public class Types extends Object
The class that defines the constants that are used to identify generic SQL types, called JDBC types.
This class is never instantiated.
| Modifier and Type | Field and Description |
|---|---|
static int |
ARRAY
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
ARRAY . |
static int |
BIGINT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
BIGINT . |
static int |
BINARY
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
BINARY . |
static int |
BIT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
BIT . |
static int |
BLOB
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
BLOB . |
static int |
BOOLEAN
The constant in the Java programming language, somtimes referred to
as a type code, that identifies the generic SQL type
BOOLEAN . |
static int |
CHAR
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
CHAR . |
static int |
CLOB
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
CLOB . |
static int |
DATALINK
The constant in the Java programming language, somtimes referred to
as a type code, that identifies the generic SQL type
DATALINK . |
static int |
DATE
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
DATE . |
static int |
DECIMAL
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
DECIMAL . |
static int |
DISTINCT
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
DISTINCT . |
static int |
DOUBLE
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
DOUBLE . |
static int |
FLOAT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
FLOAT . |
static int |
INTEGER
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
INTEGER . |
static int |
JAVA_OBJECT
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
JAVA_OBJECT . |
static int |
LONGNVARCHAR
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
LONGNVARCHAR . |
static int |
LONGVARBINARY
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
LONGVARBINARY . |
static int |
LONGVARCHAR
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
LONGVARCHAR . |
static int |
NCHAR
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
NCHAR |
static int |
NCLOB
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
NCLOB . |
static int |
NULL
The constant in the Java programming language
that identifies the generic SQL value
NULL . |
static int |
NUMERIC
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
NUMERIC . |
static int |
NVARCHAR
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
NVARCHAR . |
static int |
OTHER
The constant in the Java programming language that indicates
that the SQL type is database-specific and
gets mapped to a Java object that can be accessed via
the methods
getObject and setObject . |
static int |
REAL
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
REAL . |
static int |
REF
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
REF . |
static int |
REF_CURSOR
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
REF CURSOR . |
static int |
ROWID
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
ROWID |
static int |
SMALLINT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
SMALLINT . |
static int |
SQLXML
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
XML . |
static int |
STRUCT
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
STRUCT . |
static int |
TIME
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
TIME . |
static int |
TIME_WITH_TIMEZONE
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
TIME WITH TIMEZONE . |
static int |
TIMESTAMP
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
TIMESTAMP . |
static int |
TIMESTAMP_WITH_TIMEZONE
The constant in the Java programming language, sometimes referred to
as a type code, that identifies the generic SQL type
TIMESTAMP WITH TIMEZONE . |
static int |
TINYINT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
TINYINT . |
static int |
VARBINARY
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
VARBINARY . |
static int |
VARCHAR
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
VARCHAR . |
public static final int BIT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
BIT
.
public static final int TINYINT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
TINYINT
.
public static final int SMALLINT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
SMALLINT
.
public static final int INTEGER
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
INTEGER
.
public static final int BIGINT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
BIGINT
.
public static final int FLOAT
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
FLOAT
.
public static final int REAL
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
REAL
.
public static final int DOUBLE
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
DOUBLE
.
public static final int NUMERIC
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
NUMERIC
.
public static final int DECIMAL
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
DECIMAL
.
public static final int CHAR
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
CHAR
.
public static final int VARCHAR
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
VARCHAR
.
public static final int LONGVARCHAR
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
LONGVARCHAR
.
public static final int DATE
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
DATE
.
public static final int TIME
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
TIME
.
public static final int TIMESTAMP
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
TIMESTAMP
.
public static final int BINARY
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
BINARY
.
public static final int VARBINARY
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
VARBINARY
.
public static final int LONGVARBINARY
The constant in the Java programming language, sometimes referred
to as a type code, that identifies the generic SQL type
LONGVARBINARY
.
public static final int NULL
The constant in the Java programming language
that identifies the generic SQL value
NULL
.
public static final int OTHER
getObject
and setObject
.public static final int JAVA_OBJECT
JAVA_OBJECT
.public static final int DISTINCT
DISTINCT
.public static final int STRUCT
STRUCT
.public static final int ARRAY
ARRAY
.public static final int BLOB
BLOB
.public static final int CLOB
CLOB
.public static final int REF
REF
.public static final int DATALINK
DATALINK
.public static final int BOOLEAN
BOOLEAN
.public static final int ROWID
ROWID
public static final int NCHAR
NCHAR
public static final int NVARCHAR
NVARCHAR
.public static final int LONGNVARCHAR
LONGNVARCHAR
.public static final int NCLOB
NCLOB
.public static final int SQLXML
XML
.public static final int REF_CURSOR
REF CURSOR
.public static final int TIME_WITH_TIMEZONE
TIME WITH TIMEZONE
.public static final int TIMESTAMP_WITH_TIMEZONE
TIMESTAMP WITH TIMEZONE
.Dracula Javadoc Sample, Made with Allan Im.


| Apps Components Interfaces All Files Source Tree | source: beta.CC2420Radio.ieee.802.15.4.MLME.MLME_RESET.nc |
The MLME-SAP reset primitives specify how to reset the MAC sublayer to its default values.
| Author: | Joe Polastre |
Commands |
Events |
Commands - Details |
Parameters: |
SetDefaultPIB - If TRUE, the MAC sublayer is reset and all MAC PIB attributes are set to their default values. If FALSE, the MAC sublayer is reset but all MAC PIB attributes retain their values prior to the generation of the reset primitive. |


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 We don't either! We will only send you an email once a month.
