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Configuration

There are two main methods for configuring Prisma Client Python:

  1. Through the [tool.prisma] section in the pyproject.toml file for your project

    Used for any configuration that needs to happen pre-generation such as changing the location of the binaries.

  2. Through the generator block in your schema.prisma file

    Used for any configuration that applies directly to the generated code such as generating a synchronous or asynchronous client.

Generator Options

Options are passed to Prisma Client Python using the generator block in the schema.prisma file

For example:

generator db {
  provider = "prisma-client-py"
  config_option = "value"
}
See the official docs for options that are not specific to Prisma Client Python.

Interface

See setup for more information.

This option configures the method you will use to interface with the client.

Valid values are:

  • asyncio
  • sync

If asyncio is used then the generated client will be asynchronous and code must be ran using asyncio, e.g.

user = await db.user.find_unique(where={'id': 'user_id'})

And if sync is used then the generated client will be synchronous, e.g.

user = db.user.find_unique(where={'id': 'user_id'})

Partial Type Generator

Custom partial models can be generated along with the prisma client, see partial types for how to make use of partial types.

The script that generates the partial types can be configured using the partial_type_generator option which defaults to prisma/partial_types.py

You can pass either an absolute module import or a path.

Warning

Passing a module will also import any parent packages, e.g. given foo.bar.partials, foo and bar will also be imported

Examples

generator db {
  provider = "prisma-client-py"
  partial_type_generator = "scripts/partial_types.py"
}
generator db {
  provider = "prisma-client-py"
  partial_type_generator = "scripts.partial_types"
}

Recursive Type Depth

Warning

Increasing the number of types generated can exponentially increase the time taken and resources used by static type checkers.

As some python static type checkers do not support recursive types, Prisma Client Python can generate recursive and psuedo-recursive types to an arbitrary depth.

This depth can be controlled with the recursive_type_depth option, if -1 is given then recursive types will be generated and if a value greater than or equal to 2 is given then psuedo-recursive types will be generated to the given depth.

Examples

These examples use the following schema.prisma models

model Post {
  id         String     @id @default(cuid())
  title      String
  author     User?      @relation(fields: [author_id], references: [id])
  author_id  String?
  categories Category[]
}

model User {
  id      String   @id @default(cuid())
  name    String
  posts   Post[]
  profile Profile?
}

model Category {
  id    Int    @id @default(autoincrement())
  posts Post[]
  name  String
}

model Profile {
  id      Int    @id @default(autoincrement())
  user    User   @relation(fields: [user_id], references: [id])
  user_id String @unique
  bio     String
}
Default

The default for this option is 5. This allows for recursive types up to the following depth.

user = await db.user.find_unique(
    where={'id': user_id},
    include={
        'profile': True,
        'posts': {
            'include': {
                'categories': {
                    'include': {
                        'posts': True
                    }
                }
            }
        },
    },
)
Recursive

If you are using a type checker that supports recursive types such as pyright, you can generate fully recursive types which means that there is no depth restriction.

You can do this by setting recursive_type_depth to -1.

generator db {
  provider = "prisma-client-py"
  recursive_type_depth = -1
}
Minimum Value

Generating a lot of types can drastically decreas the speed of static type checkers, in order to mitigate this it is possible to decrease the amount of types generated to any amount greater than 1.

generator db {
  provider = "prisma-client-py"
  recursive_type_depth = 2
}

Recursive types are now only valid up to the following depth.

user = await db.user.find_unique(
    where={'id': user_id},
    include={
        'profile': True,
        'posts': True,
    },
)
Increase

Warning

Increasing the number of types generated can exponentially increase the time taken and resources used by static type checkers.

There is no maximum value, recursive types can be nested arbitrarily deep.

generator db {
  provider = "prisma-client-py"
  recursive_type_depth = 8
}

Recursive types are now only valid up to the following depth.

user = await db.user.find_unique(
    where={'id': user_id},
    include={
        'profile': True,
        'posts': {
            'include': {
                'categories': {
                    'include': {
                        'posts': {
                            'include': {
                                'categories': True
                            }
                        }
                    }
                }
            }
        },
    },
)

Config Options

Options can either be passed to Prisma Client Python through the pyproject.toml file for your project, under the tool.prisma key, for example:

[tool.prisma]
# cache engine binaries in a directory relative to your project
binary_cache_dir = '.binaries'

Or through environment variables, e.g. PRISMA_BINARY_CACHE_DIR. In the case that the same option is set using both methods, the environment variable will take precedence.

Binary Cache Directory

This option controls where the Prisma Engine and Prisma CLI binaries should be downloaded to. This defaults to a cache directory that includes the current Prisma Engine version.

Option Environment Variable Default
binary_cache_dir PRISMA_BINARY_CACHE_DIR /{home}/.cache/prisma-python/binaries/{prisma_version}/{engine_version}

Home Directory

This option can be used to change the base directory of the binary_cache_dir option without having to worry about versioning the Prisma binaries. This is useful if you need to download the binaries to a local directory.

Option Environment Variable Default
home_dir PRISMA_HOME_DIR ~

Prisma Version

This option controls the version of Prisma to use. It should be noted that this is intended to be internal and only the pinned Prisma version is guaranteed to be supported.

Option Environment Variable Default
prisma_version PRISMA_VERSION 5.8.0

Expected Engine Version

This is an internal option that is here as a safeguard for the prisma_version option. If you modify the prisma_version option then you must also update this option to use the corresponding engine version. You can find a list of engine versions here.

Option Environment Variable Default
expected_engine_version PRISMA_EXPECTED_ENGINE_VERSION 0a83d8541752d7582de2ebc1ece46519ce72a848

Binary Platform

This option is useful if you need to make use of the binaryTargets schema option to build your application on one platform and deploy it on another.

This allows you to set the current platform dynamically as Prisma Client Python does not have official support for binaryTargets and although we do have some safe guards in place to attempt to use the correct binary, it has not been thoroughly tested.

A list of valid options can be found here.

Option Environment Variable
binary_platform PRISMA_BINARY_PLATFORM

Use Global Node

This option configures whether or not Prisma Client Python will attempt to use the globally installed version of Node, if it is available, to run the Prisma CLI.

Option Environment Variable Default
use_global_node PRISMA_USE_GLOBAL_NODE True

Use nodejs-bin

This option configures whether or not Prisma Client Python will attempt to use the installed version of the nodejs-bin package, if it is available, to run the Prisma CLI.

Option Environment Variable Default
use_nodejs_bin PRISMA_USE_NODEJS_BIN True

Extra Nodeenv Arguments

This option allows you to pass additional arguments to nodeenv which is the package we use to automatically download a Node binary to run the CLI with.

Arguments are passed after the path, for example:

python -m nodeenv <path> <extra args>
Option Environment Variable
nodeenv_extra_args PRISMA_NODEENV_EXTRA_ARGS

Nodeenv Cache Directory

This option configures where Prisma Client Python will store the Node binary that is installed by nodeenv.

Note that this does not make use of the Home Directory option and instead uses the actual user home directory.

Option Environment Variable Default
nodeenv_cache_dir PRISMA_NODEENV_CACHE_DIR ~/.cache/prisma-python/nodeenv/