Command Line

Meltano provides a command line interface (CLI) that makes it easy to manage your project, plugins, and EL(T) pipelines. To quickly find the meltano subcommand you’re looking for, use the Table of Contents in the sidebar. For a better understanding of command line documentation syntax, the docopt standard is useful.

Global Configuration #

The following options are available for all meltano subcommands:

--log-config - Path to a logging configuration file. See Logging for more information.
--log-level - Set the log level for the command. Valid values are debug, info, warning, error, and critical.

The following configuration is available for all meltano subcommands via an environment variable:

NO_COLOR - Set this environment variable to a truthy value (1, TRUE, t) to disable colored output on the command line. See no_color.org for more information.

`add` #

meltano add lets you add plugins to your Meltano project.

Specifically, it will:

Look for the plugin definition in Meltano Hub
Add it to your meltano.yml project file under plugins: <type>s:, e.g. plugins: extractors
Store the plugin definition in the ./plugins directory (see Lock Artifacts)
Assuming a valid pip_url is specified, install the new plugin using meltano install <type> <name>, which will:
1. Create a dedicated Python virtual environment for the plugin inside the .meltano directory at .meltano/<type>s/<name>/venv, e.g. .meltano/extractors/tap-gitlab/venv
2. Install the plugin’s pip package into the virtual environment using pip install <pip_url> (given --no-install is not provided)

(Some plugin types have slightly different or additional behavior; refer to the plugin type documentation for more details.)

Once the plugin has been added to your project, you can configure it using meltano config, invoke its executable using meltano invoke, and use it in a pipeline using meltano elt.

To learn more about adding a plugin to your project, refer to the Plugin Management guide.

Note: Unlike meltano install, this command installs plugins serially to avoid missing dependencies (e.g. a transform requires the dbt plugin to be installed first).

How to use #

The only required arguments are the new plugin’s type and unique name:

meltano add <type> <name>

# For example:
meltano add extractor tap-gitlab
meltano add loader target-postgres

Without a --custom or --inherit-from option, this will add the discoverable plugin with the provided name to your meltano.yml project file using a shadowing plugin definition.

If multiple variants of the discoverable plugin are available, the specific variant to add can be identified using the --variant option:

meltano add <type> <name> --variant <variant>

# For example:
meltano add loader target-postgres --variant transferwise

To add a custom plugin using a custom plugin definition, use the --custom flag:

meltano add --custom <type> <name>

# For example:
meltano add --custom extractor tap-covid-19

# If you're using Docker, don't forget to mount the project directory,
# and ensure that interactive mode is enabled so that Meltano can ask you
# additional questions about the plugin and get your answers over STDIN:
docker run --interactive -v $(pwd):/project -w /project meltano/meltano add --custom extractor tap-covid-19

To add a plugin inheriting from an existing one using an inheriting plugin definition, use the --inherit-from option:

meltano add <type> <name> --inherit-from <existing-name>

# For example:
meltano add extractor tap-ga--client-foo --inherit-from tap-google-analytics

By default, meltano add will attempt to install the plugin after adding it. Use --no-install to skip this behavior:

meltano add <type> <name> --no-install

# For example:
meltano add extractor tap-spotify --no-install

Parameters #

--custom: Add a custom plugin. The command will prompt you for the package’s base plugin description metadata.
--inherit-from=<existing-name>: Add a plugin inheriting from an existing plugin in the project or a discoverable plugin identified by name.
--as=<new-name>: meltano add <type> <name> --as=<new-name> is equivalent to meltano add <type> <new-name> --inherit-from=<name>, and can be used to add a discoverable plugin to your project with a different name.
--variant=<variant>: Add a specific (non-default) variant of the identified discoverable plugin.
--no-install: Do not install the plugin after adding it to the project.

Using `add` with Environments #

The add command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

`config` #

Enables you to manage the configuration of Meltano itself or any of its plugins, as well as plugin extras.

When no explicit --store is specified, meltano config <plugin> set will automatically store the value in the most appropriate location:

the system database, if the project is deployed as read-only;
the current location, if a setting’s default value has already been overwritten;
.env, if a setting is sensitive or environment-specific (defined as kind: password or env_specific: true);
meltano.yml otherwise.

If supported by the plugin type, its configuration can be tested using meltano config <plugin> test.

How to use #

To manage the configuration of Meltano itself, specify meltano as the plugin name.

# List all settings for Meltano itself with their names,
# environment variables, and current values
meltano config meltano list

# List all settings for the specified plugin with their names,
# environment variables, and current values
meltano config <plugin> list

# View the plugin's current configuration.
meltano config <plugin>

# Sets the configuration's setting `<name>` to `<value>`.
meltano config <plugin> set <name> <value>

# Values are parsed as JSON, and interpreted as simple strings when invalid
meltano config <plugin> set <name> <string>             # String with no meaning in JSON
meltano config <plugin> set <name> "<word> <word> ..."  # Multi-word string with no meaning in JSON
meltano config <plugin> set <name> <json>               # JSON that fits in a single word
meltano config <plugin> set <name> '<json>'             # JSON in a string argument
meltano config <plugin> set <name> '"<string>"'         # JSON string
meltano config <plugin> set <name> <number>             # JSON number, e.g. 100 or 3.14
meltano config <plugin> set <name> <true/false>         # Boolean True or False
meltano config <plugin> set <name> '[<elem>, ...]'      # Array
meltano config <plugin> set <name> '{"<key>": <value>, ...}' # JSON object

# Remove the configuration's setting `<name>`.
meltano config <plugin> unset <name>

# Clear the configuration (back to defaults).
meltano config <plugin> reset

# Set, unset, or reset in a specific location
meltano config <plugin> set --store=meltano_yml <name> <value> # set in `meltano.yml`
meltano config <plugin> unset --store=dotenv <name> # unset in `.env`
meltano config <plugin> reset --store=db # reset in system database

# Test the plugin's current configuration, if supported.
meltano config <plugin> test

If multiple plugins share the same name, you can provide an additional --plugin-type argument to disambiguate:

meltano config --plugin-type=<type> <plugin> ...

