django-mass-migration


Namedjango-mass-migration JSON
Version 0.3.8 PyPI version JSON
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home_pagehttps://github.com/adamalton/django-mass-migration
SummaryDjango app for long-running data migrations
upload_time2024-10-02 17:05:05
maintainerNone
docs_urlNone
authorAdam Alton
requires_pythonNone
licenseNone
keywords django djangae django-gcloud-connectors google app engine
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            Django Mass Migration
=====================

A Django app which provides utilities for performing data operations on (optionally) large datasets.

Similar to Django's built-in migration system, it allows you to define data migrations to be performed on the database,
and to apply those migration operations to your database, and it tracks which migrations have been applied and which haven't.

Unlike Django's built-in migration system, it is designed for performing long-running data modification tasks
where there could be a significant amount of time between when the migration is started and when it's finished.
See [Concepts](#concepts).
It is particularly useful for schemaless databases where Django's normal concept of schema changes doesn't apply.

Due to the expectation that migrations maybe be long-running, and just for awesomeness, it provides a web based (rather than terminal based) interface for managing the migrations.

The actual running of the operations can be done on a "backend" of your choosing, e.g. a task queue.
A backend for running migration operations on [Djangae](https://gitlab.com/potato-oss/djangae/djangae) with [Glcoudc](https://gitlab.com/potato-oss/google-cloud/django-gcloud-connectors/) is bundled with the app.


Installation
------------

1. Install the package: `pip install django-mass-migration`
2. Add `massmigration` to `settings.INSTALLED_APPS`.
3. Add  `path("migrations/", include("massmigration.urls"))` to your root urlconf.
4. If you're using the bundled backend, set `settings.MASSMIGRATION_TASK_QUEUE` to a Google Cloud Tasks queue name.


Creating A Migration
--------------------

To create a new migration, run the `makemassmigration` management command:

```python manage.py makemassmigration myapp my_migration_name```

This command has two required, positional arguments:

1. `app_label` - this should be the name of an installed app in your project.
2. `migration_name` - this should be the name that you want to give you migration.

The command also takes the following optional arguments:

* `--template` - this should be the name of one of the supplied templates in `massmigration/templates/migration_templates`, without the extension, e.g. `--template=mapper`. See [Migration Types](#migration-types). The default is `mapper`.

A file will be created inside a folder called 'massmigrations' in your app, using the supplied migration name.
E.g. `myapp/massmigrations/001_my_migration.py`.
This is a blank slate for you to write your migration code in.


Migration Types
---------------

There are three broad types of migration for you to choose from.

### simple

This is for a migration which is just a single Python function.
It's intended for small operations which you know your backend can perform in one step.

### mapper

This is for mapping a function over the instances of a Django queryset.
You define a queryset and an `operation` function, and the migration will call that function on each object in the queryset.

The backend must be able to handle iterating over the queryset.
The bundled DjangaeBackend can handle almost infinite sized querysets.

### custom

If you want to take matters into your own hands you can write an entirely custom migration.
These can still be tracked the same as the other operations, but the implementation of what your migration
does and how your the backend handles it are up to you.

Running with Multiple DBs
-------------------
If your project connects to multiple databases it is possible to run your migrations against each database individually.
The migrations are not forced on a specific DB but rather the `db_alias` is passed to both to `get_queryset(db_alias)` (for mappers migrations) and `operation` (for simple migrations) giving control back to the developer to customise what is retrieved for the migration.

By default a migration can be run on any available database. That can be customised but setting `allowed_db_aliases` on the migration class.


Applying Migrations
-------------------

There are two ways to apply a migration to the database:

### Via the Web UI

1. Optionally: ensure that the Django admin is set up in your project.
2. Deploy your project, including the new migration file.
3. Either:
    - Go to the Django Admin site and under Mass Migrations -> Migration Record, click the "Manage Migrations" button; or
    - Go directly to the URL of `reverse("massmigration_manage")` whatever path you've configured that to be on.
5. Next to your new migration, click "Run...".
6. Click "Run migration".
7. Wait for the migration to be listed as applied in the Migration Record list view, or check the logging from your backend.

### Programmatically

If you want to create your own system for applying migrations, you can use the API functions.
Or you will be able to, once I've written them.


Protecting Code Which Requires Migrations
-----------------------------------------

Sometimes in the development cycle of your application, you will want to ensure that a particular migration has been run,
usually when you've added new code which expects the migration to have been applied before the code is run.

To handle this, Mass Migration provides the following utilities:

#### `massmigration.enforcement.requires_migration`

This is a function decorator which ensures that the function cannot be executed until the specified migration has been applied.
For example:

```python
@requires_migration(("myapp", "0001_my_migration"))
def my_function():
	...
```


This will raise `massmigration.exceptions.RequiredMigrationNotApplied` if the function is called before the migration is applied.

### Multiple DBs Support
When running on multiple databases, by default, the utilities assume that the migration must have been applied on all the databases specified by the Migration's `allowed_db_aliases` attribute.
To customise that behaviour the decorators accept an optional `db_aliases` list to specify a subset of the aliases allowed for the migration and require only those to have been applied.

