Audit

Enables auditing for a model.

1. Overview
2. audit_model_class
3. exclude_columns
4. mask_columns
5. foreign_column_name
6. readable_child_columns
7. where
8. default
9. is_readable
10. is_temporary
11. on_change_pre_save
12. on_change_post_save
13. on_change_save_finished

Overview

Specify the audit class to use and attach this column to your model. Everytime the model is created/updated/deleted, the audit class will record the action and the changes. Your audit model must have the following columns:

Name	type
class	str
resource_id	str
action	str
data	json
created_at	created

The names are not currently adjustable.

1. Class is a string that records the name of the class that the action happened for. This allows you to use the same audit class for multiple, different, resources.
2. resource_id is the id of the record which the audit entry is for.
3. Action is the actual action taken (create/update/delete)
4. Data is a serialized record of what columns in the record were changed (both their previous and new values)
5. The time the audit record was created

audit_model_class

Required

The model class for the destination that will store the audit data.

exclude_columns

Optional

A list of columns that shouldn’t be copied into the audit record.

To be clear, these are columns from the model class that the audit column is attached to. If only excluded columns are updated then no audit record will be created.

mask_columns

Optional

A list of columns that should be masked when copied into the audit record.

With masked columns a generic value is placed in the audit record (e.g. XXXXX) which denotes that the column was changed, but it does not record either old or new values.

foreign_column_name

Optional

The name of the column in the child table that connects it back to the parent.

By default this is populated by converting the model class name from TitleCase to snake_case and appending _id. So, if the model class is called ProductCategory, this becomes product_category_id. This MUST correspond to the actual name of a column in the child table. This is used so that the parent can find its child records.

Example:

import clearskies

class Product(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    name = clearskies.columns.String()
    my_parent_category_id = clearskies.columns.String()

class Category(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    name = clearskies.columns.String()
    products = clearskies.columns.HasMany(Product, foreign_column_name="my_parent_category_id")

def test_has_many(products: Product, categories: Category):
    toys = categories.create({"name": "Toys"})

    fidget_spinner = products.create({"name": "Fidget Spinner", "my_parent_category_id": toys.id})
    crayon = products.create({"name": "Crayon", "my_parent_category_id": toys.id})
    ball = products.create({"name": "Ball", "my_parent_category_id": toys.id})

    return toys.products.sort_by("name", "asc")

cli = clearskies.contexts.Cli(
    clearskies.endpoints.Callable(
        test_has_many,
        model_class=Product,
        readable_column_names=["id", "name"],
    ),
    classes=[Category, Product],
)

if __name__ == "__main__":
    cli()

Compare to the first example for the HasMany class. In that case, the column in the product model which contained the category id was category_id, and the products column didn’t have to specify the foreign_column_name (since the column name followed the naming rule). As a result, category.products was able to find all children of a given category. In this example, the name of the column in the product model that contains the category id was changed to my_parent_category_id. Since this no longer matches the naming convention, we had to specify foreign_column_name="my_parent_category_id" in Category.products, in order for the HasMany column to find the children. Therefore, when invoked it returns the same thing:

{
    "status": "success",
    "error": "",
    "data": [
        {
            "id": "3cdd06e0-b226-4a4a-962d-e8c5acc759ac",
            "name": "Ball"
        },
        {
            "id": "debc7968-976a-49cd-902c-d359a8abd032",
            "name": "Crayon"
        },
        {
            "id": "0afcd314-cdfc-4a27-ac6e-061b74ee5bf9",
            "name": "Fidget Spinner"
        }
    ],
    "pagination": {},
    "input_errors": {}
}

readable_child_columns

Optional

Columns from the child table that should be included when converting this column to JSON.

where

Optional

Additional conditions to add to searches on the child table.

import clearskies

class Order(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    total = clearskies.columns.Float()
    status = clearskies.columns.Select(["Open", "In Progress", "Closed"])
    user_id = clearskies.columns.String()

class User(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    name = clearskies.columns.String()
    orders = clearskies.columns.HasMany(Order, readable_child_column_names=["id", "status"])
    large_open_orders = clearskies.columns.HasMany(
        Order,
        readable_child_column_names=["id", "status"],
        where=[Order.status.equals("Open"), "total>100"],
    )

def test_has_many(users: User, orders: Order):
    user = users.create({"name": "Bob"})

    order_1 = orders.create({"status": "Open", "total": 25.50, "user_id": user.id})
    order_2 = orders.create({"status": "Closed", "total": 35.50, "user_id": user.id})
    order_3 = orders.create({"status": "Open", "total": 125, "user_id": user.id})
    order_4 = orders.create({"status": "In Progress", "total": 25.50, "user_id": user.id})

    return user.large_open_orders

cli = clearskies.contexts.Cli(
    clearskies.endpoints.Callable(
        test_has_many,
        model_class=Order,
        readable_column_names=["id", "total", "status"],
        return_records=True,
    ),
    classes=[Order, User],
)

if __name__ == "__main__":
    cli()

The above example shows two different ways of adding conditions. Note that where can be either a list or a single condition. If you invoked this you would get:

