name: Submit Dependency Graph
on:
  workflow_dispatch:
  push:
    branches:
      - master

permissions: {}

jobs:
  generate-and-submit:
    permissions:
      contents: write
    runs-on: ubuntu-latest
    steps:
    - uses: actions/checkout@v5
    - uses: actions/setup-java@v5
      with:
        distribution: temurin
        java-version: 17
    - name: Setup Gradle

        processMemberOf(user, groupList, roleList, "https://graph.microsoft.com/v1.0/me/memberOf");
        user.setGroups(groupList.stream().distinct().toArray(n -> new String[n]));
        user.setRoles(roleList.stream().distinct().toArray(n -> new String[n]));
    }

    /**
     * Processes member-of information from Microsoft Graph API.
     * @param user The Azure AD user.

  assert(session);
  {
    tensorflow::mutex_lock c(session->graph->mu);
    VLOG(1) << "Dequeuing named tensor with id " << tensor_id
            << ", with input graph: "
            << session->graph->graph.ToGraphDefDebug().DebugString();
  }

  TF_Operation* dequeue_op = TF_GraphOperationByName(
      session->graph,
      tensorflow::strings::StrCat("fifo_queue_dequeue_", tensor_id).c_str());

  "durations" : [ {
    "testProject" : "excludeRuleMergingBuild",
    "linux" : 232
  } ]
}, {
  "scenario" : "org.gradle.performance.regression.corefeature.LargeDependencyGraphPerformanceTest.resolve large dependency graph (parallel = false, locking = true)",
  "durations" : [ {

But **FastAPI** will know that it has to solve `query_extractor` first, to pass the results of that to `query_or_cookie_extractor` while calling it.

///

```mermaid
graph TB

query_extractor(["query_extractor"])
query_or_cookie_extractor(["query_or_cookie_extractor"])

read_query["/items/"]

query_extractor --> query_or_cookie_extractor --> read_query
```

* Calling your dependency ("dependable") function with the correct parameters.
* Get the result from your function.
* Assign that result to the parameter in your *path operation function*.

```mermaid
graph TB

common_parameters(["common_parameters"])
read_items["/items/"]
read_users["/users/"]

common_parameters --> read_items
common_parameters --> read_users
```

    have resulted in an error. When this happens, a noop is returned and the
    input tensors are marked non-feedable. In other words, if they are used as
    keys in `feed_dict` argument to `session.run()`, an error will be raised.
    Also, because some assert ops don't make it into the graph, the graph
    structure changes. A different graph can result in different per-op random

* Even dependencies can have dependencies, creating a hierarchy or **"graph" of dependencies**.
* All **automatically handled** by the framework.
* All the dependencies can require data from requests and **augment the path operation** constraints and automatic documentation.

Because we have a proxy with a path prefix of `/api/v1` for our app, the frontend needs to fetch the OpenAPI schema at `/api/v1/openapi.json`.

```mermaid
graph LR

browser("Browser")
proxy["Proxy on http://0.0.0.0:9999/api/v1/app"]
server["Server on http://127.0.0.1:8000/app"]

browser --> proxy
proxy --> server
```

/// tip