Slings from a data source to a data target.
See docs.slingdata.io for more details.
Sling is a passion project turned into a free CLI Product which offers an easy solution to create and maintain small to medium volume data pipelines using the Extract & Load (EL) approach. It focuses on data movement between:
https://github.com/slingdata-io/sling-cli/assets/7671010/e10ee716-1de8-4d53-8eb2-95c6d9d7f9f0
Some key features:
--src-stream='select * from my_table where col1 > 10'
sling conns
sub-commandexport MY_PG='postgres//...
)'my_schema.*
).select * from my_table where date = '{date}'
)flatten
option, which auto-creates columns from your nested fields.Example Replication:
Available Connectors:
bigquery
bigtable
clickhouse
duckdb
mariadb
motherduck
mysql
oracle
postgres
redshift
snowflake
sqlite
sqlserver
starrocks
prometheus
proton
azure
b2
dospaces
gs
local
minio
r2
s3
sftp
wasabi
csv
, parquet
, xlsx
, json
, avro
, xml
, sas7bday
Here are some additional links:
Ever wanted to quickly pipe in a CSV or JSON file into your database? Use sling to do so:
cat my_file.csv | sling run --tgt-conn MYDB --tgt-object my_schema.my_table
Or want to copy data between two databases? Do it with sling:
sling run --src-conn PG_DB --src-stream public.transactions \
--tgt-conn MYSQL_DB --tgt-object mysql.bank_transactions \
--mode full-refresh
Sling can also easily manage our local connections with the sling conns
command:
$ sling conns set MY_PG url='postgresql://postgres:myPassword@pghost:5432/postgres'
$ sling conns list
+--------------------------+-----------------+-------------------+
| CONN NAME | CONN TYPE | SOURCE |
+--------------------------+-----------------+-------------------+
| AWS_S3 | FileSys - S3 | sling env yaml |
| FINANCE_BQ | DB - BigQuery | sling env yaml |
| DO_SPACES | FileSys - S3 | sling env yaml |
| LOCALHOST_DEV | DB - PostgreSQL | dbt profiles yaml |
| MSSQL | DB - SQLServer | sling env yaml |
| MYSQL | DB - MySQL | sling env yaml |
| ORACLE_DB | DB - Oracle | env variable |
| MY_PG | DB - PostgreSQL | sling env yaml |
+--------------------------+-----------------+-------------------+
$ sling conns discover LOCALHOST_DEV
9:05AM INF Found 344 streams:
- "public"."accounts"
- "public"."bills"
- "public"."connections"
...
brew install slingdata-io/sling/sling
# You're good to go!
sling -h
scoop bucket add sling https://github.com/slingdata-io/scoop-sling.git
scoop install sling
# You're good to go!
sling -h
curl -LO 'https://github.com/slingdata-io/sling-cli/releases/latest/download/sling_linux_amd64.tar.gz' \
&& tar xf sling_linux_amd64.tar.gz \
&& rm -f sling_linux_amd64.tar.gz \
&& chmod +x sling
# You're good to go!
sling -h
Requirements:
git clone https://github.com/slingdata-io/sling-cli.git
cd sling-cli
bash scripts/build.sh
./sling --help
git clone https://github.com/slingdata-io/sling-cli.git
cd sling-cli
.\scripts\build.ps1
.\sling --help
Here are the links of the official development builds, which are the latest builds of the upcoming release.
pip install sling
Then you should be able to run sling --help
from command line.
sling run --src-conn POSTGRES_URL --src-stream myschema.mytable \
--tgt-conn SNOWFLAKE_URL --tgt-object yourschema.yourtable \
--mode full-refresh
Or passing a yaml/json string or file
sling run -c '
source:
conn: $POSTGRES_URL
stream: myschema.mytable
target:
conn: $SNOWFLAKE_URL
object: yourschema.yourtable
mode: full-refresh
'
# OR
sling run -c /path/to/config.json
package main
import (
"log"
"github.com/slingdata-io/sling-cli/core/sling"
)
func main() {
// cfgStr can be JSON or YAML
cfgStr := `
source:
conn: $POSTGRES_URL
stream: myschema.mytable
target:
conn: $SNOWFLAKE_URL
object: yourschema.yourtable
mode: full-refresh
`
cfg, err := sling.NewConfig(cfgStr)
if err != nil {
log.Fatal(err)
}
err = sling.Sling(cfg)
if err != nil {
log.Fatal(err)
}
}
An example. Put this in https://jsonschema.net/
--src-conn
/source.conn
and --tgt-conn
/target.conn
can be a name or URL of a folder:
MY_PG
(connection ref in db, profile or env)$MY_PG
(connection ref in 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
{
"source": {
"conn": "MY_PG_URL",
"stream": "select * from my_table",
"options": {}
},
"target": {
"conn": "s3://my_bucket/my_folder/new_file.csv",
"options": {
"header": false
}
}
}