Falkonry C# Client to access Falkonry Condition Prediction APIs
* Create Datastream for narrow/historian style data from a single entity
* Create Batch Datastream for narrow/historian style data from a single entity
* Create Datastream for narrow/historian style data from a multiple entities
* Create Datastream for wide style data from a single entity
* Create Datastream for wide style data from a multiple entities
* Create Datastream with microseconds precision
* Retrieve Datastreams
* Retrieve Datastream by id
* Delete Datastream by id
* Add EntityMeta to a Datastream
* Get EntityMeta of a Datastream
* Create Assessment
* Retrieve Assessments
* Retrieve Assessment by Id
* Delete Assessment
* Get Condition List Of Assessment
* Add historical narrow input data (json format) to multi entity Datastream (Used for model revision)
* Add historical narrow input data (csv format) single entity to Datastream (Used for model revision)
* Add historical wide input data (json format) to single entity Datastream (Used for model revision)
* Add historical wide input data (csv format) to multi entity Datastream (Used for model revision)
* Add historical narrow input data (json format) to single entity Batch Datastream (Used for model revision)
* Add historical narrow input data (csv format) multi entity to Batch Datastream (Used for model revision)
* Add historical wide input data (json format) to multi entity Batch Datastream (Used for model revision)
* Add historical wide input data (csv format) to single entity Batch Datastream (Used for model revision)
* Add live input data (json format) to Datastream (Used for live monitoring)
* Add live input data (csv format) to Datastream (Used for live monitoring)
* Add live input data (json format) from a stream to Datastream (Used for live monitoring)
* Add live input data (csv format) from a stream to Datastream (Used for live monitoring)
* Add facts data (json format) to Assessment of single entity datastream
* Add facts data (json format) to Assessment of single entity Batch datastream
* Add facts data (json format) with addition tag to Assessment of multi entity datastream
* Add facts data (csv format) to Assessment of single entity datastream
* Add facts data (csv format) with tags Assessment of single entity datastream
* Add facts data (json format) from a stream to Assessment of multi entity datastream
* Add facts data (csv format) from a stream to Assessment of multi entity datastream
* Get facts data
* Get Datastream Input data
* Get Historian Output from Assessment
* Get Streaming Output
* Datastream On (Start live monitoring of datastream)
* Datastream Off (Stop live monitoring of datastream)
* Get auth token from the Falkonry Service UI.
* Read below examples for integration with various data formats.
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
var Field = new Field();
var Signal = new Signal();
Signal.ValueIdentifier = "value";
Signal.TagIdentifier = "tag";
Signal.IsSignalPrefix = true;
Field.Signal = Signal;
Field.Time = time;
ds.Field = Field;
ds.DataSource = datasource;
var rnd = new System.Random();
var randomNumber = System.Convert.ToString(rnd.Next(1, 10000));
ds.Name = "TestDS" + randomNumber;
ds.Field.Time = time;
ds.DataSource = datasource;
var datastream = _falkonry.CreateDatastream(ds);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
var Field = new Field();
var Signal = new Signal();
Signal.ValueIdentifier = "value";
Field.BatchIdentifier = "Batch";
Field.Signal = Signal;
Field.Time = time;
ds.Field = Field;
ds.DataSource = datasource;
var rnd = new System.Random();
var randomNumber = System.Convert.ToString(rnd.Next(1, 10000));
ds.Name = "TestDS" + randomNumber;
ds.Field.Time = time;
ds.DataSource = datasource;
var datastream = _falkonry.CreateDatastream(ds);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
var Field = new Field();
var Signal = new Signal();
Signal.ValueIdentifier = "value";
Signal.TagIdentifier = "tag";
Signal.IsSignalPrefix = true;
Signal.Delimiter = "_";
Field.Signal = Signal;
Field.Time = time;
ds.Field = Field;
ds.DataSource = datasource;
var rnd = new System.Random();
var randomNumber = System.Convert.ToString(rnd.Next(1, 10000));
ds.Name = "TestDS" + randomNumber;
ds.Field.Time = time;
ds.DataSource = datasource;
var datastream = _falkonry.CreateDatastream(ds);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
var Field = new Field();
var Signal = new Signal();
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
// Input List
var inputList = new List<Input>();
var currents = new Input();
currents.Name = "current";
currents.ValueType = new ValueType();
currents.EventType = new EventType();
currents.ValueType.Type = "Numeric";
currents.EventType.Type = "Samples";
inputList.Add(currents);
var vibration = new Input();
vibration.Name = "vibration";
vibration.ValueType = new ValueType();
vibration.EventType = new EventType();
vibration.ValueType.Type = "Numeric";
