DEPS: migrate to Pydantic 2

.github/workflows/test_conda_build.yaml

@@ -33,7 +33,7 @@ jobs:
         uses: conda-incubator/setup-miniconda@v2
         with:
           auto-update-conda: true
-          python-version: 3.8
+          python-version: 3.11
           channels: conda-forge
           activate-environment: nebari-dev
 

pyproject.toml

@@ -65,7 +65,8 @@ dependencies = [
     "kubernetes==27.2.0",
     "pluggy==1.3.0",
     "prompt-toolkit==3.0.36",
-    "pydantic==1.10.12",
+    "pydantic==2.4.2",
+    "typing-extensions==4.7.1; python_version < '3.9'",
     "pynacl==1.5.0",
     "python-keycloak==3.3.0",
     "questionary==2.0.0",

src/_nebari/config.py

@@ -2,27 +2,27 @@
 import pathlib
 import re
 import sys
-import typing
+from typing import Any, Dict, List, Union
 
 import pydantic
 
 from _nebari.utils import yaml
 
 
-def set_nested_attribute(data: typing.Any, attrs: typing.List[str], value: typing.Any):
+def set_nested_attribute(data: Any, attrs: List[str], value: Any):
     """Takes an arbitrary set of attributes and accesses the deep
     nested object config to set value
     """
 
-    def _get_attr(d: typing.Any, attr: str):
+    def _get_attr(d: Any, attr: str):
         if isinstance(d, list) and re.fullmatch(r"\d+", attr):
             return d[int(attr)]
         elif hasattr(d, "__getitem__"):
             return d[attr]
         else:
             return getattr(d, attr)
 
-    def _set_attr(d: typing.Any, attr: str, value: typing.Any):
+    def _set_attr(d: Any, attr: str, value: Any):
         if isinstance(d, list) and re.fullmatch(r"\d+", attr):
             d[int(attr)] = value
         elif hasattr(d, "__getitem__"):
@@ -63,6 +63,15 @@ def set_config_from_environment_variables(
     return config
 
 
+def dump_nested_model(model_dict: Dict[str, Union[pydantic.BaseModel, str]]):
+    result = {}
+    for key, value in model_dict.items():
+        result[key] = (
+            value.model_dump() if isinstance(value, pydantic.BaseModel) else value
+        )
+    return result
+
+
 def read_configuration(
     config_filename: pathlib.Path,
     config_schema: pydantic.BaseModel,
@@ -77,7 +86,8 @@ def read_configuration(
         )
 
     with filename.open() as f:
-        config = config_schema(**yaml.load(f.read()))
+        config_dict = yaml.load(f)
+        config = config_schema(**config_dict)
 
     if read_environment:
         config = set_config_from_environment_variables(config)
@@ -87,14 +97,15 @@ def read_configuration(
 
 def write_configuration(
     config_filename: pathlib.Path,
-    config: typing.Union[pydantic.BaseModel, typing.Dict],
+    config: Union[pydantic.BaseModel, Dict],
     mode: str = "w",
 ):
     """Write the nebari configuration file to disk"""
     with config_filename.open(mode) as f:
         if isinstance(config, pydantic.BaseModel):
-            yaml.dump(config.dict(), f)
+            yaml.dump(config.model_dump(), f)
         else:
+            config = dump_nested_model(config)
             yaml.dump(config, f)
 
 

src/_nebari/initialize.py

@@ -3,6 +3,7 @@
 import re
 import tempfile
 from pathlib import Path
+from typing import Any, Dict
 
 import pydantic
 import requests
@@ -45,7 +46,7 @@ def render_config(
     region: str = None,
     disable_prompt: bool = False,
     ssl_cert_email: str = None,
-):
+) -> Dict[str, Any]:
     config = {
         "provider": cloud_provider,
         "namespace": namespace,
@@ -189,7 +190,7 @@ def render_config(
     from nebari.plugins import nebari_plugin_manager
 
     try:
-        config_model = nebari_plugin_manager.config_schema.parse_obj(config)
+        config_model = nebari_plugin_manager.config_schema.model_validate(config)
     except pydantic.ValidationError as e:
         print(str(e))
 

src/_nebari/provider/cicd/github.py

@@ -4,7 +4,7 @@
 
 import requests
 from nacl import encoding, public
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field, RootModel
 
 from _nebari.constants import LATEST_SUPPORTED_PYTHON_VERSION
 from _nebari.provider.cicd.common import pip_install_nebari
@@ -143,49 +143,34 @@ class GHA_on_extras(BaseModel):
     paths: List[str]
 
