resutil 0.2.1

Resutil is a utility to manage experimental result data obtained from Python projects. It also manages dependency such as codes and input data with result data. Data is synced to the cloud for team sharing and collaboration.

Resutil

Japanese readme is here

What is Resutil

Resutil is a utility to manage experimental result data obtained from Python projects. It also manages dependency such as codes and input data with result data. Data is synced to cloud storage (Google Cloud Storage, Google Drive, or a Resutil server) for team sharing and collaboration.

Why choose Resutil?

• Simple: Easy to install and can be quickly integrated into your project.
• High Reproducibility: Tracks programs, input data, and experimental results.
• Open-source and free: Join development to future release of Resutil.

Features

• Sync experimental data saved in a specific directory to cloud storage (Google Cloud Storage, Google Drive, or Resutil server) after the program execution finished.
• Save information necessary to reproduce the experiment in a YAML file.
• Execution command
• Input files given as arguments (only files within folders managed by resutil)
• Git commit hash
• Uncommitted files
• Upload experimental data that hasn’t been uploaded yet.
• Download experimental data from the cloud using commands.
• Automatically download dependencies that do not existing at run time.

Installation

Open terminal and run

pip install resutil

Prepare a Google Cloud service account key JSON for Cloud Storage (downloaded later in the setup steps) and save it as key.json in your project root. A typical key file looks like:

{
    "type": "service_account",
    "project_id": "your-gcp-project",
    "private_key_id": "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx",
    "private_key": "-----BEGIN PRIVATE KEY-----\nxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx\n-----END PRIVATE KEY-----\n",
    "client_email": "[e-mail]",
    "client_id": "123456789012345678901",
    "auth_uri": "https://accounts.google.com/o/oauth2/auth",
    "token_uri": "https://oauth2.googleapis.com/token"
}

Initialize resutil

$ cd your-project-root-directory
$ resutil init
Input project name (resutil): MyProj
Input directory name to store results (results): results
Do you want to add .gitignore to results? (Y/n): Y
Input storage_type (gcs/gdrive/server): gcs
Input key file_path (key.json): key.json
Do you want to add key.json to .gitignore? (Y/n): Y
Input bucket name: resutil
✅ Initialized.

The bucket name is your Cloud Storage bucket, and resutil-conf.yaml will be created with this configuration.

Modify main function in your project like:

# Import resutil
import resutil

# Add decorator before the main function
@resutil.main()
def main_func(params):
    # A directory is automatically created, and its path is stored in params.ex_dir
    ex_dir = params.ex_dir 

    # Execute the program HERE🚀
    # Resutil will handle the rest

if __name__ == "__main__":
    main_func()

Usage

Running resutil without arguments launches an interactive TUI for managing experiments. You can also use subcommands directly.

Running experiments

Run the program integrated with Resutil. You will first be prompted for a comment, and then an experiment result directory will be automatically created. This directory will include a name composed of a sequential alphabet, date, time, and your comment. The directory is then zipped and uploaded to the specified cloud storage after the program finishes.

$ python sample.py

✨ Running your code with Resutil

📦 Connected to Google Cloud Storage
  📁 Bucket name: resutil
  📁 Project dir: your_project

📝 Input comment for this experiment (press [tab] key for completion): nice-comment

🔍 Unstaged files will be stored in the result dir:
  - README.ja.md
  - README.md
🚀 Running the main function...

### Your code's output

🗂️ Uploading: aapfup_20240704T191555_nice-comment
ℹ️ There are 9 other experiment directories that have not been uploaded.
✅ Done

How to setup cloud storage for Resutil

Resutil supports Google Cloud Storage (default), Google Drive, and Resutil server. Below are the steps for each.

Google Cloud Storage (recommended)

1. Create a GCP project (if needed): In the Google Cloud Console, create or reuse a project.
2. Enable Cloud Storage API: Open API Library, search for “Cloud Storage”, and enable it.
3. Create a bucket: Go to Cloud Storage Browser, click Create Bucket, and set a name (e.g., resutil) and location/class.
4. Create a service account: In IAM & Admin → Service Accounts, click Create Service Account and name it (e.g., resutil-bot).
5. Grant permissions: Give the service account the Storage Object Admin (or at least Storage Object User + Storage Legacy Bucket Reader) role for the bucket so it can read/write objects.
6. Create and download a key: On the service account page, open Keys → Add Key → Create new key → choose JSON, then download key.json and place it in your project root (add to .gitignore).
7. Run resutil init: Choose gcs, enter the path to key.json, and the bucket name you created.

Google Drive

1. Create a folder in Google Drive and note the folder ID (the part after folders/ in the URL).
2. In Google Cloud Console, create/reuse a project and a service account; download a JSON key.
3. Enable Google Drive API for the project.
4. Share the Drive folder with the service account email from the JSON key, giving Editor access.
5. Run resutil init, choose gdrive, set key.json, and provide the base folder ID.

Resutil Server

1. Run resutil init, choose server, and enter the server URL and bucket name.
2. Run resutil login to authenticate via SSO.

