all_tags

def all_tags(repo: Optional[str] = None) -> list[str]

import dvc.api

tags = dvc.api.all_tags()
print(f"Found {len(tags)} tags: {tags}")

import dvc.api

tags = dvc.api.all_tags()

print("Release metrics:")
for tag in tags:
    if tag.startswith('v'):  # Version tags
        metrics = dvc.api.metrics_show(rev=tag)
        print(f"{tag}: {metrics}")

import dvc.api

# Get all release tags
tags = dvc.api.all_tags(repo="https://github.com/example/ml-project")

# Get latest version tag
version_tags = [t for t in tags if t.startswith('v')]
latest = sorted(version_tags)[-1]

print(f"Downloading model from {latest}")

# Read model from that tag
with dvc.api.open(
    'models/model.pkl',
    repo="https://github.com/example/ml-project",
    rev=latest
) as f:
    import pickle
    model = pickle.load(f)

import dvc.api
import pandas as pd

tags = dvc.api.all_tags()
release_tags = sorted([t for t in tags if t.startswith('v')])

results = []
for tag in release_tags:
    try:
        metrics = dvc.api.metrics_show(rev=tag)
        results.append({
            'release': tag,
            'accuracy': metrics.get('metrics.json', {}).get('accuracy'),
            'f1_score': metrics.get('metrics.json', {}).get('f1')
        })
    except Exception:
        continue

df = pd.DataFrame(results)
print(df)

import dvc.api

# Get all production tags
tags = dvc.api.all_tags()
prod_tags = [t for t in tags if 'prod' in t.lower()]

print(f"Found {len(prod_tags)} production releases:\n")

for tag in prod_tags:
    print(f"{tag}:")
    
    # Get model parameters
    params = dvc.api.params_show(rev=tag)
    print(f"  Model: {params.get('train', {}).get('model_type')}")
    
    # Get performance metrics
    metrics = dvc.api.metrics_show(rev=tag)
    print(f"  Accuracy: {metrics.get('metrics.json', {}).get('accuracy')}")
    print()