The dataset project provides a JSON API for JSON object storage via the datasetd application. This repository hosts a TypeScript module targeting Deno for integrating datasetd JSON API managed dataset collections.
The TypeScript ts_dataset module is for working with
the JSON API provided by datasetd.
There are two exported classes defined – DatasetApiClient
and Dataset
. The first is a low level HTTP wrapper mapping
basic dataset verbs to the JSON API. The later provides those verbs
where the objects are TypeScript based. Most applications using dataset
collections hosted via datasetd will use the latter class.
Here’s a simple example of exercising some of the method available with the Dataset object. This demo code assumes datasetd running on localhost on port 8485 and a dataset set collection called “my_objects.ds” has been defined the in YAML configuration of datasetd.
import { Dataset } from "https://caltechlibrary.github.io/ts_dataset/mod.ts";
const port = 8485;
const c_name = "my_objects.ds";
const ds = new Dataset(port, c_name);
// Get a list of keys
let keys = await ds.keys();
console.log(`there are ${keys.length} object(s) found in ${c_name}`);
// Create a new object
let key = "object_key_three";
let obj = {
"one": 1,
"two": "number 2",
"three": true,
"updated": (new Date).toISOString()
;
}
await ds.create(key, obj);
= await ds.keys()
keys console.log(`there are now ${keys.length} object(s) found in ${c_name}`);
// Read back an object
let nObj = await ds.read(key);
console.log(`this is the read object ${JSON.stringify(nObj, null, " ")}`);
// Update our object.
.updated = (new Date).toLocaleString();
objawait ds.update(key, obj);
// Read back updated object
= await ds.read(key);
nObj console.log(`this is the now our object ${JSON.stringify(nObj, null, " ")}`);
// Remove our object
await ds.delete(key);
= await ds.keys()
keys console.log(`there are now ${keys.length} object(s) found in ${c_name}`);
ts_dataset
is a TypeScript module targeting Deno.
Installation can be done via an import statement in your TypeScript
module. You can also clone the GitHub repository at https://caltechlibrary.github.io/ts_dataset. The from
value in your import statement should point to https://caltechlibrary.github.io/ts_dataset/mod.ts if
you want to use it that way. Similarly you can add it to your project’s
deps.ts
file with a line like.
export * from "https://caltechlibrary.github.io/ts_dataset/mod.ts";
ts_dataset
is only useful in conjunction with a running
dataset web
service. This is provided by datasetd available as part of installing
dataset. See the GitHub repo https://github.com/caltechlibrary/dataset for more
details.
To (re)generate the website content clone this repository, change into it and run “make”.
I use tmux to run the demo. It’s convenient. I start with one window and get everything setup and startup datasetd using a Deno task. Then I split the window and run the demo. Below is what I type to run the demo (comments indicate where to switch windows, explain actions).
# Start up tmux
tmux
# clone this repository and change directory
git clone https://github.com/caltechlibrary/ts_dataset
cd ts_dataset
# Use deno tasks to setup our test and demo dataset collections
deno task setup_datasets
# Start the datasetd
deno task run_datasetd
# Split the tmux window (e.g. Ctrl-b ") and run the demo
deno task demo
You can file a GitHub issue or reach out to the authors listed in the codemeta.json file. See SUPPORT file in this repository.
Contributions and help are welcome. See CONTRIBUTING.md
file in this
repository.
Software produced by the Caltech Library is Copyright © 2024 California Institute of Technology. This software is freely distributed under a modified BSD 3-clause license. Please see the LICENSE file for more information.
This work was funded by the California Institute of Technology Library.