codeforms 0.2.1

Python library for creating, validating, and rendering web forms using Pydantic

codeforms

A Python library for dynamically creating, validating, and rendering web forms using Pydantic.

Installation

pip install codeforms

Or with uv:

uv add codeforms

Requires Python 3.9+.

Quick Start

Creating a Form

Everything starts with the Form class. A form is defined with a name and a list of fields.

from codeforms import Form, TextField, EmailField, NumberField

form = Form(
    name="UserRegistration",
    fields=[
        TextField(name="full_name", label="Full Name", required=True),
        EmailField(name="email", label="Email", required=True),
        NumberField(name="age", label="Age"),
    ]
)

The Form Class

The Form class is the main container for your form structure.

• id — Auto-generated UUID.
• name — Form name (used in HTML export and validation).
• fields — A list of field objects (e.g. TextField, EmailField).
• css_classes — Optional CSS classes for the <form> tag.
• version — Form version number.
• attributes — Dictionary of additional HTML attributes for the <form> tag.

Field Types

All fields inherit from FormFieldBase and share these common attributes:

• name — Field name (maps to name in HTML).
• label — User-visible label.
• field_type — Field type (FieldType enum).
• required — Whether the field is mandatory.
• placeholder — Placeholder text inside the field.
• default_value — Default value.
• help_text — Help text displayed below the field.
• css_classes — CSS classes for the field element.
• readonly — Whether the field is read-only.
• attributes — Additional HTML attributes for the <input> tag.

Available Fields

• TextField — Generic text input (<input type="text">).
  • minlength, maxlength: Min/max text length.
  • pattern: Regex pattern for validation.
• EmailField — Email address (<input type="email">).
• NumberField — Numeric value (<input type="number">).
  • min_value, max_value: Allowed value range.
  • step: Increment step.
• DateField — Date picker (<input type="date">).
  • min_date, max_date: Allowed date range.
• SelectField — Dropdown select (<select>).
  • options: List of SelectOption(value="...", label="...").
  • multiple: Enables multi-select.
  • min_selected, max_selected: Selection count limits (multi-select only).
• RadioField — Radio buttons (<input type="radio">).
  • options: List of SelectOption.
  • inline: Display options inline.
• CheckboxField — Single checkbox (<input type="checkbox">).
• CheckboxGroupField — Group of checkboxes.
  • options: List of SelectOption.
  • inline: Display options inline.
• FileField — File upload (<input type="file">).
  • accept: Accepted file types (e.g. "image/*,.pdf").
  • multiple: Allow multiple file uploads.
• HiddenField — Hidden field (<input type="hidden">).

Data Validation

codeforms offers multiple ways to validate user-submitted data, leveraging Pydantic's validation engine.

Recommended: FormDataValidator

The most robust approach is FormDataValidator.create_model, which dynamically generates a Pydantic model from your form definition. This gives you powerful validations and detailed error messages automatically.

from codeforms import Form, FormDataValidator, TextField, SelectField, SelectOption
from pydantic import ValidationError

# 1. Define your form
form = Form(
    name="MyForm",
    fields=[
        TextField(name="name", label="Name", required=True),
        SelectField(
            name="country",
            label="Country",
            options=[
                SelectOption(value="us", label="United States"),
                SelectOption(value="uk", label="United Kingdom"),
            ]
        )
    ]
)

# 2. Create the validation model
ValidationModel = FormDataValidator.create_model(form)

# 3. Validate incoming data
user_data = {"name": "John", "country": "us"}

try:
    validated = ValidationModel.model_validate(user_data)
    print("Valid!", validated)
except ValidationError as e:
    print("Validation errors:", e.errors())

This approach integrates seamlessly with API backends like FastAPI or Flask, since it produces standard Pydantic models.

Other Validation Methods

Two simpler alternatives exist, though FormDataValidator is preferred:

1. form.validate_data(data) — Built-in method on the Form class. Less flexible; doesn't produce Pydantic models.
2. validate_form_data(form, data) — Standalone function with basic validation logic.

Exporting Forms

Once your form is defined, you can export it to different formats.

# Export to plain HTML
html_output = form.export('html', submit=True)
print(html_output['output'])

# Export to HTML with Bootstrap 5 classes
bootstrap_output = form.export('html_bootstrap5', submit=True)
print(bootstrap_output['output'])

# Export to JSON
json_output = form.to_json()
print(json_output)

# Export to a Python dictionary
dict_output = form.to_dict()
print(dict_output)

Supported Formats

Format	Description
html	Semantic HTML
html_bootstrap4	HTML with Bootstrap 4 classes
html_bootstrap5	HTML with Bootstrap 5 classes
json_schema	JSON Schema (draft-07)
json	JSON representation of the form
dict	Python dictionary representation

HTML export can also generate a <script> block for basic client-side validation.