vibration.EventType.Type = "Samples";
inputList.Add(vibration);
var state = new Input();
state.Name = "state";
state.ValueType = new ValueType();
state.EventType = new EventType();
state.ValueType.Type = "Categorical";
state.EventType.Type = "Samples";
inputList.Add(state);
ds.InputList = inputList;
var Field = new Field();
var Signal = new Signal();
Field.Signal = Signal;
Field.Time = time;
ds.Field = Field;
ds.DataSource = datasource;
var rnd = new System.Random();
var randomNumber = System.Convert.ToString(rnd.Next(1, 10000));
ds.Name = "TestDS" + randomNumber;
ds.Field.Time = time;
ds.DataSource = datasource;
var datastream = _falkonry.CreateDatastream(ds);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
var Field = new Field();
var Signal = new Signal();
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
// Input List
var inputList = new List<Input>();
var currents = new Input();
currents.Name = "current";
currents.ValueType = new ValueType();
currents.EventType = new EventType();
currents.ValueType.Type = "Numeric";
currents.EventType.Type = "Samples";
inputList.Add(currents);
var vibration = new Input();
vibration.Name = "vibration";
vibration.ValueType = new ValueType();
vibration.EventType = new EventType();
vibration.ValueType.Type = "Numeric";
vibration.EventType.Type = "Samples";
inputList.Add(vibration);
var state = new Input();
state.Name = "state";
state.ValueType = new ValueType();
state.EventType = new EventType();
state.ValueType.Type = "Categorical";
state.EventType.Type = "Samples";
inputList.Add(state);
ds.InputList = inputList;
var Field = new Field();
Field.EntityIdentifier = "Unit";
var Signal = new Signal();
Field.Signal = Signal;
Field.Time = time;
ds.Field = Field;
ds.DataSource = datasource;
var rnd = new System.Random();
var randomNumber = System.Convert.ToString(rnd.Next(1, 10000));
ds.Name = "TestDS" + randomNumber;
ds.Field.Time = time;
ds.DataSource = datasource;
var datastream = _falkonry.CreateDatastream(ds);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var time = new Time();
time.Zone = "GMT";
time.Identifier = "time";
time.Format = "iso_8601";
var datasource = new Datasource();
datasource.Type = "PI";
var ds = new DatastreamRequest();
var Field = new Field();
var Signal = new Signal();
Signal.ValueIdentifier = "value";
Signal.TagIdentifier = "tag";
Signal.IsSignalPrefix = true;
Field.Signal = Signal;
Field.Time = time;
ds.Field = Field;
ds.DataSource = datasource;
var rnd = new System.Random();
var randomNumber = System.Convert.ToString(rnd.Next(1, 10000));
ds.Name = "TestDS" + randomNumber;
ds.TimePrecision = "micro"; # this is use to store your data in different date time format. If input data precision is in micorseconds then set "micro" else "millis". If not sent then it will be "millis"
ds.Field.Time = time;
ds.DataSource = datasource;
var datastream = _falkonry.CreateDatastream(ds);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
List<Datastream> datastreams = _falkonry.GetDatastreams();
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
Datastream datastream = _falkonry.GetDatastream('datastreamId')
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
_falkonry.DeleteDatastream('datastreamId')
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
// Create Datastream
datastream = falkonry.getDatastream(datastream.id);
// Create EntityMetaRequest
List<EntityMetaRequest> entityMetaRequestList = new List<EntityMetaRequest>();
EntityMetaRequest entityMetaRequest1 = new EntityMetaRequest();
entityMetaRequest1.label = "User readable label";
entityMetaRequest1.sourceId = "1234-21342134";
entityMetaRequest1.path = "//root/branch1/";
EntityMetaRequest entityMetaRequest2 = new EntityMetaRequest();
entityMetaRequest2.label = "User readable label2";
entityMetaRequest2.sourceId = "1234-213421rawef";
entityMetaRequest2.path = "//root/branch2/";
entityMetaRequestList.Add(entityMetaRequest1);
entityMetaRequestList.Add(entityMetaRequest2);
List<EntityMeta> entityMetaResponseList = falkonry.postEntityMeta(entityMetaRequestList, datastream);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
// Get entitymeta
entityMetaResponseList = falkonry.getEntityMeta('datastream-id');
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
AssessmentRequest asmt = new AssessmentRequest();
asmt.name = "assessment name here";
asmt.datastream= "datastream id";
Assessment assessment = falkonry.createAssessment(asmt);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
List<Assessment> assessmentList = falkonry.getAssessments();
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
Assessment assessment = falkonry.getAssessment('assessment-id');
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
falkonry.DeleteAssessment('assessment-id');
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTimeIdentifier", "time");
options.Add("endTimeIdentifier", "end");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("entityIdentifier", "entities");
