Basic Metaphor

FormEncode performs look-before-you-leap validation. The idea being that you check all the data related to an operation, then apply it. This is in contrast to a transactional system, where you just start applying the data and if there's a problem you raise an exception. Someplace else you catch the exception and roll back the transaction. Of course FormEncode works fine with such a system, but because nothing is done until everything validates, you can use this without transactions.

FormEncode generally works on primitive types. These are things like strings, lists, dictionaries, integers, etc. This fits in with look-before-you-leap; often your domain objects won't exist until after you apply the user's request, so it's necessary to work on an early form of the data. Also, FormEncode doesn't know anything about your domain objects or classes; it's just easier to keep it this way.

Validation only operates on a single "value" at a time. This is Python, collections are easy, and collections are themselves a single "value" made up of many pieces. A "Schema validator" is a validator made up of many subvalidators. By using this single metaphor, without separating the concept of "field" and "form", it is possible to create reusable validators that work on compound structures, to validate "whole forms" instead of just single fields, and to support better validation composition.

Also, "validation" and "conversion" are generally applied at the same time. In the documentation this is frequently just referred to as "validation", but anywhere validation can happen, conversion can also happen.

Domain Objects

These are your objects, specific to your application. I know nothing about them, and cannot know. FormEncode doesn't do anything with these objects, and doesn't try to know anything about them.

Validation as directional, not intrinsic

One false start from earlier projects was an attempt to tie validators into the objects they validate against. E.g., you might have a SQLObject class like:

class Address(SQLObject):
    fname = StringCol(notNull=True)
    lname = StringCol(notNull=True)
    mi = StringCol()

It is tempting to take the restrictions of the Address class and automatically come up with a validation schema. This may yet be a viable goal (and to a degree is attainable), but in practical terms validation tends to be both more and less restrictive. Also, validation is contextual; what validation you apply is dependent on the source of the data.

Often in an API we are more restrictive than we may be in a user interface, demanding that everything be specified explicitly. In a UI we may assist the user by filling in values on their behalf. The specifics of this depend on the UI and the objects in question.

At the same time, we are often more restrictive in a UI. For instance, we may demand that the user enter something that appears to be a valid phone number. But for historical reasons, we may not make that demand for objects that already exist, or we may put in a tight restriction on the UI keeping in mind that it can more easily be relaxed and refined than a restriction in the domain objects or underlying database. Also, we may trust the programmer to use the API in a reasonable way, but we seldom trust user data in the same way.

In essence, there is an "inside" and an "outside" to the program. FormEncode is a toolkit for bridging those two areas in a sensible and secure way. The specific way we bridge this depends on the nature of the user interface. An XML-RPC interface can make some assumptions that a GUI cannot make. An HTML interface can typically make even fewer assumptions, including the basic integrity of the input data. It isn't reasonable that the object should know about all means of inputs, and the varying UI requirements of those inputs; user interfaces are volatile, and more art than science, but domain objects work better when they remain stable. For this reason the validation schemas are kept in separate objects.

It also didn't work well to annotate domain objects with validation schemas, though the option remains open. This is experimentation that belongs outside of the core of FormEncode, simply because it's more specific to your domain than it is to FormEncode.

Two sides, two aspects

FormEncode does both validation and conversion at the same time. Validation necessarily happens with every conversion; for instance, you may want to convert string representation of dates to internal date objects; that conversion can fail if the string representation is malformed.

To keep things simple, there's only one operation: conversion. An exception raised means there was an error. If you just want to validate, that's a conversion that doesn't change anything.

Similarly, there's two sides to the system, the foreign data and the local data. In Validator the local data is called "python" (meaning, a natural Python data structure), so we convert to_python and from_python. Unlike some systems, validators explicitly convert in both directions.

For instance, consider the date conversion. In one form, you may want a date like mm/dd/yyyy. It's easy enough to make the necessary converter; but the date object that the converter produces doesn't know how it's supposed to be formatted for that form. Using repr() or any method that binds an object to its form representation is a bad idea. The converter best knows how to undo its work. So a date converter that expects mm/dd/yyyy will also know how to turn a datetime into that format.

(This becomes even more interesting with compound validators.)

Presentation

At one time FormEncode included form generation in addition to validation. The form generation worked okay; it was reasonably attractive, and in many ways quite powerful. I might revisit it. But generation is limited. It works great at first, then you hit a wall -- you want to make a change, and you just can't, it doesn't fit into the automatic generation.

There are also many ways to approach the generation; again it's something that is tied to the framework, the presentation layer, and the domain objects, and FormEncode doesn't know anything about those.

FormEncode does provide htmlfill. You produce the form however you want. Write it out by hand. Use a templating language. Use a form generator. Whatever. Then htmlfill (which specifically understands HTML) fills in the form and any error messages. There are several advantages to this:

• Using htmlfill, form generation is easy. You can just think about how to map a form description or model class to simple HTML. You don't have to think about any of the low-level stuff about filling attributes with defaults or past request values.
• htmlfill works with anything that produces HTML. There's zero preference for any particular templating language, or even general style of templating language.
• If you do form generation, but it later turns out to be insufficiently flexible, you can put the generated form into your template and extend it there; you'll lose automatic synchronization with your models, but you won't lose any functionality.
• Hand-written forms are just as functional as generated forms.

Declarative and Imperative

All of the objects -- schemas, repeating elements, individual validators -- can be created imperatively, though more declarative styles often look better (specifically using subclassing instead of construction). You are free to build the objects either way.

An example of programmatically building form generation: htmlfill_schemabuilder looks for special attributes in an HTML form and builds a validation schema from that.