Configure Mend Bolt for GitHub

.whitesource

@@ -0,0 +1,14 @@
+{
+  "scanSettings": {
+    "baseBranches": []
+  },
+  "checkRunSettings": {
+    "vulnerableCheckRunConclusionLevel": "failure",
+    "displayMode": "diff",
+    "useMendCheckNames": true
+  },
+  "issueSettings": {
+    "minSeverityLevel": "LOW",
+    "issueType": "DEPENDENCY"
+  }
+}

CHANGELOG.md

@@ -6,6 +6,12 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## Unreleased
 
+### Added
+
+- You can now deploy Gradio applications. This requires Posit Connect release 2024.11.0
+  or later. Use `rsconnect deploy gradio` to deploy, or `rsconnect write-manifest gradio`
+  to create a manifest file.
+
 ### Changed
 
 - The `rsconnect content build run --poll-wait` argument specifies an integral

README.md

@@ -4,8 +4,8 @@ This package provides a CLI (command-line interface) for interacting
 with and deploying to Posit Connect. This is also used by the
 [`rsconnect-jupyter`](https://github.com/rstudio/rsconnect-jupyter) package to deploy
 Jupyter notebooks via the Jupyter web console. Many types of content supported by Posit
-Connect may be deployed by this package, including WSGI-style APIs, Dash, Streamlit, and
-Bokeh applications.
+Connect may be deployed by this package, including WSGI-style APIs, Dash, Streamlit,
+Gradio, and Bokeh applications.
 
 Content types not directly supported by the CLI may also be deployed if they include a
 prepared `manifest.json` file. See ["Deploying R or Other
@@ -288,9 +288,10 @@ You can deploy a variety of APIs and applications using sub-commands of the
 * `dash`: Python Dash apps
 * `streamlit`: Streamlit apps
 * `bokeh`: Bokeh server apps
+* `gradio`: Gradio apps
 
 All options below apply equally to the `api`, `fastapi`, `dash`, `streamlit`,
-and `bokeh` sub-commands.
+`gradio`, and `bokeh` sub-commands.
 
