py2store.utils.glom

glom is a util to extract stuff from nested structures. It’s one of those excellent utils that I’ve written many times, but never got quite right. Mahmoud Hashemi got it right.

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Copyright (c) 2018, Mahmoud Hashemi

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Now, at the time of writing this, I’ve already transformed it to bend it to my liking. At some point it may become something else, but I wanted there to be a trace of what my seed was. Though I can’t promise I’ll maintain the same functionality as I transform this module, here’s a tutorial on how to use it in it’s original form:

https://glom.readthedocs.io/en/latest/

I only took the main (core) module from the glom project. Here’s the original docs of this glom module.

If there was ever a Python example of “big things come in small packages”, glom might be it.

The glom package has one central entrypoint, glom.glom(). Everything else in the package revolves around that one function.

A couple of conventional terms you’ll see repeated many times below:

• target - glom is built to work on any data, so we simply refer to the object being accessed as the “target”

• spec - (aka “glomspec”, short for specification) The accompanying template used to specify the structure of the return value.

Now that you know the terms, let’s take a look around glom’s powerful semantics.

class py2store.utils.glom.Auto(spec=None)

Switch to Auto mode (the default)

TODO: this seems like it should be a sub-class of class Spec() – if Spec() could help define the interface for new “modes” or dialects that would also help make match mode feel less duct-taped on

class py2store.utils.glom.Call(func=None, args=None, kwargs=None)

Call specifies when a target should be passed to a function, func.

Call is similar to partial() in that it is no more powerful than lambda or other functions, but it is designed to be more readable, with a better repr.

Parameters

func (callable) – a function or other callable to be called with the target

Call combines well with T to construct objects. For instance, to generate a dict and then pass it to a constructor:

>>> class ExampleClass(object):
...    def __init__(self, attr):
...        self.attr = attr
...
>>> target = {'attr': 3.14}
>>> glom(target, Call(ExampleClass, kwargs=T)).attr
3.14

This does the same as glom(target, lambda target: ExampleClass(**target)), but it’s easy to see which one reads better.

Note

Call is mostly for functions. Use a T object if you need to call a method.

Warning

Call has a successor with a fuller-featured API, new in 19.3.0: the Invoke specifier type.

glomit(target, scope)

run against the current target

class py2store.utils.glom.Check(spec=T, **kwargs)

Check objects are used to make assertions about the target data, and either pass through the data or raise exceptions if there is a problem.

If any check condition fails, a CheckError is raised.

Parameters

• spec – a sub-spec to extract the data to which other assertions will be checked (defaults to applying checks to the target itself)

• type – a type or sequence of types to be checked for exact match

• equal_to – a value to be checked for equality match (“==”)

• validate – a callable or list of callables, each representing a check condition. If one or more return False or raise an exception, the Check will fail.

• instance_of – a type or sequence of types to be checked with isinstance()

• one_of – an iterable of values, any of which can match the target (“in”)

• default – an optional default value to replace the value when the check fails (if default is not specified, GlomCheckError will be raised)

Aside from spec, all arguments are keyword arguments. Each argument, except for default, represent a check condition. Multiple checks can be passed, and if all check conditions are left unset, Check defaults to performing a basic truthy check on the value.

exception py2store.utils.glom.CheckError(msgs, check, path)

This GlomError subtype is raised when target data fails to pass a Check’s specified validation.

An uncaught CheckError looks like this:

>>> target = {'a': {'b': 'c'}}
>>> glom(target, {'b': ('a.b', Check(type=int))})  
Traceback (most recent call last):
...
glom.CheckError: target at path ['a.b'] failed check, got error: "expected type to be 'int', found type 'str'"

If the Check contains more than one condition, there may be more than one error message. The string rendition of the CheckError will include all messages.

You can also catch the CheckError and programmatically access messages through the msgs attribute on the CheckError instance.

Note

As of 2018-07-05 (glom v18.2.0), the validation subsystem is still very new. Exact error message formatting may be enhanced in future releases.

class py2store.utils.glom.Coalesce(*subspecs, **kwargs)

Coalesce objects specify fallback behavior for a list of subspecs.

