pandera
jsonschema
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pandera | jsonschema | |
---|---|---|
7 | 4 | |
3,007 | 4,432 | |
5.2% | 1.2% | |
9.1 | 8.8 | |
3 days ago | 5 days ago | |
Python | Python | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pandera
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Unit testing functions that input/output dataframes?
I use Pandera, so I just need to define the expected input/output schemas (i.e. column names, types, and constraints on them), and Pandera automatically generates fake data for the unit tests, and validates the result: https://github.com/unionai-oss/pandera
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Great Expectations is annoyingly cumbersome
Please DM me! Or we can discuss in this issue which I just created: https://github.com/unionai-oss/pandera/issues/1042
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Data validation for dashboards
In my opinion for simple data validation tasks the best solution is always Pandera.
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Show HN: Pandera 0.8.0 – validate pandas, dask, modin, and koalas dataframes
* adds support for mypy static type-linting if you need that extra type safety
Repo: https://github.com/pandera-dev/pandera
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Pandera 0.8.0: Schema Validation for Pandas, Dask, Modin, and Koalas DataFrames. Oh, and also out-of-the-box Pydantic and Mypy support :)
Repo: https://github.com/pandera-dev/pandera
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How heavily do you use Great Expectations?
pandera
jsonschema
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Forced to move away from Django template because of nested forms ?
Forms are hard. We use python jsonschema to write our form schemas and validation and use react json schema form for the front end. It's a long time in the making and we still have to write widgets and extensions to get everything we need. Good luck.
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I wrote okjson - A fast, simple, and pythonic JSON Schema Validator
I had a requirement to process and validate large payloads of JSON concurrently for a web service, initially I implemented it using jsonschema and fastjsonschema but I found the whole JSON Schema Specification to be confusing at times and on top of that wanted better performance. Albeit there are ways to compile/cache the schema, I wanted to move away from the schema specification so I wrote a validation library inspired by the design of tiangolo/sqlmodel (type hints) to solve this problem easier.
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Validating a YAML file
This is a hard problem, because, if I understand you correctly, you issue is that you are using something like this: https://github.com/Julian/jsonschema, but want to make the error messages more specific. That means you will need to understand the package sufficiently to find out where it is encountering issues and then provide a more human readable error. Definitely doable, but the first piece, understanding the package enough to revise the messages is difficult.
- Simple method for JSON body minimum required keys checking
What are some alternatives?
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
Cerberus - Lightweight, extensible data validation library for Python
Schematics - Python Data Structures for Humans™.
schema - Schema validation just got Pythonic
pointblank - Data quality assessment and metadata reporting for data frames and database tables
voluptuous - CONTRIBUTIONS ONLY: Voluptuous, despite the name, is a Python data validation library.
swifter - A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
dbt-expectations - Port(ish) of Great Expectations to dbt test macros
colander - A serialization/deserialization/validation library for strings, mappings and lists.
sweetviz - Visualize and compare datasets, target values and associations, with one line of code.
valideer - Lightweight data validation and adaptation Python library.