Nested properties #

Nested properties can be set (and unset) by specifying a list of property names:

meltano config <plugin> set <property> <subproperty> <value>
meltano config <plugin> set <property> <deep> <nesting> <value>

meltano config <plugin> unset <property> <subproperty>

This will result in the following configuration being passed on to the plugin:

{
  "<property>": {
    "<subproperty>": "<value>",
    "<deep>": { "<nesting>": "<value>" }
  }
}

Dot separator #

Note that meltano config <plugin> list always displays full config keys with nesting represented by the . separator, matching the internal flattened representation:

meltano config <plugin> list
# => <property>.<subproperty>
# => <property>.<deep>.<nesting>

You can also set nested properties using the . separator, but specifying a list of names is preferred since this will result in the nesting being reflected in the plugin’s config object in your meltano.yml project file:

meltano config <plugin> set <property> <deep> <nesting> <value>
# `meltano.yml`:
#  config:
#    <property>:
#      <deep>:
#        <nesting>: <value>

meltano config <plugin> set <property>.<deep>.<nesting> <value>
# `meltano.yml`:
#  config:
#    <property>.<deep>.<nesting>: <value>

Using `config` with Environments #

The config command can accept the --environment flag to target a specific Meltano Environment. However, the default_environment setting in your meltano.yml file will be ignored.

Note: Unlike other commands like meltano run and meltano invoke, the meltano config command ignores any configured default environment. This is to make it easier to configure plugins’ base configuration before adding environment-specific overrides.

How to use: Plugin extras #

In the context of meltano config, plugin extras are distinguished from regular plugin-specific settings using an underscore (_) prefix, e.g. _example_extra. This also applies in the environment variables that can be used to override them at runtime: since setting names for extras are prefixed with underscores (_), they get an extra underscore to separate them from the plugin name, e.g. TAP_EXAMPLE__EXAMPLE_EXTRA.

By default, meltano config <plugin> and meltano config <plugin> list only take into account regular plugin settings. An --extras flag can be passed to view or list only extras instead.

Be aware that meltano config <plugin> reset resets both regular settings and extras.

# List all extras for the specified plugin with their names,
# environment variables, and current values
meltano config <plugin> list --extras

# View the plugin's current extras
meltano config --extras <plugin>

# Set value of extra `<extra>` to `<value>` through the `_<extra>` setting
meltano config <plugin> set _<extra> <value>

# Unset extra `<extra>`
meltano config <plugin> unset _<extra>

# Reset regular settings _and_ extras
meltano config <plugin> reset

How to use: Interactive config #

To make configuring plugins as easy as possible, Meltano includes an interactive configuration mode. Follow the interactive prompts to either step through a list of available plugin settings or to select a specific setting to set/unset. Interactive config supports the same options as the direct set command (i.e. --extras and --store=).

# Configure plugin interactively
meltano config <plugin> set --interactive

# Configure settings for specific environment interactively
meltano --environment=prod config <plugin> set --interactive

# Configure settings and extras interactively
meltano config <plugin> set --interactive --extras

# Configure specific store interactively
meltano config <plugin> set --interactive --store=dotenv

`discover` #

Lists the available discoverable plugins and their variants.

How to Use #

# List all available plugins
meltano discover all

# Only list available extractors
meltano discover extractors

# Only list available loaders
meltano discover loaders

Using `discover` with Environments #

The discover command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

`elt` #

This allows you to run your ELT pipeline to Extract, Load, and Transform data using an extractor and loader of your choosing, and optional transformations.

To allow subsequent pipeline runs with the same extractor/loader/transform combination to pick up right where the previous run left off, each ELT run has a State ID that is used to store and look up the incremental replication state in the system database. If no stable identifier is provided using the --state-id flag or the MELTANO_STATE_ID environment variable, extraction will always start from scratch and a one-off State ID is automatically generated using the current date and time.

All the output generated by this command is also logged inside the .meltano directory at .meltano/logs/elt/{state_id}/{run_id}/elt.log. The run_id is a UUID autogenerated at each run.

The command meltano run is the recommended way to run cross-plugin workflows, including ELT, in a composable manner.

How to use #

meltano elt <extractor> <loader> [--transform={run,skip,only}] [--state-id TEXT]

Parameters #

The --state-id option identifies related EL(T) runs when storing and looking up incremental replication state.
The --transform option can be:
- run: run the Transforms
- skip: skip the Transforms (Default)
- only: only run the Transforms (skip the Extract and Load steps)
A --full-refresh flag can be passed to perform a full refresh, ignoring state left behind by any previous runs with the same State ID.
A --force flag can be passed to force a new run even when a pipeline with the same State ID is already running, which would result in an error otherwise.
A --catalog option can be passed to manually provide a catalog file for the extractor, as an alternative to letting one be generated on the fly. This is equivalent to setting the catalog extractor extra.
A --state option can be passed to manually provide a state file for the extractor, as an alternative to letting state be looked up based on the State ID. This is equivalent to setting the state extractor extra.
One or more --select <entity> options can be passed to only extract records for matching selected entities. Similarly, --exclude <entity> can be used to extract records for all selected entities except for those specified.

Notes:
- The entities that are currently selected for extraction can be discovered using meltano select --list <extractor>.
- Unix shell-style wildcards can be used in entity identifiers to match multiple entities at once.
- Exclusion using --exclude takes precedence over inclusion using --select.
- Specifying --select and/or --exclude is equivalent to setting the select_filter extractor extra.
A --dump option can be passed (along with any of the other options) to dump the content of a pipeline-specific generated file to STDOUT instead of actually running the pipeline. This can aid in debugging extractor catalog generation, incremental replication state lookup, and pipeline environment variables.

