🎏 📁 📊 ⏮️ 🏤:

```
.
├── app                  # "app" is a Python package
│   ├── __init__.py      # this file makes "app" a "Python package"
│   ├── main.py          # "main" module, e.g. import app.main
│   ├── dependencies.py  # "dependencies" module, e.g. import app.dependencies
│   └── routers          # "routers" is a "Python subpackage"
│   │   ├── __init__.py  # makes "routers" a "Python subpackage"

/compiler/testData/mockJDK9/ "Kotlin Build Infrastructure"
/compiler/testData/mockJDKModified/ "Kotlin Build Infrastructure"
/compiler/testData/moduleProtoBuf/ "Kotlin JVM"
/compiler/testData/modules.xml/ "Kotlin Compiler Core"
/compiler/testData/multiModule/ "Kotlin Compiler Core"
# UNKNOWN: /compiler/testData/multiplatform/
/compiler/testData/parseCodeFragment/ "Kotlin Compiler Core"

    ├── database.py
    ├── main.py
    ├── models.py
    └── schemas.py
```

The file `__init__.py` is just an empty file, but it tells Python that `sql_app` with all its modules (Python files) is a package.

Now let's see what each file/module does.

## Install `SQLAlchemy`

First you need to install `SQLAlchemy`:

<div class="termy">

```console
$ pip install sqlalchemy

---> 100%
```

cc_library(
    name = "dlpack",
    srcs = ["dlpack.cc"],
    hdrs = ["dlpack.h"],
    copts = tf_copts() + [
        "-fexceptions",
        "-fno-strict-aliasing",
    ],
    features = ["-use_header_modules"],
    visibility = ["//tensorflow:__subpackages__"],
    deps = [
        ":c_api",
        ":c_api_experimental",
        ":tfe_tensorhandle_internal",
        "//tensorflow/c:tf_status_helper",

        return false;
      }
    }
    return false;
  }

  /**
   * Returns an unmodifiable view of the specified navigable set. This method allows modules to
   * provide users with "read-only" access to internal navigable sets. Query operations on the
   * returned set "read through" to the specified set, and attempts to modify the returned set,

    }

    interface AmbiguousExpects : KtFirDiagnostic<KtNamedDeclaration> {
        override val diagnosticClass get() = AmbiguousExpects::class
        val declaration: KtSymbol
        val modules: List<FirModuleData>
    }

    interface NoActualClassMemberForExpectedClass : KtFirDiagnostic<KtNamedDeclaration> {
        override val diagnosticClass get() = NoActualClassMemberForExpectedClass::class

particular Contributor. A Contribution 'originates' from a Contributor if it was added to the Program by such Contributor itself or anyone acting on such Contributor's behalf. Contributions do not include additions to the Program which: (i) are separate modules of software distributed in conjunction with the Program under their own license agreement, and (ii) are not derivative works of the Program. "Contributor" means any person or entity that distributes the Program. "Licensed Patents " mean patent claims...

) : KtAbstractFirDiagnostic<KtNamedDeclaration>(firDiagnostic, token), KtFirDiagnostic.ActualWithoutExpect

internal class AmbiguousExpectsImpl(
    override val declaration: KtSymbol,
    override val modules: List<FirModuleData>,
    firDiagnostic: KtPsiDiagnostic,
    token: KtLifetimeToken,
) : KtAbstractFirDiagnostic<KtNamedDeclaration>(firDiagnostic, token), KtFirDiagnostic.AmbiguousExpects

    size.
*   TensorFlow 1.15 contains a complete implementation of the 2.0 API in its
    `compat.v2` module. It contains a copy of the 1.15 main module (without
    `contrib`) in the `compat.v1` module. TensorFlow 1.15 is able to emulate 2.0
    behavior using the `enable_v2_behavior()` function. This enables writing
    forward compatible code: by explicitly importing either

      BiMap<K, V> synchronizedBiMap(BiMap<K, V> bimap) {
    return Synchronized.biMap(bimap, null);
  }

  /**
   * Returns an unmodifiable view of the specified bimap. This method allows modules to provide
   * users with "read-only" access to internal bimaps. Query operations on the returned bimap "read
   * through" to the specified bimap, and attempts to modify the returned map, whether direct or via