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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 CLI options are available for the top-level meltano command:

Current Working Directory Configuration

Log Configurations

  • --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.

No Color

The no color 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:

  1. Look for the plugin definition in Meltano Hub
  2. Add it to your meltano.yml project file under plugins: <type>s:, e.g. plugins: extractors
  3. Store the plugin definition in the ./plugins directory (see Lock Artifacts)
  4. Assuming a valid pip_url is specified, install the new plugin using meltano install <type> <name>, which will:
  5. 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
  6. Install the plugin's pip package into the virtual environment using pip install <pip_url> (given --no-install is not provided)
  7. 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-install flag to meltano add.

(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 run.

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
# You can ignore the required Python declared by a plugin by using --force-install flag
meltano add extractor tap-gitlab --force-install
meltano add loader target-postgres

Without a --custom, --inherit-from or --from-ref 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

To add a plugin from a plugin definition YAML file as a custom plugin, use the --from-ref option referencing a URL or local path:

meltano add --from-ref <ref> <type> <name>

# For example:
# URL
meltano add extractor tap-spotify --from-ref https://raw.githubusercontent.com/meltano/hub/main/_data/meltano/extractors/tap-spotify/matatika.yml

# Absolute local path
meltano add extractor tap-spotify --from-ref /path/to/my/meltano/project/tap-spotify--matatika.yml

# Relative local path
meltano add extractor tap-spotify --from-ref tap-spotify--matatika.yml

# The plugin name specified in the command is superseded by the value in the
# plugin definition file - using the same name is just a formality
meltano add extractor this-will-be-ignored --from-ref tap-spotify--matatika.yml

# The above also applies to the plugin variant, if provided
meltano add extractor this-will-be-ignored --variant this-will-also-be-ignored --from-ref tap-spotify--matatika.yml

# Once added, the custom plugin definition can be updated with the `--update` option
meltano add --update extractor tap-spotify --from-ref tap-spotify--matatika.yml

Using --from-ref allows you to add a plugin before it is available on Meltano Hub, such as during development or testing of a plugin. It can also be used to try out plugins that have their definition published an accessible at a public URL, external to the Hub.

Meltano will throw an error if the referenced plugin definition is invalid or missing any required properties - see the Meltano Hub plugin definition syntax for more information.

A plugin can be updated using the --update option

meltano add --update <type> <name>

# For example:
# Update from Meltano Hub
meltano add --update extractor tap-spotify

# Update from ref
meltano add --update extractor tap-spotify --from-ref tap-spotify--matatika.yml

This will update the plugin lock file and meltano.yml entry, without overwriting user-defined configuration - see Updating plugins for more information. Supplying --update for a plugin that does not already exist in a project has no additional effect.

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

By default, plugins that use Python use the version of Python that was used to run Meltano. This behavior can be overridden using the python attribute, which can be set for all plugins, or on a per-plugin basis.

When adding a new plugin, the Python version can be specified using the --python option:

meltano add <type> <name> --python <Python executable name or path>

For example, to add tap-github using Python 3.12 (assuming python3.12 is installed and on your $PATH):

meltano add extractor tap-github --python python3.12

Then regardless of the Python version used when the plugin is installed, tap-gitlab and any plugin which inherits from it will use Python 3.12.

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.

  • --update: Update a plugin in the project.

  • --from-ref=<ref>: Add a plugin from a URL or local path as a custom plugin

  • --force-install: Ignore the required Python version declared by the plugins.

  • --python: The Python version to use for the plugin. See the setting documentation for more information.

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.

compile

The compile command is currently in beta, and subject to change without corresponding semantic version updates.

How to use

Generally, the compile command need not be executed manually, as it will be run automatically by Meltano as-needed.

If you wish to manually compile a manifest file for each environment (including the no-environment manifest file), the compile command can be used like so:

meltano compile

To compile a manifest file for a specific environment:

meltano --environment <environment name> compile

To compile the no-environment manifest file:

meltano --no-environment compile

To save the manifest JSON files to a specific directory:

meltano compile --directory /some/directory/path

By default, the manifest files are saved to ${MELTANO_SYS_DIR_ROOT}/manifests, which defaults to ${MELTANO_PROJECT_ROOT}/.meltano/manifests.

Use the --indent CLI option to control the indentation in the manifest JSON files:

# Use 2 spaces of indentation instead of the default 4
meltano compile --indent 2

# Only use newlines
meltano compile --indent 0

# Remove all non-essential whitespace
meltano compile --indent -1

Using compile with Environments

The compile 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.

When an environment is specified, only the manifest JSON file for that environment will be compiled.

When no environment is explicitly specified, a manifest JSON file for each environment is compiled, including meltano-manifest.json, which is the manifest file for the project when no environment is active.

To only compile the no-environment manifest JSON file, i.e. meltano-manifest.json, pass the --no-environment CLI option to meltano.

cloud

See the full Cloud CLI reference.

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 sensitive: true 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> ...

When setting a config value that contains the character $, you can avoid expansion by escaping it with \ or using single quotes:

meltano config <plugin> set <name> "@\$a"
meltano config <plugin> set <name> '@$a'

Sensitive values

By default, values for sensitive settings are redacted from the output of meltano config commands and replaced with (redacted). If this behaviour is not desirable, you can expose them with the --unsafe flag instead. The default behaviour can be reaffirmed with the counterpart --safe flag (although functionally, this has no effect).