options.Add("valueIdentifier", "Health");
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
Assessment assessment = falkonry.getAssessment('assessment-id');
String data = "{\"time\" : \"2011-03-26T12:00:00Z\", \"entities\" : \"entity1\", \"end\" : \"2012-06-01T00:00:00Z\", \"Health\" : \"Normal\"}";
string response = falkonry.addFacts('assessment-id',data, options);
// aprioriConditionList
String [] conditionList = assessment.AprioriConditionList
// Condition Listshould contain "Normal" as label
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "{\"time\" :\"2016-03-01 01:01:01\", \"signal\":\"current\",\"value\" : 12.4,\"car\" : \"car1\"}";
var options = new SortedDictionary<string, string>();
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("timeIdentifier", "time");
options.Add("timeZone", "GMT");
options.Add("timeFormat", "YYYY-MM-DD HH:mm:ss");
options.Add("signalIdentifier", "signal");
options.Add("valueIdentifier", "value");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "time,signal,value\n" + "2016-05-05 12:00:00,current,12.4\n2016-03-01 01:01:01,vibration,20.4";
var options = new SortedDictionary<string, string>();
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "{\"time\" :\"2016-03-01 01:01:01\", \"current\" : 12.4, \"vibration\" : 3.4, \"state\" : \"On\"}";
var options = new SortedDictionary<string, string>();
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "time,Unit,current,vibration,state\n 2016-05-05T12:00:00.000Z,Unit1,12.4,3.4,On";
var options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("entityIdentifier", "Unit");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
Add historical narrow input data (json format) to single entity Batch Datastream (Used for model revision)
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "{\"time\" :\"2016-03-01 01:01:01\", \"signal\":\"current\",\"value\" : 12.4,\"batch\" : \"batch1\"}";
var options = new SortedDictionary<string, string>();
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("timeIdentifier", "time");
options.Add("timeZone", "GMT");
options.Add("timeFormat", "YYYY-MM-DD HH:mm:ss");
options.Add("signalIdentifier", "signal");
options.Add("valueIdentifier", "value");
options.Add("batchIdentifier", "batch");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
Add historical narrow input data (csv format) multi entity to Batch Datastream (Used for model revision)
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "time,signal,value,Unit,Batch\n" + "2016-05-05 12:00:00,current,12.4,uni1,batch1\n2016-03-01 01:01:01,vibration,20.4,unit2,batch2";
var options = new SortedDictionary<string, string>();
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("timeIdentifier", "time");
options.Add("timeZone", "GMT");
options.Add("timeFormat", "YYYY-MM-DD HH:mm:ss");
options.Add("signalIdentifier", "signal");
options.Add("valueIdentifier", "value");
options.Add("entityIdentifier", "Unit");
options.Add("batchIdentifier", "Batch");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "{\"time\" :\"2016-03-01 01:01:01\", \"current\" : 12.4, \"vibration\" : 3.4, \"state\" : \"On\", \"car\" : \"car1\", \"batch\" : \"batch1\"}";
var options = new SortedDictionary<string, string>();
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("timeIdentifier", "time");
options.Add("timeZone", "GMT");
options.Add("timeFormat", "YYYY-MM-DD HH:mm:ss");
options.Add("entityIdentifier", "car");
options.Add("batchIdentifier", "batch");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
Add historical wide input data (csv format) to single entity Batch Datastream (Used for model revision)
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
var data = "time,Batch,current,vibration,state\n 2016-05-05T12:00:00.000Z,batch1,12.4,3.4,On";
var options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("batchIdentifier", "Batch");
var inputstatus = _falkonry.AddInput(datastream.Id, data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
/*This particular example will read data from a AddData.json file in debug folder in bin*/
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "iso_8601");
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("fileFormat", "json");
string folder_path = Path.GetDirectoryName(System.Reflection.Assembly.GetExecutingAssembly().Location);
string path = folder_path + "/AddData.json";
//Alternatively, you can directly specify the folder path in the "folder_path" variable
byte[] bytes = System.IO.File.ReadAllBytes(path);
InputStatus inputstatus = falkonry.addInputStream('datastream-id', bytes, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
/*This particular example will read data from a AddData.json file in debug folder in bin*/
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "iso_8601");
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("fileFormat", "csv");
string folder_path = Path.GetDirectoryName(System.Reflection.Assembly.GetExecutingAssembly().Location);