```python
@requires_migration(("myapp", "0001_my_migration"), db_aliases=["my_db_alias"])
def my_function():
	...
```

### Notes:
* If the migration _is_ applied, then this will cache that fact, so it will only query the database the first time the function is called.
* The migration identifier can either be a tuple of `(app_label, migration_name)` or can be a string of `"app_label:migration_name"`.
* There is an optional second argument `skip_in_tests`, which defaults to `True`.


#### `massmigration.enforcement.view_requires_migration`

This is the same as `requires_migration` but for decorating a view function.
If the specified migration is not applied then the view will return a 503 response.



Concepts
--------

### Why Mass Migration?

#### Reason 1

Django's migration system is built for relational databases. 
These have a table schema and allow you to make a change to that schema as a single "operation",
often inside a transaction.
This means that a change to a schema is either "applied" or "not applied".

On schemaless databases (such as Google's Cloud Datastore/Firestore), there is no schema, and
therefore making a change to a "table", such as adding or removing a column, requires mapping over
each row of the table to apply that change.
This means that a change to a schema can be "applied", "not applied" or "being applied".

Django's migration system doesn't allow for this in-between state.
Its internal `Migration` model (which is nested inside the `MigrationRecorder` and cannot be edited)
which tracks migrations cannot store the fact that a migration is currently being applied; a
migration is either applied or it isn't.

This makes Django's migration recorder unsuitable for tracking changes to a schemaless database.

#### Reason 2

If you're using a schemaless database with Django, e.g. you're using Google Cloud Datastore with a
connector such as
[gcloudc](https://gitlab.com/potato-oss/google-cloud/django-gcloud-connectors/-/tree/master/gcloudc)
then making a change to your model doesn't necessarily require you to create any kind of migration
at all.

For example, if you add a new field to one of your models and you specify a default value, you can
just start using that new field with no need for a migration.
Existing rows which don't yet have that column will simply have the column added the next time
they're resaved via your model.

But in other cases, the more limited querying capabilities of a schemaless database mean that there
are times when something which could be done with an `UPDATE table` statement on SQL can't be done
so easily.
For these cases, `django-mass-migration` provides tools to let you iterate over your table rows and
perform data manipulation operations.


### General approach

TODO: long-running migrations, errors, etc.
Why long-running migrations are not run as part of the deployment process (because they take too long and you don't want to take your site down while they run).

### Model State

TODO: Stuff about why there's no model history (apps/schema_editor).

### Workflow & Code Protection

TODO: Deployment workflow and use of enforcement utilities


Settings
--------

The following settings can be used:

#### `MASSMIGRATION_BACKEND`

This should be a dotted path string to the backend class that you want to use.
The default is `"massmigration.backends.djangae.DjangaeBackend"`,
which works with SQL, Google Cloud Datastore and Firestore databases.


#### `MASSMIGRATION_TASK_QUEUE`

Used by the `DjangaeBackend`, this sets the Google Cloud Tasks queue name to be used for running migration tasks.


#### `MASSMIGRATION_RECORD_CACHE_TIMEOUT`

You're unlikely to need this.
It sets the time for caching MigrationRecords for the purpose of checking a migration's status during mapper operations.


Backends
--------

Currently `massmigration` includes a `DjangaeBackend` for running migrations on Google App Engine
applications which are using [djangae](https://djangae.readthedocs.io/).

Due to the nature of different hosting platforms having different types of task queue systems, each
platform will require a slightly different backend, but these can easily be written and plugged in
(merge requests welcome!).

### DjangaeBackend

This runs simple migrations using `djangae.tasks.deferred` and runs mapper migrations using
`djangae.tasks.defer_iteration_with_finalize`.

It can be configured via the `backend_params` attribute on your `Migration` classes, using the
following two items:

* `defer_kwargs`: a dict of kwargs which will get passed to the `defer` call for simple migrations.
* `defer_iteration_with_finalize_kwargs` - a dict of kwargs which will get passed through to `defer_iteration_with_finalize` for mapper migrations.

            