Subspecs are passed as positional arguments, and keyword arguments control defaults. Each subspec is evaluated in turn, and if none match, a CoalesceError is raised, or a default is returned, depending on the options used.

Note

This operation may seem very familar if you have experience with SQL or even C# and others.

In practice, this fallback behavior’s simplicity is only surpassed by its utility:

>>> target = {'c': 'd'}
>>> glom(target, Coalesce('a', 'b', 'c'))
'd'

glom tries to get 'a' from target, but gets a KeyError. Rather than raise a PathAccessError as usual, glom coalesces into the next subspec, 'b'. The process repeats until it gets to 'c', which returns our value, 'd'. If our value weren’t present, we’d see:

>>> target = {}
>>> glom(target, Coalesce('a', 'b'))  
Traceback (most recent call last):
...
glom.CoalesceError: no valid values found. Tried ('a', 'b') and got (PathAccessError, PathAccessError) (at path [])

Same process, but because target is empty, we get a CoalesceError. If we want to avoid an exception, and we know which value we want by default, we can set default:

>>> target = {}
>>> glom(target, Coalesce('a', 'b', 'c'), default='d-fault')
'd-fault'

'a', 'b', and 'c' weren’t present so we got 'd-fault'.

Parameters

• subspecs – One or more glommable subspecs

• default – A value to return if no subspec results in a valid value

• default_factory – A callable whose result will be returned as a default

• skip – A value, tuple of values, or predicate function representing values to ignore

• skip_exc – An exception or tuple of exception types to catch and move on to the next subspec. Defaults to GlomError, the parent type of all glom runtime exceptions.

If all subspecs produce skipped values or exceptions, a CoalesceError will be raised. For more examples, check out the tutorial, which makes extensive use of Coalesce.

exception py2store.utils.glom.CoalesceError(coal_obj, skipped, path)

This GlomError subtype is raised from within a Coalesce spec’s processing, when none of the subspecs match and no default is provided.

The exception object itself keeps track of several values which may be useful for processing:

Parameters

• coal_obj (Coalesce) – The original failing spec, see Coalesce’s docs for details.

• skipped (list) – A list of ignored values and exceptions, in the order that their respective subspecs appear in the original coal_obj.

• path – Like many GlomErrors, this exception knows the path at which it occurred.

>>> target = {}
>>> glom(target, Coalesce('a', 'b'))  
Traceback (most recent call last):
...
glom.CoalesceError: no valid values found. Tried ('a', 'b') and got (PathAccessError, PathAccessError) ...

class py2store.utils.glom.Fill(spec=None)

A specifier type which switches to glom into “fill-mode”. For the spec contained within the Fill, glom will only interpret explicit specifier types (including T objects). Whereas the default mode has special interpretations for each of these builtins, fill-mode takes a lighter touch, making Fill great for “filling out” Python literals, like tuples, dicts, sets, and lists.

>>> target = {'data': [0, 2, 4]}
>>> spec = Fill((T['data'][2], T['data'][0]))
>>> glom(target, spec)
(4, 0)

As you can see, glom’s usual built-in tuple item chaining behavior has switched into a simple tuple constructor.

(Sidenote for Lisp fans: Fill is like glom’s quasi-quoting.)

exception py2store.utils.glom.GlomError

The base exception for all the errors that might be raised from glom() processing logic.

By default, exceptions raised from within functions passed to glom (e.g., len, sum, any lambda) will not be wrapped in a GlomError.

class py2store.utils.glom.Glommer(**kwargs)

All the wholesome goodness that it takes to make glom work. This type mostly serves to encapsulate the type registration context so that advanced uses of glom don’t need to worry about stepping on each other’s toes.

Glommer objects are lightweight and, once instantiated, provide the glom() method we know and love:

>>> glommer = Glommer()
>>> glommer.glom({}, 'a.b.c', default='d')
'd'
>>> Glommer().glom({'vals': list(range(3))}, ('vals', len))
3

Instances also provide register() method for localized control over type handling.

Parameters

register_default_types (bool) – Whether or not to enable the handling behaviors of the default glom(). These default actions include dict access, list and iterable iteration, and generic object attribute access. Defaults to True.

register(target_type, **kwargs)

Register target_type so glom() will know how to handle instances of that type as targets.

