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Project description
jashin
Assorted Python utilities.
jashin.dictattr module
jashin.dictattr
provides ItemAttr
and DictModel
to define class that wraps dictionary objects.
To wrap a dictionary like this,
userdict = {
"name": "test user",
"age": 20
}
You can use ItemAttr
and DictModel
as follows.
from jashin.dictattr import ItemAttr, DictModel
from dateutil.parser import parse as dateparse
class User(DictModel):
name = ItemAttr()
age = ItemAttr()
user = User(userdict)
print(user.name, user.created)
user.age = 30 # updates userdict
pritn(userdict['age']) # prints 30
ItemAttr
supports nested objects.
companydict = {
"CEO": {
name: "A CEO",
age: "21",
}
"COO": {
name: "A COO",
age: "31",
}
}
To wrap a dictionary above, you can provide Company
class.
class Company(DictModel):
CEO = ItemAttr(User)
COO = ItemAttr(User)
company = Company(companydict)
print(company.CEO.name) # prints 'A CEO'
DictModel
class is not mandatory, but is provied to avoid boilerplate code. ItemAttr
works any classes with __dictattr_get__
method.
class User:
name = ItemAttr()
age = ItemAttr()
def __init__(self, record):
self._recdict = record
def __dictattr_get__(self):
"Called by ItemAttr object to get dictionary"
return self._recdict
Type annotation is supported.
class User(DictModel):
name = ItemAttr[str]() # Explicity specify type
age = ItemAttr(int) # Inferred from `int` function.
user.name = "name" # OK
user.age = "30" # Incompatible types in assignment
# The right hand side expression has type "str",
# but 'age' attribute has type "int".
jashin.elapsed module
The jashin.elapsed
measures elapsed time of arbitrary sections.
Sections can be specified by with
block.
>>> from jashin.elapsed import Elapsed
>>> e = Elapsed()
>>> def test():
... a = 1
... for i in range(10):
... with e("section 1"):
... a += 1
...
... with e("section 2"):
... a += 1
...
>>> test()
>>> e.print()
section 1: n:10 sum:0.00002 ave:0.00000
section 2: n:10 sum:0.00002 ave:0.00000
Or by pair of begin(name)
and end()
methods.
>>> from jashin.elapsed import Elapsed
>>> e = Elapsed()
>>> def test2():
... a = 1
... for i in range(10):
... e.begin("section A"):
... a += 1
... e.end()
...
... e.begin("section B"):
... a += 1
... e.end()
...
>>> test2()
>>> e.print()
section A: n:10 sum:0.00002 ave:0.00000
section B: n:10 sum:0.00002 ave:0.00000
jashin.jsondefault module
To serialize arbitrary object into JSON, you should define default
function.
def converter(obj):
if isinstance(obj, set):
return list[obj]
if isinstance(obj, datetime):
return obj.isoformat()
...
print(json.dumps(obj, default=converter))
This is tedious. The jashin.jsondefault.common
provides common functionary to make popular types of objects JSON serializable.
from jashin import jsondefault
repo = jsondefault.common()
print(json.dumps(obj, default=repo)
Since jashin.jsondefault.common
is a single-dispatch generic function, you can extend it to convert your custom objects.
from jashin import jsondefault
@dataclass
def Foo:
attr1:int = 100
repo = jsondefault.common()
@repo.register(Foo)
def conv_foo(obj):
return {'attr1': obj.foo}
print(json.dumps(object, default=repo)
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