 
-class GHA_on(BaseModel):
-    # to allow for dynamic key names
-    __root__: Dict[str, GHA_on_extras]
-
-    # TODO: validate __root__ values
-    # `push`, `pull_request`, etc.
-
-
-class GHA_job_steps_extras(BaseModel):
-    # to allow for dynamic key names
-    __root__: Union[str, float, int]
+GHA_on = RootModel[Dict[str, GHA_on_extras]]
+GHA_job_steps_extras = RootModel[Union[str, float, int]]
 
 
 class GHA_job_step(BaseModel):
     name: str
-    uses: Optional[str]
-    with_: Optional[Dict[str, GHA_job_steps_extras]] = Field(alias="with")
-    run: Optional[str]
-    env: Optional[Dict[str, GHA_job_steps_extras]]
-
-    class Config:
-        allow_population_by_field_name = True
+    uses: Optional[str] = None
+    with_: Optional[Dict[str, GHA_job_steps_extras]] = Field(alias="with", default=None)
+    run: Optional[str] = None
+    env: Optional[Dict[str, GHA_job_steps_extras]] = None
+    model_config = ConfigDict(populate_by_name=True)
 
 
 class GHA_job_id(BaseModel):
     name: str
     runs_on_: str = Field(alias="runs-on")
-    permissions: Optional[Dict[str, str]]
+    permissions: Optional[Dict[str, str]] = None
     steps: List[GHA_job_step]
-
-    class Config:
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
 
-class GHA_jobs(BaseModel):
-    # to allow for dynamic key names
-    __root__: Dict[str, GHA_job_id]
+GHA_jobs = RootModel[Dict[str, GHA_job_id]]
 
 
 class GHA(BaseModel):
     name: str
     on: GHA_on
-    env: Optional[Dict[str, str]]
+    env: Optional[Dict[str, str]] = None
     jobs: GHA_jobs
 
 
@@ -204,23 +189,15 @@ def checkout_image_step():
     return GHA_job_step(
         name="Checkout Image",
         uses="actions/checkout@v3",
-        with_={
-            "token": GHA_job_steps_extras(
-                __root__="${{ secrets.REPOSITORY_ACCESS_TOKEN }}"
-            )
-        },
+        with_={"token": GHA_job_steps_extras("${{ secrets.REPOSITORY_ACCESS_TOKEN }}")},
     )
 
 
 def setup_python_step():
     return GHA_job_step(
         name="Set up Python",
         uses="actions/setup-python@v4",
-        with_={
-            "python-version": GHA_job_steps_extras(
-                __root__=LATEST_SUPPORTED_PYTHON_VERSION
-            )
-        },
+        with_={"python-version": GHA_job_steps_extras(LATEST_SUPPORTED_PYTHON_VERSION)},
     )
 
 
@@ -242,7 +219,7 @@ def gen_nebari_ops(config):
     env_vars = gha_env_vars(config)
 
     push = GHA_on_extras(branches=[config.ci_cd.branch], paths=["nebari-config.yaml"])
-    on = GHA_on(__root__={"push": push})
+    on = GHA_on({"push": push})
 
     step1 = checkout_image_step()
     step2 = setup_python_step()
@@ -272,7 +249,7 @@ def gen_nebari_ops(config):
         ),
         env={
             "COMMIT_MSG": GHA_job_steps_extras(
-                __root__="nebari-config.yaml automated commit: ${{ github.sha }}"
+                "nebari-config.yaml automated commit: ${{ github.sha }}"
             )
         },
     )
@@ -291,7 +268,7 @@ def gen_nebari_ops(config):
         },
         steps=gha_steps,
     )
-    jobs = GHA_jobs(__root__={"build": job1})
+    jobs = GHA_jobs({"build": job1})
 
     return NebariOps(
         name="nebari auto update",
@@ -312,18 +289,16 @@ def gen_nebari_linter(config):
     pull_request = GHA_on_extras(
         branches=[config.ci_cd.branch], paths=["nebari-config.yaml"]
     )
-    on = GHA_on(__root__={"pull_request": pull_request})
+    on = GHA_on({"pull_request": pull_request})
 