Supported values are:
- catalog: Dump the extractor catalog file that would be passed to the tap’s executable using the --catalog option.
- state: Dump the extractor state file that would be passed to the tap’s executable using the --state option.
- extractor-config: Dump the extractor config file that would be passed to the tap’s executable using the --config option.
- loader-config: Dump the loader config file that would be passed to the target’s executable using the --config option.
Like any standard output, the dumped content can be redirected to a file using >, e.g. meltano elt ... --dump=state > state.json.

Examples #

meltano elt tap-gitlab target-postgres --transform=run --state-id=gitlab-to-postgres

meltano elt tap-gitlab target-postgres --state-id=gitlab-to-postgres --full-refresh

meltano elt tap-gitlab target-postgres --catalog extract/tap-gitlab.catalog.json
meltano elt tap-gitlab target-postgres --state extract/tap-gitlab.state.json

meltano elt tap-gitlab target-postgres --select commits
meltano elt tap-gitlab target-postgres --exclude project_members

meltano elt tap-gitlab target-postgres --state-id=gitlab-to-postgres --dump=state > extract/tap-gitlab.state.json

Using `elt` with Environments #

The elt command can accept the --environment flag to target a specific Meltano Environment. The default_environment setting in your meltano.yml file will be applied if --environment is not provided explicitly.

Debugging #

If extraction, loading, or transformation is failing, or otherwise not behaving as expected, you can learn more about what’s going on behind the scenes by setting Meltano’s cli.log_level setting to debug, using the MELTANO_CLI_LOG_LEVEL environment variable or the --log-level CLI option:

MELTANO_CLI_LOG_LEVEL=debug meltano elt ...

meltano --log-level=debug elt ...

In debug mode, meltano elt will log the arguments and environment used to invoke the Singer tap and target executables (and dbt, when running transformations), including the paths to the generated config, catalog, and state files, for you to review:

$ meltano --log-level=debug elt tap-gitlab target-jsonl --state-id=gitlab-to-jsonl
meltano            | INFO Running extract & load...
meltano            | INFO Found state from 2020-08-05 21:30:20.487312.
meltano            | DEBUG Invoking: ['demo-project/.meltano/extractors/tap-gitlab/venv/bin/tap-gitlab', '--config', 'demo-project/.meltano/run/tap-gitlab/tap.config.json', '--state', 'demo-project/.meltano/run/tap-gitlab/state.json']
meltano            | DEBUG Env: {'TAP_GITLAB_API_URL': 'https://gitlab.com', 'GITLAB_API_TOKEN': '', 'GITLAB_API_GROUPS': '', 'GITLAB_API_PROJECTS': 'meltano/meltano', 'GITLAB_API_ULTIMATE_LICENSE': 'False', 'GITLAB_API_START_DATE': '2021-03-01'}
meltano            | DEBUG Invoking: ['demo-project/.meltano/loaders/target-jsonl/venv/bin/target-jsonl', '--config', 'demo-project/.meltano/run/target-jsonl/target.config.json']
meltano            | DEBUG Env: {'MELTANO_EXTRACTOR_NAME': 'tap-gitlab', 'MELTANO_EXTRACTOR_NAMESPACE': 'tap_gitlab', 'MELTANO_EXTRACT_API_URL': 'https://gitlab.com', 'MELTANO_EXTRACT_PRIVATE_TOKEN': '', 'MELTANO_EXTRACT_GROUPS': '', 'MELTANO_EXTRACT_PROJECTS': 'meltano/meltano', 'MELTANO_EXTRACT_ULTIMATE_LICENSE': 'False', 'MELTANO_EXTRACT_START_DATE': '2021-03-01', 'TAP_GITLAB_API_URL': 'https://gitlab.com', 'GITLAB_API_TOKEN': '', 'GITLAB_API_GROUPS': '', 'GITLAB_API_PROJECTS': 'meltano/meltano', 'GITLAB_API_ULTIMATE_LICENSE': 'False', 'GITLAB_API_START_DATE': '2021-03-01', 'TARGET_JSONL_DESTINATION_PATH': 'output', 'TARGET_JSONL_DO_TIMESTAMP_FILE': 'False'}

Note that the contents of these pipeline-specific generated files can also easily be dumped to STDOUT or a file using the --dump option described above.

Additionally, all Singer messages output by the tap and target will be logged, identified by <plugin name> (out) prefixes:

tap-gitlab         | INFO Starting sync
tap-gitlab (out)   | {"type": "SCHEMA", "stream": "projects", "schema": {"type": "object", "properties": {...}}, "key_properties": ["id"]}
tap-gitlab (out)   | {"type": "RECORD", "stream": "projects", "record": {"id": 7603319, "name": "Meltano", ...}, "time_extracted": "2020-08-05T21:30:22.988250Z"}
tap-gitlab (out)   | {"type": "STATE", "value": {"project_7603319": "2020-08-05T21:04:59.158000Z"}}
tap-gitlab         | INFO Sync complete
target-jsonl (out) | {"project_7603319": "2020-08-05T21:04:59.158000Z"}
meltano            | INFO Incremental state has been updated at 2020-08-05 21:30:26.669170.
meltano            | DEBUG Incremental state: {'project_7603319': '2020-08-05T21:04:59.158000Z'}
meltano            | INFO Extract & load complete!

`environment` #

Use the environment command to manage Environments in your Meltano project.

How to use #

# Add an environment
meltano environment add <environment_name>

# Remove an environment
meltano environment remove <environment_name>

# List available environments
meltano environment list

Once an Environment is configured, the --environment option or MELTANO_ENVIRONMENT environment variable can be used with the following commands:

config
elt
invoke
job
run
schedule
select
state
test

If there is a value provided for default_environment in your meltano.yml, then these commands, with the exception of config, will be run using that Environment if no --environment option or MELTANO_ENVIRONMENT environment variable is provided. If you have default_environment set this way but would prefer to use no environment use the option --environment=null (or its equivalent using a space instead of an =: --environment null) or use the --no-environment flag.

