Skip to main content

Vladiate is a strict validation tool for CSV files

Project description

Vladiate
========

Description
-----------

Vladiate helps you write explicit assertions for every field of your CSV
file.

Features
--------

**Write validation schemas in plain-old Python**
No UI, no XML, no JSON, just code.

**Write your own validators**
Vladiate comes with a few by default, but there's no reason you can't write
your own.

**Validate multiple files at once**
Either with the same schema, or different ones.

Documentation
-------------

Installation
~~~~~~~~~~~~

Installing:

::

$ pip install vladiate

Quickstart
~~~~~~~~~~

Below is an example of a ``vladfile.py``

.. code:: python

from vladiate import Vlad
from vladiate.validators import UniqueValidator, SetValidator
from vladiate.inputs import LocalFile

class YourFirstValidator(Vlad):
source = LocalFile('vampires.csv')
validators = {
'Column A': [
UniqueValidator()
],
'Column B': [
SetValidator(['Vampire', 'Not A Vampire'])
]
}

Here we define a number of validators for a local file ``vampires.csv``,
which would look like this:

::

Column A,Column B
Vlad the Impaler,Not A Vampire
Dracula,Vampire
Count Chocula,Vampire

We then run ``vladiate`` in the same directory as your ``.csv`` file:

::

$ vladiate

And get the following output:

::

Validating YourFirstValidator(source=LocalFile('vampires.csv'))
Passed! :)

Handling Changes
^^^^^^^^^^^^^^^^

Let's imagine that you've gotten a new CSV file,
``potential_vampires.csv``, that looks like this:

::

Column A,Column B
Vlad the Impaler,Not A Vampire
Dracula,Vampire
Count Chocula,Vampire
Ronald Reagan,Maybe A Vampire

If we were to update our first validator to use this file as follows:

::

- class YourFirstValidator(Vlad):
- source = LocalFile('vampires.csv')
+ class YourFirstFailingValidator(Vlad):
+ source = LocalFile('potential_vampires.csv')

we would get the following error:

::

Validating YourFirstFailingValidator(source=LocalFile('potential_vampires.csv'))
Failed :(
SetValidator failed 1 time(s) on field: 'Column B'
Invalid fields: ['Maybe A Vampire']

And we would know that we'd either need to sanitize this field, or add
it to the ``SetValidator``.

Starting from scratch
^^^^^^^^^^^^^^^^^^^^^

To make writing a new ``vladfile.py`` easy, Vladiate will give
meaningful error messages.

Given the following as ``real_vampires.csv``:

::

Column A,Column B,Column C
Vlad the Impaler,Not A Vampire
Dracula,Vampire
Count Chocula,Vampire
Ronald Reagan,Maybe A Vampire

We could write a bare-bones validator as follows:

.. code:: python

class YourFirstEmptyValidator(Vlad):
source = LocalFile('real_vampires.csv')
validators = {}

Running this with ``vladiate`` would give the following error:

::

Validating YourFirstEmptyValidator(source=LocalFile('real_vampires.csv'))
Missing...
Missing validators for:
'Column A': [],
'Column B': [],
'Column C': [],

Vladiate expects something to be specified for every column, *even if it
is an empty list* (more on this later). We can easily copy and paste
from the error into our ``vladfile.py`` to make it:

.. code:: python

class YourFirstEmptyValidator(Vlad):
source = LocalFile('real_vampires.csv')
validators = {
'Column A': [],
'Column B': [],
'Column C': [],
}

When we run *this* with ``vladiate``, we get:

::

Validating YourSecondEmptyValidator(source=LocalFile('real_vampires.csv'))
Failed :(
EmptyValidator failed 4 time(s) on field: 'Column A'
Invalid fields: ['Dracula', 'Vlad the Impaler', 'Count Chocula', 'Ronald Reagan']
EmptyValidator failed 4 time(s) on field: 'Column B'
Invalid fields: ['Maybe A Vampire', 'Not A Vampire', 'Vampire']
EmptyValidator failed 4 time(s) on field: 'Column C'
Invalid fields: ['Real', 'Not Real']

This is because Vladiate interprets an empty list of validators for a
field as an ``EmptyValidator``, which expects an empty string in every
field. This helps us make meaningful decisions when adding validators to
our ``vladfile.py``. It also ensures that we are not forgetting about a
column or field which is not empty.

