Best Practices For Custom Validation In Sharepoint Forms

Validating SharePoint Forms Inputs

Validation of form inputs is critical for collecting clean, accurate data in SharePoint. When forms lack proper validation, faulty data can enter the system leading to errors, inconsistencies, and poor data quality. Implementing robust validation logic checks inputs as they are entered, blocking bad data from the start.

Effective validation requires assessing what can go wrong with form inputs. Rules check for incorrect data types, invalid formats, length requirements, semantic constraints, and more. Custom validations fine-tune the rules for specific data needs beyond basic requirements.

Why Validation Matters for Better Data

Well-designed custom validation rules facilitate higher quality user submissions in SharePoint forms. Validation stops incorrect or inconsistent inputs, guiding users to enter valid data. The end results are cleaner data and less errors.

Without validation, SharePoint lists and libraries easily accumulate messy, inaccurate information. Faulty data creates work tracking down errors while trying to manage unreliable information. The risks multiply in forms related to regulations, record-keeping, equipment specifications, or scientific data.

Custom validation tailored to unique data parameters also improves user experience. Immediate feedback quickly flags problems for users before submitting defective inputs. The user avoids the frustration of rejected submissions and retrys. Validation integrated at the field level through javascript or backend logic proactively coaches better data entries.

Types of Validation for SharePoint Forms

SharePoint provides default validation services covering essential data quality checks. Configuration options or custom coding address more advanced needs. The main validation methods available consist of:

• Required Field Validation
• Data Type Validation
• Custom Validation with Patterns

Required Field Validation

Marking fields as required mandates users enter information. If left blank, required fields prevent form submission. Required validations act as a simple method to make certain inputs necessary.

The downside arises when inadequately checking required entries. Faulty data still uploads with only blank values blocked. Additional logic validates properly formatted, useful information gets collected in mandatory fields.

Data Type Validation

SharePoint data types designate the nature of inputs. Data attributes consist of single line of text, multiple lines of text, choice, number, currency, date and time, lookup, and yes/no. Data types render input boxes and format values appropriated for the kind of information entered.

The inherent validation automatically typechecks entries. Users cannot enter anything other than the specified data style. For example, text fields reject numerical inputs. Date selections must conform to date specifications.

However, the automatic verification based on datatypes also has limits. Constraints related to data contents, contexts, or rules require added logic.

Custom Validation with Patterns

Custom validations supplement SharePoint’s default type checking, required attributes, and input formatting. Specifically crafted rules match precise data parameters or business needs. Regular expressions provide an effective method for custom validations.

Regex formulas define field constraints checking the patterns of inputs. Well-designed expressions validate strings match expected compositions. For example, regex can check specific date formats, standard zip code or phone number patterns, or text arrangements.

Custom rules perform validations not possible in standard SharePoint. The regex syntax enables detailed requirements ensuring higher quality submissions to meet unique criteria.

Implementing Custom Validation in Forms

Custom validation stretches beyond SharePoint’s out-of-the-box validation features for greater data precision. Programming options create regex rules, requiredness dependancies, or complex logic tailored to specialized data needs.

Common techniques for advanced custom validation include:

• Using Column Validation
• Validating with Event Receivers
• Client-Side Validation with JQuery

Using Column Validation

SharePoint columns support custom validation formulas placed directly in column settings. Column rules check data as users fill in fields. The formulas based on regex check if entries match predefined patterns.

Column validations function well for straightforward rules operating independently. Chains of dependent rules work better coded elsewhere. Client-side or event receiver validations also improve performance handling intensive operations.

Validating with Event Receivers

Event receiver custom code activates during defined SharePoint actions. Validation logic added to event receivers check submissions flowing into lists and libraries. Rules process against complete item sets submitted from forms.

Using event receivers centralize complex logic apart from individual columns. Dependencies, multi-step rules, and external calls validate collectively. Load balanced event receivers also improve performance on high traffic systems.

Client-Side Validation with JQuery

JQuery scripts add client-side validation without serverside dependencies. Scripts attach to form fields running browser-side as users enter data. Real-time field validation saves round trips to the server improving performance.

Client-side validation user faster feedback on incorrect entries before form submission. Scripts also save server workload handling processing in the browser. Client validation works for checking field patterns, blocking submissions, and warning visuals.

Best Practices for Custom Validations

Well planned custom validations require foresight into user expectations, potential faulty input scenarios, and how to counteract bad data. Best practices optimize form validation for cleaner entries without obstructing user experience.

Validate Early

The sooner bad data hits a checkpoint, the less chances of propagation. Early validations provide immediate user feedback on incorrect entries preventing submission of overall defective records. Field and entry validations activate as close to the source inputs as possible.

Event receivers come second catching bad data collected into items but before reaching the lists or libraries. Validating early in the process improves system stability and performance.

Give Clear Error Messages

Unclear error messages confuse users, fail to communicate issues, and deliver poor experience. Well defined messages indicate the exact validation rule violated including specifics on the expected format.

Guiding error text moves the user closer to accurate data entry. Background context also improves user understanding of the validation intent and why certain data criteria matter.

Use Regex for Complex Checks

Regex provides validation precision checking specific textual patterns impossible otherwise. Expressions fine tune requirements like specialized date variants, identifiers, legal formats, or scientific notations.

Regex syntax enables exact match validations tailored to unique data needs. Wide expression range handles simple to advanced scenario checks with customizable error prompts.

Test Validation Thoroughly

Flawed validation logic risks higher data corruption than no validation at all. Rigorous testing uncovers gaps in rule definitions, exceptions, and false error triggers.

Testing validation requires both positive and negative test cases. Verify properly formatted “good” data passes clean while diverse incorrect “bad” data rightly triggers validation stops. Regression test amendments to confirm no side effect failures.

Example Custom Validation Code

[Provide examples demonstrating custom validation code in action]