     step1 = checkout_image_step()
     step2 = setup_python_step()
     step3 = install_nebari_step(config.nebari_version)
 
     step4_envs = {
-        "PR_NUMBER": GHA_job_steps_extras(__root__="${{ github.event.number }}"),
-        "REPO_NAME": GHA_job_steps_extras(__root__="${{ github.repository }}"),
-        "GITHUB_TOKEN": GHA_job_steps_extras(
-            __root__="${{ secrets.REPOSITORY_ACCESS_TOKEN }}"
-        ),
+        "PR_NUMBER": GHA_job_steps_extras("${{ github.event.number }}"),
+        "REPO_NAME": GHA_job_steps_extras("${{ github.repository }}"),
+        "GITHUB_TOKEN": GHA_job_steps_extras("${{ secrets.REPOSITORY_ACCESS_TOKEN }}"),
     }
 
     step4 = GHA_job_step(
@@ -336,7 +311,7 @@ def gen_nebari_linter(config):
         name="nebari", runs_on_="ubuntu-latest", steps=[step1, step2, step3, step4]
     )
     jobs = GHA_jobs(
-        __root__={
+        {
             "nebari-validate": job1,
         }
     )

src/_nebari/provider/cicd/gitlab.py

@@ -1,40 +1,34 @@
 from typing import Dict, List, Optional, Union
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field, RootModel
 
 from _nebari.constants import LATEST_SUPPORTED_PYTHON_VERSION
 from _nebari.provider.cicd.common import pip_install_nebari
 
-
-class GLCI_extras(BaseModel):
-    # to allow for dynamic key names
-    __root__: Union[str, float, int]
+GLCI_extras = RootModel[Union[str, float, int]]
 
 
 class GLCI_image(BaseModel):
     name: str
-    entrypoint: Optional[str]
+    entrypoint: Optional[str] = None
 
 
 class GLCI_rules(BaseModel):
     if_: Optional[str] = Field(alias="if")
-    changes: Optional[List[str]]
-
-    class Config:
-        allow_population_by_field_name = True
+    changes: Optional[List[str]] = None
+    model_config = ConfigDict(populate_by_name=True)
 
 
 class GLCI_job(BaseModel):
-    image: Optional[Union[str, GLCI_image]]
-    variables: Optional[Dict[str, str]]
-    before_script: Optional[List[str]]
-    after_script: Optional[List[str]]
+    image: Optional[Union[str, GLCI_image]] = None
+    variables: Optional[Dict[str, str]] = None
+    before_script: Optional[List[str]] = None
+    after_script: Optional[List[str]] = None
     script: List[str]
-    rules: Optional[List[GLCI_rules]]
+    rules: Optional[List[GLCI_rules]] = None
 
 
-class GLCI(BaseModel):
-    __root__: Dict[str, GLCI_job]
+GLCI = RootModel[Dict[str, GLCI_job]]
 
 
 def gen_gitlab_ci(config):
@@ -76,7 +70,7 @@ def gen_gitlab_ci(config):
     )
 
     return GLCI(
-        __root__={
+        {
             "render-nebari": render_nebari,
         }
     )

src/_nebari/provider/cloud/amazon_web_services.py

@@ -7,25 +7,18 @@
 import boto3
 from botocore.exceptions import ClientError, EndpointConnectionError
 
-from _nebari import constants
+from _nebari.constants import AWS_ENV_DOCS
 from _nebari.provider.cloud.commons import filter_by_highest_supported_k8s_version
+from _nebari.utils import check_environment_variables
 from nebari import schema
 
 MAX_RETRIES = 5
 DELAY = 5
 
 
-def check_credentials():
-    """Check for AWS credentials are set in the environment."""
-    for variable in {
-        "AWS_ACCESS_KEY_ID",
-        "AWS_SECRET_ACCESS_KEY",
-    }:
-        if variable not in os.environ:
-            raise ValueError(
-                f"""Missing the following required environment variable: {variable}\n
-                Please see the documentation for more information: {constants.AWS_ENV_DOCS}"""
-            )
+def check_credentials() -> None:
+    required_variables = {"AWS_ACCESS_KEY_ID", "AWS_SECRET_ACCESS_KEY"}
+    check_environment_variables(required_variables, AWS_ENV_DOCS)
 
 
 @functools.lru_cache()