POST /job API

Readme.md

@@ -312,6 +312,26 @@ kue.app.set('title', 'My Application');
     $ curl -X DELETE http://local:3000/job/2
     {"message":"job 2 removed"}
 
+### POST /job
+
+  Create a job:
+
+    $ curl -H "Content-Type: application/json" -X POST -d \
+        '{
+           "type": "email",
+           "data": {
+             "title": "welcome email for tj",
+             "to": "tj@learnboost.com",
+             "template": "welcome-email"
+           },
+           "options" : {
+             "attempts": 5,
+             "priority": "high"
+           }
+         }' http://localhost:3000/job
+    {"message":"job 3 created"}
+
+
 ## Parallel Processing With Cluster
 
  The example below shows how you may use [Cluster](http://learnboost.github.com/cluster) to spread the job processing load across CPUs. By default cluster will create one worker per CPU, however you can specify this number via `.set('workers', N)`.

lib/http/index.js

@@ -61,6 +61,7 @@ app.get('/job/:id/log', provides('json'), json.log);
 app.put('/job/:id/state/:state', provides('json'), json.updateState);
 app.put('/job/:id/priority/:priority', provides('json'), json.updatePriority);
 app.del('/job/:id', provides('json'), json.remove);
+app.post('/job', provides('json'), express.bodyParser(), json.createJob);
 
 // routes
 

lib/http/routes/json.js

@@ -122,6 +122,29 @@ exports.job = function(req, res){
   });
 };
 
+/**
+ * Create a job.
+ */
+
+exports.createJob = function(req, res) {
+  if (!req.body.type)
+    return res.send({ error: 'Must provide job type' }, 400);
+
+  var job = new Job(req.body.type, req.body.data || {});
+  var options = req.body.options;
+  if (options && options.attempts)
+    job.attempts(parseInt(options.attempts));
+  if (options && options.priority)
+    job.priority(options.priority);
+
+  job.save(function(err, resp) {
+    if (err)
+      return res.send({ error: err.message }, 500);
+    res.send({ message: 'job ' + job.id + ' created' });
+  });
+};
+
+
 /**
  * Remove job :id.
  */