Metadata-Version: 2.2
Name: mlflow-go-backend
Version: 0.1.0
Summary: MLflow is an open source platform for the complete machine learning lifecycle
Maintainer-email: Databricks <mlflow-oss-maintainers@googlegroups.com>
License:                                  Apache License
                                   Version 2.0, January 2004
                                http://www.apache.org/licenses/
        
           TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
        
           1. Definitions.
        
              "License" shall mean the terms and conditions for use, reproduction,
              and distribution as defined by Sections 1 through 9 of this document.
        
              "Licensor" shall mean the copyright owner or entity authorized by
              the copyright owner that is granting the License.
        
              "Legal Entity" shall mean the union of the acting entity and all
              other entities that control, are controlled by, or are under common
              control with that entity. For the purposes of this definition,
              "control" means (i) the power, direct or indirect, to cause the
              direction or management of such entity, whether by contract or
              otherwise, or (ii) ownership of fifty percent (50%) or more of the
              outstanding shares, or (iii) beneficial ownership of such entity.
        
              "You" (or "Your") shall mean an individual or Legal Entity
              exercising permissions granted by this License.
        
              "Source" form shall mean the preferred form for making modifications,
              including but not limited to software source code, documentation
              source, and configuration files.
        
              "Object" form shall mean any form resulting from mechanical
              transformation or translation of a Source form, including but
              not limited to compiled object code, generated documentation,
              and conversions to other media types.
        
              "Work" shall mean the work of authorship, whether in Source or
              Object form, made available under the License, as indicated by a
              copyright notice that is included in or attached to the work
              (an example is provided in the Appendix below).
        
              "Derivative Works" shall mean any work, whether in Source or Object
              form, that is based on (or derived from) the Work and for which the
              editorial revisions, annotations, elaborations, or other modifications
              represent, as a whole, an original work of authorship. For the purposes
              of this License, Derivative Works shall not include works that remain
              separable from, or merely link (or bind by name) to the interfaces of,
              the Work and Derivative Works thereof.
        
              "Contribution" shall mean any work of authorship, including
              the original version of the Work and any modifications or additions
              to that Work or Derivative Works thereof, that is intentionally
              submitted to Licensor for inclusion in the Work by the copyright owner
              or by an individual or Legal Entity authorized to submit on behalf of
              the copyright owner. For the purposes of this definition, "submitted"
              means any form of electronic, verbal, or written communication sent
              to the Licensor or its representatives, including but not limited to
              communication on electronic mailing lists, source code control systems,
              and issue tracking systems that are managed by, or on behalf of, the
              Licensor for the purpose of discussing and improving the Work, but
              excluding communication that is conspicuously marked or otherwise
              designated in writing by the copyright owner as "Not a Contribution."
        
              "Contributor" shall mean Licensor and any individual or Legal Entity
              on behalf of whom a Contribution has been received by Licensor and
              subsequently incorporated within the Work.
        
           2. Grant of Copyright License. Subject to the terms and conditions of
              this License, each Contributor hereby grants to You a perpetual,
              worldwide, non-exclusive, no-charge, royalty-free, irrevocable
              copyright license to reproduce, prepare Derivative Works of,
              publicly display, publicly perform, sublicense, and distribute the
              Work and such Derivative Works in Source or Object form.
        
           3. Grant of Patent License. Subject to the terms and conditions of
              this License, each Contributor hereby grants to You a perpetual,
              worldwide, non-exclusive, no-charge, royalty-free, irrevocable
              (except as stated in this section) patent license to make, have made,
              use, offer to sell, sell, import, and otherwise transfer the Work,
              where such license applies only to those patent claims licensable
              by such Contributor that are necessarily infringed by their
              Contribution(s) alone or by combination of their Contribution(s)
              with the Work to which such Contribution(s) was submitted. If You
              institute patent litigation against any entity (including a
              cross-claim or counterclaim in a lawsuit) alleging that the Work
              or a Contribution incorporated within the Work constitutes direct
              or contributory patent infringement, then any patent licenses
              granted to You under this License for that Work shall terminate
              as of the date such litigation is filed.
        