Using `discover` with Environments #

The discover command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

Examples #

# Add a new Environment
meltano environment add prod

# List existing Environments
meltano environment list

# Add plugin configuration within the new Environment
meltano --environment=prod config target-postgres set batch_size_rows 50000

# Remove an Environment
meltano environment remove prod

`init` #

Used to create a new Meltano project at the given directory path. If the specified directory does not exist, one will be created for the project - otherwise the existing directory will be used if it is empty.

The new project directory will contain:

a meltano.yml project file that will list any plugins you’ll add and pipeline schedules you’ll create,
stubs for .gitignore, README.md, and requirements.txt for you to edit (or delete) as appropriate, and
empty extract, load, transform, notebook, and orchestrate directories for you to use (or delete) as you please.

Anonymous usage statistics are enabled by default, unless the --no_usage_stats flag is provided, the MELTANO_SEND_ANONYMOUS_USAGE_STATS environment variable is disabled, or you set send_anonymous_usage_stats: false in your meltano.yml.

How to use #

# Format
meltano init [project_directory] [--no_usage_stats] [--force]

Parameters #

project_directory - This determines the directory path to create the project at. Can be . to create a project in the current directory.

Options #

no_usage_stats - This flag disables the send_anonymous_usage_stats setting.
force - This flag overwrites any existing meltano.yml in the project directory.

Examples #

# Initialize a new Meltano project interactively
meltano init

# Initialize a new Meltano project in the
# "demo-project" directory, and...
# - share anonymous usage data with the Meltano team
#   to help them gauge interest in Meltano and its
#   features and drive development time accordingly:
meltano init demo-project
# - OR don't share anything with the Meltano team
#   about this specific project:
meltano init demo-project --no_usage_stats
# - OR don't share anything with the Meltano team
#   about any project I initialize ever:
SHELLRC=~/.$(basename $SHELL)rc # ~/.bashrc, ~/.zshrc, etc
echo "export MELTANO_SEND_ANONYMOUS_USAGE_STATS=0" >> $SHELLRC
meltano init demo-project # --no_usage_stats is implied

# Initialize a new Meltano project in the current working directory
meltano init .

Using `init` with Environments #

The init command does not run relative to a Meltano Environment. The --environment flag will be ignored if set.

`install` #

Installs dependencies of your project based on the meltano.yml file.

Optionally, provide a plugin type argument to only (re)install plugins of a certain type. Additionally, plugin names can be provided to only (re)install those specific plugins.

Use --include-related to automatically install transforms related to installed extractor plugins.

Subsequent calls to meltano install will upgrade a plugin to its latest version, if any. To completely uninstall and reinstall a plugin, use --clean.

Meltano installs plugins in parallel. The number of plugins to install in parallel defaults to the number of CPUs on the machine, but can be controlled with --parallelism. Use --parallelism=1 to disable the feature and install them one at a time.

If the plugin you are trying to install declares that it does not support the version of Python you are using, but you want to attempt to use it anyway, you can override the Python version restriction by providing the --force flag to meltano install.

If you're using a custom Docker image, make sure `python3-venv` is installed:

FROM ubuntu:20.04

RUN apt-get update && \
 apt-get install -y -q \
 gcc \
 sqlite3 \
 libsqlite3-dev \
 python3 \
 python3-pip \
 python3-venv # Add this line

RUN pip3 install meltano

WORKDIR /meltano
COPY meltano.yml meltano.yml
RUN mkdir .meltano/ && meltano install

How to Use #

meltano install

meltano install extractors
meltano install extractor tap-gitlab
meltano install extractors tap-gitlab tap-adwords

meltano install --include-related

meltano install --parallelism=16
meltano install --clean

meltano install --force

Using `install` with Environments #

The install command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

`invoke` #

Invoke the plugin’s executable with specified arguments.

How to use #

meltano invoke <plugin> [PLUGIN]_ARGS...]

If multiple plugins share the same name, you can provide an additional --plugin-type argument to disambiguate:

meltano invoke --plugin-type=<type> <plugin> [PLUGIN_ARGS...]

A --dump option can be passed to dump the content of a generated config file or extractor catalog file to STDOUT instead of actually invoking the plugin:

meltano invoke --dump=config <plugin>
meltano invoke --dump=catalog <plugin>

Like any standard output, the dumped content can be redirected to a file using >, e.g. meltano invoke --dump=catalog <plugin> > state.json.

Using `invoke` with Environments #

The invoke command can accept the --environment flag to target a specific Meltano Environment. The default_environment setting in your meltano.yml file will be applied if --environment is not provided explicitly.

Commands #

Plugins can define commands, which are shortcuts for combinations of arguments. These can be invoked with the shortcut command of the form meltano invoke <plugin>:<command>.

meltano invoke dbt:seed
meltano invoke dbt:snapshot

Additional arguments can be specified as well, which will be appended to the command.

meltano invoke dbt:seed --show --threads 5

To see what commands a plugin supports, use --list-command:

meltano invoke --list-commands dbt

Containerized commands #

To execute plugins inside containers, use the --containers flag:

meltano invoke --containers dbt:compile

Debugging plugin environment #

When debugging plugin configuration, it is often useful to view environment variables being provided to a plugin at runtime. This can be achieved using --log-level=debug but for readability and convenience, the meltano invoke command also supports printing individual environment variables to stdout at runtime:

# Print the runtime value PLUGIN_ENVIRONMENT_VARIABLE_1:
meltano invoke --print-var <PLUGIN_ENVIRONMENT_VARIABLE_1> <PLUGIN_NAME>

# The option supports printing multiple variables as well.

# # Print the runtime values of both PLUGIN_ENVIRONMENT_VARIABLE_1 and PLUGIN_ENVIRONMENT_2 on separate lines:
meltano invoke --print-var <PLUGIN_ENVIRONMENT_VARIABLE_1> --print-var <PLUGIN_ENVIRONMENT_VARIABLE_2> <PLUGIN_NAME>

`lock` #

meltano lock creates lock files for non-custom plugins in the project.

