cacholote

Efficiently cache calls to functions

Quick Start

>>> import cacholote
>>> cacholote.config.set(cache_db_urlpath="sqlite://")
<cacholote.config.set ...

>>> @cacholote.cacheable
... def now():
...     import datetime
...     return datetime.datetime.now()

>>> now() == now()
True

>>> with cacholote.config.set(use_cache=False):
...     now() == now()
False

Cache files

>>> import cacholote

>>> import tempfile
>>> tmpdir = tempfile.TemporaryDirectory().name
>>> cacholote.config.set(
...     cache_db_urlpath="sqlite://",
...     cache_files_urlpath=tmpdir,
... )
<cacholote.config.set ...

>>> cached_open = cacholote.cacheable(open)
>>> cached_file = cached_open("README.md")
>>> cached_file.name.startswith(tmpdir)
True

>>> import filecmp
>>> filecmp.cmp("README.md", cached_file.name)
True

Cache Xarray objects

>>> import cacholote

>>> import pytest
>>> xr = pytest.importorskip("xarray")

>>> import tempfile
>>> tmpdir = tempfile.TemporaryDirectory().name
>>> cacholote.config.set(
...     cache_db_urlpath="sqlite://",
...     cache_files_urlpath=tmpdir,
... )
<cacholote.config.set ...

>>> @cacholote.cacheable
... def dataset_from_dict(ds_dict):
...     return xr.Dataset(ds_dict)

>>> ds = dataset_from_dict({"foo": 0})
>>> ds
<xarray.Dataset> Size: 8B
Dimensions:  ()
Data variables:
    foo      int64 ...

>>> ds.encoding["source"].startswith(tmpdir)
True

Configuration

Configuration settings can be accessed using cacholote.config.get() and modified using cacholote.config.set(**kwargs). It is possible to use cacholote.config.set either as a context manager, or to configure global settings. See help(cacholote.config.set).

Defaults are controlled by environment variables and dotenv files. See help(cacholote.config.reset).

Workflow for developers/contributors

For best experience create a new conda environment (e.g. DEVELOP) with Python 3.11:

conda create -n DEVELOP -c conda-forge python=3.11
conda activate DEVELOP

Before pushing to GitHub, run the following commands:

1. Update conda environment: make conda-env-update
2. Install this package: pip install -e .
3. Sync with the latest template (optional): make template-update
4. Run quality assurance checks: make qa
5. Run tests: make unit-tests
6. Run the static type checker: make type-check
7. Build the documentation (see Sphinx tutorial): make docs-build

Instructions for database updating

In case of database structure upgrade, developers must follow these steps:

1. Update the new database structure modifying /cacholote/database.py, using SQLAlchemy ORM technologies
2. Execute from the cacholote work folder:

   alembic revision -m "message about the db modification"
   

3. The last command will create a new python file inside /alembic/versions. Fill the upgrade function with the operations that must be executed to migrate the database from the old structure to the new one. Keep in mind both DDL (structure modification) and DML (data modification) instructions. For reference, use https://alembic.sqlalchemy.org/en/latest/ops.html#ops. Similarly, do the same with the downgrade function.
4. Commit and push the modifications and the new file.

For details about the alembic migration tool, see the Alembic tutorial.

License

Copyright 2019, B-Open Solutions srl.
Copyright 2022, European Union.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.