JSON Schema Export

Generate a standard JSON Schema (draft-07) from any form. The resulting schema is compatible with tools like React JSON Schema Form, Angular Formly, and any JSON Schema validator.

import json
from codeforms import (
    Form, TextField, EmailField, NumberField, SelectField, SelectOption,
    CheckboxField, form_to_json_schema,
)

form = Form(
    name="registration",
    fields=[
        TextField(name="name", label="Full Name", required=True, minlength=2, maxlength=100),
        EmailField(name="email", label="Email", required=True),
        NumberField(name="age", label="Age", min_value=18, max_value=120),
        SelectField(
            name="country",
            label="Country",
            required=True,
            options=[
                SelectOption(value="us", label="United States"),
                SelectOption(value="uk", label="United Kingdom"),
            ],
        ),
        CheckboxField(name="terms", label="Accept Terms", required=True),
    ],
)

# Option 1: Direct function call
schema = form_to_json_schema(form)
print(json.dumps(schema, indent=2))

# Option 2: Via form.export()
result = form.export("json_schema")
schema = result["output"]

Output:

{
  "$schema": "http://json-schema.org/draft-07/schema#",
  "type": "object",
  "title": "registration",
  "properties": {
    "name": {
      "type": "string",
      "minLength": 2,
      "maxLength": 100,
      "title": "Full Name"
    },
    "email": {
      "type": "string",
      "format": "email",
      "title": "Email"
    },
    "age": {
      "type": "number",
      "minimum": 18,
      "maximum": 120,
      "title": "Age"
    },
    "country": {
      "type": "string",
      "enum": ["us", "uk"],
      "title": "Country"
    },
    "terms": {
      "type": "boolean",
      "title": "Accept Terms"
    }
  },
  "required": ["name", "email", "country", "terms"],
  "additionalProperties": false
}

Field Type Mapping

codeforms Field	JSON Schema Type	Extra Keywords
TextField	string	minLength, maxLength, pattern
EmailField	string (format: "email")	—
NumberField	number	minimum, maximum, multipleOf
DateField	string (format: "date")	—
SelectField	string + enum	—
SelectField (multiple=True)	array of enum strings	minItems, maxItems, uniqueItems
RadioField	string + enum	—
CheckboxField	boolean	—
CheckboxGroupField	array of enum strings	uniqueItems
FileField	string (contentEncoding: "base64")	—
FileField (multiple=True)	array of base64 strings	—
HiddenField	string	—
UrlField	string (format: "uri")	minLength, maxLength
TextareaField	string	minLength, maxLength
ListField	array	minItems, maxItems

Field annotations like label, help_text, default_value, and readonly map to the JSON Schema keywords title, description, default, and readOnly respectively.

Fields inside FieldGroup and FormStep containers are flattened into the top-level properties automatically.

Internationalization (i18n)

All validation and export messages are locale-aware. English (en) and Spanish (es) are included out of the box, and you can register any additional language at runtime via register_locale().

Switching Locales

from codeforms import set_locale, get_locale, get_available_locales

print(get_locale())            # "en"
print(get_available_locales()) # ["en", "es"]

set_locale("es")
# All validation messages will now be in Spanish

Registering a Custom Locale

You can add any locale at runtime. Missing keys automatically fall back to English.

from codeforms import register_locale, set_locale

register_locale("pt", {
    "field.required": "Este campo é obrigatório",
    "field.required_named": "O campo {name} é obrigatório",
    "email.invalid": "E-mail inválido",
    "number.min_value": "O valor deve ser maior ou igual a {min}",
    "form.validation_success": "Dados validados com sucesso",
    "form.data_validation_error": "Erro na validação dos dados",
})

set_locale("pt")

Using the Translation Function

The t() function translates a message key, with optional interpolation:

from codeforms import t, set_locale

set_locale("en")
print(t("field.required"))                     # "This field is required"
print(t("field.required_named", name="email")) # "The field email is required"

set_locale("es")
print(t("field.required"))                     # "Este campo es requerido"
print(t("text.minlength", min=3))              # "La longitud mínima es 3"

Locale-Aware Validation

All validation functions respect the active locale:

from codeforms import Form, TextField, validate_form_data, set_locale

form = Form(
    name="example",
    fields=[TextField(name="name", label="Name", required=True)]
)

set_locale("en")
result = validate_form_data(form, {})
print(result["errors"][0]["message"])  # "The field name is required"

set_locale("es")
result = validate_form_data(form, {})
print(result["errors"][0]["message"])  # "El campo name es requerido"

See examples/i18n_usage.py for a full working example.

