databricks-cli/libs/filer/workspace_files_extensions_...

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package filer
import (
"context"
"net/http"
"testing"
"github.com/databricks/databricks-sdk-go/experimental/mocks"
"github.com/databricks/databricks-sdk-go/service/workspace"
"github.com/stretchr/testify/assert"
"github.com/stretchr/testify/mock"
)
// Mocks client.DatabricksClient from the databricks-sdk-go package.
type mockApiClient struct {
mock.Mock
}
func (m *mockApiClient) Do(ctx context.Context, method, path string,
headers map[string]string, request any, response any,
visitors ...func(*http.Request) error) error {
args := m.Called(ctx, method, path, headers, request, response, visitors)
// Set the http response from a value provided in the mock call.
p := response.(*wsfsFileInfo)
*p = args.Get(1).(wsfsFileInfo)
return args.Error(0)
}
func TestFilerWorkspaceFilesExtensionsErrorsOnDupName(t *testing.T) {
for _, tc := range []struct {
name string
language workspace.Language
notebookExportFormat workspace.ExportFormat
notebookPath string
filePath string
expectedError string
}{
{
Add support for non-Python ipynb notebooks to DABs (#1827) ## Changes ### Background The workspace import APIs recently added support for importing Jupyter notebooks written in R, Scala, or SQL, that is non-Python notebooks. This now works for the `/import-file` API which we leverage in the CLI. Note: We do not need any changes in `databricks sync`. It works out of the box because any state mapping of local names to remote names that we store is only scoped to the notebook extension (i.e., `.ipynb` in this case) and is agnostic of the notebook's specific language. ### Problem this PR addresses The extension-aware filer previously did not function because it checks that a `.ipynb` notebook is written in Python. This PR relaxes that constraint and adds integration tests for both the normal workspace filer and extensions aware filer writing and reading non-Python `.ipynb` notebooks. This implies that after this PR DABs in the workspace / CLI from DBR will work for non-Python notebooks as well. non-Python notebooks for DABs deployment from local machines already works after the platform side changes to the API landed, this PR just adds integration tests for that bit of functionality. Note: Any platform side changes we needed for the import API have already been rolled out to production. ### Before DABs deploy would work fine for non-Python notebooks. But DABs deployments from DBR would not. ### After DABs deploys both from local machines and DBR will work fine. ## Testing For creating the `.ipynb` notebook fixtures used in the integration tests I created them directly from the VSCode UI. This ensures high fidelity with how users will create their non-Python notebooks locally. For Python notebooks this is supported out of the box by VSCode but for R and Scala notebooks this requires installing the Jupyter kernel for R and Scala on my local machine and using that from VSCode. For SQL, I ended up directly modifying the `language_info` field in the Jupyter metadata to create the test fixture. ### Discussion: Issues with configuring language at the cell level The language metadata for a Jupyter notebook is standardized at the notebook level (in the `language_info` field). Unfortunately, it's not standardized at the cell level. Thus, for example, if a user changes the language for their cell in VSCode (which is supported by the standard Jupyter VSCode integration), it'll cause a runtime error when the user actually attempts to run the notebook. This is because the cell-level metadata is encoded in a format specific to VSCode: ``` cells: []{ "vscode": { "languageId": "sql" } } ``` Supporting cell level languages is thus out of scope for this PR and can be revisited along with the workspace files team if there's strong customer interest.