Commands

resutil init

resutil init creates resutil-conf.yaml in your project folder such as:

project_name: MyProj
results_dir: results/
storage_type: gcs
storage_config:
  backet_name: resutil  # bucket name
  key_file_path: key.json

resutil push

The resutil push command is used to upload experimental data to the cloud that does not exist in the cloud result directory.

resutil push [exp_name] uploads experiment a specific directory to the cloud. Depending directorys included in exp-config.yaml are automtically uploaded. --no-dependency option restrain automatic dependency upload.

resutil push --all will upload all experimental data to the cloud.

This is useful for keeping your local data up-to-date with the data stored in the cloud, especially when multiple people are working on the same project and updating the experimental data.

resutil pull

The resutil pull command is used to download a specific experimental data from the cloud that does not exist in the local result directory.

resutil pull [exp_name] downloads experiment directory from cloud. Depending directorys included in exp-config.yaml are automtically downlowded. --no-dependency option restrain automatic dependency download.

resutil pull --all will download all experimental data from the cloud that is not currently in your local result directory.

This is useful for keeping your local data up-to-date with the data stored in the cloud, especially when multiple people are working on the same project and updating the experimental data.

resutil add

The resutil add command is used to add an experiment directory without executing any code.

You can use it as follows: resutil add [comment] -d [DEPENDENCY1] [DEPENDENCY2].... This command adds an experiment directory named "comment" and sets its dependencies. The dependencies are other experiments that this experiment depends on.

For example, if you have two experiments exp1 and exp2 and a new experiment depends on them, you can add the new experiment with the following command: resutil add "new experiment" -d exp1 exp2. This will create a new experiment directory named "new experiment" and set exp1 and exp2 as its dependencies.

resutil list

The resutil list command lists experiments in the cloud storage.

resutil rm

The resutil rm command removes experiments. You can use it as follows: resutil resutil rm [-l] [-r] EXPERIMENT1 [EXPERIMENT2].... --local or -l option removes only local experiment directory, whereas --remote or -r option for experiment data in cloud. Specifying neither options removes both experiments.

resutil comment EXPERIMENTAL

resutil comment [EXPERIMENT] [COMMENT] adds or modifies a comment following the timestamp in the experiment name. Both local and cloud experiment names will change if they exist. Note that Resutil regards a different experiment name as a different experiment, so this does not affect the name of the same experiment other users have already pulled.

resutil login

resutil login authenticates with a Resutil server via SSO. Credentials are saved to ~/.resutil/credentials.json. You can specify the server URL with --server-url; otherwise, it is read from resutil-conf.yaml.

resutil logout

resutil logout removes saved credentials from ~/.resutil/credentials.json.

resutil --version

resutil --version displays the installed version of Resutil.

Environment Variables

When running code that integrates Resutil, you can use the following environment variables:

RESUTIL_COMMENT Specifies a comment required at the start of execution. This prevents the need to prompt for a comment during execution.

RESUTIL_NO_INTERACTIVE Enables non-interactive mode. This prevents any user prompts during execution. This is useful when running as a batch job. If RESUTIL_COMMENT is not specified, no comment will be added to the experiment directory.

RESUTIIL_REMOTE Suppresses uploading results to cloud storage.

RESUTIL_DEBUG Enables debug mode where a temporary directory is used as experiment directory. The temporary directory will not be uploaded to cloud storage.

Saving checkpoint

For long-running executions, call param.save_checkpoint() to temporarily upload the data in the experiment directory.

Directory structure in the cloud storage

<bucket root>
├── MyProj  # Project directory
│   ├── aakuqj_20240511T174522_ex1.zip  # zip file of Experiment directory
│   │   ├── resutil-exp.yaml            # Experiment information
│   │   └── data.txt                    # Data (example)
│   ├── aamxrp_20240606T135747_ex2.zip
│   │   ├── resutil-exp.yaml
│   │   ├── data.txt
│   │   └── uncommited_files       # Uncommitted files
│   │       └── main.py
│   ...
│   
├── OtherProj
│
...

Experiment directories are formatted as xxxxxx_yyyymmddTHHMMSS_comment, where xxxxxx is timestamped for easy ordering and tab completion in shells.

resutil-exp.yaml [WIP]

Each experiment directory has resutil-exp.yaml, which contains information to reproduce experimental results.

cmd: Execution command
params: Options at runtime
  hoo: xxx
  bar: 123
dependency: Dependencies (automatically extracted from directories in the command)
  - ex1
  - ex2

how to publish

1. Change version number of pyproject.toml
2. merge branch to main
3. Add v*.. tag will automatically deploy to PyPI
4. Add a release note to GitHub such as:

   ## New Features
   - Add `--resutil_debug` and `--resutil_no_remote` options for trial-and-error phase
   - `-A` or `--all` options can be omitted for `resutil push/pull` commands
   
   ## Bug Fixed
   - Fix a bug resuitl does not works properly when git is not initialized