A python library for accessing and searching dictionaries via /slashed/paths ala xpath
Basically it lets you glob over a dictionary as if it were a filesystem. It allows you to specify globs (ala the bash eglob syntax, through some advanced fnmatch.fnmatch magic, or using Python's `re`regular expressions ) to access dictionary elements, and provides some facility for filtering those results.
sdists are available on pypi: http://pypi.python.org/pypi/dpath
The best way to install dpath is via easy_install or pip.
easy_install dpath pip install dpath
import dpathAll of the functions in this library (except 'merge') accept a 'separator' argument, which is the character that should separate path components. The default is '/', but you can set it to whatever you want.
Suppose we have a dictionary like this:
x = {
"a": {
"b": {
"3": 2,
"43": 30,
"c": [],
"d": ['red', 'buggy', 'bumpers'],
}
}
}... And we want to ask a simple question, like "Get me the value of the key '43' in the 'b' hash which is in the 'a' hash". That's easy.
>>> help(dpath.get)
Help on function get in module dpath:
get(obj, glob, separator='/')
Given an object which contains only one possible match for the given glob,
return the value for the leaf matching the given glob.
If more than one leaf matches the glob, ValueError is raised. If the glob is
not found, KeyError is raised.
>>> dpath.get(x, '/a/b/43')
30Or you could say "Give me a new dictionary with the values of all
elements in x['a']['b'] where the key is equal to the glob '[cd]'. Okay.
>>> help(dpath.search)
Help on function search in module dpath:
search(obj, glob, yielded=False)
Given a path glob, return a dictionary containing all keys
that matched the given glob.
If 'yielded' is true, then a dictionary will not be returned.
Instead tuples will be yielded in the form of (path, value) for
every element in the document that matched the glob.... Sounds easy!
>>> result = dpath.search(x, "a/b/[cd]")
>>> print(json.dumps(result, indent=4, sort_keys=True))
{
"a": {
"b": {
"c": [],
"d": [
"red",
"buggy",
"bumpers"
]
}
}
}Note : Using Python's re regular expressions instead of globs is explained below re_regexp; defining your own string matcher objects is shown in generalized_string_match below.
... Wow that was easy. What if I want to iterate over the results, and not get a merged view?
>>> for x in dpath.search(x, "a/b/[cd]", yielded=True): print(x)
...
('a/b/c', [])
('a/b/d', ['red', 'buggy', 'bumpers'])... Or what if I want to just get all the values back for the glob? I don't care about the paths they were found at:
>>> help(dpath.values)
Help on function values in module dpath:
values(obj, glob, separator='/', afilter=None, dirs=True)
Given an object and a path glob, return an array of all values which match
the glob. The arguments to this function are identical to those of search(),
and it is primarily a shorthand for a list comprehension over a yielded
search call.
>>> dpath.values(x, '/a/b/d/*')
['red', 'buggy', 'bumpers']Let's use that same dictionary, and set keys like 'a/b/[cd]' to the value 'Waffles'.
>>> help(dpath.set)
Help on function set in module dpath:
set(obj, glob, value)
Given a path glob, set all existing elements in the document
to the given value. Returns the number of elements changed.
>>> dpath.set(x, 'a/b/[cd]', 'Waffles')
2
>>> print(json.dumps(x, indent=4, sort_keys=True))
{
"a": {
"b": {
"3": 2,
"43": 30,
"c": "Waffles",
"d": "Waffles"
}
}
}Let's make a new key with the path 'a/b/e/f/g', set it to "Roffle". This behaves like 'mkdir -p' in that it makes all the intermediate paths necessary to get to the terminus.
>>> help(dpath.new)
Help on function new in module dpath:
new(obj, path, value)
Set the element at the terminus of path to value, and create
it if it does not exist (as opposed to 'set' that can only
change existing keys).
path will NOT be treated like a glob. If it has globbing
characters in it, they will become part of the resulting
keys
>>> dpath.new(x, 'a/b/e/f/g', "Roffle")
>>> print(json.dumps(x, indent=4, sort_keys=True))
{
"a": {
"b": {
"3": 2,
"43": 30,
"c": "Waffles",
"d": "Waffles",
"e": {
"f": {
"g": "Roffle"
}
}
}
}
}This works the way we expect with lists, as well. If you have a list object and set index 10 of that list object, it will grow the list object with None entries in order to make it big enough:
>>> dpath.new(x, 'a/b/e/f/h', [])
>>> dpath.new(x, 'a/b/e/f/h/13', 'Wow this is a big array, it sure is lonely in here by myself')
>>> print(json.dumps(x, indent=4, sort_keys=True))
{
"a": {
"b": {
"3": 2,
"43": 30,
"c": "Waffles",
"d": "Waffles",
"e": {
"f": {
"g": "Roffle",
"h": [
null,
null,
null,
null,
null,
null,
null,
null,
null,
null,
null,
null,
null,
"Wow this is a big array, it sure is lonely in here by myself"
]
}
}
}
}
}Handy!