2024-11-13 21:39:51 +00:00
name: "python source notebook and file with source extension",
language: workspace.LanguagePython,
notebookExportFormat: workspace.ExportFormatSource,
notebookPath: "/dir/foo",
filePath: "/dir/foo.py",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.py resolve to the same name /foo.py. Changing the name of one of these objects will resolve this issue",
},
{
Add support for non-Python ipynb notebooks to DABs (#1827) ## Changes ### Background The workspace import APIs recently added support for importing Jupyter notebooks written in R, Scala, or SQL, that is non-Python notebooks. This now works for the `/import-file` API which we leverage in the CLI. Note: We do not need any changes in `databricks sync`. It works out of the box because any state mapping of local names to remote names that we store is only scoped to the notebook extension (i.e., `.ipynb` in this case) and is agnostic of the notebook's specific language. ### Problem this PR addresses The extension-aware filer previously did not function because it checks that a `.ipynb` notebook is written in Python. This PR relaxes that constraint and adds integration tests for both the normal workspace filer and extensions aware filer writing and reading non-Python `.ipynb` notebooks. This implies that after this PR DABs in the workspace / CLI from DBR will work for non-Python notebooks as well. non-Python notebooks for DABs deployment from local machines already works after the platform side changes to the API landed, this PR just adds integration tests for that bit of functionality. Note: Any platform side changes we needed for the import API have already been rolled out to production. ### Before DABs deploy would work fine for non-Python notebooks. But DABs deployments from DBR would not. ### After DABs deploys both from local machines and DBR will work fine. ## Testing For creating the `.ipynb` notebook fixtures used in the integration tests I created them directly from the VSCode UI. This ensures high fidelity with how users will create their non-Python notebooks locally. For Python notebooks this is supported out of the box by VSCode but for R and Scala notebooks this requires installing the Jupyter kernel for R and Scala on my local machine and using that from VSCode. For SQL, I ended up directly modifying the `language_info` field in the Jupyter metadata to create the test fixture. ### Discussion: Issues with configuring language at the cell level The language metadata for a Jupyter notebook is standardized at the notebook level (in the `language_info` field). Unfortunately, it's not standardized at the cell level. Thus, for example, if a user changes the language for their cell in VSCode (which is supported by the standard Jupyter VSCode integration), it'll cause a runtime error when the user actually attempts to run the notebook. This is because the cell-level metadata is encoded in a format specific to VSCode: ``` cells: []{ "vscode": { "languageId": "sql" } } ``` Supporting cell level languages is thus out of scope for this PR and can be revisited along with the workspace files team if there's strong customer interest.
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name: "scala source notebook and file with source extension",
language: workspace.LanguageScala,
notebookExportFormat: workspace.ExportFormatSource,
notebookPath: "/dir/foo",
filePath: "/dir/foo.scala",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.scala resolve to the same name /foo.scala. Changing the name of one of these objects will resolve this issue",
},
{
Add support for non-Python ipynb notebooks to DABs (#1827) ## Changes ### Background The workspace import APIs recently added support for importing Jupyter notebooks written in R, Scala, or SQL, that is non-Python notebooks. This now works for the `/import-file` API which we leverage in the CLI. Note: We do not need any changes in `databricks sync`. It works out of the box because any state mapping of local names to remote names that we store is only scoped to the notebook extension (i.e., `.ipynb` in this case) and is agnostic of the notebook's specific language. ### Problem this PR addresses The extension-aware filer previously did not function because it checks that a `.ipynb` notebook is written in Python. This PR relaxes that constraint and adds integration tests for both the normal workspace filer and extensions aware filer writing and reading non-Python `.ipynb` notebooks. This implies that after this PR DABs in the workspace / CLI from DBR will work for non-Python notebooks as well. non-Python notebooks for DABs deployment from local machines already works after the platform side changes to the API landed, this PR just adds integration tests for that bit of functionality. Note: Any platform side changes we needed for the import API have already been rolled out to production. ### Before DABs deploy would work fine for non-Python notebooks. But DABs deployments from DBR would not. ### After DABs deploys both from local machines and DBR will work fine. ## Testing For creating the `.ipynb` notebook fixtures used in the integration tests I created them directly from the VSCode UI. This ensures high fidelity with how users will create their non-Python notebooks locally. For Python notebooks this is supported out of the box by VSCode but for R and Scala notebooks this requires installing the Jupyter kernel for R and Scala on my local machine and using that from VSCode. For SQL, I ended up directly modifying the `language_info` field in the Jupyter metadata to create the test fixture. ### Discussion: Issues with configuring language at the cell level The language metadata for a Jupyter notebook is standardized at the notebook level (in the `language_info` field). Unfortunately, it's not standardized at the cell level. Thus, for example, if a user changes the language for their cell in VSCode (which is supported by the standard Jupyter VSCode integration), it'll cause a runtime error when the user actually attempts to run the notebook. This is because the cell-level metadata is encoded in a format specific to VSCode: ``` cells: []{ "vscode": { "languageId": "sql" } } ``` Supporting cell level languages is thus out of scope for this PR and can be revisited along with the workspace files team if there's strong customer interest.