Built-in Validators
^^^^^^^^^^^^^^^^^^^

Vladiate comes with a few common validators built-in:

*class* ``Validator``

Generic validator. Should be subclassed by any custom validators. Not to
be used directly.

*class* ``CastValidator``

Generic "can-be-cast-to-x" validator. Should be subclassed by any
cast-test validator. Not to be used directly.

*class* ``IntValidator``

Validates whether a field can be cast to an ``int`` type or not.

:``empty_ok=False``:
Specify whether a field which is an empty string should be ignored.

*class* ``FloatValidator``

Validates whether a field can be cast to an ``float`` type or not.

:``empty_ok=False``:
Specify whether a field which is an empty string should be ignored.

*class* ``SetValidator``

Validates whether a field is in the specified set of possible fields.

:``valid_set=[]``:
List of valid possible fields
:``empty_ok=False``:
Implicity adds the empty string to the specified set.

*class* ``UniqueValidator``

Ensures that a given field is not repeated in any other column. Can
optionally determine "uniqueness" with other fields in the row as well via
``unique_with``.

:``unique_with=[]``:
List of field names to make the primary field unique with.

*class* ``RegexValidator``

Validates whether a field matches the given regex using `re.match()`.

:``pattern=r'di^'``:
The regex pattern. Fails for all fields by default.

*class* ``EmptyValidator``

Ensure that a field is always empty. Essentially the same as an empty
``SetValidator``. This is used by default when a field has no
validators.

*class* ``Ignore``

Always passes validation. Used to explicity ignore a given column.

Built-in Input Types
^^^^^^^^^^^^^^^^^^^^

Vladiate comes with the following input types:

*class* ``VladInput``

Generic input. Should be subclassed by any custom inputs. Not to be used
directly.

*class* ``LocalFile``

Read from a file local to the filesystem.

:``filename``:
Path to a local CSV file.

*class* ``S3File``

Read from a file in S3. Uses the `boto <https://github.com/boto/boto>`_
library. Optionally can specify either a full path, or a bucket/key pair.

:``path=None``:
A full S3 filepath (e.g., ``s3://foo.bar/path/to/file.csv``)

:``bucket=None``:
S3 bucket. Must be specified with a ``key``.

:``key=None``:
S3 key. Must be specified with a ``bucket``.

Running Vlads Programatically
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

*class* ``Vlad``

Initialize a Vlad programatically

:``source``:
Required. Any `VladInput`.

:``validators={}``:
List of validators. Optional, defaults to the class variable `validators`
if set, otherwise uses `EmptyValidator` for all fields.

For example:

.. code:: python

from vladiate import Vlad
from vladiate.inputs import LocalFile
Vlad(source=LocalFile('path/to/local/file.csv').validate()

Testing
~~~~~~~

To run the tests

::

python setup.py test

Authors
-------

- `Dustin Ingram <https://github.com/di>`__
- `Clara Bennett<https://github.com/csojinb>`__

License
-------

Open source MIT license.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

vladiate-0.0.8.tar.gz (13.3 kB view details)

Uploaded Source

File details

Details for the file vladiate-0.0.8.tar.gz.

File metadata

  • Download URL: vladiate-0.0.8.tar.gz
  • Upload date:
  • Size: 13.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for vladiate-0.0.8.tar.gz
Algorithm Hash digest
SHA256 ba6d566d756fe8e2c4df640879113862f67d7015c1635bfa189de20777b25ab4
MD5 514c3235252de75a3032c4dc35943403
BLAKE2b-256 988d91bb04a06773303cdd3ab20994480561a7079dcf98acaa120047e88126d4

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page