View sqlmesh on Snyk Open Source Advisor

Package Health Score

76 / 100

security
Security review needed
popularity
Popular
maintenance
Healthy
community
Sustainable

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Popularity

Popular

GitHub Stars: 1.89K
Forks: 167
Contributors: 80

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package sqlmesh, we found that it has been starred 1,887 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Dec 12, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 0
H
1
M
0
L

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

License

Apache-2.0

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 74
Open PR: 10
Last Release: 10 days ago
Last Commit: 6 days ago

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

We found that sqlmesh 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

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: No
Contributors: 80
Funding: No

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

We found a way for you to contribute to the project! Looks like sqlmesh is missing a Code of Conduct.

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Package

Python Versions Compatibility: ==3.*

Age: 2 years
Latest Release: 6 days ago
Dependencies: 12 Direct / 53 Total
Versions: 599
Maintainers: 0
Wheels: OS Independent

Readme

SQLMesh logo

SQLMesh is a next-generation data transformation framework designed to ship data quickly, efficiently, and without error. Data teams can efficiently run and deploy data transformations written in SQL or Python with visibility and control at any size.

It is more than just a dbt alternative.

Architecture Diagram

Core Features

> Get instant SQL impact analysis of your changes, whether in the CLI or in SQLMesh Plan Mode

Virtual Data Environments

See a full diagram of how Virtual Data Environments work
Watch this video to learn more

Create isolated development environments without data warehouse costs
Plan / Apply workflow like Terraform to understand potential impact of changes
Easy to use CI/CD bot for true blue-green deployments

Efficiency and Testing

Running this command will generate a unit test file in the tests/ folder: test_stg_payments.yaml

Runs a live query to generate the expected output of the model

sqlmesh create_test tcloud_demo.stg_payments --query tcloud_demo.seed_raw_payments "select * from tcloud_demo.seed_raw_payments limit 5"

# run the unit test
sqlmesh test

MODEL (
  name tcloud_demo.stg_payments,
  cron '@daily',
  grain payment_id,
  audits (UNIQUE_VALUES(columns = (
      payment_id
  )), NOT_NULL(columns = (
      payment_id
  )))
);

SELECT
    id AS payment_id,
    order_id,
    payment_method,
    amount / 100 AS amount, /* `amount` is currently stored in cents, so we convert it to dollars */
    'new_column' AS new_column, /* non-breaking change example  */
FROM tcloud_demo.seed_raw_payments

test_stg_payments:
model: tcloud_demo.stg_payments
inputs:
    tcloud_demo.seed_raw_payments:
      - id: 66
        order_id: 58
        payment_method: coupon
        amount: 1800
      - id: 27
        order_id: 24
        payment_method: coupon
        amount: 2600
      - id: 30
        order_id: 25
        payment_method: coupon
        amount: 1600
      - id: 109
        order_id: 95
        payment_method: coupon
        amount: 2400
      - id: 3
        order_id: 3
        payment_method: coupon
        amount: 100
outputs:
    query:
      - payment_id: 66
        order_id: 58
        payment_method: coupon
        amount: 18.0
        new_column: new_column
      - payment_id: 27
        order_id: 24
        payment_method: coupon
        amount: 26.0
        new_column: new_column
      - payment_id: 30
        order_id: 25
        payment_method: coupon
        amount: 16.0
        new_column: new_column
      - payment_id: 109
        order_id: 95
        payment_method: coupon
        amount: 24.0
        new_column: new_column
      - payment_id: 3
        order_id: 3
        payment_method: coupon
        amount: 1.0
        new_column: new_column

Never build a table more than once
Track what data’s been modified and run only the necessary transformations for incremental models
Run unit tests for free and configure automated audits

Level Up Your SQL

Write SQL in any dialect and SQLMesh will transpile it to your target SQL dialect on the fly before sending it to the warehouse. Transpile Example

Debug transformation errors before you run them in your warehouse in 10+ different SQL dialects
Definitions using simply SQL (no need for redundant and confusing Jinja + YAML)
See impact of changes before you run them in your warehouse with column-level lineage

For more information, check out the website and documentation.

Getting Started

Install SQLMesh through pypi by running:

mkdir sqlmesh-example
cd sqlmesh-example
python -m venv .env
source .env/bin/activate
pip install sqlmesh
sqlmesh init duckdb # get started right away with a local duckdb instance

Follow the quickstart guide to learn how to use SQLMesh. You already have a head start!

Follow this example to learn how to use SQLMesh in a full walkthrough.

Join Our Community

Together, we want to build data transformation without the waste. Connect with us in the following ways:

Join the Tobiko Slack Community to ask questions, or just to say hi!
File an issue on our GitHub
Send us an email at hello@tobikodata.com with your questions or feedback
Read our blog

Contribution

Contributions in the form of issues or pull requests (from fork) are greatly appreciated.

Read more on how to contribute to SQLMesh open source.

Watch this video walkthrough to see how our team contributes a feature to SQLMesh.

sqlmesh dependencies

astor click croniter dateparser freezegun ipywidgets jinja2 pandas pydantic requests ruamel-yaml tenacity

FAQs

What is sqlmesh?

. Visit Snyk Advisor to see a full health score report for sqlmesh, including popularity, security, maintenance & community analysis.

Is sqlmesh popular?

The python package sqlmesh receives a total of 18,987 weekly downloads. As such, sqlmesh popularity was classified as a popular. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is sqlmesh well maintained?

We found that sqlmesh demonstrated a healthy version release cadence and project activity. It has a community of 80 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is sqlmesh safe to use?

While scanning the latest version of sqlmesh, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 16 December-2024, at 14:26 (UTC).

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Security

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Community

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Package

Readme

Core Features

Getting Started

Join Our Community

Contribution

sqlmesh dependencies

FAQs

What is sqlmesh?

Is sqlmesh popular?

Is sqlmesh well maintained?

Is sqlmesh safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Fix identified vulnerabilities

Monitor for new issues

Package Health Score

Explore Similar Packages

Direct Usage Popularity

Security and license risk for latest version

Commit Frequency

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Keep your project healthy

Check your requirements.txt

Snyk Vulnerability Scanner

Readme

Core Features

Getting Started

Join Our Community

Contribution

sqlmesh dependencies

FAQs

What is sqlmesh?

Is sqlmesh popular?

Is sqlmesh well maintained?

Is sqlmesh safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues