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import glob
import json
import os
import sqlite3
from datetime import datetime
from huggingface_hub import CommitScheduler
try:
from trackio.context_vars import current_scheduler
from trackio.dummy_commit_scheduler import DummyCommitScheduler
from trackio.utils import TRACKIO_DIR
except: # noqa: E722
from context_vars import current_scheduler
from dummy_commit_scheduler import DummyCommitScheduler
from utils import TRACKIO_DIR
class SQLiteStorage:
@staticmethod
def get_project_db_path(project: str) -> str:
"""Get the database path for a specific project."""
safe_project_name = "".join(
c for c in project if c.isalnum() or c in ("-", "_")
).rstrip()
if not safe_project_name:
safe_project_name = "default"
return os.path.join(TRACKIO_DIR, f"{safe_project_name}.db")
@staticmethod
def init_db(project: str) -> str:
"""
Initialize the SQLite database with required tables.
Returns the database path.
"""
db_path = SQLiteStorage.get_project_db_path(project)
os.makedirs(os.path.dirname(db_path), exist_ok=True)
with SQLiteStorage.get_scheduler().lock:
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cursor.execute("""
CREATE TABLE IF NOT EXISTS metrics (
id INTEGER PRIMARY KEY AUTOINCREMENT,
timestamp TEXT NOT NULL,
project_name TEXT NOT NULL,
run_name TEXT NOT NULL,
step INTEGER NOT NULL,
metrics TEXT NOT NULL
)
""")
conn.commit()
return db_path
@staticmethod
def get_scheduler():
"""
Get the scheduler for the database based on the environment variables.
This applies to both local and Spaces.
"""
if current_scheduler.get() is not None:
return current_scheduler.get()
hf_token = os.environ.get("HF_TOKEN")
dataset_id = os.environ.get("TRACKIO_DATASET_ID")
if dataset_id is None:
scheduler = DummyCommitScheduler()
else:
scheduler = CommitScheduler(
repo_id=dataset_id,
repo_type="dataset",
folder_path=TRACKIO_DIR,
private=True,
squash_history=True,
token=hf_token,
)
current_scheduler.set(scheduler)
return scheduler
@staticmethod
def log(project: str, run: str, metrics: dict):
"""
Safely log metrics to the database. Before logging, this method will ensure the database exists
and is set up with the correct tables. It also uses the scheduler to lock the database so
that there is no race condition when logging / syncing to the Hugging Face Dataset.
"""
db_path = SQLiteStorage.init_db(project)
with SQLiteStorage.get_scheduler().lock:
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cursor.execute(
"""
SELECT MAX(step)
FROM metrics
WHERE project_name = ? AND run_name = ?
""",
(project, run),
)
last_step = cursor.fetchone()[0]
current_step = 0 if last_step is None else last_step + 1
current_timestamp = datetime.now().isoformat()
cursor.execute(
"""
INSERT INTO metrics
(timestamp, project_name, run_name, step, metrics)
VALUES (?, ?, ?, ?, ?)
""",
(
current_timestamp,
project,
run,
current_step,
json.dumps(metrics),
),
)
conn.commit()
@staticmethod
def bulk_log(
project: str,
run: str,
metrics_list: list[dict],
steps: list[int] | None = None,
timestamps: list[str] | None = None,
):
"""Bulk log metrics to the database with specified steps and timestamps."""
if not metrics_list:
return
if steps is None:
steps = list(range(len(metrics_list)))
if timestamps is None:
timestamps = [datetime.now().isoformat()] * len(metrics_list)
if len(metrics_list) != len(steps) or len(metrics_list) != len(timestamps):
raise ValueError(
"metrics_list, steps, and timestamps must have the same length"
)
db_path = SQLiteStorage.init_db(project)
with SQLiteStorage.get_scheduler().lock:
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
data = []
for i, metrics in enumerate(metrics_list):
data.append(
(
timestamps[i],
project,
run,
steps[i],
json.dumps(metrics),
)
)
cursor.executemany(
"""
INSERT INTO metrics
(timestamp, project_name, run_name, step, metrics)
VALUES (?, ?, ?, ?, ?)
""",
data,
)
conn.commit()
@staticmethod
def get_metrics(project: str, run: str) -> list[dict]:
"""Retrieve metrics for a specific run. The metrics also include the step count (int) and the timestamp (datetime object)."""
db_path = SQLiteStorage.get_project_db_path(project)
if not os.path.exists(db_path):
return []
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cursor.execute(
"""
SELECT timestamp, step, metrics
FROM metrics
WHERE project_name = ? AND run_name = ?
ORDER BY timestamp
""",
(project, run),
)
rows = cursor.fetchall()
results = []
for row in rows:
timestamp, step, metrics_json = row
metrics = json.loads(metrics_json)
metrics["timestamp"] = timestamp
metrics["step"] = step
results.append(metrics)
return results
@staticmethod
def get_projects() -> list[str]:
"""Get list of all projects by scanning database files."""
projects = []
if not os.path.exists(TRACKIO_DIR):
return projects
db_files = glob.glob(os.path.join(TRACKIO_DIR, "*.db"))
for db_file in db_files:
try:
with sqlite3.connect(db_file) as conn:
cursor = conn.cursor()
cursor.execute(
"SELECT name FROM sqlite_master WHERE type='table' AND name='metrics'"
)
if cursor.fetchone():
cursor.execute("SELECT DISTINCT project_name FROM metrics")
project_names = [row[0] for row in cursor.fetchall()]
projects.extend(project_names)
except sqlite3.Error:
continue
return list(set(projects))
@staticmethod
def get_runs(project: str) -> list[str]:
"""Get list of all runs for a project."""
db_path = SQLiteStorage.get_project_db_path(project)
if not os.path.exists(db_path):
return []
with sqlite3.connect(db_path) as conn:
cursor = conn.cursor()
cursor.execute(
"SELECT DISTINCT run_name FROM metrics WHERE project_name = ?",
(project,),
)
return [row[0] for row in cursor.fetchall()]
def finish(self):
"""Cleanup when run is finished."""
pass
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