{
    "status": "success",
    "error": "",
    "data": [
        {
            "id": "6ad99935-ac9a-40ef-a1b2-f34538cc6529",
            "total": 125.0,
            "status": "Open"
        }
    ],
    "pagination": {},
    "input_errors": {}
}

Finally, an individual condition can also be a callable that accepts the child model class, adds any desired conditions, and then returns the modified model class. Like usual, this callable can request any defined depenency. So, for instance, the following column definition is equivalent to the example above:

class User(clearskies.Model):
    # removing unchanged part for brevity
    large_open_orders = clearskies.columns.HasMany(
        Order,
        readable_child_column_names=["id", "status"],
        where=lambda model: model.where("status=Open").where("total>100"),
    )

default

Optional

A default value to set for this column.

The default is only used when creating a record for the first time, and only if a value for this column has not been set.

import clearskies

class Widget(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    name = clearskies.columns.String(default="Jane Doe")

cli = clearskies.contexts.Cli(
    clearskies.endpoints.Callable(
        lambda widgets: widgets.create(no_data=True),
        model_class=Widget,
        readable_column_names=["id", "name"]
    ),
    classes=[Widget],
)

if __name__ == "__main__":
    cli()

Which when invoked returns:

{
    "status": "success",
    "error": "",
    "data": {
        "id": "03806afa-b189-4729-a43c-9da5aa17bf14",
        "name": "Jane Doe"
    },
    "pagination": {},
    "input_errors": {}
}

is_readable

Optional

Whether or not this column can be converted to JSON and included in an API response.

If this is set to False for a column and you attempt to set that column as a readable_column in an endpoint, clearskies will throw an exception.

is_temporary

Optional

Whether or not this column is temporary. A temporary column is not persisted to the backend.

Temporary columns are useful when you want the developer or end user to set a value, but you use that value to trigger additional behavior, rather than actually recording it. Temporary columns often team up with actions or are used to calculate other values. For instance, in our setable example above, we had both an age and a date of birth column, with the date of birth calculated from the age. This obviously results in two columns with similar data. One could be marked as temporary and it will be available during the save operation, but it will be skipped when saving data to the backend:

import clearskies

class Pet(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    name = clearskies.columns.String()
    date_of_birth = clearskies.columns.Date(is_temporary=True)
    age = clearskies.columns.Integer(
        setable=lambda data, model, now:
            (now-dateparser.parse(model.latest("date_of_birth", data))).total_seconds()/(86400*365),
    )
    created = clearskies.columns.Created()

cli = clearskies.contexts.Cli(
    clearskies.endpoints.Callable(
        lambda pets: pets.create({"name": "Spot", "date_of_birth": "2020-05-03"}),
        model_class=Pet,
        readable_column_names=["id", "age", "date_of_birth"],
    ),
    classes=[Pet],
)

if __name__ == "__main__":
    cli()

Which will return:

{
    "status": "success",
    "error": "",
    "data": {
        "id": "ee532cfa-91cf-4747-b798-3c6dcd79326e",
        "age": 5,
        "date_of_birth": null
    },
    "pagination": {},
    "input_errors": {}
}

e.g. the date_of_birth column is empty. To be clear though, it’s not just empty - clearskies made no attempt to set it. If you were using an SQL database, you would not have to put a date_of_birth column in your table.

on_change_pre_save

Optional

Actions to take during the pre-save step of the save process if the column has changed during the active save operation.

Pre-save happens before the data is persisted to the backend. Actions/callables in this step must return a dictionary. The data in the dictionary will be included in the save operation. Since the save hasn’t completed, any data in the model itself reflects the model before the save operation started. Actions in the pre-save step must NOT make any changes directly, but should ONLY return modified data for the save operation. In addition, they must be idempotent - they should always return the same value when called with the same data. This is because clearskies can call them more than once. If a pre-save hook changes the save data, then clearskies will call all the pre-save hooks again in case this new data needs to trigger further changes. Stateful changes should be reserved for the post_save or save_finished stages.

Callables and actions can request any dependencies provided by the DI system. In addition, they can request two named parameters:

1. model - the model involved in the save operation
2. data - the new data being saved

The key here is that the defined actions will be invoked regardless of how the save happens. Whether the model.save() function is called directly or the model is creatd/modified via an endpoint, your business logic will always be executed. This makes for easy reusability and consistency throughout your application.

