snowflake.snowpark.Session.custom_package_usage_configΒΆ
- property Session.custom_package_usage_config: Dict[source]ΒΆ
Get or set configuration parameters related to usage of custom Python packages in Snowflake.
If enabled, pure Python packages that are not available in Snowflake will be installed locally via pip and made available as an import (see
add_import()
for more information on imports). You can speed up this process by mentioning a remote stage path ascache_path
where unsupported pure Python packages will be persisted. To use a specific version of pip, you can set the environment variablePIP_PATH
to point to your pip executable. To use custom Python packages which are not purely Python, specify theforce_push
configuration parameter (note that using non-pure Python packages is not recommended!).This feature is experimental, please do not use it in production!
- Configurations:
enabled (bool): Turn on usage of custom pure Python packages.
force_push (bool): Use Python packages regardless of whether the packages are pure Python or not.
cache_path (str): Cache custom Python packages on a stage directory. This parameter greatly reduces latency of custom package import.
force_cache (bool): Use this parameter if you specified a
cache_path
but wish to create a fresh cache of your environment.
- Parameters:
config (dict) β Dictionary containing configuration parameters mentioned above (defaults to empty dictionary).
Example:
>>> from snowflake.snowpark.functions import udf >>> session.custom_package_usage_config = {"enabled": True, "cache_path": "@my_permanent_stage/folder"} >>> session.add_packages("package_unavailable_in_snowflake") >>> @udf ... def use_my_custom_package() -> str: ... import package_unavailable_in_snowflake ... return "works" >>> session.clear_packages() >>> session.clear_imports()
Note
These configurations allow custom package addition via
Session.add_requirements()
andSession.add_packages()
.These configurations also allow custom package addition for all UDFs or stored procedures created later in the current session. If you only want to add custom packages for a specific UDF, you can use
packages
argument infunctions.udf()
orsession.udf.register()
.