Skip to content

⚡ Bolt: Optimize AdaptiveMemory with persistent SQLite connection and WAL mode #13

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Draft
google-labs-jules wants to merge 1 commit into
base: main
Choose a base branch
from
Draft

⚡ Bolt: Optimize AdaptiveMemory with persistent SQLite connection and WAL mode #13

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
3 changes: 3 additions & 0 deletions .jules/bolt.md
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,3 @@
## 2024-05-23 - SQLite Performance Pattern
**Learning:** Reusing a single `sqlite3` connection with `PRAGMA journal_mode=WAL` provides ~25x speedup over opening/closing connections per operation for write workloads. However, in a multi-threaded Python app, this requires explicit locking (`threading.RLock`) and robust `check_same_thread=False` configuration.
**Action:** Always prefer persistent connections with WAL for SQLite in Python, wrapped in a thread-safe class with proper lifecycle management (open/close).
Loading