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name: "r source notebook and file with source extension",
language: workspace.LanguageR,
notebookExportFormat: workspace.ExportFormatSource,
notebookPath: "/dir/foo",
filePath: "/dir/foo.r",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.r resolve to the same name /foo.r. Changing the name of one of these objects will resolve this issue",
},
{
Add support for non-Python ipynb notebooks to DABs (#1827) ## Changes ### Background The workspace import APIs recently added support for importing Jupyter notebooks written in R, Scala, or SQL, that is non-Python notebooks. This now works for the `/import-file` API which we leverage in the CLI. Note: We do not need any changes in `databricks sync`. It works out of the box because any state mapping of local names to remote names that we store is only scoped to the notebook extension (i.e., `.ipynb` in this case) and is agnostic of the notebook's specific language. ### Problem this PR addresses The extension-aware filer previously did not function because it checks that a `.ipynb` notebook is written in Python. This PR relaxes that constraint and adds integration tests for both the normal workspace filer and extensions aware filer writing and reading non-Python `.ipynb` notebooks. This implies that after this PR DABs in the workspace / CLI from DBR will work for non-Python notebooks as well. non-Python notebooks for DABs deployment from local machines already works after the platform side changes to the API landed, this PR just adds integration tests for that bit of functionality. Note: Any platform side changes we needed for the import API have already been rolled out to production. ### Before DABs deploy would work fine for non-Python notebooks. But DABs deployments from DBR would not. ### After DABs deploys both from local machines and DBR will work fine. ## Testing For creating the `.ipynb` notebook fixtures used in the integration tests I created them directly from the VSCode UI. This ensures high fidelity with how users will create their non-Python notebooks locally. For Python notebooks this is supported out of the box by VSCode but for R and Scala notebooks this requires installing the Jupyter kernel for R and Scala on my local machine and using that from VSCode. For SQL, I ended up directly modifying the `language_info` field in the Jupyter metadata to create the test fixture. ### Discussion: Issues with configuring language at the cell level The language metadata for a Jupyter notebook is standardized at the notebook level (in the `language_info` field). Unfortunately, it's not standardized at the cell level. Thus, for example, if a user changes the language for their cell in VSCode (which is supported by the standard Jupyter VSCode integration), it'll cause a runtime error when the user actually attempts to run the notebook. This is because the cell-level metadata is encoded in a format specific to VSCode: ``` cells: []{ "vscode": { "languageId": "sql" } } ``` Supporting cell level languages is thus out of scope for this PR and can be revisited along with the workspace files team if there's strong customer interest.
2024-11-13 21:39:51 +00:00
name: "sql source notebook and file with source extension",
language: workspace.LanguageSql,
notebookExportFormat: workspace.ExportFormatSource,
notebookPath: "/dir/foo",
filePath: "/dir/foo.sql",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.sql resolve to the same name /foo.sql. Changing the name of one of these objects will resolve this issue",
},
{
Add support for non-Python ipynb notebooks to DABs (#1827) ## Changes ### Background The workspace import APIs recently added support for importing Jupyter notebooks written in R, Scala, or SQL, that is non-Python notebooks. This now works for the `/import-file` API which we leverage in the CLI. Note: We do not need any changes in `databricks sync`. It works out of the box because any state mapping of local names to remote names that we store is only scoped to the notebook extension (i.e., `.ipynb` in this case) and is agnostic of the notebook's specific language. ### Problem this PR addresses The extension-aware filer previously did not function because it checks that a `.ipynb` notebook is written in Python. This PR relaxes that constraint and adds integration tests for both the normal workspace filer and extensions aware filer writing and reading non-Python `.ipynb` notebooks. This implies that after this PR DABs in the workspace / CLI from DBR will work for non-Python notebooks as well. non-Python notebooks for DABs deployment from local machines already works