Parameters

• target_type (type) – A type expected to appear in a glom() call target

• get (callable) – A function which takes a target object and a name, acting as a default accessor. Defaults to getattr().

• iterate (callable) – A function which takes a target object and returns an iterator. Defaults to iter() if target_type appears to be iterable.

• exact (bool) – Whether or not to match instances of subtypes of target_type.

Note

The module-level register() function affects the module-level glom() function’s behavior. If this global effect is undesirable for your application, or you’re implementing a library, consider instantiating a Glommer instance, and using the register() and Glommer.glom() methods instead.

class py2store.utils.glom.Inspect(*a, **kw)

The Inspect specifier type provides a way to get visibility into glom’s evaluation of a specification, enabling debugging of those tricky problems that may arise with unexpected data.

Inspect can be inserted into an existing spec in one of two ways. First, as a wrapper around the spec in question, or second, as an argument-less placeholder wherever a spec could be.

Inspect supports several modes, controlled by keyword arguments. Its default, no-argument mode, simply echos the state of the glom at the point where it appears:

>>> target = {'a': {'b': {}}}
>>> val = glom(target, Inspect('a.b'))  # wrapping a spec
---
path:   ['a.b']
target: {'a': {'b': {}}}
output: {}
---

Debugging behavior aside, Inspect has no effect on values in the target, spec, or result.

Parameters

• echo (bool) – Whether to print the path, target, and output of each inspected glom. Defaults to True.

• recursive (bool) – Whether or not the Inspect should be applied at every level, at or below the spec that it wraps. Defaults to False.

• breakpoint (bool) – This flag controls whether a debugging prompt should appear before evaluating each inspected spec. Can also take a callable. Defaults to False.

• post_mortem (bool) – This flag controls whether exceptions should be caught and interactively debugged with pdb on inspected specs.

All arguments above are keyword-only to avoid overlap with a wrapped spec.

Note

Just like pdb.set_trace(), be careful about leaving stray Inspect() instances in production glom specs.

class py2store.utils.glom.Invoke(func)

Specifier type designed for easy invocation of callables from glom.

Parameters

func (callable) – A function or other callable object.

Invoke is similar to functools.partial(), but with the ability to set up a “templated” call which interleaves constants and glom specs.

For example, the following creates a spec which can be used to check if targets are integers:

>>> is_int = Invoke(isinstance).specs(T).constants(int)
>>> glom(5, is_int)
True

And this composes like any other glom spec:

>>> target = [7, object(), 9]
>>> glom(target, [is_int])
[True, False, True]

Another example, mixing positional and keyword arguments:

>>> spec = Invoke(sorted).specs(T).constants(key=int, reverse=True)
>>> target = ['10', '5', '20', '1']
>>> glom(target, spec)
['20', '10', '5', '1']

Invoke also helps with evaluating zero-argument functions:

>>> glom(target={}, spec=Invoke(int))
0

(A trivial example, but from timestamps to UUIDs, zero-arg calls do come up!)

Note

Invoke is mostly for functions, object construction, and callable objects. For calling methods, consider the T object.

constants(*a, **kw)

Returns a new Invoke spec, with the provided positional and keyword argument values stored for passing to the underlying function.

>>> spec = Invoke(T).constants(5)
>>> glom(range, (spec, list))
[0, 1, 2, 3, 4]

Subsequent positional arguments are appended:

>>> spec = Invoke(T).constants(2).constants(10, 2)
>>> glom(range, (spec, list))
[2, 4, 6, 8]

Keyword arguments also work as one might expect:

>>> round_2 = Invoke(round).constants(ndigits=2).specs(T)
>>> glom(3.14159, round_2)
3.14

constants() and other Invoke methods may be called multiple times, just remember that every call returns a new spec.

classmethod specfunc(spec)

Creates an Invoke instance where the function is indicated by a spec.

>>> spec = Invoke.specfunc('func').constants(5)
>>> glom({'func': range}, (spec, list))
[0, 1, 2, 3, 4]

specs(*a, **kw)

Returns a new Invoke spec, with the provided positional and keyword arguments stored to be interpreted as specs, with the results passed to the underlying function.

