Package Health Score

84 / 100

security
No known security issues
popularity
Recognized
maintenance
Healthy
community
Active

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Popularity

Recognized

GitHub Stars: 282
Forks: 191
Contributors: 30

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package semantic-link, we found that it has been starred 282 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Nov 12, 2024
Direct Vulnerabilities: 0
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0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

Yes

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Maintenance

Healthy

Commit Frequency

Open Issues: 0
Open PR: 6
Last Release: 14 days ago
Last Commit: 4 days ago

Further analysis of the maintenance status of semantic-link based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that semantic-link demonstrates a positive version release cadence with at least one new version released in the past 3 months.

As a healthy sign for on-going project maintenance, we found that the GitHub repository had at least 1 pull request or issue interacted with by the community.

Community

Active

Readme: Yes
Contributing.md: Yes
Code of Conduct: Yes
Contributors: 30
Funding: No

With more than 10 contributors for the semantic-link repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: >=3.10

Age: 1 year
Latest Release: 14 days ago
Dependencies: 0 Direct
Versions: 26
Maintainers: 1
Wheels: OS Independent

Readme

Semantic link is a feature that allows you to establish a connection between Power BI datasets and Synapse Data Science in Microsoft Fabric.

The primary goals of semantic link are to facilitate data connectivity, enable the propagation of semantic information, and seamlessly integrate with established tools used by data scientists, such as notebooks.

Semantic link helps you to preserve domain knowledge about data semantics in a standardized way that can speed up data analysis and reduce errors.

Package (PyPi) | API reference documentation | Product documentation | Samples

By downloading, installing, using or accessing this distribution package for semantic link, you agree to the Terms of Service.

This package has been tested with Microsoft Fabric.

Getting started

Prerequisites

A Microsoft Fabric subscription. Or sign up for a free Microsoft Fabric (Preview) trial.
Sign in to Microsoft Fabric.
Create a new notebook or a new spark job to use this package. Note that semantic link is supported only within Microsoft Fabric.

About the semantic link packages

The functionalities for semantic link are split into multiple packages to allow for a modular installation. If you want to install only a subset of the semantic link functionalities, you can install the individual packages instead of the semantic-link meta-package. This can help solve dependency issues. The following are some of the available packages:

semantic-link - The meta-package that depends on all the individual semantic link packages and serves as a convenient way to install all the semantic link packages at once.
semantic-link-sempy - The package that contains the core semantic link functionality.
semantic-link-functions-holidays - A package that contains semantic functions for holidays and dependence on holidays.
semantic-link-functions-geopandas - A package that contains semantic functions for geospatial data and dependence on geopandas.
...

Install the `semantic-link` meta package

For Spark 3.4 and above, Semantic link is available in the default runtime when using Fabric, and there's no need to install it. If you're using Spark 3.3 or below, or if you want to update to the most recent version of Semantic Link, you have two options:

To install the most recent version semantic-link in your notebook kernel by executing this code in a notebook cell:
```
%pip install -U semantic-link
```
Alternatively, you can add semantic link to your Fabric environments directly. For more information, see library management in Fabric environments.

Key concepts

SemPy offers the following capabilitites:

Connectivity to Power BI
Connectivity through Power BI Spark native connector
Data augmentation with Power BI measures
Semantic propagation for pandas users
Built-in and custom semantic functions

Change logs

0.8.3

fix: race conditions in sempy initialization during multithreading

0.8.2

Telemetry Updates, bugfixes

0.8.1

fix inaccuracy in the row count for certain scenarios when using the list_tables function with extended=True.

0.8.0

add list_dataflow_storage_accounts
fix list_dataflows: fix listing wrong results
fix overflowing column metadata resolving warnings in dataset clients
update fabric.read_table: support setting the import option by onelake_import_method parameter
update FabricDataFrame.to_lakehouse_table: support setting the export option by method parameter

0.7.7

fix list_partitions: records per segment calculation
Added resolve_dataset_id and resolve_dataset_name

0.7.6

update evaluate_dax: allow limiting number rows
fix create_notebook: supported resolving default lakehouse from another workspace
fix api doc: removed broken xrefs
fix get_artifact_id for high concurrency

0.7.5

FabricRestClient & PowerBIRestClient: support waiting for long-run operations
FabricRestClient & PowerBIRestClient: support paged responses
Added resolve_item_id and resolve_item_name
evaluate_dax: support reading data from semantic models with read-only access

0.7.4

internal bug fixes

0.7.3

add delta_column_mapping_mode parameter to FabricDataFrame.to_onelake_table
update find_relationships: swap from/to for relationships to align with PowerBI
make sure users can execute DAX against semantic models they have access to AND not have access to the workspace
support jupyter runtime
update list_columns : added missing workspace parameter
fix list_partitions: record / segment computation
fix list_tables_duplicates
fix list_tables(extended=True)
fix broken doc links

0.7.2

list_* (additional_xmla_properties): handle property names that might fail for some rows
fix list_tables

0.7.1

fix list_annotations

0.7.0

add create_tom_server
add additional_xmla_properties argument to all applicable list_* functions
add list_annotations
update list_columns: alternate columns/tables
update list_relationships: add extended argument
update list_hierarchies: add extended argument
update list_partitions: add extended argument
update list_measures: add additional columns
fix plot_relationship_metadata: arrows for relationships point in the same direction as PowerBI
fix list_datasources

0.6.0

add list_datasources
add list_dataflows
add list_apps
add list_list_gateways
add list_tables
add list_calcuation_items
add list_columns
add list_perspectives
introduce the "extended" flag to query DMVs with more information (e.g. table size)
add additional xmla properties
update capacity id to lower case
make FabricDataFrame creation more robust
fix list_translations

Next steps

View our Samples

FAQs

What is semantic-link?

Semantic link for Microsoft Fabric. Visit Snyk Advisor to see a full health score report for semantic-link, including popularity, security, maintenance & community analysis.

Is semantic-link popular?

The python package semantic-link receives a total of 21,870 weekly downloads. As such, semantic-link popularity was classified as a recognized. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is semantic-link well maintained?

We found that semantic-link demonstrated a healthy version release cadence and project activity. It has a community of 30 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is semantic-link safe to use?

The python package semantic-link was scanned for known vulnerabilities and missing license, and no issues were found. Thus the package was deemed as safe to use. See the full health analysis review.

Last updated on 25 November-2024, at 16:44 (UTC).

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