           4. Redistribution. You may reproduce and distribute copies of the
              Work or Derivative Works thereof in any medium, with or without
              modifications, and in Source or Object form, provided that You
              meet the following conditions:
        
              (a) You must give any other recipients of the Work or
                  Derivative Works a copy of this License; and
        
              (b) You must cause any modified files to carry prominent notices
                  stating that You changed the files; and
        
              (c) You must retain, in the Source form of any Derivative Works
                  that You distribute, all copyright, patent, trademark, and
                  attribution notices from the Source form of the Work,
                  excluding those notices that do not pertain to any part of
                  the Derivative Works; and
        
              (d) If the Work includes a "NOTICE" text file as part of its
                  distribution, then any Derivative Works that You distribute must
                  include a readable copy of the attribution notices contained
                  within such NOTICE file, excluding those notices that do not
                  pertain to any part of the Derivative Works, in at least one
                  of the following places: within a NOTICE text file distributed
                  as part of the Derivative Works; within the Source form or
                  documentation, if provided along with the Derivative Works; or,
                  within a display generated by the Derivative Works, if and
                  wherever such third-party notices normally appear. The contents
                  of the NOTICE file are for informational purposes only and
                  do not modify the License. You may add Your own attribution
                  notices within Derivative Works that You distribute, alongside
                  or as an addendum to the NOTICE text from the Work, provided
                  that such additional attribution notices cannot be construed
                  as modifying the License.
        
              You may add Your own copyright statement to Your modifications and
              may provide additional or different license terms and conditions
              for use, reproduction, or distribution of Your modifications, or
              for any such Derivative Works as a whole, provided Your use,
              reproduction, and distribution of the Work otherwise complies with
              the conditions stated in this License.
        
           5. Submission of Contributions. Unless You explicitly state otherwise,
              any Contribution intentionally submitted for inclusion in the Work
              by You to the Licensor shall be under the terms and conditions of
              this License, without any additional terms or conditions.
              Notwithstanding the above, nothing herein shall supersede or modify
              the terms of any separate license agreement you may have executed
              with Licensor regarding such Contributions.
        
           6. Trademarks. This License does not grant permission to use the trade
              names, trademarks, service marks, or product names of the Licensor,
              except as required for reasonable and customary use in describing the
              origin of the Work and reproducing the content of the NOTICE file.
        
           7. Disclaimer of Warranty. Unless required by applicable law or
              agreed to in writing, Licensor provides the Work (and each
              Contributor provides its Contributions) on an "AS IS" BASIS,
              WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
              implied, including, without limitation, any warranties or conditions
              of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
              PARTICULAR PURPOSE. You are solely responsible for determining the
              appropriateness of using or redistributing the Work and assume any
              risks associated with Your exercise of permissions under this License.
        
           8. Limitation of Liability. In no event and under no legal theory,
              whether in tort (including negligence), contract, or otherwise,
              unless required by applicable law (such as deliberate and grossly
              negligent acts) or agreed to in writing, shall any Contributor be
              liable to You for damages, including any direct, indirect, special,
              incidental, or consequential damages of any character arising as a
              result of this License or out of the use or inability to use the
              Work (including but not limited to damages for loss of goodwill,
              work stoppage, computer failure or malfunction, or any and all
              other commercial damages or losses), even if such Contributor
              has been advised of the possibility of such damages.
        
           9. Accepting Warranty or Additional Liability. While redistributing
              the Work or Derivative Works thereof, You may choose to offer,
              and charge a fee for, acceptance of support, warranty, indemnity,
              or other liability obligations and/or rights consistent with this
              License. However, in accepting such obligations, You may act only
              on Your own behalf and on Your sole responsibility, not on behalf
              of any other Contributor, and only if You agree to indemnify,
              defend, and hold each Contributor harmless for any liability
              incurred by, or claims asserted against, such Contributor by reason
              of your accepting any such warranty or additional liability.
        
           END OF TERMS AND CONDITIONS
        
           APPENDIX: How to apply the Apache License to your work.
        
              To apply the Apache License to your work, attach the following
              boilerplate notice, with the fields enclosed by brackets "[]"
              replaced with your own identifying information. (Don't include
              the brackets!)  The text should be enclosed in the appropriate
              comment syntax for the file format. We also recommend that a
              file or class name and description of purpose be included on the
              same "printed page" as the copyright notice for easier
              identification within third-party archives.
        