How to use #

# Lock all plugins
meltano lock --all

# Lock all plugins of a certain type
meltano lock --all --plugin-type=<type>

# Lock specific plugins
meltano lock <name> <name_two>

# Lock specific plugins and disambiguate by type
meltano lock <name> <name_two> --plugin-type=<type>

# Use --update in combination with any of the above to update the lock file
# with the latest definition from MeltanoHub
meltano lock --all --update

Using `lock` with Environments #

The lock command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

`remove` #

meltano remove removes one or more plugins of the same type from your Meltano project.

Specifically, plugins will be removed from the:

meltano.yml project file
Installation found in the .meltano directory under .meltano/<plugin_type>/<plugin_name>
plugin_settings table in the system database
./plugins/<plugin type>/ lock file directory

How to Use #

meltano remove <type> <name>
meltano remove <type> <name> <name_two>

Using `remove` with Environments #

The remove command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

Examples #

# meltano will attempt to remove an extractor called tap-gitlab
meltano remove extractor tap-gitlab

# meltano will attempt to remove two loaders; target-postgres and target-csv
meltano remove loader target-postgres target-csv

`run` #

Run a set of command blocks in series.

Command blocks are specified as a list of plugin names, e.g. meltano run some_tap some_mapping some_target some_plugin:some_cmd and are run in the order they are specified from left to right. A failure in any block will cause the entire run to abort.

Multiple commmand blocks can be chained together or repeated, and extractor/loader pairs will automatically be linked to perform EL work. If you have an active environment defined, a State ID is autogenerated for each extractor/loader pair and used to store and look up the incremental replication state in the system database. This allows subsequent runs with the same extractor and loader combinations to start where the previous run ended. The format of the generated id’s is <environment_name>:<tap_name>-to-<target_name>(:<state_id_suffix). Note that inline mapping names are not included when generating IDs.

Note that if no environment is active, meltano run does not generate a State ID and it does not track state.

In addition to explicitly specifying plugin names you can also execute one or more named jobs alongside other commands.

How to use #

meltano run tap-gitlab target-postgres
meltano run tap-gitlab target-postgres dbt-postgres:clean dbt-postgres:test dbt-postgres:run
meltano run tap-gitlab target-postgres tap-salesforce target-mysql
meltano run tap-gitlab target-postgres dbt-postgres:run tap-postgres target-bigquery
meltano --environment=<ENVIRONMENT> run tap-gitlab target-postgres
meltano run tap-gitlab one-mapping another-mapping target-postgres
meltano run tap-gitlab target-postgres simple-job
meltano run --state-id-suffix=<STATE_ID_SUFFIX> tap-gitlab target-postgres

Parameters #

run will attempt to run incrementally and save state by default. Four top level flags are provided to alter behavior:

--dry-run just parse the invocation, validate it, and explain what would be executed. Does not execute anything. (implicitly enables –log-level=debug for ‘console’ named handlers).
--no-state-update will disable state saving for this invocation.
--full-refresh will force a full refresh and ignore the prior state. The new state after completion will still be updated with the execution results, unless --no-state-update is also specified.
--force will force a job run even if a conflicting job with the same generated ID is in progress.
--state-id-suffix define a custom suffix to generate a state ID with for each EL pair.

Examples:

# run the two pipelines in series
# the autogenerated ID for the first EL pair will be 'dev:tap-gitlab-to-target-postgres'
# the autogenerated ID for the second EL pair will be 'dev:tap-gitlab-to-target-mysql'
meltano --environment=dev run tap-gitlab hide-secrets target-postgres tap-salesforce target-mysql

# run the pipelines in series, performing a full refresh for all.
meltano --environment=dev run --full-refresh tap-gitlab target-postgres tap-salesforce target-mysql ...

# run the pipelines in series, forcing each if a conflicting job is found.
meltano --environment=dev run --force tap-gitlab target-postgres tap-salesforce target-mysql ...

# run a pipeline with a custom state ID suffix
# the autogenerated ID for the EL pair will be 'dev:tap-gitlab-to-target-postgres:pipeline-alias'
meltano --environment=dev --state-id-suffix pipeline-alias run tap-gitlab hide-secrets target-postgres

Using `run` with Environments #

The run command always requires a Meltano Environment to be set. The environment name can be provided using the --environment flag or with the default_environment setting in your meltano.yml file.

`job` #

Use the job command to define one or more sequences of tasks. A job can contain a single task or many tasks. As of today all tasks are run sequentially. You can run a specified job by passing the job name as an argument to meltano run. You can also schedule jobs using meltano schedule.

How to use #

# Add a job with a single task representing a run command
meltano job add <job_name> --tasks "<tap_name> <mapping_name> <target_name> <command>"

# Add a new job with multiple tasks by passing arrays in yaml format, where each item represents a run command.
# This will generate one task per array element:
# task 1: <tap_name> <target_name>
# task 2: <command>
# task 3: <tap2_name> <target2_name>
# etc.
meltano job add <job_name> --tasks "[<tap_name> <target_name>, <command>, <tap2_name> <target2_name>, ...]"

# Update an existing job with new tasks
meltano job set <job_name> --tasks "<tap_name> <mapping_name> <target_name> <command>"
meltano job set <job_name> --tasks "[<tap_name> <target_name>, <command>, <tap2_name> <target2_name>, ...]"

