A python module for getting useful data out of ixbrl files. The library is at an early stage - feedback and improvements are very welcome.
New in version 0.5.3: Support for exclude
and continuation
elements within XBRL documents. Thanks to @wcollinscw for adding support for exclude elements.
New in version 0.5: Support for Python 3.11 has been added. I've had some problems with Python 3.11 and Windows as lxml binaries aren't yet available. Also new in version 0.5 is type checking - the whole library now has types added.
New in version 0.4: I've added initial support for pure XBRL files as well as tagged HTML iXBRL files. Feedback on this feature is welcome - particularly around getting values out of numeric items.
The module requires BeautifulSoup and lxml to parse the documents.
word2number is used to process the
numeric items with the numsenwords
format.
You can install from pypi using pip:
pip install ixbrlparse
You can run the module directly to extract data from an IXBRL file.
python -m ixbrlparse example_file.html
The various options for using this can be found through:
python -m ixbrlparse -h
# optional arguments:
# -h, --help show this help message and exit
# --outfile OUTFILE Where to output the file
# --format {csv,json,jsonlines,jsonl}
# format of the output
# --fields {numeric,nonnumeric,all}
# Which fields to output
An example of usage is shown in test.py
.
from ixbrlparse import IXBRL
You need to pass a file handle or other object with a .read()
method.
with open('sample_ixbrl.html', encoding="utf8") as a:
x = IXBRL(a)
If your IXBRL data comes as a string then use a io.StringIO
wrapper to
pass it to the class:
import io
from ixbrlparse import IXBRL
content = '''<some ixbrl content>'''
x = IXBRL(io.StringIO(content))
These are held in the object. The contexts are stored as a dictionary with the context
id as the key, and a ixbrlContext
object as the value.
print(x.contexts)
# {
# "cfwd_2018_03_31": ixbrlContext(
# id="cfwd_2018_03_31",
# entity="0123456", # company number
# segments=[], # used for hypercubes
# instant="2018-03-31",
# startdate=None, # used for periods
# enddate=None, # used for periods
# ),
# ....
# }
The units are stored as key:value dictionary entries
print(x.units)
# {
# "GBP": "ISO4107:GBP"
# "shares": "shares"
# }
Numeric facts are stored in x.numeric
as a list of ixbrlNumeric
objects.
The ixbrlNumeric.value
object contains the value as a parsed python number
(after the sign and scale formatting values have been applied).
ixbrlNumeric.context
holds the context object relating to this value.
The .name
and .schema
values give the key of this value, according to
the applied schema.
Non-numeric facts are stored in x.nonnumeric
as a list of ixbrlNonnumeric
objects, with similar .value
, .context
, .name
and .schema
values.
The value of .value
will be a string for non-numeric facts.
By default, the parser will throw an exception if it encounters an error when processing the document.
You can parse raise_on_error=False
to the initial object to suppress
these exceptions. You can then access a list of the errors (and the element)
that created them through the .errors
attribute. For example:
with open('sample_ixbrl.html', encoding="utf8") as a:
x = IXBRL(a, raise_on_error=False)
print(x.errors) # populated with any exceptions found
# [ eg...
# {
# "error": <NotImplementedError>,
# "element": <BeautifulSoupElement>
# }
# ]
Note that the error catching is only available for parsing of .nonnumeric
and numeric
items in the document. Any other errors with parsing will be
thrown as normal no matter what raise_on_error
is set to.
Tests can be run with pytest
:
pip install -e . # install the package
pytest tests
coverage run -m pytest tests
coverage html
python -m http.server -d htmlcov
mypy ixbrlparse tests
Black and isort should be run before committing any changes.
isort ixbrlparse tests
black ixbrlparse tests
black . && isort . && mypy ixbrlparse tests && coverage run -m pytest tests && coverage html --fail-under=100
python -m build
twine upload dist/*
git tag v<VERSION_NUMBER>
git push origin v<VERSION_NUMBER>
The development requirements are installed using pip install -r dev-requirements.txt
.
Any additional requirements for the module itself must be added to
install_requires
in setup.py
. You should then generate a new
requirements.txt
using using pip-tools
(pip-compile
). You can then run pip-sync
to install the
requirement.
Any additional development requirements must be added to dev-requirements.in
and then the dev-requirements.txt
should be generated using pip-compile dev-requirements.in
. You can then install the development requirements using
pip-sync dev-requirements.txt
.
Originally developed for a project with Power to Change looking at how to extract data from financial documents of community businesses.