           Copyright [yyyy] [name of copyright owner]
        
           Licensed under the Apache License, Version 2.0 (the "License");
           you may not use this file except in compliance with the License.
           You may obtain a copy of the License at
        
               http://www.apache.org/licenses/LICENSE-2.0
        
           Unless required by applicable law or agreed to in writing, software
           distributed under the License is distributed on an "AS IS" BASIS,
           WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
           See the License for the specific language governing permissions and
           limitations under the License.
        
Project-URL: homepage, https://mlflow.org
Project-URL: issues, https://github.com/mlflow/mlflow-go-backend/issues
Project-URL: documentation, https://mlflow.org/docs/latest/index.html
Project-URL: repository, https://github.com/mlflow/mlflow-go-backend
Keywords: mlflow,go,golang,ai,databricks
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: End Users/Desktop
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Information Technology
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: cffi>=1.17.1
Requires-Dist: mlflow>=2.19.0
Requires-Dist: psycopg2-binary>=2.9.9

# Go backend for MLflow

In order to increase the performance of the tracking server and the various stores, we propose to rewrite the server and store implementation in Go.


# Topics
* [Installation](#installation)
* [Mage](#mage)
* [Contributing](./CONTRIBUTING.md)
* [Common information](#common-information)
  * [MLflow source code](#mlflow-source-code)
  * [Protos](#protos)
  * [Request validation](#request-validation)
  * [Data access](#data-access)
  * [Linting](#linting)
* [Usage](#usage)
  * [Go Server](#go-server)
  * [Building the Go binary](#building-the-go-binary)
  * [Client-side Go implementation](#client-side-go-implementation)
  * [Go store in Python](#go-store-in-python)
* [Misc](#misc)
  * [Debug Failing Tests](#debug-failing-tests)
  * [Supported endpoints](#supported-endpoints)
  * [Targeting Local Postgres in Python Tests](#targeting-local-postgres-in-python-tests)

## Installation

This package is not yet available on PyPI and currently requires the [Go SDK](https://go.dev) to be installed.

You can then install the package via pip:
```bash
pip install git+https://github.com/mlflow/mlflow-go-backend.git
```

## Mage

This repository uses [mage](https://magefile.org/) to streamline some utility functions.

```bash
# Install mage (already done in the dev container)
go install github.com/magefile/mage@v1.15.0
```

```bash
# See all targets
mage
```

```bash
# Execute single target
mage generate
```

The beauty of Mage is that we can use regular Go code for our scripting. That being said, we are not married to this tool.

## Common information

### MLflow source code

To integrate with MLflow, you need to include the source code. The [mlflow/mlflow](https://github.com/mlflow/mlflow/) repository contains proto files that define the tracking API. It also includes Python tests that we use to verify our Go implementation produces identical behaviour.

We use a `.mlflow.ref` file to specify the exact location from which to pull our sources. The format should be `remote#reference`, where `remote` is a git remote and `reference` is a branch, tag, or commit SHA.

If the `.mlflow.ref` file is modified and becomes out of sync with the current source files, the mage target will automatically detect this. To manually force a sync, you can run `mage repo:update`.

### Protos

To ensure we stay compatible with the Python implementation, we aim to generate as much as possible based on the `.proto` files.

By running

```bash
mage generate
```

Go code will be generated. Use the protos files from `.mlflow.repo` repository.

This includes the generation of:

- Structs for each endpoint. ([pkg/protos](./pkg/protos/service.pb.go))
- Go interfaces for each service. ([pkg/contract/service/*.g.go](./pkg/contract/service/tracking.g.go))
- [fiber](https://gofiber.io/) routes for each endpoint. ([pkg/server/routes/*.g.go](./pkg/server/routes/tracking.g.go))

If there is any change in the proto files, this should ripple into the Go code.

### Request validation

We use [Go validator](https://github.com/go-playground/validator) to validate all incoming request structs.
As the proto files don't specify any validation rules, we map them manually in [pkg/cmd/generate/validations.go](./cmd/generate/validations.go).

Once the mapping has been done, validation will be invoked automatically in the generated fiber code.

When the need arises, we can write custom validation function in [pkg/validation/validation.go](./validation/validation.go).

