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Install & Compatibility
Where this runs
tested against v0.14.0 · 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 · 70.9MB
glibcpy 3.10–3.95 runs
installs and imports cleanly · install 5.8s · import 0.000s · 69MB
69MB installed
● package 69MB
Code
Verified usage
Verified import paths — ran on the pinned version, not inferred.
JobsClient
✓ from google.cloud.dataflow_v1beta3 import JobsClient
✗ from google.cloud.dataflow_v1beta3 import JobsClient
This quickstart demonstrates how to initialize the Dataflow Jobs client and list existing Dataflow jobs in a specified Google Cloud project and region. Ensure your `GOOGLE_CLOUD_PROJECT` environment variable is set and you have authenticated via `gcloud auth application-default login`.
import os
from google.cloud.dataflow_v1beta3 import JobsClient
from google.cloud.dataflow_v1beta3.types import ListJobsRequest
# Set your Google Cloud Project ID (e.g., via GOOGLE_CLOUD_PROJECT environment variable)
project_id = os.environ.get("GOOGLE_CLOUD_PROJECT", "your-gcp-project-id")
region = "us-central1" # Dataflow jobs are regional, specify the region where your jobs run
if project_id == "your-gcp-project-id":
print("WARNING: Please set the GOOGLE_CLOUD_PROJECT environment variable or replace 'your-gcp-project-id'.")
exit()
try:
# Initialize the client (will use Application Default Credentials by default)
client = JobsClient()
# Create a request to list jobs in a specific project and region
request = ListJobsRequest(project_id=project_id, location=region)
print(f"Listing Dataflow jobs for project '{project_id}' in region '{region}':")
response = client.list_jobs(request=request)
jobs_found = False
for job in response.jobs:
print(f" Job ID: {job.id}, Name: {job.name}, Type: {job.type}, State: {job.current_state}")
jobs_found = True
if not jobs_found:
print(" No Dataflow jobs found.")
except Exception as e:
print(f"An error occurred: {e}")
print("Ensure you have authenticated with `gcloud auth application-default login` and enabled the Dataflow API in your project.")
Debug
Known issues
gotchaThis library (`google-cloud-dataflow-client`) is for *managing* Dataflow jobs and interacting with the Dataflow service. It is not for *defining* data processing pipelines. Pipeline definition is done using the Apache Beam SDK (`apache-beam` library).fixUse `apache-beam` for writing and defining your Dataflow pipelines. Use `google-cloud-dataflow-client` for programmatic control over the Dataflow service itself (e.g., listing, launching, or updating jobs).
affects: All versions
gotchaGoogle Cloud client libraries often expose API versions (e.g., `v1beta3`) directly in their import paths. Using an incorrect or deprecated API version in your import statement (e.g., `from google.cloud.dataflow_v1` instead of `dataflow_v1beta3`) can lead to `ImportError` or unexpected API behavior.fixAlways refer to the official documentation or the library's source code for the exact and recommended import paths for the specific API version you intend to use. For `google-cloud-dataflow-client` version `0.11.0`, the primary API surface is `dataflow_v1beta3`.
affects: All versions
gotchaDataflow operations are regional. When interacting with the Dataflow service, it is crucial to specify the correct `location` (region) for listing or creating jobs. Failing to do so may result in not finding expected jobs or encountering errors.fixEnsure that the `location` parameter is explicitly provided in your client calls (e.g., `client.list_jobs(project_id=project_id, location='us-central1')`) and matches the region where your Dataflow jobs are deployed or expected to run.
affects: All versions
deprecatedThe Dataflow API `v1beta3` is a beta release and, as such, its methods and types are subject to backward-incompatible changes without a long deprecation period. While generally stable, rely on `beta` components with caution in production environments.fixMonitor official Google Cloud Dataflow documentation and release notes for updates to the API and client library. Be prepared to adapt your code if `v1beta3` features are modified or a new, more stable API version becomes available and is recommended.
affects: All versions of `google-cloud-dataflow-client` that expose `v1beta3` clients (e.g., 0.11.0)
Upgrade
Version history
0.14.0latest on PyPI · released Jun 3, 2026
Audit
Dependencies
google-api-corerequiredCore library for Google API clients, providing common functionality like transport, authentication, and retry logic.