Struct dcsv::VirtualData

pub struct VirtualData {
    pub columns: Vec<Column>,
    pub rows: Vec<Row>,
}

Virtual data struct which contains csv information

• VirtualData holds row information as hashmap. Therefore modifying data( cell, row or column ) is generally faster than virtual array struct.
• VirtualData cannot have duplicate column name due to previous hashmap implementaiton
• VirtualData allows limiters to confine csv value’s possible states.

Fields

columns: Vec<Column>

rows: Vec<Row>

Implementations

impl VirtualData

pub fn read_only(&self) -> ReadOnlyData

Get read only data from virtual data

This clones every value into a ReadOnlyData. If the purpose is to simply iterate over values, prefer read_only_ref method.

pub fn read_only_ref(&self) -> ReadOnlyDataRef<'_>

Get read only data from virtual data, but as reference

pub fn set_cell_from_string(
    &mut self,
    x: usize,
    y: usize,
    value: &str
) -> DcsvResult<()>

Set cell’s value with given string value

This will fail if the value cannot be converted to column’s type

pub fn insert_column_with_type(
    &mut self,
    column_index: usize,
    column_name: &str,
    column_type: ValueType,
    limiter: Option<ValueLimiter>,
    placeholder: Option<Value>
) -> DcsvResult<()>

Insert a column with given column informations

Args

• column_index : Position to put column
• column_name : New column name
• column_type : Column’s type
• limiter : Set limiter with
• placeholder : Placeholder will be applied to every row

pub fn set_limiter(
    &mut self,
    column: usize,
    limiter: &ValueLimiter,
    panic: bool
) -> DcsvResult<()>

Set a limiter to a column

Args

• column : column’s index
• limiter : Target limiter
• panic : If true, failed set will occur panic

pub fn qualify(
    &self,
    column: usize,
    limiter: &ValueLimiter
) -> DcsvResult<Vec<&Row>>

Qualify data and get reference of qualifed rows.

pub fn qualify_multiple(
    &self,
    qualifiers: Vec<(usize, &ValueLimiter)>
) -> DcsvResult<Vec<&Row>>

Qualify data with multiple limiters and get reference of qualifed rows.

pub fn export_schema(&self) -> String

Export virtual data’s schema(limiter) as string form

Schema is expressed as csv value. Each line is structured with following order.

• column
• type
• default
• variant
• pattern

pub fn try_get_column_index(&self, src: &str) -> Option<usize>

Get a column index from src

Src can be either colum name or column index If colum index is out of range, it returns none

pub fn get_iterator(&self) -> IntoIter<&Value>

Get iterator.

This methods returns iterator which respects column orders

pub fn get_row_iterator(&self, row_index: usize) -> DcsvResult<IntoIter<&Value>>

Get iterator of a row with given index

This respects columns orders

Trait Implementations

impl Clone for VirtualData

fn clone(&self) -> VirtualData

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Default for VirtualData

fn default() -> Self

Returns the “default value” for a type.

impl Display for VirtualData

to_string implementation for virtual data

This returns csv value string

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl<'data> From<&'data VirtualData> for ReadOnlyDataRef<'data>

fn from(data: &'data VirtualData) -> Self

Converts to this type from the input type.

impl From<&VirtualData> for ReadOnlyData

fn from(data: &VirtualData) -> Self

Converts to this type from the input type.

impl VCont for VirtualData

fn new() -> Self

Create empty virtual data

fn move_row(&mut self, src_index: usize, target_index: usize) -> DcsvResult<()>

Move given row to a target row index

fn move_column(&mut self, src_index: usize, target_index: usize) -> DcsvResult<()>

Move a given column to target column index

fn rename_column(&mut self, column_index: usize, new_name: &str) -> DcsvResult<()>

Rename a column

Column’s name cannot be an exsiting name

• column : column_index
• new_name : New column name

fn set_column(&mut self, column_index: usize, value: Value) -> DcsvResult<()>

Set values to a column

Given value will override every row’s value

fn edit_row(
    &mut self,
    row_index: usize,
    values: &[Option<Value>]
) -> DcsvResult<()>

Edit a row

Only edit row’s cell when value is not none

fn set_row(&mut self, row_index: usize, values: &[Value]) -> DcsvResult<()>

Set values to a row

This assumes that given values accord to column’s order. This method will fail when given value fails to qualify column’s limiter.

fn get_cell(&self, x: usize, y: usize) -> Option<&Value>

get cell data by coordinate

fn set_cell(&mut self, x: usize, y: usize, value: Value) -> DcsvResult<()>

Set cell value by coordinate

fn insert_row(
    &mut self,
    row_index: usize,
    source: Option<&[Value]>
) -> DcsvResult<()>

Insert a row to given index

This can yield out of rnage error

fn delete_row(&mut self, row_index: usize) -> bool

Delete a row with given row_index

This doesn’t fail but silently do nothing if index is out of range

fn delete_column(&mut self, column_index: usize) -> DcsvResult<()>

Delete a column with given column index

fn get_row_count(&self) -> usize

Get total rows count

fn get_column_count(&self) -> usize

Get total columns count

fn drop_data(&mut self)

Drop all data from virtual data

fn apply_all<F: FnMut(&mut Value)>(&mut self, f: F)

Apply closure to all values

fn insert_column(
    &mut self,
    column_index: usize,
    column_name: &str
) -> DcsvResult<()>

Insert a column with given column informations