apache-airflow-providers-singularity
Provider package apache-airflow-providers-singularity for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Airflow and need to execute tasks in Singularity containers. The package is actively maintained, carries no security vulnerabilities, has low install friction, and is part of the official Airflow provider ecosystem. Install only if Singularity (or Apptainer) is available on your worker nodes; otherwise it will not function.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Singularity runtime installed on the Airflow worker nodes; Python >=3.10; apache-airflow >=2.11.0.
- Low install friction; pure Python wheel.
- Requires apache-airflow >=2.11.0 and spython >=0.0.56.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license; you can use, modify, and distribute this package freely in commercial and private projects, with minimal restrictions.
last release 2026-06-07 (68 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 184,538 downloads/mo, #10,034 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-singularity
from airflow.providers.singularity.operators.singularity import SingularityOperator
from airflow import DAG
with DAG('example') as dag:
task = SingularityOperator(
task_id='run_container',
image='docker://ubuntu:latest',
command='echo hello'
)- Whether Singularity must be installed on all worker nodes or only on specific execution nodes.
- Whether the package supports Apptainer (the maintained fork of Singularity) or only the original Singularity runtime.
- Specific performance characteristics or limitations when running large numbers of containerized tasks.
What it is and what it does
This is an Apache Airflow provider package that adds Singularity container support to Airflow workflows. It wraps the spython library to allow Airflow tasks to execute inside Singularity containers, enabling reproducible, isolated task execution within your Airflow DAGs. The package is part of the official Airflow ecosystem and integrates seamlessly with Airflow's task scheduling and orchestration.
You install it on top of an existing Airflow installation (>=2.11.0) to gain access to Singularity operators and hooks. It supports Python 3.10 through 3.14 and depends on spython (>=0.0.56) to communicate with the Singularity runtime. The package is actively maintained and carries no known security vulnerabilities.
Use it for
- Run containerized scientific computing tasks in Airflow pipelines using Singularity images.
- Execute isolated workloads on HPC clusters where Singularity is the standard container runtime.
- Reproduce complex computational environments across different Airflow worker nodes via container images.
- Integrate legacy or specialized applications packaged as Singularity containers into Airflow workflows.
- Enforce resource isolation and dependency management for multi-tenant Airflow task execution.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Airflow and need to execute tasks in Singularity containers.
The package is actively maintained, carries no security vulnerabilities, has low install friction, and is part of the official Airflow provider ecosystem. Install only if Singularity (or Apptainer) is available on your worker nodes; otherwise it will not function.
Install
apache-airflow-providers-singularity on PyPI
Before you install
Low install friction; pure Python wheel. Requires apache-airflow >=2.11.0 and spython >=0.0.56. Actively maintained with recent release (68 days old), part of the Apache Airflow ecosystem with strong upstream support.
Requires Singularity runtime installed on the Airflow worker nodes; Python >=3.10; apache-airflow >=2.11.0.
License in practice
Apache-2.0 permissive license; you can use, modify, and distribute this package freely in commercial and private projects, with minimal restrictions.
Quickstart
pip install apache-airflow-providers-singularity
from airflow.providers.singularity.operators.singularity import SingularityOperator
from airflow import DAG
with DAG('example') as dag:
task = SingularityOperator(
task_id='run_container',
image='docker://ubuntu:latest',
command='echo hello'
)Verify before relying
- Whether Singularity must be installed on all worker nodes or only on specific execution nodes.
- Whether the package supports Apptainer (the maintained fork of Singularity) or only the original Singularity runtime.
- Specific performance characteristics or limitations when running large numbers of containerized tasks.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesapache-airflowapache-airflow-providers-common-compatspython |
| Maintenance | Actively maintained 68 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 184,538 / month, #10,034 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_providers_singularity-3.9.4-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “airflow singularity provider”
- apache-airflow-providers-singularityIntegrates Singularity container runtime with Apache Airflow,…
- apache-airflow-providers-common-ioProvides common I/O utilities and operators for Apache Airflow…
- apache-airflow-providers-sqliteIntegrates SQLite databases with Apache Airflow as a provider…
Give your agent the search over MCP, or paste the wish link into any chat.
More Monitoring packages
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
Provides generated Python code for OpenTelemetry semantic conventions, enabling standardized attribute naming and constant definitions for instrumentation and telemetry collection.
Install it if you are using OpenTelemetry and want to follow semantic conventions correctly.
Provides the reference implementation of the OpenTelemetry API for collecting and exporting traces, metrics, and logs from Python applications.
Provides the abstract API and interfaces for OpenTelemetry instrumentation in Python, defining how to emit traces, metrics, and logs without tying code to a specific SDK implementation.
Exports OpenTelemetry observability data to an OpenTelemetry Collector using Protobuf-encoded messages over HTTP.
Install it if you are using OpenTelemetry in Python and need to send data to a Collector over HTTP.
Provides automatic instrumentation commands and programmatic APIs to inject distributed tracing into Python applications without code changes, detecting and instrumenting packages used by your program.
Install it if you need distributed tracing without code changes and have compatible instrumented packages in your environment.
See also apache-airflow-providers-docker · apache-airflow-providers-jenkins · spython · apache-airflow-providers-zendesk · apache-airflow-providers-openfaas · apache-airflow-providers-asana · apache-airflow-providers-apache-flink · apache-airflow-providers-cloudant · apache-airflow-providers-apache-tinkerpop · cwltool