after the platform side changes to the API landed, this PR just adds integration tests for that bit of functionality. Note: Any platform side changes we needed for the import API have already been rolled out to production. ### Before DABs deploy would work fine for non-Python notebooks. But DABs deployments from DBR would not. ### After DABs deploys both from local machines and DBR will work fine. ## Testing For creating the `.ipynb` notebook fixtures used in the integration tests I created them directly from the VSCode UI. This ensures high fidelity with how users will create their non-Python notebooks locally. For Python notebooks this is supported out of the box by VSCode but for R and Scala notebooks this requires installing the Jupyter kernel for R and Scala on my local machine and using that from VSCode. For SQL, I ended up directly modifying the `language_info` field in the Jupyter metadata to create the test fixture. ### Discussion: Issues with configuring language at the cell level The language metadata for a Jupyter notebook is standardized at the notebook level (in the `language_info` field). Unfortunately, it's not standardized at the cell level. Thus, for example, if a user changes the language for their cell in VSCode (which is supported by the standard Jupyter VSCode integration), it'll cause a runtime error when the user actually attempts to run the notebook. This is because the cell-level metadata is encoded in a format specific to VSCode: ``` cells: []{ "vscode": { "languageId": "sql" } } ``` Supporting cell level languages is thus out of scope for this PR and can be revisited along with the workspace files team if there's strong customer interest.
2024-11-13 21:39:51 +00:00
name: "python jupyter notebook and file with source extension",
language: workspace.LanguagePython,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
Add support for non-Python ipynb notebooks to DABs (#1827) ## Changes ### Background The workspace import APIs recently added support for importing Jupyter notebooks written in R, Scala, or SQL, that is non-Python notebooks. This now works for the `/import-file` API which we leverage in the CLI. Note: We do not need any changes in `databricks sync`. It works out of the box because any state mapping of local names to remote names that we store is only scoped to the notebook extension (i.e., `.ipynb` in this case) and is agnostic of the notebook's specific language. ### Problem this PR addresses The extension-aware filer previously did not function because it checks that a `.ipynb` notebook is written in Python. This PR relaxes that constraint and adds integration tests for both the normal workspace filer and extensions aware filer writing and reading non-Python `.ipynb` notebooks. This implies that after this PR DABs in the workspace / CLI from DBR will work for non-Python notebooks as well. non-Python notebooks for DABs deployment from local machines already works after the platform side changes to the API landed, this PR just adds integration tests for that bit of functionality. Note: Any platform side changes we needed for the import API have already been rolled out to production. ### Before DABs deploy would work fine for non-Python notebooks. But DABs deployments from DBR would not. ### After DABs deploys both from local machines and DBR will work fine. ## Testing For creating the `.ipynb` notebook fixtures used in the integration tests I created them directly from the VSCode UI. This ensures high fidelity with how users will create their non-Python notebooks locally. For Python notebooks this is supported out of the box by VSCode but for R and Scala notebooks this requires installing the Jupyter kernel for R and Scala on my local machine and using that from VSCode. For SQL, I ended up directly modifying the `language_info` field in the Jupyter metadata to create the test fixture. ### Discussion: Issues with configuring language at the cell level The language metadata for a Jupyter notebook is standardized at the notebook level (in the `language_info` field). Unfortunately, it's not standardized at the cell level. Thus, for example, if a user changes the language for their cell in VSCode (which is supported by the standard Jupyter VSCode integration), it'll cause a runtime error when the user actually attempts to run the notebook. This is because the cell-level metadata is encoded in a format specific to VSCode: ``` cells: []{ "vscode": { "languageId": "sql" } } ``` Supporting cell level languages is thus out of scope for this PR and can be revisited along with the workspace files team if there's strong customer interest.