Dynamic Forms

Conditional Visibility

Fields can be shown or hidden based on the value of other fields using visible_when. This is metadata that your frontend can use for dynamic UI, and the backend can respect during validation.

from codeforms import Form, TextField, SelectField, SelectOption, VisibilityRule

form = Form(
    name="address",
    fields=[
        SelectField(
            name="country",
            label="Country",
            required=True,
            options=[
                SelectOption(value="US", label="United States"),
                SelectOption(value="AR", label="Argentina"),
            ],
        ),
        TextField(
            name="state",
            label="State",
            required=True,
            visible_when=[
                VisibilityRule(field="country", operator="equals", value="US"),
            ],
        ),
        TextField(
            name="province",
            label="Province",
            required=True,
            visible_when=[
                VisibilityRule(field="country", operator="equals", value="AR"),
            ],
        ),
    ],
)

Supported operators: equals, not_equals, in, not_in, gt, lt, is_empty, is_not_empty.

Dynamic Validation

Use validate_form_data_dynamic() to validate only the fields that are currently visible:

from codeforms import validate_form_data_dynamic

result = validate_form_data_dynamic(
    form,
    {"country": "US", "state": "California"},
    respect_visibility=True,
)
print(result["success"])  # True — "province" is hidden, so not required

The legacy validate_form_data() function is unchanged and always validates all fields regardless of visibility.

Checking Visible Fields

visible = form.get_visible_fields({"country": "US"})
print([f.name for f in visible])  # ["country", "state"]

See examples/conditional_visibility.py for a full working example.

Dependent Options

Use DependentOptionsConfig to define option sets that change based on another field's value:

from codeforms import SelectField, SelectOption, DependentOptionsConfig

city_field = SelectField(
    name="city",
    label="City",
    options=[  # all possible options (for static HTML rendering)
        SelectOption(value="nyc", label="New York City"),
        SelectOption(value="bsas", label="Buenos Aires"),
    ],
    dependent_options=DependentOptionsConfig(
        depends_on="country",
        options_map={
            "US": [SelectOption(value="nyc", label="New York City")],
            "AR": [SelectOption(value="bsas", label="Buenos Aires")],
        },
    ),
)

The dependent_options metadata serializes to JSON for your frontend to consume. See examples/dependent_options.py.

Multi-Step Wizard Forms

Use FormStep to split a form into multiple steps. Each step contains its own fields and can be validated independently.

from codeforms import Form, FormStep, TextField, EmailField, CheckboxField

form = Form(
    name="registration",
    content=[
        FormStep(
            title="Personal Information",
            description="Tell us about yourself",
            content=[
                TextField(name="name", label="Name", required=True),
                EmailField(name="email", label="Email", required=True),
            ],
        ),
        FormStep(
            title="Confirmation",
            content=[
                CheckboxField(name="terms", label="I accept the terms", required=True),
            ],
            validation_mode="on_submit",
        ),
    ],
)

Step Validation

# Validate a single step
result = form.validate_step(0, {"name": "John", "email": "[e-mail]"})
print(result["success"])  # True

# Validate all steps at once
result = form.validate_all_steps({
    "name": "John",
    "email": "[e-mail]",
    "terms": True,
})
print(result["success"])  # True

Wizard Helpers

steps = form.get_steps()       # List[FormStep]
fields = form.fields           # Flat list of all fields across all steps

HTML Export

Wizard forms export with data-wizard="true" on the <form> tag. Each step renders as a <section data-step="true"> (not <fieldset>), so you can wire up your own step navigation in JavaScript.

See examples/wizard_form.py for a full working example.

Custom Field Types

You can create your own field types by subclassing FormFieldBase and registering them with register_field_type(). Custom fields integrate seamlessly with forms, JSON serialization, validation, and HTML export.

Defining a Custom Field

from codeforms import FormFieldBase, register_field_type

class PhoneField(FormFieldBase):
    field_type: str = "phone"       # unique string identifier
    country_code: str = "+1"

class RatingField(FormFieldBase):
    field_type: str = "rating"
    min_rating: int = 1
    max_rating: int = 5

register_field_type(PhoneField)
register_field_type(RatingField)

Using Custom Fields in Forms

from codeforms import Form, TextField

form = Form(
    name="feedback",
    fields=[
        TextField(name="name", label="Name", required=True),
        PhoneField(name="phone", label="Phone", country_code="+54"),
        RatingField(name="score", label="Score", max_rating=10),
    ],
)

JSON Roundtrip

Custom fields serialize and deserialize automatically (as long as the field type is registered before deserialization):

import json

json_str = form.to_json()
restored = Form.loads(json_str)

assert isinstance(restored.fields[1], PhoneField)
assert restored.fields[1].country_code == "+54"

Listing Registered Types

from codeforms import get_registered_field_types

for name, classes in sorted(get_registered_field_types().items()):
    print(f"{name}: {[c.__name__ for c in classes]}")

See examples/custom_fields.py for a full working example.

License

MIT