# TransformDataContext

### ProcessRows

Processes each row in the table using the provided filter predicate and data processor actions.

Parameters:

* `isValid`: A function that returns a boolean indicating if the process is valid.
* `FilterPredicate`: A function to filter input rows.
* `DataProcessor`: An action to process each row.

#### Example:

```csharp
Func<bool> isValid = () => true;
Func<DataRow, bool> filterPredicate = row => row.Field<int>("ID") > 10;
Action<DataRow, long> dataProcessor = (row, index) => Console.WriteLine(row);

data.ProcessRows(isValid, filterPredicate, dataProcessor);
```

### ProcessTable

Processes the entire table using the provided data processor action.

Parameters:

* `isValid`: A function that returns a boolean indicating if the process is valid.
* `DataProcessor`: An action to process the table.

#### Example:

```csharp
Func<bool> isValid = () => true;
Action<DataTable> dataProcessor = table => Console.WriteLine(table.Rows.Count);

data.ProcessTable(isValid, dataProcessor);
```

### ProcessRowsOfClass

Processes each row of the table by converting it to a target class. It sends non-null rows to the data processor.

Parameters:

* `isValid`: A function that returns a boolean indicating if the process is valid.
* `DataProcessor`: An action to process each row.

#### Example:

```csharp
Func<bool> isValid = () => true;
Action<DataRow, bool, MyClass> dataProcessor = (row, clean, myClass) => Console.WriteLine(myClass);

data.ProcessRowsOfClass<MyClass>(isValid, dataProcessor);
```

### ParallelRowFilter

Filters rows in parallel based on the provided predicate.

Parameters:

* `predicate`: A function to filter rows.

#### Example:

```csharp
Func<DataRow, bool> predicate = row => row.Field<int>("ID") > 10;

var filteredRows = data.ParallelRowFilter(predicate);
```

### ColumnNullOrEmptyFilter

Checks if a column value in a row is null or empty.

Parameters:

* `row`: The data row.
* `column`: The column name.

#### Example:

```csharp
var isNullOrEmpty = data.ColumnNullOrEmptyFilter(row, "ColumnName");
```

### EachColumnWithType

Iterates over each column and uses the callback if the column type is valid.

Parameters:

* `row`: The data row.
* `columns`: A dictionary of column names and boolean values.
* `t`: The type to validate.
* `FilterNulls`: If true, no callback is given on null values.
* `col`: A callback function.

#### Example:

```csharp
Dictionary<string, bool> columns = new Dictionary<string, bool> { { "Column1", true }, { "Column2", false } };
Type type = typeof(string);
Action<string, string, bool> callback = (colName, value, isNull) => Console.WriteLine($"{colName}: {value}");

data.EachColumnWithType(row, columns, type, callback);
```

### EachColumn

Iterates over each column in the dictionary and casts the value to the specified type.

Parameters:

* `row`: The data row.
* `columns`: A dictionary of column names and boolean values.
* `FilterNulls`: If true, no callback is given on null values.
* `col`: A callback function.

#### Example:

```csharp
Dictionary<string, bool> columns = new Dictionary<string, bool> { { "Column1", true }, { "Column2", false } };
Action<string, string, bool> callback = (colName, value, isNull) => Console.WriteLine($"{colName}: {value}");

data.EachColumn<string>(row, columns, callback);
```

### RequiredColumns

Checks if the specified columns exist.

Parameters:

* `ColNames`: The column names.

#### Example:

```csharp
bool allExist = data.RequiredColumns("Column1", "Column2");
```

### RequiredColumnsOR

Checks if at least one of the specified column exists.

Parameters:

* `ColNames`: The column names.

#### Example:

```csharp
var columnsExist = data.RequiredColumnsOR("Column1", "Column2");
```

### AnyColumnsOfType

Checks if any columns exist of the specified types.

Parameters:

* `type`: The types to check for.

#### Example:

```csharp
bool columnsExist = data.AnyColumnsOfType(typeof(int), typeof(string));
```

### ColumnsOfType

Returns a list of columns that are of the specified types.

Parameters:

* `type`: The types to check for.

#### Example:

```csharp
var columns = data.ColumnsOfType(typeof(int), typeof(string));
```

### ColumnExists

Checks if a column exists.

Parameters:

* `name`: The name of the column.

#### Example:

```csharp
bool exists = data.ColumnExists("ColumnName");
```

### ColumnName

Gets the column name from the target column name.

Parameters:

* `name`: The target field name.

#### Example:

```csharp
string columnName = data.ColumnName("TargetFieldName");
```

### ToClass

Converts a data row to a specified class.