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    "description": "Django Mass Migration\n=====================\n\nA Django app which provides utilities for performing data operations on (optionally) large datasets.\n\nSimilar to Django's built-in migration system, it allows you to define data migrations to be performed on the database,\nand to apply those migration operations to your database, and it tracks which migrations have been applied and which haven't.\n\nUnlike Django's built-in migration system, it is designed for performing long-running data modification tasks\nwhere there could be a significant amount of time between when the migration is started and when it's finished.\nSee [Concepts](#concepts).\nIt is particularly useful for schemaless databases where Django's normal concept of schema changes doesn't apply.\n\nDue to the expectation that migrations maybe be long-running, and just for awesomeness, it provides a web based (rather than terminal based) interface for managing the migrations.\n\nThe actual running of the operations can be done on a \"backend\" of your choosing, e.g. a task queue.\nA backend for running migration operations on [Djangae](https://gitlab.com/potato-oss/djangae/djangae) with [Glcoudc](https://gitlab.com/potato-oss/google-cloud/django-gcloud-connectors/) is bundled with the app.\n\n\nInstallation\n------------\n\n1. Install the package: `pip install django-mass-migration`\n2. Add `massmigration` to `settings.INSTALLED_APPS`.\n3. Add  `path(\"migrations/\", include(\"massmigration.urls\"))` to your root urlconf.\n4. If you're using the bundled backend, set `settings.MASSMIGRATION_TASK_QUEUE` to a Google Cloud Tasks queue name.\n\n\nCreating A Migration\n--------------------\n\nTo create a new migration, run the `makemassmigration` management command:\n\n```python manage.py makemassmigration myapp my_migration_name```\n\nThis command has two required, positional arguments:\n\n1. `app_label` - this should be the name of an installed app in your project.\n2. `migration_name` - this should be the name that you want to give you migration.\n\nThe command also takes the following optional arguments:\n\n* `--template` - this should be the name of one of the supplied templates in `massmigration/templates/migration_templates`, without the extension, e.g. `--template=mapper`. See [Migration Types](#migration-types). The default is `mapper`.\n\nA file will be created inside a folder called 'massmigrations' in your app, using the supplied migration name.\nE.g. `myapp/massmigrations/001_my_migration.py`.\nThis is a blank slate for you to write your migration code in.\n\n\nMigration Types\n---------------\n\nThere are three broad types of migration for you to choose from.\n\n### simple\n\nThis is for a migration which is just a single Python function.\nIt's intended for small operations which you know your backend can perform in one step.\n\n### mapper\n\nThis is for mapping a function over the instances of a Django queryset.\nYou define a queryset and an `operation` function, and the migration will call that function on each object in the queryset.\n\nThe backend must be able to handle iterating over the queryset.\nThe bundled DjangaeBackend can handle almost infinite sized querysets.\n\n### custom\n\nIf you want to take matters into your own hands you can write an entirely custom migration.\nThese can still be tracked the same as the other operations, but the implementation of what your migration\ndoes and how your the backend handles it are up to you.\n\nRunning with Multiple DBs\n-------------------\nIf your project connects to multiple databases it is possible to run your migrations against each database individually.\nThe migrations are not forced on a specific DB but rather the `db_alias` is passed to both to `get_queryset(db_alias)` (for mappers migrations) and `operation` (for simple migrations) giving control back to the developer to customise what is retrieved for the migration.\n\nBy default a migration can be run on any available database. That can be customised but setting `allowed_db_aliases` on the migration class.\n\n\nApplying Migrations\n-------------------\n\nThere are two ways to apply a migration to the database:\n\n### Via the Web UI\n\n1. Optionally: ensure that the Django admin is set up in your project.\n2. Deploy your project, including the new migration file.\n3. Either:\n    - Go to the Django Admin site and under Mass Migrations -> Migration Record, click the \"Manage Migrations\" button; or\n    - Go directly to the URL of `reverse(\"massmigration_manage\")` whatever path you've configured that to be on.\n5. Next to your new migration, click \"Run...\".\n6. Click \"Run migration\".\n7. Wait for the migration to be listed as applied in the Migration Record list view, or check the logging from your backend.\n\n### Programmatically\n\nIf you want to create your own system for applying migrations, you can use the API functions.\nOr you will be able to, once I've written them.\n\n\nProtecting Code Which Requires Migrations\n-----------------------------------------\n\nSometimes in the development cycle of your application, you will want to ensure that a particular migration has been run,\nusually when you've added new code which expects the migration to have been applied before the code is run.\n\nTo handle this, Mass Migration provides the following utilities:\n\n#### `massmigration.enforcement.requires_migration`\n\nThis is a function decorator which ensures that the function cannot be executed until the specified migration has been applied.\nFor example:\n\n```python\n@requires_migration((\"myapp\", \"0001_my_migration\"))\ndef my_function():\n\t...\n```\n\n\nThis will raise `massmigration.exceptions.RequiredMigrationNotApplied` if the function is called before the migration is applied.