IPython/extensions/ipy_lookfor.py

"""
IPython extension: %lookfor command for searching docstrings

"""
# Pauli Virtanen <[e-mail]>, 2008.

import re, inspect, pkgutil, pydoc

#------------------------------------------------------------------------------
# Lookfor functionality
#------------------------------------------------------------------------------

# Cache for lookfor: {id(module): {name: (docstring, kind, index), ...}...}
# where kind: "func", "class", "module", "object"
# and index: index in breadth-first namespace traversal
_lookfor_caches = {}

# regexp whose match indicates that the string may contain a function signature
_function_signature_re = re.compile(r"[a-z_]+\(.*[,=].*\)", re.I)

def lookfor(what, modules=None, import_modules=True, regenerate=False):
    """
    Search for objects whose documentation contains all given words.
    Shows a summary of matching objects, sorted roughly by relevance.

    Parameters
    ----------
    what : str
        String containing words to look for.

    module : str, module
        Module whose docstrings to go through.
    import_modules : bool
        Whether to import sub-modules in packages.
        Will import only modules in __all__
    regenerate: bool
        Re-generate the docstring cache

    """
    # Cache
    cache = {}
    for module in modules:
        try:
            c = _lookfor_generate_cache(module, import_modules, regenerate)
            cache.update(c)
        except ImportError:
            pass
    
    # Search
    # XXX: maybe using a real stemming search engine would be better?
    found = []
    whats = str(what).lower().split()
    if not whats: return

    for name, (docstring, kind, index) in cache.iteritems():
        if kind in ('module', 'object'): 
            # don't show modules or objects
            continue
        ok = True
        doc = docstring.lower()
        for w in whats:
            if w not in doc:
                ok = False
                break
        if ok:
            found.append(name)

    # Relevance sort
    # XXX: this is full Harrison-Stetson heuristics now,
    # XXX: it probably could be improved

    kind_relevance = {'func': 1000, 'class': 1000, 
                      'module': -1000, 'object': -1000}

    def relevance(name, docstr, kind, index):
        r = 0
        # do the keywords occur within the start of the docstring?
        first_doc = "\n".join(docstr.lower().strip().split("\n")[:3])
        r += sum([200 for w in whats if w in first_doc])
        # do the keywords occur in the function name?
        r += sum([30 for w in whats if w in name])
        # is the full name long?
        r += -len(name) * 5
        # is the object of bad type?
        r += kind_relevance.get(kind, -1000)
        # is the object deep in namespace hierarchy?
        r += -name.count('.') * 10
        r += max(-index / 100, -100)
        return r

    def relevance_sort(a, b):
        dr = relevance(b, *cache[b]) - relevance(a, *cache[a])
        if dr != 0: return dr
        else: return cmp(a, b)
    found.sort(relevance_sort)

    # Pretty-print
    s = "Search results for '%s'" % (' '.join(whats))
    help_text = [s, "-"*len(s)]
    for name in found:
        doc, kind, ix = cache[name]

        doclines = [line.strip() for line in doc.strip().split("\n")
                    if line.strip()]

        # find a suitable short description
        try:
            first_doc = doclines[0].strip()
            if _function_signature_re.search(first_doc):
                first_doc = doclines[1].strip()
        except IndexError:
            first_doc = ""
        help_text.append("%s\n    %s" % (name, first_doc))

    # Output
    if len(help_text) > 10:
        pager = pydoc.getpager()
        pager("\n".join(help_text))
    else:
        print "\n".join(help_text)

def _lookfor_generate_cache(module, import_modules, regenerate):
    """
    Generate docstring cache for given module.

    Parameters
    ----------
    module : str, None, module
        Module for which to generate docstring cache
    import_modules : bool
        Whether to import sub-modules in packages.
        Will import only modules in __all__
    regenerate: bool
        Re-generate the docstring cache

    Returns
    -------
    cache : dict {obj_full_name: (docstring, kind, index), ...}
        Docstring cache for the module, either cached one (regenerate=False)
        or newly generated.
        
    """
    global _lookfor_caches

    if module is None:
        module = "numpy"

    if isinstance(module, str):
        module = __import__(module)

    if id(module) in _lookfor_caches and not regenerate:
        return _lookfor_caches[id(module)]

    # walk items and collect docstrings
    cache = {}
    _lookfor_caches[id(module)] = cache
    seen = {}
    index = 0
    stack = [(module.__name__, module)]
    while stack:
        name, item = stack.pop(0)
        if id(item) in seen: continue
        seen[id(item)] = True

        index += 1
        kind = "object"
       
        if inspect.ismodule(item):
            kind = "module"
            try:
                _all = item.__all__
            except AttributeError:
                _all = None
            # import sub-packages
            if import_modules and hasattr(item, '__path__'):
                for m in pkgutil.iter_modules(item.__path__):
                    if _all is not None and m[1] not in _all:
                        continue
                    try:
                        __import__("%s.%s" % (name, m[1]))
                    except ImportError:
                        continue
            for n, v in inspect.getmembers(item):
                if _all is not None and n not in _all:
                    continue
                stack.append(("%s.%s" % (name, n), v))
        elif inspect.isclass(item):
            kind = "class"
            for n, v in inspect.getmembers(item):
                stack.append(("%s.%s" % (name, n), v))
        elif callable(item):
            kind = "func"
        
        doc = inspect.getdoc(item)
        if doc is not None:
            cache[name] = (doc, kind, index)

    return cache

#------------------------------------------------------------------------------
# IPython connectivity
#------------------------------------------------------------------------------

from IPython.core import ipapi
ip = ipapi.get()

_lookfor_modules = ['numpy', 'scipy']

def lookfor_f(self, arg=''):
    r"""
    Search for objects whose documentation contains all given words.
    Shows a summary of matching objects, sorted roughly by relevance.

    Usage
    -----
    %lookfor +numpy  some words
    Search module 'numpy'

    %lookfor_modules numpy scipy
    Set default modules whose docstrings to search

    """
    lookfor(arg, modules=_lookfor_modules)

def lookfor_modules_f(self, arg=''):
    global _lookfor_modules
    if not arg:
        print "Modules included in %lookfor search:", _lookfor_modules
    else:
        _lookfor_modules = arg.split()

ip.expose_magic('lookfor', lookfor_f)
ip.expose_magic('lookfor_modules', lookfor_modules_f)