# List all jobs
meltano job list
meltano job list --format=json

# List a named job
meltano job list <job_name>
meltano job list <job_name> --format=json

# Remove a named job
meltano job remove <job_name>

Tasks #

A task should be of the same format as arguments supplied to the meltano run command, which can be any valid sequence of plugins (e.g. extractors, mappers, loaders, utilities, etc.) and plugin commands. Note that such a sequence is only valid if it is one of:

An extractor followed directly by a loader. E.g. tap-gitlab target-postgres
An extractor followed by one or more mappers and then a loader. E.g. tap-gitlab hide-gitlab-secrets target-postgres
A plugin invocation, with optional command. E.g. dbt-postgres:run or custom_utility_plugin
Any sequence of the above. E.g. tap-gitlab hide-gitlab-secrets target-postgres dbt-postgres:run tap-zendesk target-csv

If a job has only one task, that task can be supplied as a single quoted argument:

# A task with a single extractor and loader
meltano job add tap-gitlab-to-target-postgres --tasks "tap-gitlab target-postgres"

# A more complex task
meltano job add tap-gitlab-to-target-postgres-processed --tasks "tap-gitlab hide-gitlab-secrets target-postgres dbt-postgres:run custom-utility-plugin"

This would add the following to your meltano.yml:

jobs:
  - name: tap-gitlab-to-target-postgres
    tasks:
      - tap-gitlab target-postgres
  - name: tap-gitlab-to-target-postgres-processed
    tasks:
      - tap-gitlab hide-gitlab-secrets target-postgres dbt-postgres:run custom-utility-plugin

When an Airflow DAG is generated for a job, each task in the job definition will become a single task in the generated DAG. So while it is certainly possible to define all your jobs using only one task each, there are many scenarios in which it would be useful or even necessary to split your job into multiple tasks. For instance, job steps which must always run, fail, and be retried as a group should always be a part of the same task. And long-running job steps should likely be grouped into a separate task from shorter-running downstream steps so that those downstream steps can be rerun on their own.

Meltano does support this by allowing a job to consist of multiple tasks. Each individual task must itself be a valid sequence of extractors, mappers, loaders, and plugin commands. When multiple tasks are defined in a job, they must be supplied to the meltano job add command as an array in YAML format.

For instance the tap-gitlab-to-target-postgres-processed job in the above example could also be created as:

meltano job add tap-gitlab-to-target-postgres-processed-multiple-tasks --tasks "[tap-gitlab hide-gitlab-secrets target-postgres, dbt-postgres:run, custom-utility-plugin]"

This would add the following to your meltano.yml:

jobs:
  - name: tap-gitlab-to-target-postgres-processed-multiple-tasks
    tasks:
      - tap-gitlab hide-gitlab-secrets target-postgres
      - dbt-postgres:run
      - custom-utility-plugin

While tap-gitlab-to-target-postgres-processed and tap-gitlab-to-target-postgres-processed-multiple-tasks will run the same steps of the pipeline in the same order, scheduling the former will result in a generated DAG consisting of a single task while scheduling the latter will result in a generated DAG consisting of three tasks:

task 1: "meltano run tap-gitlab hide-gitlab-secrets target-postgres"
task 2: "meltano run dbt-postgres:run" , depends on task 1
task 3: "meltano run custom-utility-plugin", depends on task 2

Using `job` with Environments #

The job command can accept the --environment flag to target a specific Meltano Environment. However, the default_environment setting in your meltano.yml file will be ignored.

Examples #

# Add a new job named "simple-demo" that contains three tasks
# Task 1: tap-gitlab hide-gitlab-secrets target-postgres
# Task 2: dbt-postgres:run
# Task 3: tap-gitlab target-csv
meltano job add simple-demo --tasks "[tap-gitlab hide-gitlab-secrets target-postgres, dbt-postgres:run, tap-gitlab target-csv]"

# list the job named "simple-demo"
meltano job list simple-demo --format=json
# run the job named "simple-demo" using meltano run
meltano run simple-demo
# run the job named "simple-demo" AND another EL pair using meltano run
meltano run simple-demo tap-mysql target-bigquery
# remove the job named "simple-demo"
meltano job remove simple-demo

`schedule` #

An orchestrator plugin is required to use meltano schedule: refer to the Orchestration documentation to get started with Meltano orchestration.

Use the schedule command to define ELT or Job pipelines to be run by an orchestrator at regular intervals. These scheduled pipelines will be added to your meltano.yml project file. You can schedule both jobs or legacy meltano elt tasks.

You can run a specific scheduled pipeline’s corresponding meltano run or meltano elt command as a one-off using meltano schedule run <schedule_name>. Any command line options (e.g. --select=<entity> or --dry-run) will be passed on to the underlying commands.

How to use #

The interval argument can be a cron expression or one of the following presets: @hourly (0 * * * *), @daily (0 0 * * *), @weekly (0 0 * * 0), @monthly (0 0 1 * *), @yearly (0 0 1 1 *), or @once (for schedules to be triggered manually through the UI).

# Add a schedule
# Schedule a job named "my_job" to run everyday
meltano schedule add <schedule_name> --job my_job --interval "@daily"
# Schedule an ELT task to run hourly
meltano schedule add <schedule_name> --extractor <tap> --loader <target> --transform run --interval "@hourly"

# List all schedules
meltano schedule list [--format=json]

# Remove a named schedule
meltano schedule remove <schedule_name>

# Update a named schedule changing the interval
meltano schedule set <schedule_name> --interval <new-interval>
# Update a named schedule changing the referenced job
meltano schedule set <schedule_name> --job <new-job>
# Update a named ELT scheduled changing the interval AND changing the extractor
meltano schedule set <schedule_name> --extractor <new-tap> --interval <new-interval>

# Run a schedule
meltano schedule run <schedule_name>

Using `schedule` with Environments #

The schedule command can accept the --environment flag to target a specific Meltano Environment. However, the default_environment setting in your meltano.yml file will be ignored.

Examples #

# Add a new schedule named "gitlab-sync" to run the job named "gitlab-to-mysql" every day
meltano schedule add gitlab-sync --job gitlab-to-mysql --interval "@daily"

# Perform a dry-run of the schedule named "gitlab-sync"
# Behind the scenes, this will execute a `meltano run --dry-run gitlab-sync`
meltano schedule run gitlab-sync --dry-run

# Update the schedule named "gitlab-sync" to run the job named "gitlab-to-postgres" instead of "gitlab-to-mysql"
meltano schedule set gitlab-sync --job gitlab-to-postgres
# Update the schedule named "gitlab-sync" to run weekly instead of daily
meltano schedule set gitlab-sync --interval "@weekly"

# Add a legacy ELT based schedule named "gitlab-to-jsonl" to run every minute
# This specifies that the following command is to be run every minute:
# meltano elt tap-gitlab target-jsonl --state-id=gitlab-to-jsonl
meltano schedule add gitlab-to-jsonl --extractor tap-gitlab --loader target-jsonl --interval="* * * * *"
# Update the schedule named "gitlab-to-jsonl" to use target-csv instead of target-jsonl
meltano schedule set gitlab-to-jsonl --loader target-csv

`select` #

Use the select command to add select patterns to a specific extractor in your Meltano project.

meltano select [--list] [--all] <tap_name> [ENTITIES_PATTERN] [ATTRIBUTE_PATTERN]: Manage the selected entities/attributes for a specific tap.