>>> spec = Invoke(range).specs('value')
>>> glom({'value': 5}, (spec, list))
[0, 1, 2, 3, 4]

Subsequent positional arguments are appended:

>>> spec = Invoke(range).specs('start').specs('end', 'step')
>>> target = {'start': 2, 'end': 10, 'step': 2}
>>> glom(target, (spec, list))
[2, 4, 6, 8]

Keyword arguments also work as one might expect:

>>> multiply = lambda x, y: x * y
>>> times_3 = Invoke(multiply).constants(y=3).specs(x='value')
>>> glom({'value': 5}, times_3)
15

specs() and other Invoke methods may be called multiple times, just remember that every call returns a new spec.

star(args=None, kwargs=None)

Returns a new Invoke spec, with args and/or kwargs specs set to be “starred” or “star-starred” (respectively)

>>> import os.path
>>> spec = Invoke(os.path.join).star(args='path')
>>> target = {'path': ['path', 'to', 'dir']}
>>> glom(target, spec)
'path/to/dir'

Parameters

• args (spec) – A spec to be evaluated and “starred” into the underlying function.

• kwargs (spec) – A spec to be evaluated and “star-starred” into the underlying function.

One or both of the above arguments should be set.

The star(), like other Invoke methods, may be called multiple times. The args and kwargs will be stacked in the order in which they are provided.

class py2store.utils.glom.Let(**kw)

This specifier type assigns variables to the scope.

>>> target = {'data': {'val': 9}}
>>> spec = (Let(value=T['data']['val']), {'val': S['value']})
>>> glom(target, spec)
{'val': 9}

class py2store.utils.glom.Literal(value)

Literal objects specify literal values in rare cases when part of the spec should not be interpreted as a glommable subspec. Wherever a Literal object is encountered in a spec, it is replaced with its wrapped value in the output.

>>> target = {'a': {'b': 'c'}}
>>> spec = {'a': 'a.b', 'readability': Literal('counts')}
>>> pprint(glom(target, spec))
{'a': 'c', 'readability': 'counts'}

Instead of accessing 'counts' as a key like it did with 'a.b', glom() just unwrapped the literal and included the value.

Literal takes one argument, the literal value that should appear in the glom output.

This could also be achieved with a callable, e.g., lambda x: 'literal_string' in the spec, but using a Literal object adds explicitness, code clarity, and a clean repr().

class py2store.utils.glom.Path(*path_parts)

Path objects specify explicit paths when the default 'a.b.c'-style general access syntax won’t work or isn’t desirable. Use this to wrap ints, datetimes, and other valid keys, as well as strings with dots that shouldn’t be expanded.

>>> target = {'a': {'b': 'c', 'd.e': 'f', 2: 3}}
>>> glom(target, Path('a', 2))
3
>>> glom(target, Path('a', 'd.e'))
'f'

Paths can be used to join together other Path objects, as well as T objects:

>>> Path(T['a'], T['b'])
T['a']['b']
>>> Path(Path('a', 'b'), Path('c', 'd'))
Path('a', 'b', 'c', 'd')

Paths also support indexing and slicing, with each access returning a new Path object:

>>> path = Path('a', 'b', 1, 2)
>>> path[0]
Path('a')
>>> path[-2:]
Path(1, 2)

from_t()

return the same path but starting from T

classmethod from_text(text)

Make a Path from .-delimited text:

>>> Path.from_text('a.b.c')
Path('a', 'b', 'c')

items()

Returns a tuple of (operation, value) pairs.

>>> Path(T.a.b, 'c', T['d']).items()
(('.', 'a'), ('.', 'b'), ('P', 'c'), ('[', 'd'))

values()

Returns a tuple of values referenced in this path.

>>> Path(T.a.b, 'c', T['d']).values()
('a', 'b', 'c', 'd')

exception py2store.utils.glom.PathAccessError(exc, path, part_idx)

This GlomError subtype represents a failure to access an attribute as dictated by the spec. The most commonly-seen error when using glom, it maintains a copy of the original exception and produces a readable error message for easy debugging.

