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How to use batch_get_item method in localstack

Best Python code snippet using localstack_python

places.py

Source:places.py

...68            "Keys": [{"Place id ": place_id} for place_id in items]69        }70    }71    try:72        return dynamodb.batch_get_item(RequestItems=RequestItems)["Responses"]["places"]73    except Exception as e:74        return {'message': str(e)}75def add_likedPlace(data):76    place = data["place_id"]77    email = data["email"]78    response = app.get_app_db('users').query(79        KeyConditionExpression=Key('email').eq(data["email"])80    )81    likedPlaces = response.get('Items')[0]["likedPlaces"]82    likedPlaces.append(place)83    response = app.get_app_db('users').update_item(84        Key={85            'email': email,86        },87        UpdateExpression="set likedPlaces=:l",88        ExpressionAttributeValues={89            ':l': likedPlaces90        },91        ReturnValues="UPDATED_NEW"92    )93    return response["Attributes"]["likedPlaces"]94def get_list_likedPlaces(data):95    response = app.get_app_db('users').query(96        KeyConditionExpression=Key('email').eq(data["email"])97    )98    items = response.get('Items')[0]["likedPlaces"]99    RequestItems = {100        "places": {101            "Keys": [{"Place id ": place_id} for place_id in items]102        }103    }104    try:105        return dynamodb.batch_get_item(RequestItems=RequestItems)["Responses"]["places"]106    except Exception as e:107        return {'message': str(e)}108def me_placesAdded(data):109    place = data["place_id"]110    email = data["email"]111    response = app.get_app_db('users').query(112        KeyConditionExpression=Key('email').eq(data["email"])113    )114    placesAdded = response.get('Items')[0]["placesAdded"]115    placesAdded.append(place)116    response = app.get_app_db('users').update_item(117        Key={118            'email': email,119        },120        UpdateExpression="set placesAdded=:l",121        ExpressionAttributeValues={122            ':l': placesAdded123        },124        ReturnValues="UPDATED_NEW"125    )126    return response["Attributes"]["placesAdded"]127def get_me_placesAdded(data):128    response = app.get_app_db('users').query(129        KeyConditionExpression=Key('email').eq(data["email"])130    )131    items = response.get('Items')[0]["placesAdded"]132    RequestItems = {133        "places": {134            "Keys": [{"Place id ": place_id} for place_id in items]135        }136    }137    try:138        return dynamodb.batch_get_item(RequestItems=RequestItems)["Responses"]["places"]139    except Exception as e:140        return {'message': str(e)}141def add_placesVisited(data):142    place = data["place_id"]143    email = data["email"]144    response = app.get_app_db('users').query(145        KeyConditionExpression=Key('email').eq(data["email"])146    )147    visitedPlaces = response.get('Items')[0]["visitedPlaces"]148    visitedPlaces.append(place)149    response = app.get_app_db('users').update_item(150        Key={151            'email': email,152        },153        UpdateExpression="set visitedPlaces=:v",154        ExpressionAttributeValues={155            ':v': visitedPlaces156        },157        ReturnValues="UPDATED_NEW"158    )159    return response["Attributes"]["visitedPlaces"]160def get_list_placesVisited(data):161    response = app.get_app_db('users').query(162        KeyConditionExpression=Key('email').eq(data["email"])163    )164    items = response.get('Items')[0]["visitedPlaces"]165    RequestItems = {166        "places": {167            "Keys": [{"Place id ": place_id} for place_id in items]168        }169    }170    try:171        return dynamodb.batch_get_item(RequestItems=RequestItems)["Responses"]["places"]172    except Exception as e:...