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Get in Touch
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Get Directions
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{% extends 'base.html' %} {% block general_content %}
An error occurred while loading the requested page.


Bug 1720432 R[Core:Audio/Video]Fix -Wunused-but-set-variable warnings in dom/media
Bug 1722232 R[Core:Graphics]Revert the local cairo fix from bug 1717685 and take the version that was merged upstream in preference
Bug 1720986 R[Core:Graphics: WebRender]Firefox 90 breaks display of SVG objects
Bug 1717873 R[Core:Layout]Thread indentation lines sometimes invisible when printing if using "High Contrast Black" color scheme in Windows 10
Bug 1716736 N[Firefox:Nimbus Desktop Client]Add schema validation for experiment enrollments in tests
Bug 1704404 R[Firefox:Tabbed Browser]Excessive tab height when displaying page titles including Unicode math symbols
Bug 1693385 R[WebExtensions:General]support manifest.host_permissions
###########
Changes to 7 bugs - 6 fixed.


{% extends "layout.html" %} {% block body %}
Welcome to Chocobros! This site contains a simple search bar for FFTCG cards but there should be more to come in the future so stay tuned!
If you'd like to contribute to this site at all, you can do so at https://github.com/insacuri/chocobros


The DB2 function for finding the maximum value from a set of values is called MAX. However, MAX can also be used to find the maximum value for a set of rows as well.


{% load static %} {% include 'header.html' %}
You can search any job in which you are interested
You can check the history of jobs which you have applied
You can study and learn here according to your needs
You can apply here for job notifications in which field you want
You can create your profile and edit it as per your qualification.....
You can check your profile here which is going to visible to companies.


Where do we go from here?
Where do we go from here?
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Where do we go from here?
there was only one choice


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Books are indeed your best friends for life. Reading is an essential habit that must be cultivated in children right from an early age. It is a fun activity that not only gives pleasure but increases your knowledge.  Moreover, there are india books store that help you find books available to suit the taste and preferences of each and every individual
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eqilbrcom
Equilibrates an nXn complex matrix A by determining a real diagonal matrix D whose diagonal elements are integers powers of two, and a permutation matrix P ,
for details see book of Hang T. Lau, “A Java Numerical Library for Scientists and engineers|”, Chapman & Hall, 2004
Example: Can be run with F9 within the ScalaLab Editor
import numal.*;
public class Test_eqilbrcom extends Object {
public static void main(String args[]) {
int inter[] = new int[4];
double em[] = new double[8];
double d[] = new double[4];
double a1[][] = new double[4][4];
double a2[][] = new double[4][4];
em[0]=5.0e-7;
em[6]=10.0;
Basic.inimat(1,3,1,3,a1,0.0);
Basic.inimat(1,3,1,3,a2,0.0);
a1[1][1]=a1[2][2]=1.0;
a1[3][3]=2.0;
a2[1][3]=Math.pow(2.0,10.0);
a2[3][1]=Math.pow(2.0,-10.0);
Linear_algebra.eqilbrcom(a1,a2,3,em,d,inter);
System.out.println("Equilibrated matrix:\n " +
a1[1][1] + " " + a1[1][2] + " " + a1[1][3] +
"\n " + a1[2][1] + " " + a1[2][2] + " I" +
"\n " + a1[3][1] + " I " + a1[3][3] +
"\n\nEM[7]: " + (int)em[7] +
"\nD[1:3]: " + d[1] + " " + d[2] + " " + d[3] +
"\nINTER[1:3]: " + inter[1] + " " +
inter[2] + " " + inter[3]);
}
}


This is foo!
R project web site
First name: Last name:
Male Female Other
Volvo Saab Fiat Audi
Volvo Saab Mercedes Audi
I have a bike I have a car
The cat was playing in the garden.
ME! ME! ME!


OC Dashboards developed by ORM-OPSD. Developed on Tableau Software.
These dashboards use the data from the following systems
- PMP System (core project data)
- SAP-CML (for disbursement data)
- OFIS (for legacy data)
The support extended by the GBEST Program by the provision of software is also acknowledged.


Click here for general AllegroGraph documentation.
This is a description of the Python Application Programmer's Interface (API) to Franz Inc.'s AllegroGraph RDFStore™
The Python API offers convenient and efficient access to an AllegroGraph server from a Python-based application. This API provides methods for creating, querying and maintaining RDF data, and for managing the stored triples.
| The Python API deliberately emulates the Aduna Sesame API to make it easier to migrate from Sesame to AllegroGraph. The Python API has also been extended in ways that make it easier and more intuitive than the Sesame API. |
The AllegroGraphServer object represents a remote AllegroGraph server on the network. It is used to inventory and access the catalogs of that server.
Source: /AllegroGraphDirectory/src/franz/openrdf/sail/allegrographserver.py.
