Deephaven Python Integration Package is created by Deephaven Data Labs. It allows Python developers, including data scientists, to access data, run queries, and execute Python scripts directly inside Deephaven data servers to achieve maximum performance. By taking advantage of the unique streaming table capability of Deephaven and its many data ingestion facilities (Kafka, Parquet, CSV, SQL, etc.), Python developers can quickly put together a real-time data processing pipeline that is high performing and easy to consume.
If you use a Windows operating system, WSL is not required to run Deephaven via pip.
Because this package depends on the Deephaven server, it comes preinstalled with Deephaven Docker images and is made available at runtime in the Python console in the Deephaven Web UI.
from deephaven import read_csv
from deephaven.stream.kafka.consumer import kafka_consumer, TableType
from deephaven.plot import Figure, PlotStyle
csv_table = read_csv("data1.csv")
kafka_table = kafka_consumer.consume({'bootstrap.servers': 'redpanda:29092'}, topic='realtime_feed', table_type=TableType.Append)
joined_table = kafka_table.join(csv_table, on=["key_col_1", "key_col_2"], joins=["data_col1"])
plot = Figure() \
.axes(plot_style = PlotStyle.STACKED_BAR )\
.plot_cat(series_name="Categories1", t=joined_table, category="Key_col_1", y = "data_col1") \
.show()
FAQs
Deephaven Engine Python Package
We found that deephaven-core demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
Security News
Research
The Socket Research Team breaks down a malicious wrapper package that uses obfuscation to harvest credentials and exfiltrate sensitive data.
Research
Security News
Attackers used a malicious npm package typosquatting a popular ESLint plugin to steal sensitive data, execute commands, and exploit developer systems.
Security News
The Ultralytics' PyPI Package was compromised four times in one weekend through GitHub Actions cache poisoning and failure to rotate previously compromised API tokens.