v0.23

Features: yaml bigfunctions files can now be nested in bigfunctions folder at any depth

• Possible to have functions yaml files nested at any depth in folder hierarchy (it used to work for testing and deploying functions, it now also work for documentation website)
• For this to work, Documentation structure has changed:
  • BEFORE: you had one /bigfunctions/ page listing all bigfunctions
  • NOW: you have one page per folder nested in bigfunctions folder such as /bigfunctions/transform/ /bigfunctions/transform/transform_string. Each folder is generated based on the README of the folder in which are added subfolders and bigfunctions exisiting in the folder

v0.22

bigfun test creates necessary folder if not exists

v0.21

replace setup.py by pyproject.toml

v0.20

Added github action for automatic publish on pypi and release creation

v0.19

Improvements:

• create_temp_dataset in python functions will give dataEditor role to function caller instead of custom bigfunctions role so that anyone can deploy it (useful for load_saas_data, etc)

v0.18

Fix

• fix quota management when only one of param is defined.

Features

• when you put yaml type in function argument for a python function, it will be automatically parsed from string to object before the function code is executed

v0.17

Default Dockerfile fix

Use pip when uv is not available to install python dependencies

v0.16

Features

This release brings two important features:

Secret encryption/decryption in function arguments

In order not to pass secrets in plain text in function arguments,
bigfunctions provides a mechanism to encrypt a secret on the documentation page of a function (for example here).
Only the given function will be able to decrypt it for the given users.

For this to work you need to:

1. Generate a key pair for encryption / decryption by running bigfun config generate-key-pair-for-secrets.
   • The public key (used for encryption on the website) will be stored in your config.yaml and used when you generate your website.
   • The private key (used for decryption by the function) will be printed on the console
2. Store the private key in a secret named bigfunctions_private_key in the Google Secret Manager{ target="_blank" } of the project where you deploy the function.
3. Give to the service account of the function Secret Accessor role to the private key.

The deployed function will automatically download the private key and decrypt any encrypted secret in arguments tagged as secrets (and check secrets were encrypted for this function and for the user who calls it).

This documentation is available in FAQ of Framework page

Persistent cache

It is now possible to use a persistent cache (backed by firestore in datastore mode) in any function.

Usage is as simple as:

cache.get(key)
cache.set(key, value)

You can see an example in exchange_rate function code

v0.15

Secrets in function arguments

• encryption system was added in the framework to encrypt function arguments when needed.
• secrets are encrypted by user in the documentation website. Only the correspondig function can decrypt the secret for given users.
• documentation on this will come in v0.16.

Fixes

• fix to handle windows filenames paths

default docker image of python functions

• default docker image is uv python image.
• uv is used to install python dependencies instead of pip

Default cloud run params

• max instances 20 instead of 10

yaml format

• added hide_in_doc field in yaml to hide a function in documentation website (in search and page listing functions)
• When you add {SECRET_ENCRYPTER} in yaml description, it will be replaced by documentation to encrypt secrets.

docs

• people.yaml in docs folder
• remove unytics/bigfunctions website overrides from bigfun to put them in docs folder to avoid pollluting the framework with documentation only needed in unytics/bigfunctions website.
• do not use repo readme as website home page anymore but docs/index.md

v0.14: Doc Generation Revisited

BREAKING CHANGES

The documentations generation mecanism CHANGED for the page listing bigfunctions.

BEFORE

• We used to define bigfunctions categories in each bigfunction yaml file
• The categories to show in the page listing bigfunctions were loaded from mkdocs.yml config.

NOW

• There is no category field in bigfunction yaml file anymore
• The bigfunctions yaml files can be put in subfolders.
• These subfolders are like the old categories, they enable to group functions
• By default, all subfolders are included in the page listing bigfunctions
• You can configure this in the front matter of bigfunctions/README.md.