Here’s an example where we want to record a timestamp anytime an order status becomes a particular value:

import clearskies

class Order(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    status = clearskies.columns.Select(
        ["Open", "On Hold", "Fulfilled"],
        on_change_pre_save=[
            lambda data, utcnow: {"fulfilled_at": utcnow} if data["status"] == "Fulfilled" else {},
        ],
    )
    fulfilled_at = clearskies.columns.Datetime()

wsgi = clearskies.contexts.WsgiRef(
    clearskies.endpoints.Create(
        model_class=Order,
        writeable_column_names=["status"],
        readable_column_names=["id", "status", "fulfilled_at"],
    ),
)
wsgi()

You can then see the difference depending on what you set the status to:

$ curl http://localhost:8080 -d '{"status":"Open"}' | jq
{
    "status": "success",
    "error": "",
    "data": {
        "id": "a732545f-51b3-4fd0-a6cf-576cf1b2872f",
        "status": "Open",
        "fulfilled_at": null
    },
    "pagination": {},
    "input_errors": {}
}

$ curl http://localhost:8080 -d '{"status":"Fulfilled"}' | jq
{
    "status": "success",
    "error": "",
    "data": {
        "id": "c288bf43-2246-48e4-b168-f40cbf5376df",
        "status": "Fulfilled",
        "fulfilled_at": "2025-05-04T02:32:56+00:00"
    },
    "pagination": {},
    "input_errors": {}
}

on_change_post_save

Optional

Actions to take during the post-save step of the process if the column has changed during the active save.

Post-save happens after the data is persisted to the backend but before the full save process has finished. Since the data has been persisted to the backend, any data returned by the callables/actions will be ignored. If you need to make data changes you’ll have to execute a separate save operation. Since the save hasn’t finished, the model is not yet updated with the new data, and any data you fetch out of the model will refelect the data in the model before the save started.

Callables and actions can request any dependencies provided by the DI system. In addition, they can request three named parameters:

1. model - the model involved in the save operation
2. data - the new data being saved
3. id - the id of the record being saved

Here’s an example of using a post-save action to record a simple audit trail when the order status changes:

import clearskies

class Order(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    status = clearskies.columns.Select(
        ["Open", "On Hold", "Fulfilled"],
        on_change_post_save=[
            lambda model, data, order_histories: order_histories.create({
                "order_id": model.latest("id", data),
                "event": "Order status changed to " + data["status"]
            }),
        ],
    )

class OrderHistory(clearskies.Model):
    id_column_name = "id"
    backend = clearskies.backends.MemoryBackend()

    id = clearskies.columns.Uuid()
    event = clearskies.columns.String()
    order_id = clearskies.columns.BelongsToId(Order)

    # include microseconds in the created_at time so that we can sort our example by created_at
    # and they come out in order (since, for our test program, they will all be created in the same second).
    created_at = clearskies.columns.Created(date_format="%Y-%m-%d %H:%M:%S.%f")

def test_post_save(orders: Order, order_histories: OrderHistory):
    my_order = orders.create({"status": "Open"})
    my_order.status = "On Hold"
    my_order.save()
    my_order.save({"status": "Open"})
    my_order.save({"status": "Fulfilled"})
    return order_histories.where(OrderHistory.order_id.equals(my_order.id)).sort_by("created_at", "asc")

cli = clearskies.contexts.Cli(
    clearskies.endpoints.Callable(
        test_post_save,
        model_class=OrderHistory,
        return_records=True,
        readable_column_names=["id", "event", "created_at"],
    ),
    classes=[Order, OrderHistory],
)
cli()

Note that in our on_change_post_save lambda function, we use model.latest("id", data). We can’t just use data["id"] because data is a dictionary containing the information present in the save. During the create operation data["id"] will be populated, but during the subsequent edit operations it won’t be - only the status column is changing. model.latest("id", data) is basically just short hand for: data.get("id", model.id). On the other hand, we can just use data["status"] because the on_change hook is attached to the status field, so it will only fire when status is being changed, which means that the status key is guaranteed to be in the dictionary when the lambda is executed.

Finally, the post-save action has a named parameter called id, so in this specific case we could use:

lambda data, id, order_histories: order_histories.create("order_id": id, "event": data["status"])

When we execute the above script it will return something like:

{
    "status": "success",
    "error": "",
    "data": [
        {
        "id": "c550d714-839b-4f25-a9e1-bd7e977185ff",
        "event": "Order status changed to Open",
        "created_at": "2025-05-04T14:09:42.960119+00:00"
        },
        {
        "id": "f393d7b0-da21-4117-a7a4-0359fab802bb",
        "event": "Order status changed to On Hold",
        "created_at": "2025-05-04T14:09:42.960275+00:00"
        },
        {
        "id": "5b528a10-4a08-47ae-938c-fc7067603f8e",
        "event": "Order status changed to Open",
        "created_at": "2025-05-04T14:09:42.960395+00:00"
        },
        {
        "id": "91f77a88-1c38-49f7-aa1e-7f97bd9f962f",
        "event": "Order status changed to Fulfilled",
        "created_at": "2025-05-04T14:09:42.960514+00:00"
        }
    ],
    "pagination": {},
    "input_errors": {}
}

on_change_save_finished

Optional

Actions to take during the save-finished step of the save process if the column has changed in the save.

Save-finished happens after the save process has completely finished and the model is updated with the final data. Any data returned by these actions will be ignored, since the save has already finished. If you need to make data changes you’ll have to execute a separate save operation.

Callables and actions can request any dependencies provided by the DI system. In addition, they can request the following parameter:

1. model - the model involved in the save operation

Unlike pre_save and post_save, data is not provided because this data has already been merged into the model. If you need some context from the completed save operation, use methods like was_changed and previous_value.