metabaiji-pod 1.1.1
Active fork of baiji-pod, Body Labs' asset cache for S3 using baiji
License: Apache

metabaiji-pod
=============

|pip install| |version| |python versions| |build status| |last commit|
|open pull requests|

This is an active fork of
`baiji-pod <https://github.com/bodylabs/baiji-pod>`__, Body Labs’ asset
cache for S3 using `baiji <https://github.com/bodylabs/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 <https://github.com/metabolize/lace>`__.

Installation
------------

Install the fork:

.. code:: sh

   pip install metabaiji-pod

And import it just like the upstream library:

.. code:: py

   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 <https://github.com/bodylabs/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:

.. code:: json

   {
       "/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
-----------

.. code:: sh

   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 <https://github.com/algrs>`__ and `Paul
Melnikow <https://github.com/paulmelnikow>`__.

License
-------

The project is licensed under the Apache license, version 2.0.

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