The exception to this rule is meltano config <plugin> which will always output unredacted values, and is intended for debugging purposes only

# `--safe` is the effective default, whether the flag is present or not
meltano config --safe <plugin> list
meltano config <plugin> list

meltano config --unsafe <plugin> list
meltano config --unsafe <plugin> set <sensitive-name> <sensitive-value>
meltano config --unsafe <plugin> set --interactive

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`](#run) and [`meltano invoke`](#invoke), the `meltano config` command ignores any configured [default environment](/concepts/environments#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

How to use: Read setting value from a file

The --from-file option can be used to read a configuration value from a file or a piped external process. This is specially useful for storing complex data like multiline strings, or passing a value generated by a different command line application.

  • Settings of kind object or array will be deserialized accordingly.
  • The special filename - can be used to read from STDIN.
# Set setting `<name>` to the contents of `./file.txt`.
meltano config <plugin> set <name> --from-file ./file.txt

# Set setting `<name>` to the value returned by `uuidgen`.
uuidgen | meltano config <plugin> set <name> --from-file -

When setting a config value for an object or array setting, the file contents must be valid JSON.

Sensitive configuration

Values for sensitive settings (defined as sensitive: true) are redacted in the output of the following commands:

meltano config <plugin> list
meltano config set <name> <value>
meltano config <plugin> set --interactive

docs

Open the Meltano documentation site in the default browser.

el

This allows you to run your EL pipeline to Extract and Load data using an extractor and loader of your choosing,

To allow subsequent pipeline runs with the same extractor/loader combination to pick up right where the previous run left off, each EL 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 in a composable manner.

How to use

meltano el <extractor> <loader> [--state-id TEXT]

Parameters

  • The --state-id option identifies related EL(T) runs when storing and looking up incremental replication state.

  • 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.

  • A --merge-state flag can be passed to merge state with that of previous runs.

    Notes:

  • 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 el ... --dump=state > state.json.

Examples

meltano el tap-gitlab target-postgres --state-id=gitlab-to-postgres

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

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

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

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

Using el with Environments

The el 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 el ...

meltano --log-level=debug el ...

In debug mode, meltano el 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 el 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!

elt

This command is deprecated in favor of el.

This is identical to the el command, except that it also runs transformations.

How to use

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

Parameters

All the same parameters as meltano el are supported, with the following additions:

  • 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)

Examples

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

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:

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 environment with Environments

The environment 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

hub

Use the hub command to interact with the instance of Meltano Hub your Meltano project is configured to use.

Meltano will use the Meltano Hub instance at https://hub.meltano.com by default, but you can configure your project to use a different instance of Meltano Hub by setting the hub_url setting.

How to use

# Check if a connection with Meltano Hub can be established
meltano hub ping

Using environment with Environments

The hub 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.

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:

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]

Positional Arguments

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

Options

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.

To install a plugin without knowing its type, or to install multiple plugins of varying types, use the special - (any) character as the plugin type argument, followed by plugin name(s). meltano install - with no additional positional arguments has the same effect as meltano install (i.e. install all plugins).

To only install plugins for a particular schedule specify the --schedule argument. This can be useful in CI test workflows or for deployments that need to install plugins before every run.

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.

Meltano stores package installation logs in .meltano/logs/pip/{plugin_type}/{plugin_name}/pip.log. This can be useful for debugging installation issues.

How to Use

meltano install
meltano install -

meltano install extractors
meltano install extractor tap-gitlab
meltano install extractors tap-gitlab tap-adwords
meltano install - tap-gitlab target-postgres
meltano install --schedule=<schedule_name>

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:

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 command 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
meltano run --refresh-catalog tap-salesforce 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.
  • --merge-state will merge state with that of previous runs. See the example in the Meltano repository.
  • --run-id will use the provided UUID for the current run. This is useful when your workflow is managed by an external system and you want to track the run in Meltano.
  • --refresh-catalog will force a refresh of the catalog, ignoring any existing cached catalog from previous runs.

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

# run a pipeline, merging state with that of previous runs.
meltano --environment=dev run --merge-state tap-gitlab 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:

  1. An extractor followed directly by a loader. E.g. tap-gitlab target-postgres
  2. An extractor followed by one or more mappers and then a loader. E.g. tap-gitlab hide-gitlab-secrets target-postgres
  3. A plugin invocation, with optional command. E.g. dbt-postgres:run or custom_utility_plugin
  4. 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 EL 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 el and meltano elt tasks.

You can run a specific scheduled pipeline's corresponding meltano run, meltano el 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.

Note that the state ID generated under the hood when invoking meltano schedule run will differ depending on the type of schedule:

  • For jobs, the state ID is autogenerated based on the environment, plugins, and state ID suffix (if provided). The same as if you were using meltano run.

    jobs:
    - name: salesforce-to-parquet
    tasks:
    - tap-salesforce target-parquet
    schedules:
    - name: salesforce-daily # State ID will be 'dev:tap-salesforce-to-target-parquet', for example
    interval: "0 12 * * *"
    job: salesforce-to-parquet
  • For EL schedules, the state ID is the schedule name itself. This means that the state will be shared across all runs of the same schedule.

    schedules:
    - name: salesforce-daily # State ID will be 'salesforce-daily'
    interval: "@daily"
    extractor: tap-salesforce
    loader: target-parquet

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 one of @manual, @once, or @none (for schedules that are to be triggered manually).

@manual, @once, and @none are all aliases for one another. They have no functional difference, and can be used interchangeably.

# Add a schedule
# Schedule a job named "my_job" to run everyday
meltano schedule add <schedule_name> --job my_job --interval "@daily"
# Schedule an EL task to run hourly
meltano schedule add <schedule_name> --extractor <tap> --loader <target> --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 EL 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 EL based schedule named "gitlab-to-jsonl" to run every minute
# This specifies that the following command is to be run every minute:
# meltano el 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 el, 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 environment
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.

upgrade

Upgrade Meltano and your Meltano project to the latest version.

When called without arguments, this will:

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