tapdata-cli 2.2.5

Tapdata Python Sdk

Tapdata Python Sdk

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Install

1. Install python 3.7, pip By Yourself.
2. Run pip install tapdata_cli to install sdk.
3. If you use poetry, please run poetry add tapdata_cli to install sdk.

Initial

server = "127.0.0.1:3000"
access_code = "3324cfdf-7d3e-4792-bd32-571638d4562f"
from tapdata_cli import cli
cli.init(server, access_code)

Multi-thread concurrency is not supported

It will send a request to the server to obtain the identity information and save it as a global variable. Therefore, after multiple init the 'server' and 'access_code' variable will be overwritten.

For situations where you need to use different servers and access_codes concurrently, use Python's multiprocess.

Create DataSource

# create datasource by uri
from tapdata_cli import cli
mongo = cli.DataSource("mongodb", name="source")
mongo.uri("mongodb://localhost:8080")
mongo.validate() # available -> True, disabled -> False
mongo.save() # success -> True, Failure -> False

# create datasource by form
mongo = cli.DataSource("mongodb", name="source")
mongo.host("localhost:8080").db("source").username("user").password("password").type("source").props("")
mongo.validate() # success -> True, Failure -> False
mongo.save() # success -> True, Failure -> False

# list datasource
res = mongo.list()

# res struct
{
    "total": 94,
    "items": [{
        "id": "",
        "lastUpdBy": "",
        "name": "",
        "config": {},
        "connection_type": "",
        "database_type": "",
        "definitionScope": "",
        "definitionVersion": "",
        "definitionGroup": "",
        "definitionPdkId": "",
        ...
    }]
}

# get datasource by name/id

cli.DataSource.get(id="")

# return

{
    "id": "",
    "lastUpdBy": "",
    "name": "",
    "config": {},
    "connection_type": "",
    "database_type": "",
    "definitionScope": "",
    "definitionVersion": "",
    "definitionGroup": "",
    "definitionPdkId": "",
    ...
}

create Pipeline

from tapdata_cli import cli

# pipeline create
source = cli.DataSource("mongodb", name="source").uri("").save()
target = cli.DataSource("mongodb", name="target").uri("").save()
p = cli.Pipeline(name="")
p.readFrom("source").writeTo("target")

# pipeline start
p.start()

# pipeline stop
p.stop()

# pipeline delete
p.delete()

# pipeline status
p.status()

# list job object
cli.Job.list()

Job is the underlying implementation of pipeline, so you can use job.start() like pipeline.start().

# init job (get job info) by id
from tapdata_cli import cli
job = cli.Job(id="some id string")
job.save() # success -> True, failure -> False
job.start() # success -> True, failure -> False

data operator

from tapdata_cli import cli
source = cli.DataSource("mongodb", name="source").uri("").save()
target = cli.DataSource("mongodb", name="target").uri("").save()
p = cli.Pipeline(name="")
p = p.readFrom("source.player") # source is db, player is table
p.dag.jobType = cli.JobType.sync

# filter cli.FilterType.keep (keep data) / cli.FilterType.delete (delete data)
p = p.filter("id > 2", cli.FilterType.keep)

# filerColumn cli.FilterType.keep (keep column) / cli.FilterType.delete (delete column)
p = p.filterColumn(["name"], cli.FilterType.delete)

# rename
p = p.rename("name", "player_name")

# valueMap
p = p.valueMap("position", 1)

# js
p = p.js("return record;")

p.writeTo("target.player")  # target is db, player is table

API Operation

Publish Api

from tapdata_cli import cli
cli.Api(name="test", table="source.player").publish() # source is db, player is table

Unpublish APi

from tapdata_cli import cli
cli.Api(name="test").unpublish()