### Data access

Initially, we want to focus on supporting Postgres SQL. We chose [Gorm](https://gorm.io/) as ORM to interact with the database.

We do not generate any Go code based on the database schema. Gorm has generation capabilities but they didn't fit our needs. The plan would be to eventually assert the current code still matches the database schema via an integration test.

All the models use pointers for their fields. We do this for performance reasons and to distinguish between zero values and null values.

### Linting

We have enabled various linters from [golangci-lint](https://golangci-lint.run/), you can run these via:

```bash
pre-commit run golangci-lint --all-files
```

Sometimes `golangci-lint` can complain about unrelated files, run `golangci-lint cache clean` to clear the cache.

## Usage

### Go server

To enable use of the Go server, users can run the `mlflow-go server` command.

```bash
# Start the Go server with a database URI
# Other databases are supported as well: sqlite, mysql and mssql
mlflow-go server --backend-store-uri postgresql://postgres:postgres@localhost:5432/postgres
```

This will launch the python process as usual. Within Python, a random port is chosen to start the existing server and a Go child process is spawned. The Go server will use the user specified port (5000 by default) and spawn the actual Python server as its own child process (`gunicorn` or `waitress`).
Any incoming requests the Go server cannot process will be proxied to the existing Python server.

Any Go-specific options can be passed with `--go-opts`, which takes a comma-separated list of key-value pairs.

```bash
mlflow-go server --backend-store-uri postgresql://postgres:postgres@localhost:5432/postgres --go-opts log_level=debug,shutdown_timeout=5s
```

MLflow client could be pointed the Go server:

```python
import mlflow

# Use the Go server
mlflow.set_tracking_uri("http://localhost:5000")

# Use MLflow as usual
mlflow.set_experiment("my-experiment")

with mlflow.start_run():
    mlflow.log_param("param", 1)
    mlflow.log_metric("metric", 2)
```

### Building the Go binary

To ensure everything still compiles:

```bash
go build -o /dev/null ./pkg/cmd/server
```

or

```bash
python -m mlflow_go.lib . /tmp
```

### Client-side Go implementation

```python
import mlflow
import mlflow_go

# Enable the Go client implementation (disabled by default)
mlflow_go.enable_go()

# Set the tracking URI (you can also set it via the environment variable MLFLOW_TRACKING_URI)
# Currently only database URIs are supported
mlflow.set_tracking_uri("sqlite:///mlflow.db")

# Use MLflow as usual
mlflow.set_experiment("my-experiment")

with mlflow.start_run():
    mlflow.log_param("param", 1)
    mlflow.log_metric("metric", 2)
```

### Go store in Python

```python
import logging
import mlflow
import mlflow_go

# Enable debug logging
logging.basicConfig()
logging.getLogger('mlflow_go').setLevel(logging.DEBUG)

# Enable the Go client implementation (disabled by default)
mlflow_go.enable_go()

# Instantiate the tracking store with a database URI
tracking_store = mlflow.tracking._tracking_service.utils._get_store('sqlite:///mlflow.db')

# Call any tracking store method
tracking_store.get_experiment(0)

# Instantiate the model registry store with a database URI
model_registry_store = mlflow.tracking._model_registry.utils._get_store('sqlite:///mlflow.db')

# Call any model registry store method
model_registry_store.get_latest_versions("model")
```

## Misc

### Debug Failing Tests

Sometimes, it can be very useful to modify failing tests and use `print` statements to display the current state or differences between objects from Python or Go services.

Adding `"-vv"` to the `pytest` command in `magefiles/tests.go` can also provide more information when assertions are not met.

### Targeting Local Postgres in Python Tests

At times, you might want to apply store calls to your local database to investigate certain read operations via the local tracking server.

You can achieve this by changing:

```python
def test_search_runs_datasets(store: SqlAlchemyStore):
```

to:

```python
def test_search_runs_datasets():
    db_uri = "postgresql://postgres:postgres@localhost:5432/postgres"
    artifact_uri = Path("/tmp/artifacts")
    artifact_uri.mkdir(exist_ok=True)
    store = SqlAlchemyStore(db_uri, artifact_uri.as_uri())
```

in the test file located in `.mlflow.repo`.

### Supported endpoints

The currently supported endpoints can be found by running mage command:

```bash
mage endpoints
```

