Data Model CLI

Parse the Dallas Central Appraisal District (DCAD) data dictionary into sqlalchemy metadata. Use the generated metadata to generate Flask-SQLAlchemy model code, using flask-sqlacodegen.

This will convert this data dictionary structure:

TABLE [ABATEMENT_EXEMPT]                Table containing information for abatement if applicable
        [ACCOUNT_NUM]                   The DCAD Account number
        [APPRAISAL_YR]                  The appraisal year for the data
        [TOT_VAL]                       The total value for the property

into

from flask_sqlalchemy import SQLAlchemy


db = SQLAlchemy()



class AbatementExempt(db.Model):
    __tablename__ = 'abatement_exempt'

    account_num = db.Column(db.Integer, primary_key=True, nullable=False, info='The DCAD Account number')
    appraisal_yr = db.Column(db.Integer, primary_key=True, nullable=False, info='The appraisal year for the data')
    tot_val = db.Column(db.Float, info='The total value for the property')

Example (using the entery point)

generate_sqlalchemy path/to/file.txt --outfile models.py --flask

To see the full list of options

generate_sqlalchemy --help

Table Parser

This parser functions as a dictionary parser for the invidual table exports. It also coerces and validates the data. It uses the same naming convention logic to identify field types as the Data Model process.

Where to get it

[PyPI](https://pypi.org/project/dcad-parser-hydrospanner/)

pip install dcad-parser-hydrospanner