> For the complete documentation index, see [llms.txt](https://www.csvpath.org/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://www.csvpath.org/getting-started/more-csv-and-excel-validation/your-first-validation-the-easy-way.md).

# Your First Validation, The Easy Way

CsvPath Language offers both rules-based validation and schemas. Validation rules are powerful. A rule can do things that a schema can't do. But sometimes just clarifying the shape of the data is enough. Both approaches are important tools. 

CsvPath's claim to fame is the power of rules-based validation — no other validation language offers the same capabilities for delimited, tabular data. But CsvPath is also really good at structural validation. You can see more examples and [read about the difference between these approaches here](/topics/higher-level-topics/validation/schemas-or-rules.md).

Here's our First Validation example again, this time using a simple schema. We'll use the `line()` function to specify what each line of data looks like in a valid CSV or Excel file. This snippet is the whole validation:

```xquery
    line(
        string.notnone("firstname"),
        string.notnone("lastname", 30),
        string("say")
    )
```

We expect exactly three headers and require two of them to always have values.

We could run this using the CLI, but let's see how to do it with Python.

```python
from csvpath import CsvPath

csvpath = """
    ~ 
     id: First Validation, Simplified!
     description: Check if a file is valid
     validation-mode: print, no-raise, fail 
    ~
    $trivial.csv[*][
    line(
        string.notnone("firstname"),
        string.notnone("lastname", 30),
        string("say")
    )
]"""

path = CsvPath().parse(csvpath)
path.fast_forward()
if not path.is_valid:
    print(f"The file is invalid")
```

Two lines to run the validation. Two lines to print a warning if the CSV file is invalid. Simple!

We also added some optional metadata and a mode configuration in a comment. The comment is the part between the `~` characters.

In the metadata we are saying that the `id` field will become the csvpath's `identity`. The identity is available on the `CsvPath` instance's `identity` property. It will be used in printing out any built-in validation errors. 

The `description` is ours to use as we wish—it is a user-defined field. And the `validation-mode` is a setting that tells the `CsvPath` instance what to do when there is a validation error. In this case we want to print errors, but not raise exceptions, and we want the file to be marked as invalid if there are errors. We sometimes call this failing the file. 

There's a lot more you could do, of course. This is barely the tip of the iceberg. Keep reading and experimenting!