 #### Including Extra Files
 
@@ -470,8 +471,8 @@ rsconnect deploy notebook --title "My Notebook" my-notebook.ipynb
 ```
 
 When using `rsconnect deploy api`, `rsconnect deploy fastapi`, `rsconnect deploy dash`,
-`rsconnect deploy streamlit`, or `rsconnect deploy bokeh`, the title is derived from the directory
-containing the API or application.
+`rsconnect deploy streamlit`, `rsconnect deploy bokeh`, or `rsconnect deploy gradio`,
+the title is derived from the directory containing the API or application.
 
 When using `rsconnect deploy manifest`, the title is derived from the primary
 filename referenced in the manifest.
@@ -726,7 +727,7 @@ rsconnect content search --help
 #   -c, --cacert FILENAME           The path to trusted TLS CA certificates.
 #   --published                     Search only published content.
 #   --unpublished                   Search only unpublished content.
-#   --content-type [unknown|shiny|rmd-static|rmd-shiny|static|api|tensorflow-saved-model|jupyter-static|python-api|python-dash|python-streamlit|python-bokeh|python-fastapi|quarto-shiny|quarto-static]
+#   --content-type [unknown|shiny|rmd-static|rmd-shiny|static|api|tensorflow-saved-model|jupyter-static|python-api|python-dash|python-streamlit|python-bokeh|python-fastapi|python-gradio|quarto-shiny|quarto-static]
 #                                   Filter content results by content type.
 #   --r-version VERSIONSEARCHFILTER
 #                                   Filter content results by R version.

rsconnect/main.py

@@ -1738,7 +1738,7 @@ def deploy_app(
 generate_deploy_python(app_mode=AppModes.STREAMLIT_APP, alias="streamlit", min_version="1.8.4")
 generate_deploy_python(app_mode=AppModes.BOKEH_APP, alias="bokeh", min_version="1.8.4")
 generate_deploy_python(app_mode=AppModes.PYTHON_SHINY, alias="shiny", min_version="2022.07.0")
-
+generate_deploy_python(app_mode=AppModes.PYTHON_GRADIO, alias="gradio", min_version="2024.11.0")
 
 @deploy.command(
     name="other-content",
@@ -2272,6 +2272,7 @@ def manifest_writer(
 generate_write_manifest_python(AppModes.PYTHON_FASTAPI, alias="fastapi")
 generate_write_manifest_python(AppModes.PYTHON_SHINY, alias="shiny")
 generate_write_manifest_python(AppModes.STREAMLIT_APP, alias="streamlit")
+generate_write_manifest_python(AppModes.PYTHON_GRADIO, alias="gradio")
 
 
 # noinspection SpellCheckingInspection

rsconnect/models.py

@@ -97,6 +97,7 @@ class AppModes:
     STATIC_QUARTO = AppMode(14, "quarto-static", "Quarto Document", ".qmd")
     PYTHON_SHINY = AppMode(15, "python-shiny", "Python Shiny Application")
     JUPYTER_VOILA = AppMode(16, "jupyter-voila", "Jupyter Voila Application")
+    PYTHON_GRADIO = AppMode(17, "python-gradio", "Gradio Application")
 
     _modes = [
         UNKNOWN,
@@ -116,6 +117,7 @@ class AppModes:
         STATIC_QUARTO,
         PYTHON_SHINY,
         JUPYTER_VOILA,
+        PYTHON_GRADIO
     ]
 
     Modes = Literal[
@@ -136,6 +138,7 @@ class AppModes:
         "quarto-static",
         "python-shiny",
         "jupyter-voila",
+        "python-gradio"
     ]
 
     _cloud_to_connect_modes = {

tests/test_bundle.py

@@ -1059,9 +1059,7 @@ def test_make_tensorflow_manifest_empty(self):
             manifest,
             {
                 "version": 1,
-                "metadata": {
-                    "appmode": "tensorflow-saved-model"
-                },
+                "metadata": {"appmode": "tensorflow-saved-model"},
                 "files": {},
             },
         )
@@ -1082,9 +1080,7 @@ def test_make_tensorflow_manifest(self):
             manifest,
             {
                 "version": 1,
-                "metadata": {
-                    "appmode": "tensorflow-saved-model"
-                },
+                "metadata": {"appmode": "tensorflow-saved-model"},
                 "files": {
                     "1/saved_model.pb": {"checksum": mock.ANY},
                 },
@@ -1105,17 +1101,15 @@ def test_make_tensorflow_bundle(self):
                     [
                         "1/saved_model.pb",
                         "manifest.json",
-                        ],
-                    )
+                    ],
+                )
                 manifest_data = tar.extractfile("manifest.json").read().decode("utf-8")
                 manifest = json.loads(manifest_data)
                 self.assertEqual(
                     manifest,
                     {
                         "version": 1,
-                        "metadata": {
-                            "appmode": "tensorflow-saved-model"
-                        },
+                        "metadata": {"appmode": "tensorflow-saved-model"},
                         "files": {
                             "1/saved_model.pb": {"checksum": mock.ANY},
                         },
@@ -2909,6 +2903,76 @@ def test_make_manifest_bundle():
         assert manifest["files"].keys() == bundle_json["files"].keys()
 
 
+gradio_dir = os.path.join(cur_dir, "./testdata/gradio")
+gradio_file = os.path.join(cur_dir, "./testdata/gradio/app.py")
+
+
+def test_make_api_manifest_gradio():
+    gradio_dir_ans = {
+        "version": 1,
+        "locale": "en_US.UTF-8",
+        "metadata": {"appmode": "python-gradio"},
+        "python": {
+            "version": "3.8.12",
+            "package_manager": {"name": "pip", "version": "23.0.1", "package_file": "requirements.txt"},
+        },
+        "files": {
+            "requirements.txt": {"checksum": "381ccadfb8d4848add470e33033b198f"},
+            "app.py": {"checksum": "22feec76e9c02ac6b5a34a083e2983b6"},
+        },
+    }
+    environment = create_python_environment(
+        gradio_dir,
+    )
+    manifest, _ = make_api_manifest(
+        gradio_dir,
+        None,
+        AppModes.PYTHON_GRADIO,
+        environment,
+        None,
+        None,
+    )
+
+    assert gradio_dir_ans["metadata"] == manifest["metadata"]
+    assert gradio_dir_ans["files"].keys() == manifest["files"].keys()
+
+
+def test_make_api_bundle_gradio():
+    gradio_dir_ans = {
+        "version": 1,
+        "locale": "en_US.UTF-8",
+        "metadata": {"appmode": "python-gradio"},
+        "python": {
+            "version": "3.8.12",
+            "package_manager": {"name": "pip", "version": "23.0.1", "package_file": "requirements.txt"},
+        },
+        "files": {
+            "requirements.txt": {"checksum": "381ccadfb8d4848add470e33033b198f"},
+            "app.py": {"checksum": "22feec76e9c02ac6b5a34a083e2983b6"},
+        },
+    }
+    environment = create_python_environment(
+        gradio_dir,
+    )
+    with make_api_bundle(
+        gradio_dir,
+        None,
+        AppModes.PYTHON_GRADIO,
+        environment,
+        None,
+        None,
+    ) as bundle, tarfile.open(mode="r:gz", fileobj=bundle) as tar:
+        names = sorted(tar.getnames())
+        assert names == [
+            "app.py",
+            "manifest.json",
+            "requirements.txt",
+        ]
+        bundle_json = json.loads(tar.extractfile("manifest.json").read().decode("utf-8"))
+        assert gradio_dir_ans["metadata"] == bundle_json["metadata"]
+        assert gradio_dir_ans["files"].keys() == bundle_json["files"].keys()
+
+
 empty_manifest_file = os.path.join(cur_dir, "./testdata/Manifest_data/empty_manifest.json")
 missing_file_manifest = os.path.join(cur_dir, "./testdata/Manifest_data/missing_file_manifest.json")
 

tests/testdata/gradio/app.py

@@ -0,0 +1,12 @@
+import gradio as gr
+
+def greet(name, intensity):
+    return "Hello, " + name + "!" * int(intensity)
+
+demo = gr.Interface(
+    fn=greet,
+    inputs=["text", "slider"],
+    outputs=["text"],
+)
+
+demo.launch(auth = ("username", "password"))

tests/testdata/gradio/requirements.txt

@@ -0,0 +1 @@
+gradio