Fistro

A fixture generator based on type annotations.

Examples

from dataclasses import dataclass
from datetime import datetime, date
from typing import List

from fistro.fistro import generate


@dataclass
class Employee:
   id: int
   birthday: date
   last_access: datetime
   password: str
   number_plates: List[int]
   name: str = 'Carlos Sánchez'

employee = generate(Employee)()
print(employee)

It will show something like this:

Employee(id=5809893100, birthday=datetime.date(559, 3, 6), last_access=datetime.datetime(1053, 8, 29, 19, 11, 14), password="iFZ>?)V0'", number_plates=[85863115, 3528889142, 2818728907, 6043092538, 4985672707], name='Carlos Sánchez')

generate function can be called with to_json or to_dict boolean pararameters to return json or dict representation respectively:

class AreaOfCompany(BaseModel):                     
    enable: bool                                    
    riskOwner: str                                  
    description: str                                
    name: str                                       
    code: str
    
print(fistro.generate(AreaOfCompany, as_dict=True))

>>> {'enable': True, 'riskOwner': 'LqPqS\x0c{kZ', 'description': 'k1917GvOV', 'name': '`;ORxzQ7i', 'code': 'w2 |P\rEps'}

print(fistro.generate(AreaOfCompany, as_json=True))

>>> {"enable": true, "riskOwner": "h@Ij34u?H", "description": ",R,G%0<y#", "name": "K4.\u000b:lK!}", "code": "fvitVYrk3"}

Another useful functions are generate_from_json and get_class_body_from_annotations:

from json import loads

from fistro.fistro import generate_from_json, get_class_body_from_annotations

specific_str = """{
            "_id": "5ae09b3947467b00111e7bf6",
            "localExposure": 0,
            "answer": "mitigate",
            "idRisk": "5ae09b3947467b00111e7bf6",
            "version": 4,
            "country": "BR",
            "company": "0185",
            "currency": "BRL",
            "zone": "DIRT8",
            "internalRef": "RSP-BR-0185-DIRT8-105",
            "creationDate": "2017-12-13T23:00:00.000Z",
            "title": "Tributário: Contribuições Previdenciárias sobre Plano de Stock Options",
            "riskCategory": {
                "es": "22. Contingencias tributarias",
                "en": "22. Tax contingencies",
                "pt": "22. Contingências Fiscais"
            },
            "evaluationType": "quantitative",
            "basicRef": "26376309-2cc2-4a0d-9c6a-373e0a7d9043",
            "localQUANTITATIVENetCASHFLOW": 0,
            "euroQUANTITATIVENetCASHFLOW": 0,
            "localQUANTITATIVEGrossCASHFLOW": 241000000,
            "euroQUANTITATIVEGrossCASHFLOW": 57324742,
            "probability": "veryPossible",
            "status": "open",
            "commissionApproval": false,
            "companyRegistry": true,
            "companyCode": "0185",
            "IDNotification": "0aa0370e-e6d6-405c-a619-a47da0602dee",
            "localQUANTITATIVEGrossOIBDA": 241000000,
            "localQUANTITATIVEGrossCAPEX": 0,
            "localQUANTITATIVENetOIBDA": 0,
            "localQUANTITATIVENetCAPEX": 0,
            "euroQUANTITATIVEGrossOIBDA": 57324742,
            "euroQUANTITATIVEGrossCAPEX": 0,
            "euroQUANTITATIVENetOIBDA": 0,
            "euroQUANTITATIVENetCAPEX": 0,
            "hierarchy": "principal",
            "hierarchySubsidiaries": [],
            "owner": "Vasco Gruber"
        }"""

specific_json = loads(specific_str)

the_class = generate_from_json(specific_json)
print(get_class_body_from_annotations(the_class.__annotations__))

It will print:

_id: str
localExposure: int
answer: str
idRisk: str
version: int
country: str
company: str
currency: str
zone: str
internalRef: str
creationDate: str
title: str
riskCategory: typing.Dict[str, str]
evaluationType: str
basicRef: str
localQUANTITATIVENetCASHFLOW: int
euroQUANTITATIVENetCASHFLOW: int
localQUANTITATIVEGrossCASHFLOW: int
euroQUANTITATIVEGrossCASHFLOW: int
probability: str
status: str
commissionApproval: bool
companyRegistry: bool
companyCode: str
IDNotification: str
localQUANTITATIVEGrossOIBDA: int
localQUANTITATIVEGrossCAPEX: int
localQUANTITATIVENetOIBDA: int
localQUANTITATIVENetCAPEX: int
euroQUANTITATIVEGrossOIBDA: int
euroQUANTITATIVEGrossCAPEX: int
euroQUANTITATIVENetOIBDA: int
euroQUANTITATIVENetCAPEX: int
hierarchy: str
hierarchySubsidiaries: typing.List[typing.Any]
owner: str

Installation

pip install fistro

Credits

In memoriam of Chiquito de la Calzada.