

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

Project description

travisci PyPI Package latest release Supported versions Supported implementations Wheel packaging support Test line coverage Test branch coverage

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. It’s also a lot mroe compact than its verbose Unicode descriptor, CIRCLED PLUS.

Because they use only pure 7-bit 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 __future__ import print_function # Python 2/3 compatibiltiy
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' (a.k.a. 'decimal'), 'hex', 'unicode', or 'none' (or the actual None). It’s an alternative to the more explicit individual functions such as named_entities, and can be useful when the kind of entitites you want to generate is data-driven.

unescape(text) changes all entities (save the HTML and XML syntactic marers <, >, and &) into Unicode characters. It has a near-alias, unicode_entities(text) that 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.

Escaping

Converting the character entities used in text strings to more convenient encodings is the primary point of this module. This role is different from that of “escaping” key characters such as &, < and > (and possibly quotation marks such as ' and ") that have special meaning in HTML and XML. Still, the tasks overlap. They’re both about transforming strings using entity representations, and when you want to do one, you will often need to do both. namedentities therefore provides a mechanism to make this convenient.

Any of this modudle’s functions take an optional escape keyword argument. If set to True, strings are pre-processed with the equivalent of the Python standard library’s html.escape so that &, < and > are replaced with &amp;, &lt;, and &gt; respectively. Quotations are not escaped, by default.

If you provide a function instead of True, that function will be used as the escape transformation. E.g.:

import html hex_entities(’…’, escape=html.escape)

Will escape all of the HTML relevant characters, including quotations.

Notes

  • Version 1.9.4 achieves 100% branch testing coverage.

  • Version 1.9 adds the convenience HTML escaping.

  • 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 &lt;, &gt;, or &amp; (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, 3.5, 3.6, 3.7 pre-release, and late-model PyPy and PyPy3.

  • 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

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. You may also need to use version-specific pip2 and pip3 installers, depending on your local system configuration and desired version of Python.

Testing

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

tox                # normal run - speed optimized
tox -e py36        # run for a specific version only (e.g. py27, py36)
tox -c toxcov.ini  # run full coverage tests

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

namedentities-1.9.4.zip (21.8 kB view details)

Uploaded Source

Built Distribution

namedentities-1.9.4-py2.py3-none-any.whl (12.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file namedentities-1.9.4.zip.

File metadata

  • Download URL: namedentities-1.9.4.zip
  • Upload date:
  • Size: 21.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for namedentities-1.9.4.zip
Algorithm Hash digest
SHA256 0bd2a5e5f4136230429c72b7357b3370098f702fe116e09204f128dd6da614b2
MD5 57a12e0a99b5c49752804a1ff6167d73
BLAKE2b-256 9f6ed28dda74e61f53976679ad2f6778dfd1e1780d217e53eb61e50ac5e65b09

See more details on using hashes here.

File details

Details for the file namedentities-1.9.4-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for namedentities-1.9.4-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 65ccdb2950ad13a651fc62f170169ad7c13697ad702ff655f7ab5aa4fcbd162e
MD5 edd7541c5c8cf3b5de77f25a762ee595
BLAKE2b-256 8d10691788b896ae9ae840facf54c16453dfa0da8c7a915c29ea40431effb469

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page