Selection rules will be stored in the extractor’s select extra.

Not all taps support this feature. In addition, taps needs to support the --discover switch. You can use meltano invoke tap-... --discover to see if the tap supports it.

How to use #

Unix shell-style wildcards can be used in selection patterns to match multiple entities or attributes at once:

*: matches any sequence of characters
?: matches one character
[abc]: matches either a, b, or c
[!abc]: matches any character but a, b, or c

Use --list to list the current selected tap attributes.

Note: --all can be used to show all the tap attributes with their selected status.

Use --rm or --remove to remove previously added select patterns.

Using `select` with Environments #

The select command can accept the --environment flag to target a specific Meltano Environment. However, the default_environment setting in your meltano.yml file will be ignored.

Examples #

# List all available entities and attributes
meltano select tap-gitlab --list --all

# Include all attributes of an entity
meltano select tap-gitlab tags "*"

# Include specific attributes of an entity
meltano select tap-gitlab commits id
meltano select tap-gitlab commits project_id
meltano select tap-gitlab commits created_at
meltano select tap-gitlab commits author_name
meltano select tap-gitlab commits message

# Exclude matching attributes of all entities
meltano select tap-gitlab --exclude "*" "*_url"

# List selected (enabled) entities and attributes
meltano select tap-gitlab --list

Example output:

Enabled patterns:
    tags.*
    commits.id
    commits.project_id
    commits.created_at
    commits.author_name
    commits.message
    !*.*_url

Selected attributes:
    [selected ] commits.author_name
    [selected ] commits.created_at
    [automatic] commits.id
    [selected ] commits.message
    [selected ] commits.project_id
    [automatic] tags.commit_id
    [selected ] tags.message
    [automatic] tags.name
    [automatic] tags.project_id
    [selected ] tags.target

Remove patterns (--rm or --remove):

# Remove previously added select patterns
meltano select tap-gitlab --rm tags "*"
meltano select tap-gitlab --rm --exclude "*" "*_url"
meltano select tap-gitlab --rm commits id

Most shells parse glob syntax: you must escape the special characters in the select pattern by quoting the pattern.

Exclude Parameter #

Use --exclude to exclude all attributes that match the filter.

Attributes that are automatic are always included, even if they match an exclude pattern. Only attributes that are available can be excluded.

Exclusion takes precedence over inclusion. If an attribute is excluded, there is no way to include it back without removing the exclusion pattern first.

Examples #

meltano select --exclude tap-carbon-intensity '*' 'longitude'

meltano select --exclude tap-carbon-intensity '*' 'latitude'

This will exclude all longitude and latitude attributes.

`state` #

Manage Singer State for jobs via the CLI.

For more information about how Meltano uses incremental replication state, see the data integration guide.

clear #

Clear the state for a given state_id. Prompts for confirmation.

How to use #

meltano state clear [--force] <state_id>

Parameters #

The --force option will disable confirmation prompts. Use with caution.

Examples #

# Clear state. Meltano will prompt for confirmation.
meltano state clear dev:tap-gitlab-to-target-jsonl

# Clear state, overriding confirmation prompt.
meltano state clear --force dev:tap-gitlab-to-target-jsonl

get #

Retrieve state for a given state_id.

How to use #

meltano state get <state_id>

Examples #

# Print the state that would be used in the next run of dev:tap-gitlab-to-target-jsonl
meltano state get dev:tap-gitlab-to-target-jsonl

list #

List all state_ids found in the system database.

How to use #

meltano state list [--pattern] <PATTERN>

Parameters #

The --pattern option allows filtering returned state IDs by using * as a wildcard.

"*" is subject to auto-expansion in most shells: you must escape the " *" by quoting the pattern.

Examples #

# List all state IDs
meltano state list

# List only those state IDs that start with "dev:"
meltano state list 'dev:*'

# List only those state IDs that contain "tap-gitlab"
meltano state list --pattern '*tap-gitlab*'

merge #

Merge new state onto existing state for a state ID.

Not seeing merged state in the system database?

Merged state is computed at execution time. The merge command merely adds a new payload to the database which is merged together with existing payloads the next time state is read via meltano elt, meltano run, or meltano state get.

How to use #

# Read state from a file
meltano state merge <state_id> --input-file <file>

# Read state from a command-line argument
meltano state merge <state_id> <RAW STATE JSON>

# Merge state onto other state
meltano state merge <state_id> --from-state-id <src_state_id>

Parameters #

The --input-file option specifies a file to read the state from.
The --from-state-id option specifies an existing state ID to read the state from.

State must be provided in exactly one of these ways: via --input-file, via --from-state-id, or via a command line argument.

Examples #

# Provide state via a command-line argument.
# The argument must be valid JSON with a top-level key of "singer_state"
# Only the "project_123456_issues" key will be overwritten. Any other bookmarks will remain untouched.
meltano state merge dev:tap-gitlab-to-target-jsonl '{"singer_state": {"project_123456_issues": "2020-01-01"}}'

# Provide state via a file.
# The file must contain valid JSON with a top-level key of "singer_state"
# These two lines have the same effect as the one line above.
echo '{"singer_state": {"project_123456_issues": "2020-01-01"}}' > gitlab_state.json
meltano state merge dev:tap-gitlab-to-target-jsonl --input-file gitlab_state.json

# Provide state via existing state.
meltano state merge dev:tap-gitlab-to-target-jsonl --from-state-id prod:tap-gitlab-to-target-jsonl

copy #

Copy state from one state ID to another

How to use #

# Copy state from one state ID to another
meltano state copy <src_state_id> <dst_state_id>

Examples #

# Use prod state to update dev environemnt
meltano state copy prod:tap-gitlab-to-target-jsonl dev:tap-gitlab-to-target-jsonl

move #

Move state from one state ID to another, equivalent to a rename

How to use #

# Move state from one ID to another
meltano state move <src_state_id> <dst_state_id>

Examples #

# Use previous state with a new tap variant, clearing the original
meltano state move original-tap-postgres-to-target-jsonl variant-tap-postgres-to-target-jsonl

set #

Set state for a job.

