Cloudoll
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Cloudoll 4.0.0 is an aiohttp-based Python library for routing, middleware, templates, sessions, JWT, database access and application scaffolding.
Install
Python 3.9+ is required. Install only the optional drivers you use:
python -m pip install 'cloudoll==4.0.0'
python -m pip install 'cloudoll[mysql,postgres,cache]==4.0.0'
The AWS extra requires Python 3.10+. Aurora remains untested; see Aurora limitations.
Quick start
cloudoll create myapp
cd myapp
python -m pip install -r requirements.txt
cloudoll start -n myapp
The generated project targets 4.0.0 and receives a random JWT secret. Controllers and authentication middleware are examples: replace demo credentials and supply your own authorization and upload policies before deployment.
A minimal application without a configuration file:
from cloudoll.web import Application
application = Application()
@application.get('/')
async def home(request):
return {'hello': 'cloudoll'}
if __name__ == '__main__':
application.create(env=None, entry_model=None).run()
By default, create() loads config/conf.local.yaml. An explicitly selected missing file is an error. Use env=None or config={} only for intentional no-config mode. Template rendering uses Jinja2, via render_view().
Production and diagnostics
cloudoll start -n myapp -env prod -m production
Production mode stays in the foreground. Use a process manager for automatic restarts; do not mix its stop/restart commands with Cloudoll's manual management. Coordinate request draining, resource cleanup and process termination deadlines.
from cloudoll.logging import configure_logging
configure_logging(format='json', files=False)
JSON logging supports structured secret-key masking and a custom string redactor. Native MySQL/PostgreSQL support opt-in echo=True and echo_params=True; both default to false. SQL is logged at INFO and parameter output requires both switches. SQL text itself can contain secrets; avoid enabling this in production.
Application(observer=...) and observation_scope(...) expose value-free HTTP/query events. Native engines expose pool_stats(). trace_context() correlates log IDs; it is not a tracing SDK. See production contracts.
Upgrading from 3.0.14
- Replace executable configuration expressions with literal values. Missing environment variables/files and invalid core configuration fail explicitly.
- Use private Session/JWT keys. Discard cookies created with old publicly derivable keys; share the Session key across workers.
- JWT validation requires exp by default and supports issuer, audience, leeway and required claims. Invalid credentials return None; configuration errors raise. Explicit require=() permits legacy tokens without an expiry.
- Model.use(db) returns an independent Query. Records track UNSET and dirty fields; database errors propagate instead of appearing as empty results.
- Native transactions/savepoints are task-owned. Streams need an async with scope. Writes and uncertain COMMIT operations are never automatically retried.
- PostgreSQL ORM inserts use RETURNING. Raw inserts without RETURNING and batch inserts do not manufacture a primary key.
- Each Application can be created once. Discovery uses an isolated namespace; use package-relative imports for local controller helpers.
- Native pool closure defaults to 10 seconds; application resource closure uses a 10-second per-resource limit and a 30-second total budget. These deadlines cannot be disabled with None and do not bound arbitrary user cleanup code.
- Development children/reloads create independent applications at the explicit project root, including under fork. CLI verifies process identity before stop.
- HTTP Session.max_retries counts total attempts. POST/PATCH and non-replayable bodies are not automatically replayed by default.
See changelog, migration details, streaming and typing and schema generation. The schema generator is not a production database migration tool.
Development and release checks
python -m pip install -e '.[mysql,postgres,cache,dev]'
python -m ruff check cloudoll tests
python -m mypy
python -m pytest -q -m 'not integration' -k 'not aws'
python -m build
python tests/check_wheel.py dist/cloudoll-4.0.0-py3-none-any.whl
python tests/check_release.py dist/cloudoll-4.0.0-py3-none-any.whl
Native integration tests require explicitly configured disposable databases. See architecture and verification. AWS tests are excluded from ordinary CI. Passing CI is not a substitute for workload-specific testing.
Documentation and maintenance
1 maintainer
Metadata
1 maintainer
Release files for cloudoll 4.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| cloudoll-4.0.0.tar.gz | 165.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| cloudoll-4.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 277.4 kB
Release files / cloudoll-4.0.0.tar.gz
| Download URL | cloudoll-4.0.0.tar.gz |
|---|---|
| Size | 165.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.1
|
Release files / cloudoll-4.0.0-py3-none-any.whl
| Download URL | cloudoll-4.0.0-py3-none-any.whl |
|---|---|
| Size | 111.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.13.1
|
