/doc/summarize.py
http://github.com/numpy/numpy · Python · 172 lines · 120 code · 28 blank · 24 comment · 29 complexity · b2924df1f99d40360f0d419cb2d86d00 MD5 · raw file
- #!/usr/bin/env python
- """
- summarize.py
- Show a summary about which Numpy functions are documented and which are not.
- """
- from __future__ import division, absolute_import, print_function
- import os, glob, re, sys, inspect, optparse
- import collections
- sys.path.append(os.path.join(os.path.dirname(__file__), 'sphinxext'))
- from sphinxext.phantom_import import import_phantom_module
- from sphinxext.autosummary_generate import get_documented
- CUR_DIR = os.path.dirname(__file__)
- SOURCE_DIR = os.path.join(CUR_DIR, 'source', 'reference')
- SKIP_LIST = """
- # --- aliases:
- alltrue sometrue bitwise_not cumproduct
- row_stack column_stack product rank
- # -- skipped:
- core lib f2py dual doc emath ma rec char distutils oldnumeric numarray
- testing version matlib
- add_docstring add_newdoc add_newdocs fastCopyAndTranspose pkgload
- conjugate disp
- int0 object0 unicode0 uint0 string_ string0 void0
- flagsobj
- setup PackageLoader
- lib.scimath.arccos lib.scimath.arcsin lib.scimath.arccosh lib.scimath.arcsinh
- lib.scimath.arctanh lib.scimath.log lib.scimath.log2 lib.scimath.log10
- lib.scimath.logn lib.scimath.power lib.scimath.sqrt
- # --- numpy.random:
- random random.info random.mtrand random.ranf random.sample random.random
- # --- numpy.fft:
- fft fft.Tester fft.bench fft.fftpack fft.fftpack_lite fft.helper
- fft.info fft.test
- # --- numpy.linalg:
- linalg linalg.Tester
- linalg.bench linalg.info linalg.lapack_lite linalg.linalg linalg.test
- # --- numpy.ctypeslib:
- ctypeslib ctypeslib.test
- """.split()
- def main():
- p = optparse.OptionParser(__doc__)
- p.add_option("-c", "--columns", action="store", type="int", dest="cols",
- default=3, help="Maximum number of columns")
- options, args = p.parse_args()
- if len(args) != 0:
- p.error('Wrong number of arguments')
- # prepare
- fn = os.path.join(CUR_DIR, 'dump.xml')
- if os.path.isfile(fn):
- import_phantom_module(fn)
- # check
- documented, undocumented = check_numpy()
- # report
- in_sections = {}
- for name, locations in documented.items():
- for (filename, section, keyword, toctree) in locations:
- in_sections.setdefault((filename, section, keyword), []).append(name)
- print("Documented")
- print("==========\n")
- last_filename = None
- for (filename, section, keyword), names in sorted(in_sections.items()):
- if filename != last_filename:
- print("--- %s\n" % filename)
- last_filename = filename
- print(" ** ", section)
- print(format_in_columns(sorted(names), options.cols))
- print("\n")
- print("")
- print("Undocumented")
- print("============\n")
- print(format_in_columns(sorted(undocumented.keys()), options.cols))
- def check_numpy():
- documented = get_documented(glob.glob(SOURCE_DIR + '/*.rst'))
- undocumented = {}
- import numpy, numpy.fft, numpy.linalg, numpy.random
- for mod in [numpy, numpy.fft, numpy.linalg, numpy.random,
- numpy.ctypeslib, numpy.emath, numpy.ma]:
- undocumented.update(get_undocumented(documented, mod, skip=SKIP_LIST))
- for d in (documented, undocumented):
- for k in d.keys():
- if k.startswith('numpy.'):
- d[k[6:]] = d[k]
- del d[k]
- return documented, undocumented
- def get_undocumented(documented, module, module_name=None, skip=[]):
- """
- Find out which items in Numpy are not documented.
- Returns
- -------
- undocumented : dict of bool
- Dictionary containing True for each documented item name
- and False for each undocumented one.
- """
- undocumented = {}
- if module_name is None:
- module_name = module.__name__
- for name in dir(module):
- obj = getattr(module, name)
- if name.startswith('_'): continue
- full_name = '.'.join([module_name, name])
- if full_name in skip: continue
- if full_name.startswith('numpy.') and full_name[6:] in skip: continue
- if not (inspect.ismodule(obj) or isinstance(obj, collections.Callable) or inspect.isclass(obj)):
- continue
- if full_name not in documented:
- undocumented[full_name] = True
- return undocumented
- def format_in_columns(lst, max_columns):
- """
- Format a list containing strings to a string containing the items
- in columns.
- """
- lst = [str(_m) for _m in lst]
- col_len = max([len(_m) for _m in lst]) + 2
- ncols = 80//col_len
- if ncols > max_columns:
- ncols = max_columns
- if ncols <= 0:
- ncols = 1
- if len(lst) % ncols == 0:
- nrows = len(lst)//ncols
- else:
- nrows = 1 + len(lst)//ncols
- fmt = ' %%-%ds ' % (col_len-2)
- lines = []
- for n in range(nrows):
- lines.append("".join([fmt % x for x in lst[n::nrows]]))
- return "\n".join(lines)
- if __name__ == "__main__": main()