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filePath: "/dir/foo.py",
// Jupyter notebooks would correspond to foo.ipynb so an error is not expected.
expectedError: "",
},
{
name: "scala jupyter notebook and file with source extension",
language: workspace.LanguageScala,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
filePath: "/dir/foo.scala",
// Jupyter notebooks would correspond to foo.ipynb so an error is not expected.
expectedError: "",
},
{
name: "sql jupyter notebook and file with source extension",
language: workspace.LanguageSql,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
filePath: "/dir/foo.sql",
// Jupyter notebooks would correspond to foo.ipynb so an error is not expected.
expectedError: "",
},
{
name: "r jupyter notebook and file with source extension",
language: workspace.LanguageR,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
filePath: "/dir/foo.sql",
// Jupyter notebooks would correspond to foo.ipynb so an error is not expected.
expectedError: "",
},
{
name: "python jupyter notebook and file with .ipynb extension",
language: workspace.LanguagePython,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
filePath: "/dir/foo.ipynb",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.ipynb resolve to the same name /foo.ipynb. Changing the name of one of these objects will resolve this issue",
},
{
name: "scala jupyter notebook and file with .ipynb extension",
language: workspace.LanguageScala,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
filePath: "/dir/foo.ipynb",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.ipynb resolve to the same name /foo.ipynb. Changing the name of one of these objects will resolve this issue",
},
{
name: "r jupyter notebook and file with .ipynb extension",
language: workspace.LanguageR,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
filePath: "/dir/foo.ipynb",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.ipynb resolve to the same name /foo.ipynb. Changing the name of one of these objects will resolve this issue",
},
{
name: "sql jupyter notebook and file with .ipynb extension",
language: workspace.LanguageSql,
notebookExportFormat: workspace.ExportFormatJupyter,
notebookPath: "/dir/foo",
filePath: "/dir/foo.ipynb",
expectedError: "failed to read files from the workspace file system. Duplicate paths encountered. Both NOTEBOOK at /dir/foo and FILE at /dir/foo.ipynb resolve to the same name /foo.ipynb. Changing the name of one of these objects will resolve this issue",
},
} {
t.Run(tc.name, func(t *testing.T) {
mockedWorkspaceClient := mocks.NewMockWorkspaceClient(t)
mockedApiClient := mockApiClient{}
// Mock the workspace API's ListAll method.
workspaceApi := mockedWorkspaceClient.GetMockWorkspaceAPI()
workspaceApi.EXPECT().ListAll(mock.Anything, workspace.ListWorkspaceRequest{
Path: "/dir",
}).Return([]workspace.ObjectInfo{
{
Path: tc.filePath,
Language: tc.language,
ObjectType: workspace.ObjectTypeFile,
},
{
Path: tc.notebookPath,
Language: tc.language,
ObjectType: workspace.ObjectTypeNotebook,
},
}, nil)
// Mock bespoke API calls to /api/2.0/workspace/get-status, that are
// used to figure out the right file extension for the notebook.
statNotebook := wsfsFileInfo{
ObjectInfo: workspace.ObjectInfo{
Path: tc.notebookPath,
Language: tc.language,
ObjectType: workspace.ObjectTypeNotebook,
},
ReposExportFormat: tc.notebookExportFormat,
}
mockedApiClient.On("Do", mock.Anything, http.MethodGet, "/api/2.0/workspace/get-status", map[string]string(nil), map[string]string{
"path": tc.notebookPath,
"return_export_info": "true",
}, mock.AnythingOfType("*filer.wsfsFileInfo"), []func(*http.Request) error(nil)).Return(nil, statNotebook)
workspaceFilesClient := workspaceFilesClient{
workspaceClient: mockedWorkspaceClient.WorkspaceClient,
apiClient: &mockedApiClient,
root: NewWorkspaceRootPath("/dir"),
}
workspaceFilesExtensionsClient := workspaceFilesExtensionsClient{
workspaceClient: mockedWorkspaceClient.WorkspaceClient,
wsfs: &workspaceFilesClient,
}
_, err := workspaceFilesExtensionsClient.ReadDir(context.Background(), "/")
if tc.expectedError == "" {
assert.NoError(t, err)
} else {
assert.ErrorAs(t, err, &duplicatePathError{})
assert.EqualError(t, err, tc.expectedError)
}
// assert the mocked methods were actually called, as a sanity check.
workspaceApi.AssertNumberOfCalls(t, "ListAll", 1)
mockedApiClient.AssertNumberOfCalls(t, "Do", 1)
})
}
}