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---
title: Why does StrictYAML make you define a schema in Python - a Turing-complete language?
---
StrictYAML defines schemas in Python (i.e. Turing-complete) code. For example:
```python
Map({"name": Str(), "email": Str()})
```
Instead of:
```yaml
type: map
mapping:
"name":
type: str
required: yes
"email":
type: str
required: yes
```
There are some trade offs here:
Schema definition in a non-Turing-complete language like YAML makes
the schema programming language independent and gives it more
potential for being read and understood by non-programmers.
However, schema definition in a non-Turing-complete language also
restricts and makes certain use cases impossible or awkward.
Some use cases I came across included:
- Being able to import pycountry's country list and restrict "country: " to valid country names.
- Being able to implement a schema that validated date/time scalar values against the specific date/time parser I wanted.
- Being able to revalidate sections of the document on a 'second pass' that used new data - e.g. a list in one part of the document is restricted to items which come from another part.
## Counterarguments
- <https://github.com/crdoconnor/strictyaml/issues/16>
|