AllegroGraphServer(self, host, port=10035,user=None,password=None)
server = AllegroGraphServer(host="localhost", port=8080, user="test", password="pw")
| getInitfile(self) | Retrieve the contents of the server initialization file. |
| listCatalogs(self) | Returns a string containing the names of the server's catalogs. |
| openCatalog(self, name=None) | Returns a Catalog object. Name is one of the catalog names from listCatalogs() or "None" to open the rootCatalog described in the AllegroGraph configuration file. |
| openFederated(self, repositories, autocommit=False, lifetime=None, loadinitfile=False) | Open a session that federates several repositories. The repositories argument should be an array containing store designators, which can be Repository or RepositoryConnection objects, strings (naming a store in the root catalog, or the URL of a store), or (storename, catalogname) tuples. |
| openSession(self,spec, autocommit=False, lifetime=None, loadinitfile=False) | Open a session on a federated, reasoning, or filtered store. Use the helper functions in the franz.openrdf.sail.spec module to create the spec string. |
| setInitfile(self, content=None, restart=True) | Replace the current initialization file contents with the content string or remove if None. Restart specifies whether to shut down any current running back ends, so that subsequent requests will be handled by back ends that have loaded the new init file. |
| url(self) | Return the server's URL. |
| version(self) | Return the server's version as a string. |
A Catalog object is a container for multiple repositories.
Source: /AllegroGraphDirectory/src/franz/openrdf/sail/allegrographserver.py.
Invoke the Catalog constructor using the AllegroGraphServer.openCatalog() method.
catalog = server.openCatalog('scratch')
| createRepository(self, name) | Creates a new Repository within the Catalog. name is a string identifying the repository. |
| deleteRepository(self, name) | Deletes the named Respository from the Catalog. |
| getName(self) | Returns a string containing the name of this Catalog. |
| getRepository(self, name, access_verb) | Returns a Repository object. name is a repository name from listRepositories(). access_verb is one of the following:
|
| listRepositories(self) | Returns a list of repository names (triple stores) managed by this Catalog. |
A repository contains RDF data that can be queried and updated. Access to the repository can be acquired by opening a connection to it. This connection can then be used to query and/or update the contents of the repository. Depending on the implementation of the repository, it may or may not support multiple concurrent connections.
Please note that a repository needs to be initialized before it can be used and that it should be shut down before it is discarded/garbage collected. Forgetting the latter can result in loss of data (depending on the Repository implementation)!
Source: /AllegroGraphDirectory/src/franz/openrdf/repository/repository.py.
Invoke the Repository constructor using the AllegroGraphServer.getRepository() method.
myRepository = catalog.getRepository("agraph_test", Repository.ACCESS)
| getConnection(self) | Creates a RepositoryConnection object that can be used for querying and |
| getDatabaseName(self) | Returns a string containing the name of this Repository. |
| getSpec(self) | Returns a string consisting of the catalog name concatenated with the repository name. |
| getValueFactory(self) | Return a ValueFactory for this store. This is present for Aduma Sesame compatibility, but in the Python API all ValueFactory functionality has been duplicated or subsumed in the RepositoryConnection class. It isn't necessary to manipulate the ValueFactory class at all. |
| initialize(self) | A Repository must be initialized before it can be used. Returns the initialized Repository object. |
| isWritable(self) | Checks whether this Repository is writable, i.e. if the data contained in this store can be changed. |
| registerDatatypeMapping(self, predicate=None, datatype=None, nativeType=None) | Register an inlined datatype. Predicate is the URI of predicate used in the triple store. Datatype may be one of: XMLSchema.INT, XMLSchema.LONG, XMLSchema.FLOAT, XMLSchema.DATE, and XMLSchema.DATETIME. NativeType may be "int", "datetime", or "float". You must supply nativeType and either predicate or datatype. If predicate, then object arguments to triples with that predicate will use an inlined encoding of type nativeType in their internal representation. If datatype, then typed literal objects with a datatype matching datatype will use an inlined encoding of type nativeType. (Duplicated in the RepositoryConnection class for Python user convenience.) |
| shutDown(self) | Shuts the Repository down, releasing any resources that it keeps hold of. |
The RepositoryConnection class is the main interface for updating data in and performing queries on a Repository. By default, a RespositoryConnection is in autoCommit mode, meaning that each operation corresponds to a single transaction on the underlying triple store. autoCommit can be switched off, in which case it is up to the user to handle transaction commit/rollback. Note that care should be taken to always properly close a RepositoryConnection after one is finished with it, to free up resources and avoid unnecessary locks.
Note that concurrent access to the same connection object is explicitly forbidden. The client must perform its own synchronization to ensure non-concurrent access.
Several methods take a vararg argument that optionally specifies a (set of) context(s) on which the method should operate. (A context is the URI of a subgraph.) Note that a vararg parameter is optional, it can be completely left out of the method call, in which case a method either operates on a provided statement's context (if one of the method parameters is a statement or collection of statements), or operates on the repository as a whole, completely ignoring context. A vararg argument may also be null (cast to Resource) meaning that the method operates on those statements which have no associated context only.
Source: /AllegroGraphDirectory/src/franz/openrdf/repository/repositoryconnection.py.
RepositoryConnection(self, repository)
where repository is the Repository object that created this RepositoryConnection.