string path = folder_path + "/AddData.csv";
//Alternatively, you can directly specify the folder path in the "folder_path" variable
byte[] bytes = System.IO.File.ReadAllBytes(path);
InputStatus inputstatus = falkonry.addInputStream('datastream-id', bytes, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string data = "{\"time\" :\"2016-03-01 01:01:01\", \"current\" : 12.4, \"vibration\" : 3.4, \"state\" : \"On\"}";
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "YYYY-MM-DD HH:mm:ss");
options.Add("fileFormat", "json");
options.Add("streaming", "true");
options.Add("hasMoreData", "false");
InputStatus inputstatus = falkonry.addInput('datastream-id', data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string data = "time, entities, signal1, signal2, signal3, signal4" + "\n"
+ "1467729675422, entity1, 41.11, 62.34, 77.63, 4.8" + "\n"
+ "1467729675445, entity1, 43.91, 82.64, 73.63, 3.8";
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "millis");
options.Add("fileFormat", "csv");
options.Add("streaming", "true");
options.Add("hasMoreData", "false");
InputStatus inputstatus = falkonry.addInput('datastream-id', data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
/*This particular example will read data from a AddData.json file in debug folder in bin*/
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "iso_8601");
options.Add("streaming", "true");
options.Add("hasMoreData", "false");
options.Add("fileFormat", "json");
string folder_path = Path.GetDirectoryName(System.Reflection.Assembly.GetExecutingAssembly().Location);
string path = folder_path + "/AddData.json";
//Alternatively, you can directly specify the folder path in the "folder_path" variable
byte[] bytes = System.IO.File.ReadAllBytes(path);
InputStatus inputstatus = falkonry.addInputStream('datastream-id', bytes, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
/*This particular example will read data from a AddData.json file in debug folder in bin*/
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("timeIdentifier", "time");
options.Add("timeFormat", "iso_8601");
options.Add("streaming", "false");
options.Add("hasMoreData", "false");
options.Add("fileFormat", "csv");
string folder_path = Path.GetDirectoryName(System.Reflection.Assembly.GetExecutingAssembly().Location);
string path = folder_path + "/AddData.csv";
//Alternatively, you can directly specify the folder path in the "folder_path" variable
byte[] bytes = System.IO.File.ReadAllBytes(path);
InputStatus inputstatus = falkonry.addInputStream('datastream-id', bytes, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTimeIdentifier", "time");
options.Add("endTimeIdentifier", "end");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("valueIdentifier", "Health");
string token = "Add your token here";
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
String data = "{\"time\" : \"2011-03-26T12:00:00Z\", \"end\" : \"2012-06-01T00:00:00Z\", \"Health\" : \"Normal\"}";
string response = falkonry.addFacts('assessment-id',data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
string token = "Add your token here";
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
String data = "{\"Health\" : \"Normal\", \"Batch\" : \"batch1\"}";
options.Add("valueIdentifier", "Health");
options.Add("batchIdentifier", "Batch");
string response = falkonry.addFacts('assessment-id',data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTimeIdentifier", "time");
options.Add("endTimeIdentifier", "end");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("entityIdentifier", "entities");
options.Add("valueIdentifier", "Health");
options.Add("additionalTag", "testTag");
string token = "Add your token here";
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
String data = "{\"time\" : \"2011-03-26T12:00:00Z\", \"entities\" : \"entity1\", \"end\" : \"2012-06-01T00:00:00Z\", \"Health\" : \"Normal\"}";
string response = falkonry.addFacts('assessment-id',data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTimeIdentifier", "time");
options.Add("endTimeIdentifier", "end");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("valueIdentifier", "Health");
string token = "Add your token here";
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string data = "time,end,Health\n2011-03-31T00:00:00Z,2011-04-01T00:00:00Z,Normal\n2011-03-31T00:00:00Z,2011-04-01T00:00:00Z,Normal";
string response = falkonry.addFacts('assessment-id',data, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTimeIdentifier", "time");
options.Add("endTimeIdentifier", "end");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("entityIdentifier", "car");
options.Add("valueIdentifier", "Health");
options.Add("tagIdentifier", "tag");
string token = "Add your token here";
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string data = "time,end,car,Health,Tag\n2011-03-31T00:00:00Z,2011-04-01T00:00:00Z,IL9753,Normal\n2011-03-31T00:00:00Z,2011-04-01T00:00:00Z,HI3821,Normal,testTag1";