dynamodb_getitem_batchgetitem_comparison.py

Source:dynamodb_getitem_batchgetitem_comparison.py

...16        'max_attempts': 317    }18)19#Execute batch_get_item dynamodb call    20def batch_get_item(FILE_TO_READ,REGION_CONFIG):21    df = pd.DataFrame(columns=['batch_get_item'])22    dynamodb_client = boto3.client('dynamodb', config=REGION_CONFIG) 23    for i in range(0, MAX_RANGE_VALUE):24        random_lines = random.choice(open(FILE_TO_READ).readlines())25        start_timer = time.perf_counter()26        response = dynamodb_client.batch_get_item(RequestItems={'workload':27            {'Keys': [{'uuid': {'S': random_lines.strip()}}]}})28        end_timer = time.perf_counter()29        #print("%s:-:%s" %(response['ResponseMetadata']['HTTPHeaders']['content-length'],response['Responses']['workload'][0]['uuid'])) #print the response size and uuid is in response to validate the response30        df = df.append({'batch_get_item': end_timer-start_timer}, ignore_index=True)31    return df32#Execute get_item dynamodb call   33def get_item(FILE_TO_READ,REGION_CONFIG):34    df = pd.DataFrame(columns=['get_item'])35    dynamodb = boto3.resource('dynamodb', config=REGION_CONFIG)36    table = dynamodb.Table('workload')37    for i in range(0, MAX_RANGE_VALUE):38        random_lines = random.choice(open(FILE_TO_READ).readlines())39        start_timer = time.perf_counter()40        response = table.get_item(Key={'uuid': random_lines.strip()})41        end_timer = time.perf_counter()42        #print("%s:-:%s" %(response['ResponseMetadata']['HTTPHeaders']['content-length'],response['Item']['uuid'])) #print the response size and uuid is in response to validate the response43        df = df.append({'get_item': end_timer-start_timer}, ignore_index=True)44    return df45def generate_stats_graph(RESULT_FILE):46    df = pd.read_csv(RESULT_FILE)47    48        49    fig, axes = plt.subplots(2, 2, figsize=(12, 10), sharey=False)50    51    #generate response time distribution52    kwargs = dict(element='step',shrink=.8, alpha=0.6, fill=True, legend=True) 53    ax = sns.histplot(ax=axes[0,0],data=df,**kwargs)54    #ax.set(xlim=(0.00,1.00)) #set the ylim boundary if auto option is not what you need55    ax.set_title('Response Time Distribution')56    ax.set_xlabel('Response Time (s)')57    ax.set_ylabel('Request Count')58    59    60    #Response Time Distribution using boxplot61    ax = sns.boxplot(ax=axes[0,1], data=df)62    #ax.legend(fontsize='medium')63    #ax.set(ylim=(0.0,1.0)) #set the ylim boundary if auto option is not what you need64    ax.set_title('Response Time Distribution')65    ax.set_xlabel('Operation Type')66    ax.set_ylabel('Response Time (s)')67    68    69    #generate percentile distribution       70    summary = np.round(df.describe(percentiles=[0, 0.1, 0.2,71                                                     0.3, 0.4, 0.5,72                                                     0.6, 0.7, 0.8,  73                                                     0.9, 0.95, 0.99, 1],include='all'),2) # show basic statistics as in row74    stats_summary = summary.copy()75    dropping = ['count', 'mean', 'std', 'min','max'] #remove metrics not needed for percentile graph76    77    for drop in dropping:78        summary = summary.drop(drop)79    ax = sns.lineplot(ax=axes[1,0],data=summary,dashes=False, legend=True)80    ax.legend(fontsize='medium')81    #ax.set(ylim=(0.0,1.0)) #set the ylim boundary if auto option is not what you need82    ax.set_title('Percentile Distribution')83    ax.set_xlabel('Percentile')84    ax.set_ylabel('Response Time (s)')85    86    87    #generate latency/response time basic statistics 88    axes[1, 1].axis("off")89    dropping = ['0%','100%']90    for drop in dropping:91        stats_summary = stats_summary.drop(drop)    92    table_result = axes[1, 1].table(cellText=stats_summary.values,93              rowLabels=stats_summary.index,94              colLabels=stats_summary.columns,95              cellLoc = 'right', rowLoc = 'center',96              loc='upper left')97    table_result.auto_set_font_size(False)98    table_result.set_fontsize(9)99    axes[1, 1].set_title('Response Time Statistics')100    fig.tight_layout(pad=1)101    102def main():103    FILE_TO_READ ='./Data/testdata.csv'  # Replace with your test data file104    RESULT_FILE ="./Data/result-getItem-batchGetItem.csv" #Replace where the result needs to be saved105    df_get = get_item(FILE_TO_READ,REGION_CONFIG)106    df_batch = batch_get_item(FILE_TO_READ,REGION_CONFIG)107    df_col_merged = pd.concat([df_get, df_batch], axis=1)108    #print(df_col_merged.describe(percentiles=[0.25,0.5,0.75,0.90,0.95],include='all'))109    df_col_merged.to_csv(RESULT_FILE,index=False)110    generate_stats_graph(RESULT_FILE)111    112if __name__ == "__main__":113    main()...

GetRecommendation.py

Source:GetRecommendation.py

...15    16def get_recomm(genid):17    ids = [genid]18    keys = [{'userId':  {'S':i}} for i in ids]19    list_of_movie = dynamodb.batch_get_item(RequestItems = {DYNAMODB_TABLE_NAME:{"Keys":keys}})['Responses'][DYNAMODB_TABLE_NAME][0]['movielist']20    list_of_movie = list_of_movie["L"]21    return list_of_movie22def get_moviename(listofid):23    # listofid = ["3635","228"]24    keys = [{"MovieId":  {'S':i}} for i in listofid]25    return dynamodb.batch_get_item(RequestItems = {"MovieRev":{"Keys":keys}})['Responses']["MovieRev"]26    27def datacleaning(response):28    movieid = []29    rank = []30    moviename = []31    for i in range(len(response)):32        movieid.append(response[i]["L"][0]["S"])33        rank.append(response[i]["L"][1]["S"])34    response = get_moviename(movieid)35    for i in range(len(response)):36        moviename.append(response[i]['title']['S'])...

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