from docstr_md.python import PySoup, compile_md
from docstr_md.src_href import Github
src_href = Github('https://github.com/dsbowen/hemlock-berlin/blob/master')
path = 'hemlock_berlin/__init__.py'
soup = PySoup(path=path, parser='sklearn', src_href=src_href)
compile_md(soup, compiler='sklearn', outfile='docs_md/api.md')
from docstr_md.python import PySoup, compile_md
from docstr_md.src_href import Github
src_href = Github('https://github.com/dsbowen/docstr-md/blob/master')
soup = PySoup(path='test.py', parser='sklearn', src_href=src_href)
compile_md(soup, compiler='sklearn', outfile='docs_md/test.md')
from docstr_md.python import PySoup, compile_md
from docstr_md.src_href import Github
src_href = Github('https://github.com/dsbowen/selenium-tools/blob/master')
path = 'selenium_tools/__init__.py'
soup = PySoup(path=path, src_href=src_href)
compile_md(soup, outfile='docs_md/api.md')
from docstr_md.python import PySoup, compile_md
from docstr_md.src_href import Github
src_href = Github('https://github.com/dsbowen/gshap/blob/master')
soup = PySoup(path='gshap/__init__.py', parser='sklearn', src_href=src_href)
soup.rm_properties()
compile_md(soup, compiler='sklearn', outfile='docs_md/kernel_explainer.md')
g_functions = ('hypothesis', 'intergroup', 'probability_distance')
for g in g_functions:
soup = PySoup(path='gshap/{}.py'.format(g),
parser='sklearn',
src_href=src_href)
compile_md(soup, compiler='sklearn', outfile='docs_md/{}.md'.format(g))
soup = PySoup(path='gshap/datasets/__init__.py',
parser='sklearn',
src_href=src_href)
compile_md(soup, compiler='sklearn', outfile='docs_md/datasets.md')
from docstr_md.python import PySoup, compile_md
from docstr_md.src_href import Github
src_href = Github('https://github.com/dsbowen/hemlock-big5/blob/master')
soup = PySoup(path='hemlock_big5/__init__.py',
parser='sklearn',
src_href=src_href)
compile_md(soup, compiler='sklearn', outfile='docs_md/api.md')