# Vedro Valera Validator
[](https://codecov.io/gh/vedro-universe/vedro-valera-validator)
[](https://pypi.python.org/pypi/vedro-valera-validator/)
[](https://pypi.python.org/pypi/vedro-valera-validator/)
[](https://pypi.python.org/pypi/vedro-valera-validator/)
[vedro-valera-validator](https://pypi.org/project/vedro-valera-validator/) is a plugin for the Vedro framework that utilizes the [valera validator](https://pypi.org/project/valera), a package designed for data validation based on [d42 (district42) schemas](https://d42.vedro.io/docs/quick-start). Valera validator provides a simple yet powerful approach to ensure your data aligns perfectly with your expectations.
## Installation
<details open>
<summary>Quick</summary>
<p>
For a quick installation, you can use a plugin manager as follows:
```shell
$ vedro plugin install vedro-valera-validator
```
</p>
</details>
<details>
<summary>Manual</summary>
<p>
To install manually, follow these steps:
1. Install the package using pip:
```shell
$ pip3 install vedro-valera-validator
```
2. Next, activate the plugin in your `vedro.cfg.py` configuration file:
```python
# ./vedro.cfg.py
import vedro
import vedro_valera_validator
class Config(vedro.Config):
class Plugins(vedro.Config.Plugins):
class ValeraValidator(vedro_valera_validator.ValeraValidator):
enabled = True
```
</p>
</details>
## Usage
Here is an example scenario demonstrating how to decode a base64 encoded string:
```python
# ./scenarios/decode_base64_encoded_string.py
import vedro
from base64 import b64decode
from d42 import schema
class Scenario(vedro.Scenario):
subject = "decode base64 encoded string"
def given(self):
self.encoded = "Y3VjdW1iZXI="
def when(self):
self.result = {
"result": b64decode(self.encoded)
}
def then(self):
assert self.result == schema.dict({
"result": schema.bytes(b"banana")
})
```
Run the test using the command:
```shell
$ vedro run
```
If the expected and actual results don't match, a `ValidationException` will be raised, as illustrated below:
```shell
ValidationException:
- Value <class 'bytes'> at _['result'] must be equal to b'banana', but b'cucumber' given
```
## Additional Resources
For a detailed guide and further information, check out the [documentation](https://vedro.io/docs/integrations/valera-validator).
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"description": "# Vedro Valera Validator\n\n[](https://codecov.io/gh/vedro-universe/vedro-valera-validator)\n[](https://pypi.python.org/pypi/vedro-valera-validator/)\n[](https://pypi.python.org/pypi/vedro-valera-validator/)\n[](https://pypi.python.org/pypi/vedro-valera-validator/)\n\n[vedro-valera-validator](https://pypi.org/project/vedro-valera-validator/) is a plugin for the Vedro framework that utilizes the [valera validator](https://pypi.org/project/valera), a package designed for data validation based on [d42 (district42) schemas](https://d42.vedro.io/docs/quick-start). Valera validator provides a simple yet powerful approach to ensure your data aligns perfectly with your expectations.\n\n## Installation\n\n<details open>\n<summary>Quick</summary>\n<p>\n\nFor a quick installation, you can use a plugin manager as follows:\n\n```shell\n$ vedro plugin install vedro-valera-validator\n```\n\n</p>\n</details>\n\n<details>\n<summary>Manual</summary>\n<p>\n\nTo install manually, follow these steps:\n\n1. Install the package using pip:\n\n```shell\n$ pip3 install vedro-valera-validator\n```\n\n2. Next, activate the plugin in your `vedro.cfg.py` configuration file:\n\n```python\n# ./vedro.cfg.py\nimport vedro\nimport vedro_valera_validator\n\nclass Config(vedro.Config):\n\n class Plugins(vedro.Config.Plugins):\n\n class ValeraValidator(vedro_valera_validator.ValeraValidator):\n enabled = True\n```\n\n</p>\n</details>\n\n## Usage\n\nHere is an example scenario demonstrating how to decode a base64 encoded string:\n\n```python\n# ./scenarios/decode_base64_encoded_string.py\nimport vedro\nfrom base64 import b64decode\nfrom d42 import schema\n\nclass Scenario(vedro.Scenario):\n subject = \"decode base64 encoded string\"\n\n def given(self):\n self.encoded = \"Y3VjdW1iZXI=\"\n\n def when(self):\n self.result = {\n \"result\": b64decode(self.encoded)\n }\n\n def then(self):\n assert self.result == schema.dict({\n \"result\": schema.bytes(b\"banana\")\n })\n```\n\nRun the test using the command:\n\n```shell\n$ vedro run\n```\n\nIf the expected and actual results don't match, a `ValidationException` will be raised, as illustrated below:\n\n```shell\nValidationException:\n - Value <class 'bytes'> at _['result'] must be equal to b'banana', but b'cucumber' given\n ```\n\n## Additional Resources\n\nFor a detailed guide and further information, check out the [documentation](https://vedro.io/docs/integrations/valera-validator).\n",
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