@apache-arrow/esnext-umd - npm Package Compare versions

Comparing version 0.2.0 to 0.3.0

package.json

 {
   "name": "@apache-arrow/esnext-umd",
-  "version": "0.2.0",
+  "version": "0.3.0",
   "main": "Arrow.js",
@@ -22,6 +22,15 @@ "types": "Arrow.d.ts",
   "dependencies": {
+    "@types/flatbuffers": "1.6.5",
+    "@types/node": "9.3.0",
+    "@types/text-encoding-utf-8": "1.0.1",
+    "command-line-args": "5.0.1",
+    "command-line-usage": "4.1.0",
     "flatbuffers": "trxcllnt/flatbuffers-esm",
+    "json-bignum": "0.0.3",
     "text-encoding-utf-8": "^1.0.2",
-    "tslib": "^1.8.0"
+    "tslib": "1.9.0"
+  },
+  "bin": {
+    "arrow2csv": "bin/arrow2csv.js"
   }
-}
+}

README.md

@@ -25,3 +25,3 @@ <!---
 
-Arrow is a set of technologies that enable big-data systems to process and transfer data quickly.
+Arrow is a set of technologies that enable big data systems to process and transfer data quickly.
 
@@ -36,11 +36,6 @@ ## install [apache-arrow from npm](https://www.npmjs.com/package/apache-arrow)
 
-Apache Arrow is a columnar memory layout specification for encoding vectors and table-like containers of flat and nested data. The Arrow spec aligns columnar data in memory to minimize cache misses and take advantage of the latest SIMD (Single input multiple data) and GPU operations on modern processors.
+[Apache Arrow](https://github.com/apache/arrow) is a columnar memory layout specification for encoding vectors and table-like containers of flat and nested data. The Arrow spec aligns columnar data in memory to minimize cache misses and take advantage of the latest SIMD (Single input multiple data) and GPU operations on modern processors.
 
-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/), ...). By standardizing on a common binary interchange format, big data systems can reduce the costs and friction associated with cross-system communication.
+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.
 
-# Related Projects
-
-* [GoAI](http://gpuopenanalytics.com/) -- Arrow-powered GPU analytics
-* [rxjs-mapd](https://github.com/graphistry/rxjs-mapd) -- A MapD Core node-driver that returns query results as Arrow columns
-
 # Usage
@@ -188,3 +183,3 @@
 ```sh
-npm install apache-arrow # <-- combined es5/CommonJS + UMD, es2015/ESModules + UMD, and TypeScript package
+npm install apache-arrow # <-- combined es5/UMD, es2015/CommonJS/ESModules/UMD, and TypeScript package
 npm install @apache-arrow/ts # standalone TypeScript package
@@ -208,2 +203,24 @@ npm install @apache-arrow/es5-cjs # standalone es5/CommonJS package
 
+# People
+
+Full list of broader Apache Arrow [committers](https://arrow.apache.org/committers/).
+
+* Brian Hulette, CCRi,  _contributor_
+* Paul Taylor, Graphistry, Inc.,  _committer_
+
+# Powered By Apache Arrow in JS 
+
+Full list of broader Apache Arrow [projects & organizations](https://github.com/apache/arrow/blob/master/site/powered_by.md).
+ 
+## Open Source Projects
+
+* [Apache Arrow](https://arrow.apache.org) -- Parent project for Powering Columnar In-Memory Analytics, including affiliated open source projects
+* [rxjs-mapd](https://github.com/graphistry/rxjs-mapd) -- A MapD Core node-driver that returns query results as Arrow columns
+
+## Companies & Organizations
+
+* [CCRi](http://www.ccri.com/) -- Commonwealth Computer Research Inc, or CCRi, is a Central Virginia based data science and software engineering company
+* [GOAI](http://gpuopenanalytics.com/) -- GPU Open Analytics Initiative standardizes on Arrow as part of creating common data frameworks that enable developers and statistical researchers to accelerate data science on GPUs
+* [Graphistry, Inc.](https://www.graphistry.com/) - An end-to-end GPU accelerated visual investigation platform used by teams for security, anti-fraud, and related investigations. Graphistry uses Arrow in its NodeJS GPU backend and client libraries, and is an early contributing member to GOAI and Arrow\[JS\] working to bring these technologies to the enterprise.
+
 # License
@@ -216,2 +233,2 @@
 [3]: https://issues.apache.org/jira/browse/ARROW
-[4]: https://github.com/apache/arrow
+[4]: https://github.com/apache/arrow

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Improved metrics

Total package byte prevSize

668853

increased by67.62%

Lines of code

377

increased by85.71%

Number of lines in readme file

230

increased by8.49%

Number of medium supply chain risk alerts

1

decreased by-66.67%

Worsened metrics

Dependency count

9

increased by200%

Dependency changes

• + Added@types/flatbuffers@1.6.5

• + Added@types/node@9.3.0

• + Added@types/text-encoding-utf-8@1.0.1

• + Addedcommand-line-args@5.0.1

• + Addedcommand-line-usage@4.1.0

• + Addedjson-bignum@0.0.3

• + Added@types/flatbuffers@1.6.5(transitive)

• + Added@types/node@9.3.0(transitive)

• + Added@types/text-encoding-utf-8@1.0.1(transitive)

• + Addedansi-escape-sequences@4.1.0(transitive)

• + Addedargv-tools@0.1.2(transitive)

• + Addedarray-back@2.0.03.1.0(transitive)

• + Addedcommand-line-args@5.0.1(transitive)

• + Addedcommand-line-usage@4.1.0(transitive)

• + Addeddeep-extend@0.6.0(transitive)

• + Addedfind-replace@2.0.1(transitive)

• + Addedjson-bignum@0.0.3(transitive)

• + Addedlodash.camelcase@4.3.0(transitive)

• + Addedlodash.padend@4.6.1(transitive)

• + Addedreduce-flatten@1.0.1(transitive)

• + Addedtable-layout@0.4.5(transitive)

• + Addedtest-value@3.0.0(transitive)

• + Addedtslib@1.9.0(transitive)

• + Addedtypical@2.6.1(transitive)

• + Addedwordwrapjs@3.0.0(transitive)

• - Removedtslib@1.14.1(transitive)

• Updatedtslib@1.9.0