Example: The best practice is to use the Repository.getConnection() method, which supplies the repository parameter to the construction method. .
connection = myRepository.getConnection()
This table contains the repositoryConnection methods that create, maintain, search, and delete triple stores. There are following tables that list special methods for Free Text Search, Prolog Rule Inference, Geospatial Reasoning, Social Network Analysis, Transactions and Subject Triples Caching.
| add(self, arg0, arg1=None, arg2=None, contexts=None, base=None, format=None, serverSide=False) | Calls addTriple(), addStatement(), or addFile(). Best practice is to avoid add() and use addFile(), addStatement(), and addTriple() instead. arg0 may be a Statement or a filepath. If so, arg1 and arg2 default to None. arg0, arg1, and arg2 may be the subject, predicate and object of a single triple. contexts is an optional list of contexts (subgraph URIs), defaulting to None. A context is the URI of a subgraph. If None, the triple(s) will be added to the null context (the default or background graph). base is the baseURI to associate with loading a file. Defaults to None. format is an RDFFormat instance. Defaults to None, which means "guess from file extension". serverSide indicates whether the filepath refers to a file on the client computer or on the server. Defaults to False. |
| addFile(self, filePath, base=None, format=None, context=None, serverSide=False) | Loads a file into the triple store. Note that a file can be loaded into only one context. filepath identifies the file to load. context is an optional context URI (subgraph URI), defaulting to None. If None, the triple(s) will be added to the null context (the default or background graph). base is the baseURI to associate with loading a file. Defaults to None. format is an RDFFormat instance. Defaults to None, which means "guess from file extension". serverSide indicates whether the filepath refers to a file on the client computer or on the server. Defaults to False. |
| addData(self, data, rdf_format=RDFFormat.TURTLE, base_uri=None, context=None) | Loads data from a string into the triple store. Note that the data can be loaded into only one context. data is the text to be loaded. context is an optional context URI (subgraph URI), defaulting to None. If None, the triple(s) will be added to the null context (the default or background graph). base_uri is used to resolve relative URIs in data. rdf_format is the data format (an instance of RDFFormat). Defaults to RDFFormat.TURTLE. |
| addStatement(self, statement, contexts=None) | Add the supplied Statement to the specified contexts of the repository. contexts defaults to None, which adds the statement to the null context (the default or background graph). |
| addTriple(self, subject, predicate, object, contexts=None) | Adds a single triple to the repository. subject, predicate and object are the three values of the triple. contexts is an optional list of context URIs to add the triple to, defaulting to None. If None, the triple will be added to the null context (the default or background graph). |
| addTriples(self, triples_or_quads, context=ALL_CONTEXTS, ntriples=False) | Add the supplied triples_or_quads to this repository. Each triple can be a list or a tuple of Values. context is the URI of a subgraph, which will be stored in the fourth field of the "triple," defaulting to ALL_CONTEXTS. If ntriples is True, then the triples or quads are assumed to contain valid ntriples strings, and they are passed to the server with no conversion. The default value is False. |
| clear(self, contexts=ALL_CONTEXTS) | Removes all statements from the designated list of contexts (subgraphs) in the repository. If contexts is ALL_CONTEXTS (the default), it clears the repository of all statements. |
| clearNamespaces(self) | Remove all namespace declarations from the current environment. |
| close(self) | Closes the connection in order to free up resources. |
| createBNode(self, nodeID=None) | Creates a new blank node with the given node identifier. nodeID defaults to None. If nodeID is None, a new, unused node ID is generated. |
| createLiteral(self, value, datatype=None, language=None) | Create a new literal with value. datatype if supplied, should be a URI, in which case value should be a string. You may optionally include an RDF language attribute. datatype and language default to None. |
| createRange(self, lowerBound, upperBound) | Create a compound literal representing a range from lowerBound to upperBound. |
| createStatement(self, subject, predicate, object, context=None) | Create a new Statement object using the supplied subject, predicate and object and associated context, which defaults to None. The context is the URI of a subgraph. |
| createURI(self, uri=None, namespace=None, localname=None) | Creates a new URI object from the supplied string-representation(s). uri is a string representing an entire URI. namespace and localname are combined to create a URI. If two non-keyword arguments are passed, it assumes they represent a namespace/localname pair. |
| deleteDuplicateStatements(mode) | Deletes duplicate triples from the store. mode can be "spo" (triples are duplicates if they have the same subject, predicate, and object, regardless of the graph) or "spog" (triples are duplicates if they have the same subject, predicate, object, and graph). See also getDuplicateStatements below. |
| export(self, handler, contexts=ALL_CONTEXTS) | Exports all triples in the repository to an external file. handler is either an NTriplesWriter() object or an RDFXMLWriter() object. The export may be optionally confined to a list of contexts (default is ALL_CONTEXTS). Each context is the URI of a subgraph. |
| exportStatements(self, subj, pred, obj, includeInferred, handler, contexts=ALL_CONTEXTS) | Exports all triples that match subj, pred and/or obj. May optionally includeInferred statements provided by RDFS++ inference (default is False). handler is either an NTriplesWriter() object or an RDFXMLWriter() object. The export may be optionally confined to a list of contexts (default is ALL_CONTEXTS). Each context is the URI of a subgraph. |
| getAddCommitSize(self) | Returns the current setting of the add_commit_size property. See setAddCommitSize(). |
| getContextIDs(self) | Return a list of context URIs, one for each subgraph referenced by a quad in the triple store. Omits the default context because its ID would be null. |
