feat(functions): implement more functions #75

feat(functions): implement more functions

  - implement nearly all of the remaining functions
  - create a macro to quickly create simple functions
  - create a macro to quickly create simple unit tests
  - fix some doc references

core/src/column.rs

@@ -204,7 +204,7 @@ impl Column {
     ///
     /// # Arguments:
     ///
-    /// * `to_type` is a string or [DataType] of the target type
+    /// * `to_type` is a string or [crate::types::DataType] of the target type
     ///
     /// # Example:
     /// ```rust
@@ -239,11 +239,11 @@ impl Column {
     ///
     /// # Arguments:
     ///
-    /// * `cols` a value that implements the [ToLiteralExpr] trait
+    /// * `cols` a vector of Columns
     ///
     /// # Example:
     /// ```rust
-    /// df.filter(col("name").isin(["Jorge", "Bob"]));
+    /// df.filter(col("name").isin([lit("Jorge"), lit("Bob")]));
     /// ```
     pub fn isin(self, cols: Vec<Column>) -> Column {
         let mut val = cols.clone();

core/src/expressions.rs

@@ -3,15 +3,6 @@
 //! Spark Connect has a few different ways of creating expressions and different gRPC methods
 //! require expressions in different forms. These traits are used to either translate a value into
 //! a [spark::Expression] or into a [spark::expression::Literal].
-//!
-//! ## Overview
-//!
-//! - [ToExpr] accepts a `&str`, `String`, or [Column]. This trait uses the method `from` on the Column to create an expression.
-//! - [ToLiteral] is used for taking rust types into a [spark::expression::Literal]. These values are then converted into an expression
-//! - [ToLiteralExpr`] takes a literal value and converts it into a [spark::Expression]
-//! - [ToVecExpr] many gRPC methods require a `Vec<spark::Expression>` this trait is a shorthand for that transformation
-//! - [ToFilterExpr] is specifically used for filter statements
-//!
 
 use chrono::NaiveDateTime;