To delete keys in an object, use dpath.delete, which accepts the same globbing syntax as the other methods.
>>> help(dpath.delete)
delete(obj, glob, separator='/', afilter=None):
Given a path glob, delete all elements that match the glob.
Returns the number of deleted objects. Raises PathNotFound if
no paths are found to delete.Also, check out dpath.merge. The python dict update() method is great and all but doesn't handle merging dictionaries deeply. This one does.
>>> help(dpath.merge)
Help on function merge in module dpath:
merge(dst, src, afilter=None, flags=4, _path='')
Merge source into destination. Like dict.update() but performs
deep merging.
flags is an OR'ed combination of MergeType enum members.
* ADDITIVE : List objects are combined onto one long
list (NOT a set). This is the default flag.
* REPLACE : Instead of combining list objects, when
2 list objects are at an equal depth of merge, replace
the destination with the source.
* TYPESAFE : When 2 keys at equal levels are of different
types, raise a TypeError exception. By default, the source
replaces the destination in this situation.
>>> y = {'a': {'b': { 'e': {'f': {'h': [None, 0, 1, None, 13, 14]}}}, 'c': 'RoffleWaffles'}}
>>> print(json.dumps(y, indent=4, sort_keys=True))
{
"a": {
"b": {
"e": {
"f": {
"h": [
null,
0,
1,
null,
13,
14
]
}
}
},
"c": "RoffleWaffles"
}
}
>>> dpath.merge(x, y)
>>> print(json.dumps(x, indent=4, sort_keys=True))
{
"a": {
"b": {
"3": 2,
"43": 30,
"c": "Waffles",
"d": "Waffles",
"e": {
"f": {
"g": "Roffle",
"h": [
null,
0,
1,
null,
13,
14,
null,
null,
null,
null,
null,
null,
null,
"Wow this is a big array, it sure is lonely in here by myself"
]
}
}
},
"c": "RoffleWaffles"
}
}Now that's handy. You shouldn't try to use this as a replacement for the deepcopy method, however - while merge does create new dict and list objects inside the target, the terminus objects (strings and ints) are not copied, they are just re-referenced in the merged object.
All of the methods in this library (except new()) support a 'afilter' argument. This can be set to a function that will return True or False to say 'yes include that value in my result set' or 'no don't include it'.
Filtering functions receive every terminus node in a search - e.g., anything that is not a dict or a list, at the very end of the path. For each value, they return True to include that value in the result set, or False to exclude it.
Consider this example. Given the source dictionary, we want to find ALL keys inside it, but we only really want the ones that contain "ffle" in them:
>>> print(json.dumps(x, indent=4, sort_keys=True))
{
"a": {
"b": {
"3": 2,
"43": 30,
"c": "Waffles",
"d": "Waffles",
"e": {
"f": {
"g": "Roffle"
}
}
}
}
}
>>> def afilter(x):
... if "ffle" in str(x):
... return True
... return False
...
>>> result = dpath.search(x, '**', afilter=afilter)
>>> print(json.dumps(result, indent=4, sort_keys=True))
{
"a": {
"b": {
"c": "Waffles",
"d": "Waffles",
"e": {
"f": {
"g": "Roffle"
}
}
}
}
}Obviously filtering functions can perform more advanced tests (regular expressions, etc etc).
By default, dpath only understands dictionary keys that are integers or strings. String keys must be non-empty. You can change this behavior by setting a library-wide dpath option:
import dpath.options
dpath.options.ALLOW_EMPTY_STRING_KEYS = TrueAgain, by default, this behavior is OFF, and empty string keys will
result in dpath.exceptions.InvalidKeyName being thrown.
The default behavior in dpath is to assume that the path given is a string, which must be tokenized by splitting at the separator to yield a distinct set of path components against which dictionary keys can be individually glob tested. However, this presents a problem when you want to use paths that have a separator in their name; the tokenizer cannot properly understand what you mean by '/a/b/c' if it is possible for '/' to exist as a valid character in a key name.
To get around this, you can sidestep the whole "filesystem path" style, and abandon the separator entirely, by using lists as paths. All of the methods in dpath.* support the use of a list instead of a string as a path. So for example:
>>> x = { 'a': {'b/c': 0}}
>>> dpath.get(['a', 'b/c'])
0Python's re regular expressions PythonRe may be used as follows:
- The recognition of such regular expressions in strings is disabled by default, but may be easily
- enabled ( Set up this way for backwards compatibility in the cases where a path expression component would start with '{' and end in '}').
- Irrespective of this setting, the user can use re regular expressions in the list form of paths (see below).
