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How to use start_async method in lisa

Best Python code snippet using lisa_python

test_websocket.py

Source:test_websocket.py

...30    """"Open then immediately close"""31    def on_open():32        print('opened')33        client.close()34    await client.start_async(on_open=on_open, on_error=on_error)35    print('closed')36@pytest.mark.asyncio37async def test_trades(client, symbols):38    print(symbols)39    results = []40    def callback(msg):41        results.append(msg)42        client.close()43    def on_open():44        client.subscribe_trades(symbols=symbols, callback=callback)45    await client.start_async(on_open=on_open, on_error=on_error)46    result = results[0]47    assert result['stream'] == 'trades'48@pytest.mark.asyncio49async def test_market_diff(client, symbols):50    results = []51    def callback(msg):52        results.append(msg)53        client.close()54    def on_open():55        client.subscribe_market_diff(symbols=symbols, callback=callback)56    await client.start_async(on_open=on_open, on_error=on_error)57    result = results[0]58    assert result['stream'] == 'marketDiff'59@pytest.mark.asyncio60async def test_market_depth(client, symbols):61    results = []62    def callback(msg):63        results.append(msg)64        client.close()65    def on_open():66        client.subscribe_market_depth(symbols=symbols, callback=callback)67    await client.start_async(on_open=on_open, on_error=on_error)68    result = results[0]69    assert result['stream'] == 'marketDepth'70@pytest.mark.asyncio71async def test_kline(client, symbols):72    results = []73    def callback(msg):74        results.append(msg)75        client.close()76    def on_open():77        client.subscribe_kline(interval='1m', symbols=symbols, callback=callback)78    await client.start_async(on_open=on_open, on_error=on_error)79    result = results[0]80    assert result['stream'] == 'kline_1m'81@pytest.mark.asyncio82async def test_tickers(client, symbols):83    results = []84    def callback(msg):85        results.append(msg)86        client.close()87    def on_open():88        client.subscribe_ticker(symbols=symbols, callback=callback)89    await client.start_async(on_open=on_open, on_error=on_error)90    result = results[0]91    assert result['stream'] == 'ticker'92@pytest.mark.asyncio93async def test_all_tickers(client):94    results = []95    def callback(msg):96        results.append(msg)97        client.close()98    def on_open():99        client.subscribe_all_tickers(callback=callback)100    await client.start_async(on_open=on_open, on_error=on_error)101    result = results[0]102    assert result['stream'] == 'allTickers'103@pytest.mark.asyncio104async def test_mini_ticker(client, symbols):105    results = []106    def callback(msg):107        results.append(msg)108        client.close()109    def on_open():110        client.subscribe_mini_ticker(symbols=symbols, callback=callback)111    await client.start_async(on_open=on_open, on_error=on_error)112    result = results[0]113    assert result['stream'] == 'miniTicker'114@pytest.mark.asyncio115async def test_all_mini_ticker(client, symbols):116    results = []117    def callback(msg):118        results.append(msg)119        client.close()120    def on_open():121        client.subscribe_all_mini_tickers(callback=callback)122    await client.start_async(on_open=on_open, on_error=on_error)123    result = results[0]124    assert result['stream'] == 'allMiniTickers'125@pytest.mark.asyncio126async def test_blockheight(client):127    results = []128    def callback(msg):129        results.append(msg)130        client.close()131    def on_open():132        client.subscribe_blockheight(callback=callback)133    await client.start_async(on_open=on_open, on_error=on_error)134    result = results[0]135    assert 'stream' in result136@pytest.mark.asyncio137async def test_keepalive(client):138    def on_open():139        client.keepalive()140        client.close()141    await client.start_async(on_open=on_open, on_error=on_error)142@pytest.mark.asyncio143async def test_unsubscribe(client):144    results = []145    def callback(msg):146        results.append(msg)147        client.unsubscribe("blockheight")148        client.close()149    def on_open():150        client.subscribe_blockheight(callback=callback)151    await client.start_async(on_open=on_open, on_error=on_error)152    assert results153@pytest.mark.asyncio154async def test_decorator(client):155    @client.on('open')156    def callback():157        client.close()158    await client.start_async()159@pytest.mark.asyncio160async def test_decorator_async(client):161    @client.on('open')162    async def callback():163        client.close()164    await client.start_async()165@pytest.mark.asyncio166async def test_decorator_sub_queue(client):167    results = []168    @client.on("allTickers", symbols=["$all"])169    async def callback(msg):170        results.append(msg)171        client.close()172    await client.start_async()...

