From 7de4228694acc5859fc0e4c76513c38cc884dfba Mon Sep 17 00:00:00 2001
From: Junxiao-Hou <72389857+Junxiao-Hou@users.noreply.github.com>
Date: Thu, 21 Oct 2021 00:13:40 -0500
Subject: [PATCH] Add an overall module docstring (#934)

---
 src/CSV.jl | 23 +++++++++++++++++++++++
 1 file changed, 23 insertions(+)

diff --git a/src/CSV.jl b/src/CSV.jl
index fbb44f13..cd5ce95b 100644
--- a/src/CSV.jl
+++ b/src/CSV.jl
@@ -1,3 +1,26 @@
+"""
+CSV provides fast, flexible reader & writer for delimited text files in various formats.
+
+Reading:
+- `CSV.File` reads delimited data and returns a `CSV.File` object, which allows dot-access to columns and iterating rows.
+- `CSV.read` is similar to `CSV.File` but used when the input will be passed directly to a sink function such as a `DataFrame`.
+- `CSV.Rows` reads delimited data and returns a `CSV.Rows` object, which allows "streaming" the data by iterating and thereby has a lower memory footprint than `CSV.File`.
+- `CSV.Chunks` allows processing extremely large files in "batches" or "chunks".
+Writing:
+- `CSV.write` writes a [Tables.jl interface input](https://github.com/JuliaData/Tables.jl) such as a `DataFrame` to a csv file or an in-memory IOBuffer.
+- `CSV.RowWriter` creates an iterator that produces csv-formatted strings for each row in the input table.
+Here is an example of reading a csv file and passing the input to a `DataFrame`:
+```julia
+using CSV, DataFrames
+ExampleInputDF = CSV.read("ExampleInputFile.csv", DataFrame)
+```
+Here is an example of writing out a `DataFrame` to a csv file:
+```julia
+using CSV, DataFrames
+ExampleOutputDF = DataFrame(rand(10,10), :auto)
+CSV.write("ExampleOutputFile.csv", ExampleOutputDF)
+```
+"""
 module CSV
 
 if !isdefined(Base, :contains)