| getDuplicateStatements(mode) | Gets duplicate triples in the store. mode can be "spo" (triples are duplicates if they have the same subject, predicate, and object, regardless of the graph) or "spog" (triples are duplicates if they have the same subject, predicate, object, and graph). See also deleteDuplicateStatements above. |
| getNamespace(self, prefix) | Returns the namespace that is associated with prefix, if any. |
| getNamespaces(self) | Returns a Python dictionary of prefix/namespace pairings. The default namespaces are: rdf, rdfs, xsd, owl, fti, dc, and dcterms. |
| getSpec(self) | Returns a string composed of the catalog name concatenated with the repository name. |
| getStatements(self, subject, predicate, object, contexts=ALL_CONTEXTS, includeInferred=False, limit=None, tripleIDs=False, output=None, output_format=RDFFormat.NQX) |
Gets all statements with a specific subject, predicate and/or object from the repository. The result is optionally restricted to the specified set of named contexts (default is ALL_CONTEXTS). A context is the URI of a subgraph. Returns a RepositoryResult iterator that produces a 'Statement' each time that 'next' is called. May optionally includeInferred statements provided by RDFS++ inference (default is False). Takes an optional limit on the number of statements to return. If tripleIDs is True, the output includes the triple ID field (the fifth field of the quad). To serialize the statements to a file or stream, pass a file path or a file-like object as the output parameter. Set output_format to an instance of RDFFormat to control the serialization format. Note that if the output parameter is used the function returns None instead of a RepositoryResult. |
| getStatementsById(self, ids, output=None, output_format=RDFFormat.NQX) | Return all statements whose triple ID matches an ID in the list of ids. To serialize the statements to a file or stream, pass a file path or a file-like object as the output parameter. Set output_format to an instance of RDFFormat to control the serialization format. Note that if the output parameter is used the function returns None instead of a RepositoryResult. |
| getValueFactory(self) | Returns the ValueFactory object associated with this RepositoryConnection. |
| isEmpty(self) | Returns True if size() is zero. |
| prepareBooleanQuery(self, queryLanguage, queryString, baseURI=None) | Parse queryString into a Query object which can be executed against the RDF storage. queryString must be an ASK query. The result is true or false. queryLanguage is one of SPARQL, PROLOG, or COMMON_LOGIC. baseURI optionally provides a URI prefix (defaults to None). Returns a Query object. The result of query execution will be True of False. |
| prepareGraphQuery(self, queryLanguage, queryString, baseURI=None) | Parse queryString into a Query object which can be executed against the RDF storage. queryString must be a CONSTRUCT or DESCRIBE query. queryLanguage is one of SPARQL, PROLOG, or COMMON_LOGIC. baseURI optionally provides a URI prefix (defaults to None). Returns a Query object. The result of query execution is an iterator of Statements/quads. |
| prepareTupleQuery(self, queryLanguage, queryString, baseURI=None) | Embed queryString into a Query object which can be executed against the RDF storage. queryString must be a SELECT query. queryLanguage is one of SPARQL, PROLOG, or COMMON_LOGIC. baseURI optionally provides a URI prefix (defaults to None). Returns a Query object. The result of query execution is an iterator of tuples. |
| registerDatatypeMapping(self, predicate=None, datatype=None, nativeType=None) | Register an inlined datatype. Predicate is the URI of predicate used in the triple store. Datatype may be one of: XMLSchema.INT, XMLSchema.LONG, XMLSchema.FLOAT, XMLSchema.DATE, and XMLSchema.DATETIME. NativeType may be "int", "datetime", or "float". You must supply nativeType and either predicate or datatype. If predicate, then object arguments to triples with that predicate will use an inlined encoding of type nativeType in their internal representation. If datatype, then typed literal objects with a datatype matching datatype will use an inlined encoding of type nativeType. |
| remove(self, arg0, arg1=None, arg2=None, contexts=None) | Calls removeTriples() or removeStatement(). Best practice would be to avoid remove() and use removeTriples() or removeStatement() directly. arg0 may be a Statement. If so, then arg1 and arg2 default to None. arg0, arg1, and arg2 may be the subject, predicate and object of a triple. contexts is an optional list of contexts, defaulting to None. |
| removeNamespace(self, prefix) | Remove the namespace associate with prefix. |
| removeQuads(self, quads, ntriples=False) | Remove enumerated quads from this repository. Each quad can be a list or a tuple of Values. If ntriples is True (default is False), then the quads are assumed to contain valid ntriples strings, and they are passed to the server with no conversion. |
| removeQuadsByID(self, tids) | tids contains a list of triple IDs (integers). Remove all quads with IDs that match. |
| removeStatement(self, statement, contexts=None) | Removes the supplied Statement(s) from the specified contexts (default is None). |
| removeTriples(self, subject, predicate, object, contexts=None) | Removes the triples with the specified subject, predicate and object from the repository, optionally restricted to the specified contexts (defaults to None).. |
| setAddCommitSize(self, triple_count) | The threshold for commit size during triple add operations. "Set to 0 (zero) or None to clear size-based autocommit behavior. When set to an integer triple_count > 0, loads and adds commit each triple_count triples added and at the end of the triples being added. |
| setNamespace(self, prefix, namespace) | Define (or redefine) a namespace associated with prefix. |
| size(self, contexts=ALL_CONTEXTS) | Returns the number of (explicit) statements that are in the specified contexts in this repository. contexts defaults to ALL_CONTEXTS, but can be a context URI or a tuple of context URIs from getContextIDs(). Use 'null' to get the size of the default graph (the unnamed context). |
These repositoryConnection methods support user-defined triple indices. See AllegroGraph Triple Indices for more information on this topic.
