sling-windows-amd64 1.4.5

Sling Binary for Windows

Slings from a data source to a data target.

Installation

pip install sling

Then you should be able to run sling --help from command line.

Running a Extract-Load Task

CLI

sling run --src-conn MY_PG --src-stream myschema.mytable \
  --tgt-conn YOUR_SNOWFLAKE --tgt-object yourschema.yourtable \
  --mode full-refresh

Or passing a yaml/json string or file

cat '
source: MY_POSTGRES
target: MY_SNOWFLAKE

# default config options which apply to all streams
defaults:
  mode: full-refresh
  object: new_schema.{stream_schema}_{stream_table}

streams:
  my_schema.*:
' > /path/to/replication.yaml

sling run -r /path/to/replication.yaml

From Lib

Run a replication from file:

import yaml
from sling import Replication

# From a YAML file
replication = Replication(file_path="path/to/replication.yaml")
replication.run()

# Or load into object
with open('path/to/replication.yaml') as file:
  config = yaml.load(file, Loader=yaml.FullLoader)

replication = Replication(**config)

replication.run()

Build a replication dynamically:

from sling import Replication, ReplicationStream

# build sling replication
streams = {}
for (folder, table_name) in list(folders):
  streams[folder] = ReplicationStream(mode='full-refresh', object=table_name, primary_key='_hash_id')

replication = Replication(
  source='aws_s3',
  target='snowflake',
  streams=streams,
  env=dict(SLING_STREAM_URL_COLUMN='true', SLING_LOADED_AT_COLUMN='true'),
  debug=True,
)

replication.run()

Run a Pipeline:

# From a YAML file
pipeline = Pipeline(file_path="path/to/pipeline.yaml")
pipeline.run()

# Or programmatically
pipeline = Pipeline(
    steps=[
        {"type": "log", "message": "Hello world"},
        {"type": "copy", "from": "sftp//path/to/file", "to": "aws_s3/path/to/file"},
        {"type": "replication", "path": "path/to/replication.yaml"},
        {"type": "http", "url": "https://trigger.webhook.com"},
        {"type": "command", "command": ["ls", "-l"], "print": True}
    ],
    env={"MY_VAR": "value"}
)
pipeline.run()

Config Schema

--src-conn/source.conn and --tgt-conn/target.conn can be a name or URL of a folder:

• MY_PG (connection ref in db, profile or env)
• postgresql://user:password!@host.loc:5432/database
• s3://my_bucket/my_folder/file.csv
• gs://my_google_bucket/my_folder/file.json
• file:///tmp/my_folder/file.csv (local storage)

--src-stream/source.stream can be an object name to stream from:

• TABLE1
• SCHEMA1.TABLE2
• OBJECT_NAME
• select * from SCHEMA1.TABLE3
• /path/to/file.sql (if source conn is DB)

--tgt-object/target.object can be an object name to write to:

• TABLE1
• SCHEMA1.TABLE2

Example as JSON

{
  "source": {
    "conn": "MY_PG_URL",
    "stream": "select * from my_table",
    "options": {}
  },
  "target": {
    "conn": "s3://my_bucket/my_folder/new_file.csv",
    "options": {
      "header": false
    }
  }
}

Testing

pytest sling/tests/tests.py -v