PyYAML-based module to produce pretty and readable YAML-serialized data
Project description
pretty-yaml (or pyaml): Pretty YAML serialization
YAML is generally nice and easy format to read if it was written by humans.
PyYAML can a do fairly decent job of making stuff readable, and the best combination of parameters for such output that I’ve seen so far is probably this one:
>>> m = [123, 45.67, {1: None, 2: False}, u'some text']
>>> data = dict(a=u'asldnsa\nasldpáknsa\n', b=u'whatever text', ma=m, mb=m)
>>> yaml.safe_dump(data, sys.stdout, allow_unicode=True, default_flow_style=False)
a: 'asldnsa
asldpáknsa
'
b: whatever text
ma: &id001
- 123
- 45.67
- 1: null
2: false
- some text
mb: *id001
pyaml tries to improve on that a bit, with the following tweaks:
Most human-friendly representation options in PyYAML (that I know of) get picked as defaults.
Does not dump “null” values, if possible, replacing these with just empty strings, which have the same meaning but reduce visual clutter and are easier to edit.
Dicts, sets, OrderedDicts, defaultdicts, etc are representable and get sorted on output, so that output would be as diff-friendly as possible, and not arbitrarily depend on python internals.
It appears that at least recent PyYAML versions also do such sorting for python dicts.
List items get indented, as they should be.
bytestrings that can’t be auto-converted to unicode raise error, as yaml has no “binary bytes” (i.e. unix strings) type.
Attempt is made to pick more readable string representation styles, depending on the value, e.g.:
``` >>> yaml.safe_dump(cert, sys.stdout) cert: ‘—–BEGIN CERTIFICATE—–
MIIH3jCCBcagAwIBAgIJAJi7AjQ4Z87OMA0GCSqGSIb3DQEBCwUAMIHBMRcwFQYD VQQKFA52YWxlcm9uLm5vX2lzcDEeMBwGA1UECxMVQ2VydGlmaWNhdGUgQXV0aG9y
…
pyaml.p(cert): cert: | —–BEGIN CERTIFICATE—– MIIH3jCCBcagAwIBAgIJAJi7AjQ4Z87OMA0GCSqGSIb3DQEBCwUAMIHBMRcwFQYD VQQKFA52YWxlcm9uLm5vX2lzcDEeMBwGA1UECxMVQ2VydGlmaWNhdGUgQXV0aG9y … ```
“force_embed” option to avoid having &id stuff scattered all over the output (which might be beneficial in some cases, hence the option).
“&id” anchors, if used, get labels from the keys they get attached to, not just use meaningless enumerators.
“string_val_style” option to only apply to strings that are values, not keys, i.e:
>>> pyaml.p(data, string_val_style='"') key: "value\nasldpáknsa\n" >>> yaml.safe_dump(data, sys.stdout, allow_unicode=True, default_style='"') "key": "value\nasldpáknsa\n"
Has an option to add vertical spacing (empty lines) between keys on different depths, to make output much more seekable.
Result for the (rather meaningless) example above (without any additional tweaks):
>>> pyaml.p(data)
a: |
asldnsa
asldpáknsa
b: 'whatever text'
ma: &ma
- 123
- 45.67
- 1:
2: false
- 'some text'
mb: *ma
Extended example:
>>> pyaml.dump(conf, sys.stdout, vspacing=[2, 1]):
destination:
encoding:
xz:
enabled: true
min_size: 5120
options:
path_filter:
- \.(gz|bz2|t[gb]z2?|xz|lzma|7z|zip|rar)$
- \.(rpm|deb|iso)$
- \.(jpe?g|gif|png|mov|avi|ogg|mkv|webm|mp[34g]|flv|flac|ape|pdf|djvu)$
- \.(sqlite3?|fossil|fsl)$
- \.git/objects/[0-9a-f]+/[0-9a-f]+$
result:
append_to_file:
append_to_lafs_dir:
print_to_stdout: true
url: http://localhost:3456/uri
filter:
- /(CVS|RCS|SCCS|_darcs|\{arch\})/$
- /\.(git|hg|bzr|svn|cvs)(/|ignore|attributes|tags)?$
- /=(RELEASE-ID|meta-update|update)$
http:
ca_certs_files: /etc/ssl/certs/ca-certificates.crt
debug_requests: false
request_pool_options:
cachedConnectionTimeout: 600
maxPersistentPerHost: 10
retryAutomatically: true
logging:
formatters:
basic:
datefmt: '%Y-%m-%d %H:%M:%S'
format: '%(asctime)s :: %(name)s :: %(levelname)s: %(message)s'
handlers:
console:
class: logging.StreamHandler
formatter: basic
level: custom
stream: ext://sys.stderr
loggers:
twisted:
handlers:
- console
level: 0
root:
handlers:
- console
level: custom
Note that unless there are many moderately wide and deep trees of data, which are expected to be read and edited by people, it might be preferrable to directly use PyYAML regardless, as it won’t introduce another (rather pointless in that case) dependency and a point of failure.
Obligatory warning
Prime concern for this module is to chew simple types/values gracefully, and internally there are some nasty hacks (that I’m not too proud of) used to do that, which may not work with more complex serialization cases, possibly even producing non-deserializable (but still easily fixable) output.
Again, prime goal is not to serialize, say, gigabytes of complex document-storage db contents, but rather individual simple human-parseable documents, please keep that in mind (and of course, patches for hacks are welcome!).
Some Tricks
Pretty-print any yaml or json (yaml subset) file from the shell:
python -m pyaml /path/to/some/file.yaml curl -s https://status.github.com/api.json | python -m pyaml
Easier “debug printf” for more complex data (all funcs below are aliases to same thing):
pyaml.p(stuff)
pyaml.pprint(my_data)
pyaml.pprint('----- HOW DOES THAT BREAKS!?!?', input_data, some_var, more_stuff)
pyaml.print(data, file=sys.stderr) # needs "from __future__ import print_function"
Force all string values to a certain style (see info on these in PyYAML docs):
pyaml.dump(many_weird_strings, string_val_style='|') pyaml.dump(multiline_words, string_val_style='>') pyaml.dump(no_want_quotes, string_val_style='plain')
Using pyaml.add_representer() (note pyaml) as suggested in this SO thread (or #7) should also work.
Installation
It’s a regular package for Python 2.7 (not 3.X).
Using pip is the best way:
% pip install pyaml
If you don’t have it, use:
% easy_install pip % pip install pyaml
Alternatively (see also):
% curl https://raw.github.com/pypa/pip/master/contrib/get-pip.py | python % pip install pyaml
Or, if you absolutely must:
% easy_install pyaml
But, you really shouldn’t do that.
Current-git version can be installed like this:
% pip install 'git+https://github.com/mk-fg/pretty-yaml.git#egg=pyaml'
Module uses PyYAML for processing of the actual YAML files and should pull it in as a dependency.
Dependency on unidecode module is optional and should only be necessary if same-id objects or recursion is used within serialized data.
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