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Python domain model classes for the MythX platform

Project description

The MythX Domain Models

This repository contains the domain models for the MythX smart contract security analysis platform.

What is MythX?

MythX is a security analysis API that allows anyone to create purpose-built security tools for smart contract developers. Tools built on MythX integrate seamlessly into the development environments and continuous integration pipelines used throughout the Ethereum ecosystem.


The MythX domain models runs on Python 3.5+.

To get started, simply run

$ pip3 install mythx-models

Alternatively, clone the repository and run

$ pip3 install .

Or directly through Python’s setuptools:

$ python3 install


1.5.1 (2019-10-31)

  • Fix bug where new API field would raise a TypeError

  • Update pytest to 5.2.2

  • Update sphinx to 2.2.1

1.5.0 (2019-10-19)

  • Added support to group_id in models

  • Update pytest to 5.2.1

  • Update pytest-cov to 2.8.1

1.4.1 (2019-10-04)

  • Add fix for edge case where decoded locations are empty but still given

1.4.0 (2019-10-04)

  • Update pytest from 5.1.2 to 5.2.0

  • Add support for decoded locations

1.3.4 + 1.3.5 (2019-09-19)

  • Lift jsonschema dependency even more for broad support

1.3.3 (2019-09-15)

  • Update twine from 1.13.0 to 1.14.0

  • Take over jsonschema dependency to support web3py

1.3.2 (2019-09-06)

  • Update pytest from 5.1.1 to 5.1.2

  • Add models to fetch analysis input data

1.3.1 (2019-08-30)

  • Add info field to analysis status model

1.3.0 (2019-08-29)

  • Allow null values in submission request and issues response models

1.2.0 (2019-08-29)

  • Added models for source map representation (including source map decompression)

1.1.0 (2019-08-27)

  • Removed the minimum size limit for a detected issue report list

  • Added an as_list option to the detected issue response model to support non-object input

1.0.0 (2019-08-26)

  • Added all models originally in PythX

  • Extended models with BaseModel class

  • Make issue reports and various submodels JSON serializable

  • Added documentation to

  • Added CI with Travis

  • Added coverage metrics with codecov

  • Added packaging pipeline to PyPI

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