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Posted to commits@arrow.apache.org by we...@apache.org on 2018/09/22 15:37:38 UTC
[arrow] branch master updated: ARROW-2697: [JS] Add note about
published API documentation to JS README
This is an automated email from the ASF dual-hosted git repository.
wesm pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/arrow.git
The following commit(s) were added to refs/heads/master by this push:
new ca7cae9 ARROW-2697: [JS] Add note about published API documentation to JS README
ca7cae9 is described below
commit ca7cae921b2988a464b7025a5799bcddec4aca68
Author: Brian Hulette <hu...@gmail.com>
AuthorDate: Sat Sep 22 11:37:28 2018 -0400
ARROW-2697: [JS] Add note about published API documentation to JS README
Author: Brian Hulette <hu...@gmail.com>
Closes #2597 from TheNeuralBit/api-doc-readme and squashes the following commits:
25d72d9eb <Brian Hulette> Add link to generated API documentation in the README
---
js/README.md | 28 +++++++++++++++-------------
1 file changed, 15 insertions(+), 13 deletions(-)
diff --git a/js/README.md b/js/README.md
index dcc0937..a4e9d2b 100644
--- a/js/README.md
+++ b/js/README.md
@@ -37,10 +37,17 @@ Arrow is a set of technologies that enable big data systems to process and trans
Apache Arrow is the emerging standard for large in-memory columnar data ([Spark](https://spark.apache.org/), [Pandas](http://wesmckinney.com/blog/pandas-and-apache-arrow/), [Drill](https://drill.apache.org/), [Graphistry](https://www.graphistry.com), ...). By standardizing on a common binary interchange format, big data systems can reduce the costs and friction associated with cross-system communication.
-# Usage
+# Get Started
+Check out our [API documentation][7] to learn more about how to use Apache Arrow's JS implementation. You can also learn by example by checking out some of the following resources:
-## Get a table from an Arrow file on disk (in IPC format)
+* [Observable: Introduction to Apache Arrow][5]
+* [Observable: Manipulating flat arrays arrow-style][6]
+* [/js/test/unit](https://github.com/apache/arrow/tree/master/js/test/unit) - Unit tests for Table and Vector
+
+## Cookbook
+
+### Get a table from an Arrow file on disk (in IPC format)
```es6
import { readFileSync } from 'fs';
@@ -61,7 +68,7 @@ null, null, null
*/
```
-## Create a Table when the Arrow file is split across buffers
+### Create a Table when the Arrow file is split across buffers
```es6
import { readFileSync } from 'fs';
@@ -84,7 +91,7 @@ console.log(table.toString());
*/
```
-## Create a Table from JavaScript arrays
+### Create a Table from JavaScript arrays
```es6
const fields = [{
@@ -109,7 +116,7 @@ const rainfall = arrow.Table.from({
{name: "date", count: LENGTH, VALIDITY: [], DATA: rainDates } ] }] })
```
-## Load data with `fetch`
+### Load data with `fetch`
```es6
import { Table } from "apache-arrow";
@@ -122,7 +129,7 @@ fetch(require("simple.arrow")).then(response => {
});
```
-## Columns look like JS Arrays
+### Columns look like JS Arrays
```es6
import { readFileSync } from 'fs';
@@ -144,7 +151,7 @@ for (let i = -1, n = column.length; ++i < n;) {
}
```
-## Usage with MapD Core
+### Usage with MapD Core
```es6
import MapD from 'rxjs-mapd';
@@ -185,12 +192,6 @@ Index, origin_city
*/
```
-# Tutorials and examples
-
-* [JavaScript Introduction to Arrow][5]
-* [Manipulating flat arrays arrow-style][6]
-* [/js/test/unit](https://github.com/apache/arrow/tree/master/js/test/unit) - Unit tests for Table and Vector
-
# Getting involved
See [develop.md](https://github.com/apache/arrow/blob/master/develop.md)
@@ -277,3 +278,4 @@ Full list of broader Apache Arrow [projects & organizations](https://github.com/
[4]: https://github.com/apache/arrow
[5]: https://beta.observablehq.com/@theneuralbit/introduction-to-apache-arrow
[6]: https://beta.observablehq.com/@lmeyerov/manipulating-flat-arrays-arrow-style
+[7]: http://arrow.apache.org/docs/js/