snowfakery

v3.6.2

Snowfakery is a tool for generating fake data that has relations between tables. Every row is faked data, but also unique and random, like a snowflake. For more information about how to use this package see README

Latest version published 1 month ago

License: BSD-3-Clause

PyPI

GitHub

Package Health Score

84 / 100

security
No known security issues
popularity
Small
maintenance
Healthy
community
Active

Explore Similar Packages

Popularity

Small

GitHub Stars: 136
Forks: 30
Contributors: 20

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package snowfakery, we found that it has been starred 136 times.

Security

No known security issues

Security and license risk for latest version

Release Date: Mar 28, 2024
Direct Vulnerabilities: 0
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0
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0
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0
L
Indirect Vulnerabilities: 0
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0
H
0
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0
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License Risk: 0
H
0
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0
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All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

BSD-3-Clause

Security Policy

Yes

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Maintenance

Healthy

Commit Frequency

Open Issues: 34
Open PR: 24
Last Release: 1 month ago
Last Commit: 10 days ago

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

We found that snowfakery 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: 20
Funding: No

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

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Package

Python Versions Compatibility: >=3.8

Age: 4 years
Latest Release: 1 month ago
Dependencies: 0 Direct
Versions: 47
Maintainers: 4
Wheels: OS Independent

Not sure how to use snowfakery?

To help you get started, we've collected the most common ways that snowfakery is being used within popular public projects.

SFDO-Tooling / CumulusCI / cumulusci / tasks / bulkdata / generate_from_yaml.py View on Github

def generate_data(self, session, engine, base, num_records, current_batch_num):
        output_stream = SqlOutputStream.from_connection(
            session, engine, base, self.mappings
        )
        with open(self.yaml_file) as open_yaml_file:
            summary = generate(
                open_yaml_file, self.num_records, self.vars, output_stream
            )
            output_stream.close()
            if self.generate_mapping_file:
                with open(self.generate_mapping_file, "w+") as f:
                    yaml.safe_dump(
                        mapping_from_factory_templates(summary), f, sort_keys=False
                    )
                    f.close()

View more ways to use snowfakery

Snowfakery Documentation

Snowfakery is a tool for generating fake data that has relations between tables. Every row is faked data, but also unique and random, like a snowflake.

To tell Snowfakery what data you want to generate, you need to write a Recipe file in YAML.

Snowfakery can write its output to stdout, or any database accessible to SQLAlchemy. When it is embedded in CumulusCI it can output to a Salesforce org. Adding new output formats is fairly straightforward and open source contributions of that form are gratefully accepted.

Documentation

Contributing

To contribute to snowfakery you will first need to setup a virtual environment. Once you have youre virtual environment, you can install dependencies via pip:

pip install -r requirements_dev.txt

Or you can install dependencies via pip tools:

make dev-install

Now you're all set for contributing to Snowfakery!

Updating Dependencies

Performing dependency updates is easy. Just run make update-deps and commit any changes to requirements/prod.txt and requirements/dev.txt.

FAQs

What is snowfakery?

Snowfakery is a tool for generating fake data that has relations between tables. Every row is faked data, but also uniq... Visit Snyk Advisor to see a full health score report for snowfakery, including popularity, security, maintenance & community analysis.

Is snowfakery popular?

The python package snowfakery receives a total of 8,356 weekly downloads. As such, snowfakery popularity was classified as small. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is snowfakery well maintained?

We found that snowfakery demonstrated a healthy version release cadence and project activity. It has a community of 20 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is snowfakery safe to use?

The python package snowfakery 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 26 April-2024, at 11:38 (UTC).

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