string response = falkonry.addFacts('assessment-id',data, options);
Sample JSONFile:
{"time" : "2011-03-26T12:00:00.000Z", "car" : "HI3821", "end" : "2012-06-01T00:00:00.000Z", "Health" : "Normal"}
{"time" : "2014-02-10T23:00:00.000Z", "car" : "HI3821", "end" : "2014-03-20T12:00:00.000Z", "Health" : "Spalling"}
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTimeIdentifier", "time");
options.Add("endTimeIdentifier", "end");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("entityIdentifier", "car");
options.Add("valueIdentifier", "Health");
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string path = "Insert the path to your file here";
byte[] bytes = System.IO.File.ReadAllBytes(path);
string response = falkonry.AddFactsStream('assessment-id',bytes, options);
#### Add facts data (csv format) from a stream to Assessment of multi entity datastream
Sample CSVFile time,car,end,Health 2011-03-26T12:00:00Z,HI3821,2012-06-01T00:00:00Z,Normal 2014-02-10T23:00:00Z,HI3821,2014-03-20T12:00:00Z,Spalling
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTimeIdentifier", "time");
options.Add("endTimeIdentifier", "end");
options.Add("timeFormat", "iso_8601");
options.Add("timeZone", "GMT");
options.Add("entityIdentifier", "car");
options.Add("valueIdentifier", "Health");
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string path = "Insert the path to your file here";
byte[] bytes = System.IO.File.ReadAllBytes(path);
string response = falkonry.AddFactsStream('assessment-id',bytes, options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string assessment = "id of the assessment here";
string response = falkonry.getFacts('assessment',options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string datastream = "id of the datastream here";
string response = falkonry.GetDatastreamData('datastream',options);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
// Create Datastream
// create Assessment
// Add Data To dataStream
// From Falkonry UI, run a model revision.
// Fetch Historical output data for given assessment, startTime , endtime
SortedDictionary<string, string> options = new SortedDictionary<string, string>();
options.Add("startTime", "2011-01-01T01:00:00.000Z"); // in the format YYYY-MM-DDTHH:mm:ss.SSSZ
options.Add("endTime", "2011-06-01T01:00:00.000Z"); // in the format YYYY-MM-DDTHH:mm:ss.SSSZ
options.Add("responseFormat", "application/json"); // also available options 1. text/csv 2. application/json
HttpResponse httpResponse = falkonry.getHistoricalOutput(assessment, options);
// If data is not readily available then, a tracker id will be sent with 202 status code. While falkonry will genrate ouptut data
// Client should do timely pooling on the using same method, sending tracker id (__id) in the query params
// Once data is available server will response with 200 status code and data in json/csv format.
if (httpResponse.statusCode == 202)
{
Tracker trackerResponse = javascript.Deserialize<Tracker>(httpResponse.response);
// get id from the tracker
string __id = trackerResponse.__id;
// use this tracker for checking the status of the process.
options = new SortedDictionary<string, string>();
options.Add("tarckerId", __id);
options.Add("responseFormat", "application/json");
httpResponse = falkonry.getHistoricalOutput(assessment, options);
// if status is 202 call the same request again
// if statsu is 200, output data will be present in httpResponse.response field
}
if (httpResponse.statusCode > 400)
{
// Some Error has occured. Please httpResponse.response for detail message
}
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string assessment_id ="assessment ID here";
//On successfull live streaming output EventSource_Message will be triggered
private void EventSource_Message(object sender, EventSource.ServerSentEventArgs e)
{
try { var falkonryEvent = JsonConvert.DeserializeObject<FalkonryEvent>(e.Data); }
catch(System.Exception exception)
{ //log error in case of error parsing the output event }
}
//On any error while getting live streaming output, EventSource_Error will be triggered
private void EventSource_Error(object sender, EventSource.ServerSentErrorEventArgs e)
{ // Error handling }
EventSource eventSource = falkonry.GetOutput(assessment,null,null);
eventSource.Message += EventSource_Message;
eventSource.Error += EventSource_Error;
// NOTE: To stop listening to output
eventSource.Dispose();
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string datastream_id = "Your datastream id";
falkonry.onDatastream(datastream_id);
using falkonry_csharp_client;
using falkonry_csharp_client.helper.models;
string token="Add your token here";
Falkonry falkonry = new Falkonry("http://localhost:8080", token);
string datastream_id = "Your datastream id";
falkonry.offDatastream(datastream_id);
[Falkonry APIs](https://service.falkonry.io/api)
Available under MIT License