Install & Compatibility
Where this runs
tested against v4.2.2 · pip install
no network on importno background threads
Install × environment matrix
Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux
muslpy 3.10–3.95 runs
installs and imports cleanly · install 0.0s · import 0.000s · 98.5MB
glibcpy 3.10–3.95 runs
installs and imports cleanly · install 13.7s · import 0.000s · 98MB
104MB installed
● package 104MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
meltano
✓ Meltano is primarily a CLI tool. Direct programmatic import of `meltano` for end-user applications is not a common pattern. Instead, users interact with `meltano` via its command-line interface or by developing custom plugins.
Meltano is predominantly used as a command-line interface. While its internal components can be imported for plugin development, it's not designed for general programmatic use as a library within other Python applications.
This quickstart demonstrates how to initialize a new Meltano project, add an extractor (data source) and a loader (data target), configure a setting for the extractor, and then run a basic ELT pipeline. The output will be stored by the chosen loader (e.g., in `output.jsonl` if using `target-jsonl`).
# Initialize a new Meltano project
meltano init my_meltano_project
cd my_meltano_project
# Add a data source (e.g., tap-carbon-intensity)
meltano add extractor tap-carbon-intensity
# Add a data target (e.g., target-jsonl)
meltano add loader target-jsonl
# Configure an extractor setting (optional, replace with actual config)
meltano config tap-carbon-intensity set country 'GB'
# Run the ELT pipeline
meltano elt tap-carbon-intensity target-jsonl
meltano --version
Debug
Known issues
breakingMeltano v4 introduced significant breaking changes compared to v3, including a new CLI parser (Click), changes to the `meltano.yml` project file structure, and updated plugin definition schemas.fixRefer to the official Meltano v4 migration guide for detailed steps on updating `meltano.yml` and adapting to the new CLI syntax. Review your `meltano.yml` for required changes, especially in plugin configurations.
affects: v4.0.0 and later (migrating from v3.x)
breakingThe command-line syntax, particularly for `meltano config`, changed in Meltano v4 due to the new CLI parser. Old commands might no longer work as expected.fixConsult the updated documentation for the specific commands you use, especially `meltano config`. For example, `meltano config <plugin_name> set <key> <value>` is the new pattern.
affects: v4.0.0 and later (migrating from v3.x)
gotchaDocker Hub `latest` and `latest-python` tags for `meltano/meltano` image inadvertently reverted to Meltano v3 for a period around the v3.9.2 release before being corrected to v4.fixIf you rely on the `latest` Docker tags, ensure you pull the image again to get the most recent v4 version. Consider pinning to specific version tags (e.g., `meltano/meltano:v4.2.0-python`) for production environments to avoid unexpected updates.
affects: v3.9.2 to v4.2.0 (Docker users)
gotchaMeltano frequently updates its internal dependency requirements (e.g., `google-cloud-storage`, `uv`, `structlog`). While typically handled by `pip install meltano`, conflicts can arise in complex Python environments or if `meltano` is installed into a shared virtual environment.fixAlways install Meltano in a dedicated virtual environment. If dependency conflicts occur, try a fresh installation in a new environment or use `pip check` to identify specific conflicts. Consult release notes for explicit dependency bumps.
affects: All versions (especially when upgrading)
Upgrade
Version history
4.2.2latest on PyPI · released Jul 22, 2026
Audit
Dependencies
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