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cerberus-list-schema-1.0.3
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مشاهده بیشترتوضیحات
Cerburus based validation extended to support list schemas and list transposition to dictionary and python objects
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | cerberus-list-schema-1.0.3 |
| نام | cerberus-list-schema |
| نسخه کتابخانه | 1.0.3 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Amy Summers |
| ایمیل نویسنده | amy@sakuradigital.co.uk |
| آدرس صفحه اصلی | https://github.com/Firepubes/cerberus-list-schema |
| آدرس اینترنتی | https://pypi.org/project/cerberus-list-schema/ |
| مجوز | MIT |
[](https://badge.fury.io/py/cerberus-list-schema)
[](https://travis-ci.org/Fireclunge/cerberus-list-schema)
[](https://github.com/psf/black)
**Cerberus List Schema** is a **Cerberus based validation library with extended methods** to support list schemas as well
as list transposition to dictionary and python objects.
- List/array schema support
- Transposition of lists to python objects via schemas
- Support for missing values in document
## Installation
Cerberus List Schema can be installed using pip.
```
$ pip install cerberus-list-schema
```
## Extensions
### Validation
```python
>>> schema = {
>>> "type": "list",
>>> "items": [{"type": "string"}, {"type": "integer", "min": 20}],
>>> }
```
##### Simple validation
Lists can now be validated out of context of a dictionary
```python
>>> document = ["Apples", 40]
>>> v = Validator(schema)
>>> v.validate(document)
True
```
... and usual cerberus validation rules still apply
```python
>>> document = ["Apples", 15]
>>> v.validate(document)
False
>>> v.errors
{'_schema': [{1: ['min value is 20']}]}
```
##### Allow incomplete documents
In cerberus, documents that are missing information specified in a list schema will fail.
Using Cerberus List Schema you can pass `allow_list_missing=True` to a Validator object to enable incomplete lists.
```python
>>> document = ["Apples"]
>>> v.validate(document)
False
>>> v.errors
{'_schema': ['length of list should be 2, it is 1']}
>>> v = Validator(schema, allow_list_missing=True)
>>> v.validate(document)
True
```
### Normalization
##### Normalization as dict
Lists can now be normalized as dict additional to the standard cerberus validation.
By default they are given a key equalled to their list index.
```python
>>> document = {"produce": ["Apple", 5, "High"]}
>>> schema = {
>>> "produce": {
>>> "type": "list",
>>> "items": [
>>> {"type": "string"},
>>> {"type": "integer", "min": 0},
>>> {"type": "string"},
>>> ],
>>> }
>>> }
>>> v = Validator(schema)
>>> v.normalized_as_dict(document)
{"fruits": {0: "Apple", 1: 5, 2: "High"}}
```
##### Naming indexes
However by using the `name` rule, lists can be assigned to a namable dict. Note that this is different to `rename`
and should be preferred when using the dictionary normalization as rename can produce adverse effects.
```python
>>> document = {"produce": ["Apple", 5, "High"]}
>>> schema = {
>>> "produce": {
>>> "type": "list",
>>> "name": "fruits",
>>> "items": [
>>> {"name": "type", "type": "string"},
>>> {"name": "count", "type": "integer", "min": 0},
>>> {"name": "quality", "type": "string"},
>>> ],
>>> }
>>> }
>>> v = Validator(schema)
>>> v.normalized_as_dict(document)
{'fruits': {'type': 'Apple', 'count': 5, 'quality': 'High'}}
```
##### Allowing name conflicts
By default, conflicting names will throw an error.
However, `allow_name_conflicts` can be specified to ignore the error.
In this case, previous assignments will be overwritten without error
```python
>>> document = {"produce": ["Apple", "Orange"]}
>>> schema = {
>>> "produce": {
>>> "type": "list",
>>> "items": [
>>> {"name": "fruit_type", "type": "string"},
>>> {"name": "fruit_type", "type": "string"},
>>> ],
>>> }
>>> }
>>> v = Validator(schema)
>>> v.normalized_as_dict(document)
AttributeError: `name` rule (`fruit_type`) already in use by another field
>>> v.normalized_as_dict(document, allow_name_conflicts=True)
{'produce': {'type': 'Orange'}}
```
### Object Mapping
Lists can now be normalized as dict additional to the standard cerberus validation.
By default they are given a key equalled to their list index. However `name` may be used to rename
object property to that provided. (ensuring the name is a valid python variable name)
```python
>>> document = {"produce": ["Apple", 5, "High"], "supplier": ["Greg", "United Kingdom", 7.34]}
>>> schema = {
>>> "produce": {
>>> "type": "list",
>>> "name": "fruits",
>>> "items": [
>>> {"name": "type", "type": "string"},
>>> {"name": "count", "type": "integer", "min": 0},
>>> {"name": "quality", "type": "string"},
>>> ],
>>> },
>>> "supplier": {
>>> "type": "list",
>>> "items": [
>>> {"type": "string"},
>>> {"type": "string"},
>>> {"type": "string", "coerce": int},
>>> ],
>>> },
>>> }
>>> v = Validator(schema)
>>> obj = v.normalized_as_object(document)
>>> obj.fruits.type # note produce has been renamed to fruits
'Apple'
>>> obj.fruits.quality
'High'
>>> obj.supplier[0]
'Greg'
>>> obj.supplier[2] # w/ coerce as int rule applied
7
```
##### Allowing callable properties for unassigned names
Array values without a `name` property can also be callable by using `callable_numbers`. This is places an underscore
before the key index such that it can be called as a property of an object rather than by index.
```python
>>> document = ["Greg", "United Kingdom", 7.34]
>>> schema = {
>>> "type": "list",
>>> "items": [
>>> {"type": "string"},
>>> {"type": "string", "name": "country"},
>>> {"type": "string", "coerce": int},
>>> ],
>>>}
>>> v = Validator(schema)
>>> obj = v.normalized_as_object(document, callable_numbers=True)
>>> obj._0
'Greg'
>>> obj._1 # value renamed to country
>>> obj.country
'United Kingdom'
>>> obj._2
7
```
## Cerberus
More information about Cerberus and its validators can be found on their GitHub page @ https://github.com/pyeve/cerberus
Complete documentation for Cerberus is available at http://docs.python-cerberus.org
نیازمندی
| مقدار | نام |
|---|---|
| - | cerberus |
| - | munch |
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.4 | Python |
نحوه نصب
نصب پکیج whl cerberus-list-schema-1.0.3:
pip install cerberus-list-schema-1.0.3.whl
نصب پکیج tar.gz cerberus-list-schema-1.0.3:
pip install cerberus-list-schema-1.0.3.tar.gz