dagster-dg-core

library1.13.20pypypi✓ verified 24d ago

dagster-dg-core is a foundational library within the Dagster ecosystem, primarily powering the `dg` command-line interface (CLI). It enables local development, project scaffolding, deployment to environments like Dagster Cloud, and programmatic interaction with Dagster entities such as assets, runs, and jobs via CLI commands. As of version 1.13.0, it supports advanced features including AI-assisted development tools and enhanced asset management capabilities. Dagster maintains a frequent release cadence, often issuing weekly or bi-weekly patches and regular minor version updates across its libraries.

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pip install dagster dagster-dg-core

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INSTALL

IMPORT

SIG · DAGSTER-DG-CORE

dagster-dg-core

workflowpythonv1.13.20

Install

18.3s avg

Import

—

Disk

181MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v1.13.20 · 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

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.000s · 177.1MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 18.3s · import 0.000s · 173MB

181MB installed

● package 181MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

cli

✓ from dagster_dg_core import cli

Direct Python imports from `dagster_dg_core` for defining user-facing Dagster assets or ops are generally uncommon. This library primarily underpins the `dg` CLI tool. Most interaction is through command-line commands, rather than programmatic Python imports for data pipeline development.

This quickstart demonstrates how to initialize a new Dagster project and launch the development server using the `dg` CLI, which is powered by `dagster-dg-core`. This allows you to explore the Dagster UI and begin defining assets.

pip install dagster dagster-dg-core mkdir my-dagster-project cd my-dagster-project dg new --name my_first_project --preset minimal # Navigate into the newly created project directory cd my_first_project # Start the Dagster development server and UI dg dev

dg --version

Debug

Known issues

gotchaAll Dagster ecosystem packages (e.g., `dagster`, `dagster-webserver`, `dagster-dg-core`, and other `dagster-*` libraries) should always be installed at the exact same version number to ensure compatibility and avoid runtime errors. Mismatched versions are a very common source of issues.

fix

Ensure `pip install` commands specify consistent versions across all `dagster-*` packages, e.g., `pip install dagster==1.x.y dagster-dg-core==1.x.y`.

affects: All versions

breakingAs of Dagster core v1.12.18 (and corresponding `dagster-dg-core` versions), the `psycopg2-binary` package is no longer a transitive dependency of `dagster-postgres`. If your project relies on `dagster-postgres` (or integrations that use it) and implicitly used `psycopg2-binary`, you must now explicitly add `pip install psycopg2-binary` to your project dependencies.

fix

Explicitly install `psycopg2-binary` in your environment: `pip install psycopg2-binary`.

affects: >= 1.12.18

gotchaOlder versions of `dagster-dg-core` (e.g., v1.12.3) might have an over-conservative dependency pin on `typer < 0.17`. This can lead to conflicts with other Python packages that require a newer `typer` version (e.g., `>= 0.20.1`).

fix

If encountering `typer` version conflicts, ensure you are on the latest `dagster-dg-core` version, which may have relaxed the pin, or manage `typer` explicitly if feasible in your dependency resolution strategy.

affects: < 1.13.0 (specific patch versions might vary)

Upgrade

Version history

1.13.20latest on PyPI · released Aug 27, 2026

Audit

Dependencies

dagsterrequiredCore Dagster framework, required for all functionality. Must be the exact same version as dagster-dg-core.

clickrequiredUsed for building the command-line interface.

requestsrequiredFor making HTTP requests, often to Dagster Cloud APIs.

setuptoolsrequiredStandard Python packaging utility.

tabulaterequiredFor pretty-printing tabular data in the CLI output.

PyYAMLrequiredFor parsing and generating YAML configuration files.