Active fork of baiji-pod, Body Labs' asset cache for S3 using baiji
Project description
This is an active fork of baiji-pod, Body Labs’ asset cache for S3 using baiji.
The fork’s goals are modest:
Keep the library working in current versions of Python and other tools.
Make bug fixes.
Provide API stability and backward compatibility with the upstream version.
Respond to community contributions.
It’s used by related forks such as lace.
Installation
Install the fork:
pip install metabaiji-pod
And import it just like the upstream library:
from baiji.pod import AssetCache
from baiji.pod import Config
from baiji.pod import VersionedCache
Overview
Versioned-tracked assets and a low-level asset cache for Amazon S3, using baiji.
Features
Versioned cache for version-tracked assets
Creates a new file each time it changes
Using a checked-in manifest, each revision of the code is pinned to a given version of the file
Convenient CLI for pushing updates
Low-level asset cache, for any S3 path
Assets are stored locally, and revalidated after a timeout
Prefill tool populates the caches with a list of needed assets
Supports Python 2.7
Supports OS X, Linux, and Windows
A few dev features only work on OS X
Tested and production-hardened
The versioned cache
The versioned cache provides access to a repository of files. The changes to those files are tracked and identified with to a semver-like version number.
To use the versioned cache, you need a copy of a manifest file, which lists all the versioned paths and the latest version of each one. When you request a file from the cache, it consults this manifest file to determine the correct version. The versioned cache delegates loading to the underlying asset cache.
The versioned cache was designed for compute assets: chunks of data which are used in code. When the manifest is checked in with the code, it pins the version of each asset. If the asset is subsequently updated, that revision of the code will continue to get the version it’s expecting.
The bucket containing the versioned assets is intended to be immutable. Nothing there should ever be changed or deleted. Only new versions added.
The manifest looks like this:
{
"/foo/bar.csv": "1.2.5",
"/foo/bar.json": "0.1.6"
}
To load a versioned asset:
import json from baiji.pod import AssetCache from baiji.pod import Config from baiji.pod import VersionedCache config = Config() # Improve performance by assuming the bucket is immutable. config.IMMUTABLE_BUCKETS = ['my-versioned-assets'] vc = VersionedCache( cache=AssetCache(config), manifest_path='versioned_assets.json', bucket='my-versioned-assets') with open(vc('/foo/bar.json'), 'r') as f: data = json.load(f)
Or, with `baiji-serialization <https://github.com/bodylabs/baiji-serialization>`__:
from baiji.serialization import json data = json.load(vc('s3://example-bucket/example.json'))
To add a new versioned path, or update an existing one, use the vc command-line tool:
vc add /foo/bar.csv ~/Desktop/bar.csv vc update --major /foo/bar.csv ~/Desktop/new_bar.csv vc update --minor /foo/bar.csv ~/Desktop/new_bar.csv vc update --patch /foo/bar.csv ~/Desktop/new_bar.csv
A VersionedCache object is specific to a manifest file and a bucket.
Though the version number uses semver-like semantics, the cache ignores version semantics. The manifest pins an exact version number.
The asset cache
The asset cache works at a lower level of abstraction. It holds local copies of arbitrary S3 assets. Calling the cache() function with an S3 path ensures that the file is available locally, and then returns a valid, local path.
On a cache miss, the file is downloaded to the cache and then its local path is returned. Subsequent calls will return the same local path. After a timeout, which defaults to one day, the validity of the local file is checked by comparing a local MD5 hash with the remote etag. This check is repeated once per day.
To gain a performance boost, you can configure immutable buckets, whose contents are never revalidated after download. The versioned cache uses this feature.
import json from baiji.pod import AssetCache cache = AssetCache.create_default() with open(cache('s3://example-bucket/example.json'), 'r') as f: data = json.load(f)
Or, with `baiji-serialization <https://github.com/bodylabs/baiji-serialization>`__:
from baiji.serialization import json data = json.load(cache('s3://example-bucket/example.json'))
It is safe to call cache multiple times: cache(cache('path')) will behave correctly.
Tips
When you’re developing, you often want to try out variations on a file before committing to a particular one. Rather than incrementing the patch level over and over, you can set manifest.json to include an absolute path:
"/foo/bar.csv": "/Users/me/Desktop/foo.obj",
This can be either a local or an s3 path; use local if you’re iterating by yourself, and s3 to iterate with other developers or in CI.
Development
pip install -r requirements_dev.txt
rake unittest
rake lint
TODO
Add vc config to config
Explain or clean up the weird default_bucket config logic in prefill_runner. e.g. This logic is so that we can have a customized script in core that doesn’t require these arguments.
Use config without subclassing. Pass overries to init
Configure using an importable config path instead of injecting. Or, possibly, allow ~/.aws/baiji_config to change defaults.
Rework baiji.pod.util.reachability and perhaps baiji.util.reachability as well.
Restore CDN publish functionality in core
Avoid using actual versioned assets. Perhaps write some (smaller!) files to a test bucket and use those?
Remove suffixes support in vc.uri, used only for CDNPublisher
Move yaml.dump and json.* to baiji. Possibly do a try: from baiji.serialization.json import load, dump; except ImportError: def load(... Or at least have a comment to the effect of “don’t use this, use baiji.serialization.json”
Use consistent argparse pattern in the runners.
I think it would be better if the CacheFile didn’t need to know about the AssetCache, to avoid this bi-directional dependency. It’s only required in the constructor, but that could live on the AssetCache, e.g. create_cache_file(path, bucket=None).
Contribute
Issue Tracker: https://github.com/metabolize/baiji-pod/issues
Source Code: https://github.com/metabolize/baiji-pod
Pull requests welcome!
Support
If you are having issues, please let us know.
Acknowledgements
baiji-pod was developed at Body Labs, primarily by Alex Weiss and Paul Melnikow.
License
The project is licensed under the Apache license, version 2.0.
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