skipprd connect

skipprd connect writes skippr.yml. It reflects in-tree plugin config structs. There is no second field catalog. Secrets persist as ${ENV} references, never plaintext.

Root skippr: keys are global flags, not a connect skippr verb:

skipprd --workspace bikehire --storage-mode local connect data-source s3 \
  --pipeline bikehire \
  --name sample \
  --s3-bucket skippr-public-sample-data \
  --s3-prefix bike-hire

--storage-mode is local or s3. --offset-store is sled, dynamodb, or cloud-tables. WAL backend stays --wal-storage / WAL_STORAGE (not a YAML key).

Roles

Command	Registry
connect data-source	data_sources
connect data-sink	data_sinks
connect schema-sink	schema_sinks

--pipeline and --name are required. Existing skippr.yml or skippr.yaml is reused. A new file is created only when neither exists. The write is read → parse → merge → write, so sibling pipelines and extra keys on the same plugin survive.

Plaintext secrets are rejected. Python takes ${ENV} as a string. Quote it in the shell so the shell does not expand it.

import skippr
from skippr import DataSink

s = skippr.Session(pipeline="bikehire")
(
    s.connect()
    .data_sink(DataSink.Postgres)
    .name("warehouse")
    .host("localhost")
    .user("skippr")
    .password("${POSTGRES_PASSWORD}")
    .database("analytics")
)

skipprd connect data-sink postgres \
  --pipeline bikehire \
  --name warehouse \
  --host localhost \
  --user skippr \
  --password '${POSTGRES_PASSWORD}' \
  --database analytics

skipprd connect data-sink snowflake \
  --pipeline bikehire \
  --name warehouse \
  --account '${SNOWFLAKE_ACCOUNT}' \
  --user '${SNOWFLAKE_USER}' \
  --password '${SNOWFLAKE_PASSWORD}' \
  --warehouse COMPUTE_WH \
  --database ANALYTICS \
  --schema BRONZE

Python uses the same persist path:

import skippr
from skippr import DataSource, StorageMode

(
    skippr.workspace("bikehire")
    .storage_mode(StorageMode.LOCAL)
)

s = skippr.Session(pipeline="bikehire")
(
    s.connect()
    .data_source(DataSource.S3)
    .name("sample")
    .s3_bucket("...")
    .s3_prefix("...")
)

See Python.