If you see this error, you may want to:

• Check the target data is accurate using Inspect

• Catch the exception and return a semantically meaningful error message

• Use glom.Coalesce to specify a default

• Use the top-level default kwarg on glom()

In any case, be glad you got this error and not the one it was wrapping!

Parameters

• exc (Exception) – The error that arose when we tried to access path. Typically an instance of KeyError, AttributeError, IndexError, or TypeError, and sometimes others.

• path (Path) – The full Path glom was in the middle of accessing when the error occurred.

• part_idx (int) – The index of the part of the path that caused the error.

>>> target = {'a': {'b': None}}
>>> glom(target, 'a.b.c')  
Traceback (most recent call last):
...
glom.PathAccessError: could not access 'c', part 2 of Path('a', 'b', 'c'), got error: ...

class py2store.utils.glom.Spec(spec, scope=None)

Spec objects serve three purposes, here they are, roughly ordered by utility:

1. As a form of compiled or “curried” glom call, similar to Python’s built-in re.compile().

2. A marker as an object as representing a spec rather than a literal value in certain cases where that might be ambiguous.

3. A way to update the scope within another Spec.

In the second usage, Spec objects are the complement to Literal, wrapping a value and marking that it should be interpreted as a glom spec, rather than a literal value. This is useful in places where it would be interpreted as a value by default. (Such as T[key], Call(func) where key and func are assumed to be literal values and not specs.)

Parameters

• spec – The glom spec.

• scope (dict) – additional values to add to the scope when evaluating this Spec

class py2store.utils.glom.TType

T, short for “target”. A singleton object that enables object-oriented expression of a glom specification.

Note

T is a singleton, and does not need to be constructed.

Basically, think of T as your data’s stunt double. Everything that you do to T will be recorded and executed during the glom() call. Take this example:

>>> spec = T['a']['b']['c']
>>> target = {'a': {'b': {'c': 'd'}}}
>>> glom(target, spec)
'd'

So far, we’ve relied on the 'a.b.c'-style shorthand for access, or used the Path objects, but if you want to explicitly do attribute and key lookups, look no further than T.

But T doesn’t stop with unambiguous access. You can also call methods and perform almost any action you would with a normal object:

>>> spec = ('a', (T['b'].items(), list))  # reviewed below
>>> glom(target, spec)
[('c', 'd')]

A T object can go anywhere in the spec. As seen in the example above, we access 'a', use a T to get 'b' and iterate over its items, turning them into a list.

You can even use T with Call to construct objects:

>>> class ExampleClass(object):
...    def __init__(self, attr):
...        self.attr = attr
...
>>> target = {'attr': 3.14}
>>> glom(target, Call(ExampleClass, kwargs=T)).attr
3.14

On a further note, while lambda works great in glom specs, and can be very handy at times, T and Call eliminate the need for the vast majority of lambda usage with glom.

Unlike lambda and other functions, T roundtrips beautifully and transparently:

>>> T['a'].b['c']('success')
T['a'].b['c']('success')

T-related access errors raise a PathAccessError during the glom() call.

Note

While T is clearly useful, powerful, and here to stay, its semantics are still being refined. Currently, operations beyond method calls and attribute/item access are considered experimental and should not be relied upon.

class py2store.utils.glom.TargetRegistry(register_default_types=True)

responsible for registration of target types for iteration and attribute walking

get_handler(op, obj, path=None, raise_exc=True)

for an operation and object instance, obj, return the closest-matching handler function, raising UnregisteredTarget if no handler can be found for obj (or False if raise_exc=False)

register_op(op_name, auto_func=None, exact=False)

add operations beyond the builtins (‘get’ and ‘iterate’ at the time of writing).

auto_func is a function that when passed a type, returns a handler associated with op_name if it’s supported, or False if it’s not.

See glom.core.register_op() for the global version used by extensions.

exception py2store.utils.glom.UnregisteredTarget(op, target_type, type_map, path)

This GlomError subtype is raised when a spec calls for an unsupported action on a target type. For instance, trying to iterate on an non-iterable target:

>>> glom(object(), ['a.b.c'])  
Traceback (most recent call last):
...
glom.UnregisteredTarget: target type 'object' not registered for 'iterate', expected one of registered types: (...)