reid.py

Source:reid.py

...12            plt.imshow(img)13            plt.show()14            print("ffff")15            img = preprocess(img,size)16            infer_res = exec_net.start_async(request_id=0,inputs={input_layer:img})17            status=infer_res.wait()18            results = exec_net.requests[0].outputs[output_layer][0]19            for j,bbox1 in ids1.items():20                print("gggg")21                img1 = frame1[bbox1[1]:bbox1[3], bbox1[0]:bbox1[2]]22                #plt.imshow(img1)23                #plt.show()24                img1 = preprocess(img1,size)25                infer_res = exec_net.start_async(request_id=1,inputs={input_layer:img1})26                status=infer_res.wait()27                results1 = exec_net.requests[1].outputs[output_layer][0]28                print(results1.shape)29                x = torch.tensor(results).unsqueeze(0)30                y = torch.tensor(results1).unsqueeze(0)31                dis=torch.cosine_similarity(x, y)[0].numpy()32                if dis >= 0.5:33                    track_id[i]= bbox34                35def reidentification(ids,track_id,frame):36    img=frame37    track_id_copy = track_id.copy()38    for i,bbox in ids.items():39        if len(track_id) == 0:40            track_id[i] = bbox41        else:42            img = frame[bbox[1]:bbox[3], bbox[0]:bbox[2]]43            #plt.imshow(img)44            #plt.show()45            img = preprocess(img,size)46            infer_res = exec_net.start_async(request_id=0,inputs={input_layer:img})47            status=infer_res.wait()48            results = exec_net.requests[0].outputs[output_layer][0]49            dis = []50            for j,bbox_t in track_id_copy.items():51                img1 = frame[bbox_t[1]:bbox_t[3], bbox_t[0]:bbox_t[2]]52                img1 = preprocess(img1,size)53                infer_res = exec_net.start_async(request_id=1,inputs={input_layer:img1})54                status=infer_res.wait()55                results1 = exec_net.requests[1].outputs[output_layer][0]56                #print(results1.shape)57                x = torch.tensor(results).unsqueeze(0)58                y = torch.tensor(results1).unsqueeze(0)59                d=torch.cosine_similarity(x, y)[0].numpy()60                dis.append(d)61            try:62                f_idx = dis.index(max(dis))63                f = dis[f_idx]64                if f >= 0.7:65                    print("hhh")66                    track_id[f_idx] = bbox67                    i = f_idx68                else:69                    track_id[i] = bbox70                    i=i71            except Exception as e:72                print(e)73        cv2.putText(frame, str(i), bbox[:2], cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)74        cv2.rectangle(img=frame, pt1=bbox[:2], pt2=bbox[2:], color=(0,255,0), thickness=3)75    return track_id,frame76            77            78def emb(ids,frame):79    r= []80    b=[]81    for i,bbox in ids.items():82        img = frame[bbox[1]:bbox[3], bbox[0]:bbox[2]]83        img = preprocess(img,size)84        infer_res = exec_net.start_async(request_id=0,inputs={input_layer:img})85        status=infer_res.wait()86        results = exec_net.requests[0].outputs[output_layer][0]87        #print(type(results))88        r.append(results)89        b.append(bbox)90       91    return r,b92def ids_feature_(ids,frame):93    ids_feat={}94    for i,bbox in ids.items():95        img = frame[bbox[1]:bbox[3], bbox[0]:bbox[2]]96        img = preprocess(img,size)97        infer_res = exec_net.start_async(request_id=0,inputs={input_layer:img})98        status=infer_res.wait()99        results = exec_net.requests[0].outputs[output_layer][0]100        ids_feat[i]=results101    return ids_feat102def distance_(feature,feat1):103    x = torch.tensor(feature).unsqueeze(0)104    y = torch.tensor(feat1).unsqueeze(0)105    d=torch.cosine_similarity(x, y)[0].numpy()106    return d107def distance_list(feature,feat1):108    x = torch.tensor(feature[0]).unsqueeze(0)109    dis=[]110    for i in feat1:111        y = torch.tensor(i).unsqueeze(0)112        d=torch.cosine_similarity(x, y)[0].numpy()113        dis.append(d)114    115    return sum(dis)/len(dis)116def ids_feature_list(ids,frame):117    ids_feat={}118    for i,bbox in ids.items():119        img = frame[bbox[1]:bbox[3], bbox[0]:bbox[2]]120        img = preprocess(img,size)121        infer_res = exec_net.start_async(request_id=0,inputs={input_layer:img})122        status=infer_res.wait()123        results = exec_net.requests[0].outputs[output_layer][0]124        ids_feat[i]=[results]...

launcher_test.py

Source:launcher_test.py

...10    @mock.patch.object(launcher.update.status, 'get')11    def test_launches_update_when_no_update_is_running(self, mock_status_get,12                                                       mock_clear, mock_popen):13        mock_status_get.return_value = (update_status.Status.NOT_RUNNING, '')14        launcher.start_async()15        mock_clear.assert_called()16        mock_popen.assert_called_once_with(17            ('sudo', '/usr/sbin/service', 'tinypilot-updater', 'start'))18    @mock.patch.object(launcher.subprocess, 'Popen')19    @mock.patch.object(launcher.update.result_store, 'clear')20    @mock.patch.object(launcher.update.status, 'get')21    def test_launches_update_when_previous_update_succeeded(22            self, mock_status_get, mock_clear, mock_popen):23        mock_status_get.return_value = (update_status.Status.DONE, '')24        launcher.start_async()25        mock_clear.assert_called()26        mock_popen.assert_called_once_with(27            ('sudo', '/usr/sbin/service', 'tinypilot-updater', 'start'))28    @mock.patch.object(launcher.subprocess, 'Popen')29    @mock.patch.object(launcher.update.result_store, 'clear')30    @mock.patch.object(launcher.update.status, 'get')31    def test_launches_update_when_previous_update_failed(32            self, mock_status_get, mock_clear, mock_popen):33        mock_status_get.return_value = (update_status.Status.DONE,34                                        'dummy updater failure message')35        launcher.start_async()36        mock_clear.assert_called_once()37        mock_popen.assert_called_once_with(38            ('sudo', '/usr/sbin/service', 'tinypilot-updater', 'start'))39    @mock.patch.object(launcher.subprocess, 'Popen')40    @mock.patch.object(launcher.update.result_store, 'clear')41    @mock.patch.object(launcher.update.status, 'get')42    def test_does_not_launch_if_update_is_already_running(43            self, mock_status_get, mock_clear, mock_popen):44        mock_status_get.return_value = (update_status.Status.IN_PROGRESS, '')45        with self.assertRaises(launcher.AlreadyInProgressError):46            launcher.start_async()47        mock_clear.assert_not_called()...

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