| listIndices(self) | Returns a tuple containing a list of the current set of triple indices. |
| listValidIndices(self) | Returns a tuple containing the list of all possible triple indices. |
| addIndex(self, type) | Adds a specific type of index to the current set of triple indices. type is a string containing one of the following index names: spogi, spgoi, sopgi, sogpi, sgpoi, sgopi, psogi, psgoi, posgi, pogsi, pgsoi, pgosi, ospgi, osgpi, opsgi, opgsi, ogspi, ogpsi, gspoi, gsopi, gpsoi, gposi, gospi, gopsi, or i. |
| dropIndex(self, type) | Removes a specific type of index to the current set of triple indices. type is a string containing one of the following index names: spogi, spgoi, sopgi, sogpi, sgpoi, sgopi, psogi, psgoi, posgi, pogsi, pgsoi, pgosi, ospgi, osgpi, opsgi, opgsi, ogspi, ogpsi, gspoi, gsopi, gpsoi, gposi, gospi, gopsi, or i. |
The following repositoryConnection method supports free-text indexing in AllegroGraph.
| createFreeTextIndex(self, name, predicates=None, indexLiterals=None, indexResources=None, indexFields=None, minimumWordSize=None, stopWords=None, wordFilters=None) |
Create a free-text index with the given parameters. name is a string identifying the new index.
If no predicates are given, triples are indexed regardless of
predicate.
indexLiterals determines which literals to index. It can be
True (the default), False, or a list of resources, indicating
the literal types that should be indexed.
indexResources determines which resources are indexed. It can
be True, False (the default), or "short", to index only the
part of resources after the last slash or hash character.
indexFields can be a list containing any combination of the elements "subject", "predicate", "object", and "graph". The default is ["object"]. minimumWordSize, an integer, and determines the minimum size a word must have to be indexed. The default is 3. stopWords should hold a list of words that should not be indexed. When not given, a list of common English words is used. wordFilters can be used to apply some normalizing filters to words as they are indexed or queried. Can be a list of filter names. Currently, only "drop-accents" and "stem.english" are supported. |
| deleteFreeTextIndex(self, name) | Deletes the named index. |
| evalFreeTextSearch(self, pattern, infer=False, limit=None, index=None) | Return an array of statements for the given free-text pattern search. If no index is provided, all indices will be used. |
| getFreeTextIndexConfiguration(self, name) | Returns a Python dictionary containing all of the configuration settings of the named index. |
| listFreeTextIndices(self) | List the free-text indices. |
| modifyFreeTextIndex(self, name, predicates=None, indexLiterals=None, indexResources=None, indexFields=None, minimumWordSize=None, stopWords=None, wordFilters=None, reIndex=None) |
name is a string identifying the index to be modified. If no predicates are given, triples are indexed regardless of predicate. indexLiterals determines which literals to index. It can be True (the default), False, or a list of resources, indicating the literal types that should be indexed. indexResources determines which resources are indexed. It can be True, False (the default), or "short", to index only the part of resources after the last slash or hash character. indexFields can be a list containing any combination of the elements "subject", "predicate", "object", and "graph". The default is ["object"]. minimumWordSize, an integer, and determines the minimum size a word must have to be indexed. The default is 3. stopWords should hold a list of words that should not be indexed. When not given, a list of common English words is used. wordFilters can be used to apply some normalizing filters to words as they are indexed or queried. Can be a list of filter names. Currently, only "drop-accents" and "stem.english" are supported. reIndex if True (the default) will rebuild the index. If False, it will apply the new settings to new triples only, while maintaining the index data for existing triples. |
Note that text search is implemented through a SPARQL query using a "magic" predicate called fti:search. See the AllegroGraph Python API Tutorial for an example of how to set up this search.
These repositoryConnection methods support the use of Prolog rules in AllegroGraph. Any use of Prolog rules requires that you create a dedicated session to run them in.
| addRules(self, rules, language=None) | Add a sequence of one or more rules (in ASCII format). |
| loadRules(self, file ,language=None) | Load a file of rules. file is assumed to reside on the client machine. language defaults to QueryLanguage.PROLOG. For use with a dedicated session. |
These repositoryConnection methods support geospatial reasoning.
| createBox(self, xMin=None, xMax=None, yMin=None, yMax=None) | Create a rectangular search region (a box) for geospatial search. This method works for both Cartesian and spherical coordinate systems. xMin, xMax may be used to input latitude. yMin, yMax may be used to input longitude. |
| createCircle(self, x, y, radius, unit=None) | Create a circular search region for geospatial search. This method works for both Cartesian and spherical coordinate systems. radius is the radius of the circle expressed in the designated unit, which defaults to the unit assigned to the coordinate system. x and y locate the center of the circle and may be used for latitude and longitude. |
| createCoordinate(self, x=None, y=None, lat=None, long=None) | Create a coordinate point in a geospatial coordinate system. Must include x and y, or lat and long. Use this method to create the object value for a location triple. |
| createLatLongSystem(self, unit='degree', scale=None, latMin=None, latMax=None, longMin=None, longMax=None) | Create a spherical coordinate system for geospatial location matching. unit can be 'degree', 'mile', 'radian', or 'km'. scale should be your estimate of the size of a typical search region in the latitudinal direction. latMin and latMax are the bottom and top borders of the coordinate system. longMin and longMax are the left and right sides of the coordinate system. |
| createPolygon(self, vertices, uri=None, geoType=None) | Create a polygonal search region for geospatial search. The vertices are saved as triples in AllegroGraph. vertices is a list of (x, y) pairs such as [(51.0, 2.00),(60.0, -5.0),(48.0,-12.5)]. uri is an optional subject value for the vertex triples, in case you want to manipulate them. geoType is 'CARTESIAN' or 'SPHERICAL', but defaults to None. |
| createRectangularSystem(self, scale=1, unit=None, xMin=0, xMax=None, yMin=0, yMax=None) | Create a Cartesian coordinate system for geospatial location matching. scale should be your estimate of the Y size of a typical search region. unit must be None. xMin and xMax are the left and right edges of the rectangle. yMin and yMax are the bottom and top edges of the rectangle. |
| getGeoType(self) | Returns what type of geospatial object it is. |
| setGeoType(self) | Sets the geoType of a geospatial object. |
The following repositoryConnection methods support Social Network Analysis in AllegroGraph. The Python API to the Social Network Analysis methods of AllegroGraph requires Prolog queries, and therefore must be run in a dedicated session.