It should be noted that this is a pretty uncommon occurrence in production glom usage. See the setup-and-registration section for details on how to avoid this error.

An UnregisteredTarget takes and tracks a few values:

Parameters

• op (str) – The name of the operation being performed (‘get’ or ‘iterate’)

• target_type (type) – The type of the target being processed.

• type_map (dict) – A mapping of target types that do support this operation

• path – The path at which the error occurred.

py2store.utils.glom.glom(target, spec, **kwargs)

Access or construct a value from a given target based on the specification declared by spec.

Accessing nested data, aka deep-get:

>>> target = {'a': {'b': 'c'}}
>>> glom(target, 'a.b')
'c'

Here the spec was just a string denoting a path, 'a.b.. As simple as it should be. The next example shows how to use nested data to access many fields at once, and make a new nested structure.

Constructing, or restructuring more-complicated nested data:

>>> target = {'a': {'b': 'c', 'd': 'e'}, 'f': 'g', 'h': [0, 1, 2]}
>>> spec = {'a': 'a.b', 'd': 'a.d', 'h': ('h', [lambda x: x * 2])}
>>> output = glom(target, spec)
>>> pprint(output)
{'a': 'c', 'd': 'e', 'h': [0, 2, 4]}

glom also takes a keyword-argument, default. When set, if a glom operation fails with a GlomError, the default will be returned, very much like dict.get():

>>> glom(target, 'a.xx', default='nada')
'nada'

The skip_exc keyword argument controls which errors should be ignored.

>>> glom({}, lambda x: 100.0 / len(x), default=0.0, skip_exc=ZeroDivisionError)
0.0

Parameters

• target (object) – the object on which the glom will operate.

• spec (object) – Specification of the output object in the form of a dict, list, tuple, string, other glom construct, or any composition of these.

• default (object) – An optional default to return in the case an exception, specified by skip_exc, is raised.

• skip_exc (Exception) – An optional exception or tuple of exceptions to ignore and return default (None if omitted). If skip_exc and default are both not set, glom raises errors through.

• scope (dict) – Additional data that can be accessed via S inside the glom-spec.

It’s a small API with big functionality, and glom’s power is only surpassed by its intuitiveness. Give it a whirl!

py2store.utils.glom.is_iterable(x)

Similar in nature to callable(), is_iterable returns True if an object is `iterable`_, False if not. >>> is_iterable([]) True >>> is_iterable(1) False

py2store.utils.glom.make_sentinel(name='_MISSING', var_name=None)

Creates and returns a new instance of a new class, suitable for usage as a “sentinel”, a kind of singleton often used to indicate a value is missing when None is a valid input.

Parameters

• name (str) – Name of the Sentinel

• var_name (str) – Set this name to the name of the variable in its respective module enable pickleability.

>>> make_sentinel(var_name='_MISSING')
_MISSING

The most common use cases here in boltons are as default values for optional function arguments, partly because of its less-confusing appearance in automatically generated documentation. Sentinels also function well as placeholders in queues and linked lists.

Note

By design, additional calls to make_sentinel with the same values will not produce equivalent objects.

>>> make_sentinel('TEST') == make_sentinel('TEST')
False
>>> type(make_sentinel('TEST')) == type(make_sentinel('TEST'))
False

py2store.utils.glom.register(target_type, **kwargs)

Register target_type so glom() will know how to handle instances of that type as targets.

Parameters

• target_type (type) – A type expected to appear in a glom() call target

• get (callable) – A function which takes a target object and a name, acting as a default accessor. Defaults to getattr().

• iterate (callable) – A function which takes a target object and returns an iterator. Defaults to iter() if target_type appears to be iterable.

• exact (bool) – Whether or not to match instances of subtypes of target_type.

Note

The module-level register() function affects the module-level glom() function’s behavior. If this global effect is undesirable for your application, or you’re implementing a library, consider instantiating a Glommer instance, and using the register() and Glommer.glom() methods instead.

py2store.utils.glom.register_op(op_name, **kwargs)

For extension authors needing to add operations beyond the builtin ‘get’ and ‘iterate’ to the default scope. See TargetRegistry for more details.