\n\n### Multiple DBs Support\nWhen running on multiple databases, by default, the utilities assume that the migration must have been applied on all the databases specified by the Migration's `allowed_db_aliases` attribute.\nTo customise that behaviour the decorators accept an optional `db_aliases` list to specify a subset of the aliases allowed for the migration and require only those to have been applied.\n\n```python\n@requires_migration((\"myapp\", \"0001_my_migration\"), db_aliases=[\"my_db_alias\"])\ndef my_function():\n\t...\n```\n\n### Notes:\n* If the migration _is_ applied, then this will cache that fact, so it will only query the database the first time the function is called.\n* The migration identifier can either be a tuple of `(app_label, migration_name)` or can be a string of `\"app_label:migration_name\"`.\n* There is an optional second argument `skip_in_tests`, which defaults to `True`.\n\n\n#### `massmigration.enforcement.view_requires_migration`\n\nThis is the same as `requires_migration` but for decorating a view function.\nIf the specified migration is not applied then the view will return a 503 response.\n\n\n\nConcepts\n--------\n\n### Why Mass Migration?\n\n#### Reason 1\n\nDjango's migration system is built for relational databases. \nThese have a table schema and allow you to make a change to that schema as a single \"operation\",\noften inside a transaction.\nThis means that a change to a schema is either \"applied\" or \"not applied\".\n\nOn schemaless databases (such as Google's Cloud Datastore/Firestore), there is no schema, and\ntherefore making a change to a \"table\", such as adding or removing a column, requires mapping over\neach row of the table to apply that change.\nThis means that a change to a schema can be \"applied\", \"not applied\" or \"being applied\".\n\nDjango's migration system doesn't allow for this in-between state.\nIts internal `Migration` model (which is nested inside the `MigrationRecorder` and cannot be edited)\nwhich tracks migrations cannot store the fact that a migration is currently being applied; a\nmigration is either applied or it isn't.\n\nThis makes Django's migration recorder unsuitable for tracking changes to a schemaless database.\n\n#### Reason 2\n\nIf you're using a schemaless database with Django, e.g. you're using Google Cloud Datastore with a\nconnector such as\n[gcloudc](https://gitlab.com/potato-oss/google-cloud/django-gcloud-connectors/-/tree/master/gcloudc)\nthen making a change to your model doesn't necessarily require you to create any kind of migration\nat all.\n\nFor example, if you add a new field to one of your models and you specify a default value, you can\njust start using that new field with no need for a migration.\nExisting rows which don't yet have that column will simply have the column added the next time\nthey're resaved via your model.\n\nBut in other cases, the more limited querying capabilities of a schemaless database mean that there\nare times when something which could be done with an `UPDATE table` statement on SQL can't be done\nso easily.\nFor these cases, `django-mass-migration` provides tools to let you iterate over your table rows and\nperform data manipulation operations.\n\n\n### General approach\n\nTODO: long-running migrations, errors, etc.\nWhy long-running migrations are not run as part of the deployment process (because they take too long and you don't want to take your site down while they run).\n\n### Model State\n\nTODO: Stuff about why there's no model history (apps/schema_editor).\n\n### Workflow & Code Protection\n\nTODO: Deployment workflow and use of enforcement utilities\n\n\nSettings\n--------\n\nThe following settings can be used:\n\n#### `MASSMIGRATION_BACKEND`\n\nThis should be a dotted path string to the backend class that you want to use.\nThe default is `\"massmigration.backends.djangae.DjangaeBackend\"`,\nwhich works with SQL, Google Cloud Datastore and Firestore databases.\n\n\n#### `MASSMIGRATION_TASK_QUEUE`\n\nUsed by the `DjangaeBackend`, this sets the Google Cloud Tasks queue name to be used for running migration tasks.\n\n\n#### `MASSMIGRATION_RECORD_CACHE_TIMEOUT`\n\nYou're unlikely to need this.\nIt sets the time for caching MigrationRecords for the purpose of checking a migration's status during mapper operations.\n\n\nBackends\n--------\n\nCurrently `massmigration` includes a `DjangaeBackend` for running migrations on Google App Engine\napplications which are using [djangae](https://djangae.readthedocs.io/).\n\nDue to the nature of different hosting platforms having different types of task queue systems, each\nplatform will require a slightly different backend, but these can easily be written and plugged in\n(merge requests welcome!).\n\n### DjangaeBackend\n\nThis runs simple migrations using `djangae.tasks.deferred` and runs mapper migrations using\n`djangae.tasks.defer_iteration_with_finalize`.\n\nIt can be configured via the `backend_params` attribute on your `Migration` classes, using the\nfollowing two items:\n\n* `defer_kwargs`: a dict of kwargs which will get passed to the `defer` call for simple migrations.\n* `defer_iteration_with_finalize_kwargs` - a dict of kwargs which will get passed through to `defer_iteration_with_finalize` for mapper migrations.\n",
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