Parameters:

* `r`: The data row.
* `UseTargetFieldName`: If true, maps through the mapping specification.
* `Clean`: Outputs if the row could be completely converted.
* `uncleanColumnNames`: Outputs the list of names of the columns that failed to convert.

#### Example:

```csharp
MyClass myClass = data.ToClass<MyClass>(row, out bool clean, out var uncleanColumnNames);
```

### ToClassList

Converts the entire data table to a list of specified classes.

Parameters:

* `filterNull`: If true, filters out null converted items.

#### Example:

```csharp
var classList = data.ToClassList<MyClass>();
```

### GetValue

Gets a value from a data row by the map target name and converts it to the specified type.

Parameters:

* `row`: The data row.
* `name`: The name of the target column.
* `val`: Outputs the value.

#### Example:

```csharp
bool success = data.GetValue<int>(row, "ColumnName", out int value);
```

### SetAndValidateValue

Sets and validates a value of a row.

Parameters:

* `row`: The data row.
* `column`: The target column name.
* `val`: The value to set.

#### Example:

```csharp
bool success = data.SetAndValidateValue(row, "ColumnName", value);
```

### SetAndValidateValueOrReport

Sets and validates a value of a row and generates a report if it fails.

Parameters:

* `row`: The data row.
* `column`: The target column name.
* `val`: The value to set.

#### Example:

```csharp
bool success = data.SetAndValidateValueOrReport(row, "ColumnName", value);
```

### ValidateValue

Validates that a new value is valid against the map restrictions for any given column.

Parameters:

* `columnName`: The name of the column.
* `value`: The value to validate.

#### Example:

```csharp
bool valid = data.ValidateValue("ColumnName", value);
```

## DataSet Methods <mark style="color:red;">(ONLY valid in set level transforms)</mark>

### ContainsAssociatedSets

Checks if all specified data sets are present.

* **Parameters:**
  * `TransformOnly` (bool): If true, only transformed tables are returned. Default is true.
  * `SourceOnly` (bool): If true, only source (untransformed) tables are considered. Default is false.
  * `names` (string\[]): Names of the sets.
* **Returns:** A boolean indicating whether all specified sets are present.

#### Example:

```csharp
bool allSetsPresent = data.ContainsAssociatedSets(true, false, "set1", "set2");
```

### ContainsAssociatedSet

Checks if a specified data set is present.

* **Parameters:**
  * `name` (string): Name of the set.
  * `TransformOnly` (bool): If true, only transformed tables are returned. Default is true.
  * `SourceOnly` (bool): If true, only source (untransformed) tables are considered. Default is false.
* **Returns:** A boolean indicating whether the specified set is present.

#### Example:

```csharp
bool isSetPresent = data.ContainsAssociatedSet("set1", true);
```

### AssociatedSets

Retrieves all associated data sets by name.

* **Parameters:**
  * `name` (string): Name of the set.
  * `TransformOnly` (bool): If true, only transformed tables are returned. Default is true.
  * `SourceOnly` (bool): If true, only source (untransformed) tables are considered. Default is false.
* **Returns:** A list of `DataTable` objects for the specified sets.

#### Example:

```csharp
List<DataTable> sets = data.AssociatedSets("set1", true, false);
```

### DataContextFromSet

Creates a data context from a set name.

* **Parameters:**
  * `name` (string): Original table names from the set.
  * `TransformOnly` (bool): If true, only the transformed tables are considered.
  * `SourceOnly` (bool): If true, only source (untransformed) tables are considered. Default is false.
* **Returns:** A list of `TransformDataContext` objects for the specified sets.

#### Example:

```csharp
List<TransformDataContext> contexts = data.DataContextFromSet("set1", true, false);
```

### SetToClass

Converts the first available set to an enumerable of a specified type.

* **Parameters:**
  * `T` (type): Type to which the set will be converted.
  * `originalName` (string): Original name of the transform sets.
  * `TransformedOnly` (bool): If true, only transformed tables are returned. Default is true.
  * `SourceOnly` (bool): If true, only source (untransformed) tables are considered. Default is false.
  * `filterNull` (bool): If true, will filter out null rows. Default is false.
* **Returns:** An enumerable of tuples containing the data of type `T`, a boolean indicating cleanliness, and a list of unclean column names.

#### Example:

```csharp
var classData = data.SetToClass<MyClass>("set1", true, false, true);
```

### ForEachSet

Iterates over each set looking them up by original name.

* **Parameters:**
  * `originalName` (string): Original name.
  * `Callback` (Action): Callback per set.
  * `TransformedOnly` (bool): If true, only transformed tables are considered.
  * `SourceOnly` (bool): If true, only source (untransformed) tables are considered. Default is false.

#### Example:

```csharp
data.ForEachSet("set1", table => {
    // Handle each table
}, true, false);
```