Tool/Framework for testing structured data against schema definitions
Project description
Schema Enforcer
Schema Enforcer provides a framework for testing structured data against schema definitions. Right now, JSONSchema is the only schema definition language supported, but we are thinking about adding other schema definition languages at some point in the future.
Getting Started
Install
Schema Enforcer is a python library which is available on PyPi. It requires a python version of 3.7 or greater. Once a supported version of python is installed on your machine, pip can be used to install the tool by using the command python -m pip install schema-enforcer
.
bash$ python --version
Python 3.7.9
bash$ pip --version
pip 20.1.1 from /usr/local/lib/python3.7/site-packages/pip (python 3.7)
python -m pip install schema-enforcer
Note: To determine the version of python your system is using, the command
python --version
can be run from a terminal emulator
Note: Pip is a package manager for python. While most recent versions of python come with pip installed, some do not. You can determine if pip is installed on your system using the command
pip --version
. If it is not, the instructions for installing it, once python has been installed, can be found here
Overview
Schema Enforcer requires that two different elements be defined by the user:
- Schema Definition Files: These are files which define the schema to which a given set of data should adhere.
- Structured Data Files: These are files which contain data that should adhere to the schema defined in one (or multiple) of the schema definition files.
Note: Data which needs to be validated against a schema definition can come in the form of Structured Data Files or Ansible host vars. In the interest of brevity and simplicity, this README.md contains discussion only of Structured Data Files -- for more information on how to use
schema-enforcer
with ansible host vars, see the ansible_command README
When schema-enforcer
runs, it assumes directory hierarchy which should be in place from the folder in which the tool is run.
schema-enforcer
will search for schema definition files nested inside of./schema/schemas/
which end in.yml
,.yaml
, or.json
.schema-enforcer
will do a recursive search for structured data files starting in the current working diretory (./
). It does this by searching all directories (including the current working directory) for files ending in.yml
,.yaml
, or.json
. Theschema
folder and it's subdirectories are excluded from this search by default.
bash$ cd examples/example1
bash$ tree
.
├── chi-beijing-rt1
│ ├── dns.yml
│ └── syslog.yml
├── eng-london-rt1
│ ├── dns.yml
│ └── ntp.yml
└── schema
└── schemas
├── dns.yml
├── ntp.yml
└── syslog.yml
4 directories, 7 files
In the above example, chi-beijing-rt1
is a directory with structured data files containing some configuration for a router named chi-beijing-rt1
. There are two structured data files inside of this folder, dns.yml
and syslog.yml
. Similarly, the eng-london-rt1
directory contains definition files for a router named eng-london-rt1
-- dns.yml
and ntp.yml
.
The file chi-beijing-rt1/dns.yml
defines the DNS servers chi-beijing.rt1
should use. The data in this file includes a simple hash-type data structure with a key of dns_servers
and a value of an array. Each element in this array is a hash-type object with a key of address
and a value which is the string of an IP address.
bash$ cat chi-beijing-rt1/dns.yml
# jsonschema: schemas/dns_servers
---
dns_servers:
- address: "10.1.1.1"
- address: "10.2.2.2"
Note: The line
# jsonschema: schemas/dns_servers
tellsschema-enforcer
the ID of the schema which the structured data defined in the file should be validated against. The schema ID is defined by the$id
top level key in a schema definition. More information on how the structured data is mapped to a schema ID to which it should adhere can be found in the mapping_schemas README
The file schema/schemas/dns.yml
is a schema definition file. It contains a schema definition for ntp servers written in JSONSchema. The data in chi-beijing-rt1/dns.yml
and eng-london-rt1/dns.yml
should adhere to the schema defined in this schema definition file.
bash$ cat schema/schemas/dns.yml
---
$schema: "http://json-schema.org/draft-07/schema#"
$id: "schemas/dns_servers"
description: "DNS Server Configuration schema."
type: "object"
properties:
dns_servers:
type: "array"
items:
type: "object"
properties:
name:
type: "string"
address:
type: "string"
format: "ipv4"
vrf:
type: "string"
required:
- "address"
uniqueItems: true
required:
- "dns_servers"
Note: The cat of the schema definition file may be a little scary if you haven't seen JSONSchema before. Don't worry too much if it is difficult to parse right now. The important thing to note is that this file contains a schema definition to which the structured data in the files
chi-beijing-rt1/dns.yml
andeng-london-rt1/dns.yml
should adhere.
Basic usage
Once schema-enforcer has been installed, the schema-enforcer validate
command can be used run schema validations of YAML/JSON instance files against the defined schema.
bash$ schema-enforcer --help
Usage: schema-enforcer [OPTIONS] COMMAND [ARGS]...
Options:
--help Show this message and exit.
Commands:
ansible Validate the hostvar for all hosts within an Ansible...
schema Manage your schemas
validate Validates instance files against defined schema
To run the schema validations, the command schema-enforcer validate
can be run.
bash$ schema-enforcer validate
schema-enforcer validate
ALL SCHEMA VALIDATION CHECKS PASSED
To acquire more context regarding what files specifically passed schema validation, the --show-pass
flag can be passed in.
bash$ schema-enforcer validate --show-pass
PASS [FILE] ./eng-london-rt1/ntp.yml
PASS [FILE] ./eng-london-rt1/dns.yml
PASS [FILE] ./chi-beijing-rt1/syslog.yml
PASS [FILE] ./chi-beijing-rt1/dns.yml
ALL SCHEMA VALIDATION CHECKS PASSED
If we modify one of the addresses in the chi-beijing-rt1/dns.yml
file so that it's value is the boolean true
instead of an IP address string, then run the schema-enforcer
tool, the validation will fail with an error message.
bash$ cat chi-beijing-rt1/dns.yml
# jsonschema: schemas/dns_servers
---
dns_servers:
- address: true
- address: "10.2.2.2"
bash$ test-schema validate
FAIL | [ERROR] True is not of type 'string' [FILE] ./chi-beijing-rt1/dns.yml [PROPERTY] dns_servers:0:address
bash$ echo $?
1
When a structured data file fails schema validation, schema-enforcer
exits with a code of 1.
Configuration Settings
Schema enforcer will work with default settings, however, a pyproject.toml
file can be placed at the root of the path in which schema-enforcer
is run in order to override default settings or declare configuration for more advanced features. Inside of this pyproject.toml
file, tool.schema_enfocer
sections can be used to declare settings for schema enforcer. Take for example the pyproject.toml
file in example 2.
bash$ cd examples/example2 && tree -L 2
.
├── README.md
├── hostvars
│ ├── chi-beijing-rt1
│ ├── eng-london-rt1
│ └── ger-berlin-rt1
├── invalid
├── pyproject.toml
└── schema
├── definitions
└── schemas
8 directories, 2 files
In this toml file, a schema mapping is declared which tells schema enforcer which structured data files should be checked by which schema IDs.
bash$ cat pyproject.toml
[tool.schema_enforcer.schema_mapping]
# Map structured data filename to schema IDs
'dns_v1.yml' = ['schemas/dns_servers']
'dns_v2.yml' = ['schemas/dns_servers_v2']
'syslog.yml' = ['schemas/syslog_servers']
More information on available configuration settings can be found in the configuration README
Where To Go Next
Detailed documentation can be found in the README.md files inside of the docs/
directory.
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