| registerNeighborMatrix(self, name, generator, group_uris, max_depth=2) | Construct a neighbor matrix named 'name'. The generator named 'generator' is applied
to each URI in 'group_uris' (a collection of fullURIs or qnames (strings)), computing edges to max depth 'max_depth'. For use in a dedicated session. |
| registerSNAGenerator(self, name, subjectOf=None, objectOf=None, undirected=None, generator_query=None) | Create (and remember) a generator named 'name'.
If one already exists with the same name; redefine it.
'subjectOf', 'objectOf' and 'undirected' expect a list of predicate URIs, expressed as
fullURIs or qnames, that define the edges traversed by the generator.
Alternatively, instead of an adjacency map, one may provide a 'generator_query',
that defines the edges. For use in a dedicated session. |
AllegroGraph lets you set up a special RepositoryConnection (a "session") that supports transaction semantics. You can add statements to this session until you accumulate all the triples you need for a specific transaction. Then you can commit the triples in a single act. Up to that moment the triples will not be visible to other users of the repository.
If anything interrupts the accumulation of triples building to the transaction, you can roll back the session. This discards all of the uncommitted triples and resynchronizes the session with the repository as a whole.
Closing the session deletes all uncommitted triples, all rules, generators and matrices that were created in the session. Rules, generators and matrices cannot be committed. They persist as long as the session persists.
| openSession(self) | Open a dedicated session. |
| closeSession(self) | Close a dedicated session connection. |
| session(self, autocommit=False, lifetime=None, loadinitfile=False) | A dedicated connection context manager for use with the 'with' statement. Automatically calls openSession() at block start and closeSession() at block end. If autocommit is True, commits are done on each request, otherwise you will need to call commit() or rollback() as appropriate for your application. lifetime is an integer specifying the idle timeout of the session, in seconds. If lifetime is not specified, it defaults to the value of the DefaultSessionTimeout configuration directive. If specified, its value can be no larger than the value of the MaximumSessionTimeout configuration directive. See the Session directives section in Server Configuration and Control for more information. If loadinitfile is True, then the current initfile will be loaded |
| commit(self) | Commits changes on a dedicated connection. |
| rollback(self) | Rolls back changes on a dedicated connection. |
You can enable subject triple caching to speed up queries where the same subject URI appears in multiple patterns. The first time AllegroGraph retrieves triples for a specific resource, it caches the triples in memory. Subsequent query patterns that ask for the same subject URI can retrieve the matching triples very quickly from the cache. The cache has a size limit and automatically rolls over as that limit is exceeded.
| enableSubjectTriplesCache(self, size=None) | Maintain a cache of size 'size' that caches, for each accessed resource, quads where the resource appears in subject position. This can accelerate the performance of certain types of queries. The size is the maximum number of subjects whose triples will be cached. Default is 100,000. |
| disableSubjectTriplesCache(self) | Turn of caching. |
| getSubjectTriplesCacheSize(self) | Return the current size of the subject triples cache. |
The RDFFormat class is an enumeration describing the data formats supported by AllegroGraph when importing RDF data.
Source: /AllegroGraphDirectory/src/franz/openrdf/rio/rdfformat.py.
| RDFFormat.RDFXML | The RDF/XML file format. |
| RDFFormat.NTRIPLES | The N-Triples file format. |
| RDFFormat.NQUADS | The N-Quads file format. |
| RDFFormat.NQX | The NQX file format - an extension to N-Quads that can encode triple attributes. |
| RDFFormat.TURTLE | The Turtle file format. |
| RDFFormat.TRIX | The TriX file format. |
| RDFFormat.TRIG | The TriG file format. |
The Query class is non-instantiable. It is an abstract class from which the three query subclasses are derived. It is included here because of its methods, which are inherited by the subclasses.
A query on a Repository that can be formulated in one of the supported query languages (for example SPARQL). It allows one to predefine bindings in the query to be able to reuse the same query with different bindings.
Source: /AllegroGraphDirectory/src/franz/openrdf/query/query.py.