>>> import dpath >>> # enable >>> dpath.options.ALLOW_REGEX = True >>> # disable >>> dpath.options.ALLOW_REGEX = False
Now a path component may also be specified :
- in a path expression, as {<re.regexpr>} where <re.regexpr> is a regular expression accepted by the standard Python module re. For example:
>>> selPath = 'Config/{(Env|Cmd)}' >>> x = dpath.search(js.lod, selPath)>>> selPath = '{(Config|Graph)}/{(Env|Cmd|Data)}' >>> x = dpath.search(js.lod, selPath)
When using the list form for a path, a list element can also be expressed as
- a string as above
- the output of :: re.compile( args )`
An example:
>>> selPath = [ re.compile('(Config|Graph)') , re.compile('(Env|Cmd|Data)') ] >>> x = dpath.search(js.lod, selPath)More examples from a realistic json context:
Extended path glob
Designates
"**/{[^A-Za-z]{2}$}"
"Id"
r"*/{[A-Z][A-Za-z\d]*$}"
"Name","Id","Created", "Scope",...
r"**/{[A-Z][A-Za-z\d]*d$}"
EnableIPv6"
r"**/{[A-Z][A-Za-z\d]*Address$}"
"Containers/199c5/MacAddress"
With Python's character string conventions, required backslashes in the re syntax can be entered either in raw strings or using double backslashes, thus the following are equivalent:
with raw strings
equivalent with double backslash
r"**/{[A-Z][A-Za-z\d]*\d$}"
"**/{[A-Z][A-Za-z\\d]*\\d$}"
r"**/{[A-Z][A-Za-z\d]*Address$}"
"**/{[A-Z][A-Za-z\\d]*Address$}"
We provide the following abstract types, where StringMatcher is allowed in Glob in the sequence form (definitions in dpath.types) :
- StringMatcher (descriptive Union type ),
- Duck_StringMatcher: which will accept a class as a subtype, provided it offers a match method. Instances may then be used as components in the list form of paths. This method of structural subtyping is explained in PEP 544 [https://peps.python.org/pep-0544/].
- Basic_StringMatcher: an abstract base class, enabling your derived class to be recognized and participate in a match.
- Notes:
- It is required that the match method: match(self, str) -> Optional[object], returns None to reject the match.
- Using Duck_StringMatcher requires a version of Python and Pypy not less than 3.8, otherwise you should derive from base class Basic_StringMatcher. The variable dpath.options.PEP544_PROTOCOL_AVAILABLE indicates when duck typing is possible.
- Then it is up to you... Examples are provided in tests/test_duck_typing.py,
including:
match anagrams:
class Anagram(): def __init__(self, s): self.ref = "".join(sorted(s)) def match(self, st): retval = True if "".join(sorted(st)) == self.ref else None return retval mydict = TestBasics.mydict r1 = dpath.search(mydict, "**/label") r2 = dpath.search(mydict, [ '**', Anagram("bella")]) assert r1 == r2
and approximate match (requires rapidfuzz https://maxbachmann.github.io/RapidFuzz/):
class Approx(): def __init__(self, s, quality=90): self.ref = s self.quality=quality def match(self, st): fratio = rapidfuzz.fuzz.ratio(st, self.ref) retval = True if fratio > self.quality else None return retval mydict = TestBasics.mydict r1 = dpath.search(mydict, "**/placeholder") r2 = dpath.search(mydict, [ '**', Approx("placecolder")]) r3 = dpath.search(mydict, [ '**', Approx("acecolder",75)]) assert r1 == r2 assert r1 == r3
For comparison, we show now the first example reimplemented to avoid duck typing:
if not dpath.options.PEP544_PROTOCOL_AVAILABLE: class Anagram(dpath.types.Basic_StringMatcher): def __init__(self, s): self.ref = "".join(sorted(s)) def match(self, st): retval = True if "".join(sorted(st)) == self.ref else None return retval dpath.search(mydict, ['**', Anagram("bella")])
dpath is where you want to spend your time: this library has the friendly functions that will understand simple string globs, afilter functions, etc.
dpath.segments is the backend pathing library. It passes around tuples of path components instead of string globs.
We would like to thank the community for their interest and involvement. You have all made this project significantly better than the sum of its parts, and your continued feedback makes it better every day. Thank you so much!
The following authors have contributed to this project, in varying capacities:
- Caleb Case <[email protected]>
- Andrew Kesterson <[email protected]>
- Marc Abramowitz <[email protected]>
- Richard Han <[email protected]>
- Stanislav Ochotnicky <[email protected]>
- Misja Hoebe <[email protected]>
- Gagandeep Singh <[email protected]>
- Alan Gibson <[email protected]>
And many others! If we've missed you please open an PR and add your name here.