minor docs changes

NEWS.md

@@ -4,7 +4,7 @@
 - adds support for reading from multiple files at once as a vector of paths in `db_table` when using DuckDB
     - ie `db_table(db, ["path1", "path2"])`
 - adds streaming support when using DuckDB with `@collect(stream = true)`
-- allows user to customize file reading via `db_table(db, "read_*(path, args)")` when using DuckDB"
+- allows user to customize file reading via `db_table(db, "read_*(path, args)")` when using DuckDB
 
 ## v0.3.0 - 2024-07-25
 - Introduces package extensions for:

README.md

@@ -70,16 +70,8 @@ From TidierDates.jl:
 Supported aggregate functions (as supported by the backend) with more to come
 - `mean`, `minimium`, `maximum`, `std`, `sum`, `cumsum`, `cor`, `cov`, `var`
 - `@summarize` supports any SQL aggregate function in addition to the list above. Simply write the function as written in SQL syntax and it will work.
-- `copy_to` (for DuckDB, MySQL, SQLite)
 
-With DuckDB, `db_table` supports direct paths for S3 bucket locations, iceberg tables, delta table, in addition to csv, parquet, etc.
-
-DuckDB specifically enables copy_to to directly reading in `.parquet`, `.json`, `.csv`, and `.arrow` file, including https file paths.
-
-```julia
-path = "file_path.parquet"
-copy_to(conn, file_path, "table_name")
-```
+When using the DuckDB backend, if `db_table` recieves a file path (`.parquet`, `.json`, `.csv`, `iceberg` or `delta`), it does not copy it into memory. This allows for queries on files too big for memory. `db_table` also supports S3 bucket locations via DuckDB.
 
 ## What is the recommended way to use TidierDB?
 
@@ -95,7 +87,7 @@ Even though the code reads similarly to TidierData, note that no computational w
 using TidierData
 import TidierDB as DB
 
-db = DB.connect(duckdb());
+db = DB.connect(DB.duckdb());
 path_or_name = "https://gist.githubusercontent.com/seankross/a412dfbd88b3db70b74b/raw/5f23f993cd87c283ce766e7ac6b329ee7cc2e1d1/mtcars.csv"
 
 @chain DB.db_table(db, path_or_name) begin

docs/src/index.md

@@ -64,16 +64,9 @@ From TidierDates.jl:
 Supported aggregate functions (as supported by the backend) with more to come
 - `mean`, `minimium`, `maximum`, `std`, `sum`, `cumsum`, `cor`, `cov`, `var`
 - `@summarize` supports any SQL aggregate function in addition to the list above. Simply write the function as written in SQL syntax and it will work 
-- `copy_to` (for DuckDB, MySQL, SQLite)
 
-With DuckDB, `db_table` supports direct paths for S3 bucket locations, iceberg tables, delta table, in addition to csv, parquet, etc.
+When using the DuckDB backend, if `db_table` recieves a file path ( `.parquet`, `.json`, `.csv`, `iceberg` or `delta`), it does not copy it into memory. This allows for queries on files too big for memory. `db_table` also supports S3 bucket locations via DuckDB.
 
-DuckDB specifically enables copy_to to directly reading in `.parquet`, `.json`, `.csv`, and `.arrow` file, including https file paths.
-
-```julia
-path = "file_path.parquet"
-copy_to(conn, file_path, "table_name")
-```
 
 ## What is the recommended way to use TidierDB?
 
@@ -89,7 +82,7 @@ Even though the code reads similarly to TidierData, note that no computational w
 using TidierData
 import TidierDB as DB
 
-db = DB.connect(duckdb());
+db = DB.connect(DB.duckdb());
 path_or_name = "https://gist.githubusercontent.com/seankross/a412dfbd88b3db70b74b/raw/5f23f993cd87c283ce766e7ac6b329ee7cc2e1d1/mtcars.csv"
 
 @chain DB.db_table(db, path_or_name) begin

src/olympics_examples_fromweb.jl

@@ -2,7 +2,7 @@ using TidierData
 
 con = duckdb_connect("memory"); # opening DuckDB database connection.
 db = duckdb_open("con");
-copy_to(db, "https://raw.githubusercontent.com/rahkum96/Olympics-Dataset-by-sql/main/noc_regions.csv" "noc_regions")
+copy_to(db, "https://raw.githubusercontent.com/rahkum96/Olympics-Dataset-by-sql/main/noc_regions.csv", "noc_regions")
 copy_to(db, "https://raw.githubusercontent.com/rahkum96/Olympics-Dataset-by-sql/main/olympic_event.csv", "athlete_events")