How to use #

# Read state from a file
# Meltano will prompt for confirmation.
meltano state set <state_id> --input-file <file>

# Read state from a file, overriding confirmation prompt.
meltano state set --force <state_id> --input-file <file>

# Read state from a command-line argument
# Meltano will prompt for confirmation.
meltano state set <state_id> <RAW STATE JSON>

# Read state from a command-line argument, overriding confirmation prompt.
meltano state set --force <state_id> <RAW STATE JSON>

Parameters #

The --input-file option specifies a file to read the state from.
The --force option will disable confirmation prompts. Use with caution.

Examples #

# Provide state via a command-line argument, overriding confirmation prompt.
# The argument must be valid JSON with a top-level key of "singer_state"
# ALL state will be overwritten. Only the "project_123456_issues" bookmark will be used in subsequent runs.
meltano state set --force dev:tap-gitlab-to-target-jsonl '{"singer_state": {"project_123456_issues": "2020-01-01"}}'

# Provide state via a file, overriding confirmation prompt.
# The file must contain valid JSON with a top-level key of "singer_state"
# These two lines have the same effect as the one line above.
echo '{"singer_state": {"project_123456_issues": "2020-01-01"}}' > gitlab_state.json
meltano state set --force dev:tap-gitlab-to-target-jsonl --input-file gitlab_state.json

Using `state` with Environments #

The state command can accept the --environment flag to target a specific Meltano Environment. However, the default_environment setting in your meltano.yml file will be ignored.

`test` #

Run tests for one or more plugins. A test is any command with a name starting with test.

How to use #

# Runs all tests for all plugins
meltano test --all

# Run all available tests for one or more selected plugins
meltano test <plugin1> <plugin2>

# Run a named test for a single plugin
meltano test <plugin>:<test-name>

# Run a named test for one or more plugins
meltano test <plugin1>:<test-name1> <plugin2>:<test-name2>

Using `test` with Environments #

The test command can accept the --environment flag to target a specific Meltano Environment. The default_environment setting in your meltano.yml file will be applied if --environment is not provided explicitly.

`ui` (deprecated) #

The Metano UI is now deprecated. For more information see our troubleshooting page.

`user` #

This command is only relevant when Meltano is run with authentication enabled.

`add` #

Create a Meltano user account, active and ready to be used.

–overwrite, -f #

Update the user instead of creating a new one.

–role, -G #

Add the user to the role. Meltano ships with two built-in roles: admin and regular.

How to use #

meltano user add admin securepassword --role admin

Using `user` with Environments #

The user command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

`upgrade` #

Upgrade Meltano and your Meltano project to the latest version.

When called without arguments, this will:

Upgrade the meltano package
Update files managed by file bundles
Apply migrations to system database

How to use #

meltano upgrade
meltano upgrade --skip-package # Skip upgrading the Meltano package

meltano upgrade package # Only upgrade Meltano package
meltano upgrade files # Only update files managed by file bundles
meltano upgrade database # Only apply migrations to system database

Using `upgrade` with Environments #

The upgrade command does not run relative to a Meltano Environment. The --environment flag and default_environment setting in your meltano.yml file will be ignored if set.

`version` #

It is used to check which version of Meltano currently installed.

How to use #

meltano --version

Command Line

Global Configuration #

add #

How to use #

Parameters #

Using add with Environments #

config #

How to use #

Nested properties #

Dot separator #

Using config with Environments #

How to use: Plugin extras #

How to use: Interactive config #

discover #

How to Use #

Using discover with Environments #

elt #

How to use #

Parameters #

Examples #

Using elt with Environments #

Debugging #

environment #

How to use #

Using discover with Environments #

Examples #

init #

How to use #

Parameters #

Options #

Examples #

Using init with Environments #

install #

How to Use #

Using install with Environments #

invoke #

How to use #

Using invoke with Environments #

Commands #

Containerized commands #

Debugging plugin environment #

lock #

How to use #

Using lock with Environments #

remove #

How to Use #

Using remove with Environments #

Examples #

run #

How to use #

Parameters #

Using run with Environments #

job #

How to use #

Tasks #

Using job with Environments #

Examples #

schedule #

How to use #

Using schedule with Environments #

Examples #

select #

How to use #

Using select with Environments #

Examples #

Exclude Parameter #

Examples #

state #

clear #

How to use #

Parameters #

Examples #

get #

How to use #

Examples #

list #

How to use #

Parameters #

Examples #

merge #

`add` #

Using `add` with Environments #

`config` #

Using `config` with Environments #

`discover` #

Using `discover` with Environments #

`elt` #

Using `elt` with Environments #

`environment` #

Using `discover` with Environments #

`init` #

Using `init` with Environments #

`install` #

Using `install` with Environments #

`invoke` #

Using `invoke` with Environments #

`lock` #

Using `lock` with Environments #

`remove` #

Using `remove` with Environments #

`run` #

Using `run` with Environments #

`job` #

Using `job` with Environments #

`schedule` #

Using `schedule` with Environments #

`select` #

Using `select` with Environments #

`state` #

Using `state` with Environments #

`test` #

Using `test` with Environments #

`ui` (deprecated) #

`user` #

`add` #

Using `user` with Environments #

`upgrade` #

Using `upgrade` with Environments #

`version` #