The best practice is to allow the RepositoryConnection object to create an instance of one of the Query subclasses (TupleQuery, GraphQuery, BooleanQuery). There is no reason for the Python application programmer to create a Query object directly.
tupleQuery = conn.prepareTupleQuery(QueryLanguage.SPARQL, queryString) result = tupleQuery.evaluate()
| evaluate_generic_query(self, count=False, accept=None) | Evaluate a SPARQL or PROLOG query. If SPARQL, it may be a 'select', 'construct', 'describe' or 'ask' query. Return a QueryResult object, unless the accept parameter is set to 'application/sparql-results+xml' or 'application/sparql-results+json' to return the results as a string in xml or json format. (Best practice is to use (and evaluate) one of the more specific query subclasses instead of using the Query class directly.) |
| getBindings(self) | Retrieves the bindings that have been set on this query in the form of a dictionary. |
| getDataset(self) | Returns the current dataset setting for this query. |
| getIncludeInferred(self) | Returns whether or not this query will return inferred statements (if any are present in the repository). |
| removeBinding(self, name) | Removes the named binding so that it has no value. |
| setBinding(self, name, value) | Binds the named attribute to the supplied value. Any value that was previously bound to the specified attribute will be overwritten. |
| setBindings(self, dict) | Sets multiple bindings using a dictionary of attribute names and values. |
| setCheckVariables(self, setting) | If true, the presence of variables in the SELECT clause not referenced in a triple pattern are flagged. |
| setContexts(self, contexts) | Assert a set of contexts (a list of subgraph URIs) that filter all triples. |
| setDataset(self, dataset) | Specifies the dataset against which to evaluate a query, overriding any dataset that is specified in the query itself. |
| setIncludeInferred(self, includeInferred) | Determines whether results of this query should include inferred statements (if any inferred statements are present in the repository). Inference is turned off by default (which is the opposite of standard Sesame behavior). The default value of setIncludeInferred() is True. |
This subclass is used with SELECT queries. Use the RepositoryConnection object's prepareTupleQuery() method to create a TupleQuery object. The results of the query are returned in a QueryResult iterator that yields a sequence of bindingSets.
Methods
TupleQuery uses all the methods of the Query class, plus one more:
| evaluate(self, count=False) | Execute the embedded query against the RDF store. Return an iterator that produces for each step a tuple of values (resources and literals) corresponding to the variables or expressions in a 'select' clause (or its equivalent). To serialize the returned tuples to a file or stream, pass a file path or a file-like object as the output parameter. Set output_format to an instance of TupleFormat to control the serialization format. Note that if the output parameter is used the function returns None. |
This subclass is used with CONSTRUCT and DESCRIBE queries. Use the RepositoryConnection object's prepareGraphQuery() method to create a GraphQuery object. The results of the query are returned in a RepositoryResult iterator that yields a sequence of bindingSets.
Methods
GraphQuery uses all the methods of the Query class, plus one more:
| evaluate(self) | Execute the embedded query against the RDF store. Returns a RepositoryResult object. To serialize the statements to a file or stream, pass a file path or a file-like object as the output parameter. Set output_format to an instance of RDFFormat to control the serialization format. Note that if the output parameter is used the function returns None instead of a RepositoryResult. |
This subclass is used with ASK queries. Use the RepositoryConnection object's prepareBooleanQuery() method to create a BooleanQuery object. The results of the query are True or False.
Methods
BooleanQuery uses all the methods of the Query class, plus one more:
| evaluate(self) | Execute the embedded query against the RDF store. |
Source: /AllegroGraphDirectory/src/franz/openrdf/query/queryresult.py.
A QueryResult object is simply an iterator that also has a close() method that must be called to free resources. Such objects are returned as a result of SPARQL and PROLOG query evaluation and should not be constructed directly. The recommended usage looks like this:
tupleQuery = conn.prepareTupleQuery(QueryLanguage.SPARQL, queryString) with contextlib.closing(tupleQuery.evaluate()) as results: for result in results: print result
| close(self) | Shut down the iterator to be sure the resources are freed up. It is safe to call this method multiple times. |
| next(self) | Return the next Statement in the answer, if there is one. Otherwise raise a StopIteration exception. |
A QueryResult subclass used for queries that return tuples.
| getBindingNames(self) | Get the names of the bindings (a list of strings), in order of projection. |
A QueryResult subclass used for queries that return statements. Objects of this class are also RepositoryResult instances.
A RepositoryResult object is a result collection of Statement that can be iterated over. It keeps an open connection to the backend for lazy retrieval of individual results. Additionally it has some utility methods to fetch all results and add them to a collection.
By default, a RepositoryResult is not necessarily a (mathematical) set: it may contain duplicate objects. Duplicate filtering can be switched on, but this should not be used lightly as the filtering mechanism is potentially memory-intensive.
A RepositoryResult must be closed after use to free up any resources (open connections, read locks, etc.) it has on the underlying repository.
Source: /AllegroGraphDirectory/src/franz/openrdf/repository/repositoryresult.py.
Best practice is to allow a querySubclass.evaluate() method to create and return the RepositoryResult object. There is no reason for the Python application programmer to create a RepositoryResult object directly.
graphQuery = conn.prepareGraphQuery(QueryLanguage.SPARQL, queryString) with contextlib.closing(graphQuery.evaluate()) as results: for result in results: print result
| close(self) | Shut down the iterator to be sure the resources are freed up. It is safe to call this method multiple times. |
| next(self) | Return the next Statement in the answer, if there is one. Otherwise raise a StopIteration exception. |
| enableDuplicateFilter(self) | Switches on duplicate filtering while iterating over objects. The RepositoryResult will keep track of the previously returned objects in a set and on calling next() will ignore any objects that already occur in this set. Caution: use of this filtering mechanism is potentially memory-intensive. |
| asList(self) | Returns a list containing all objects of this RepositoryResult in order of iteration. The RepositoryResult is fully consumed and automatically closed by this operation. |
| addTo(self, collection) | Adds all objects of this RepositoryResult to the supplied collection. The RepositoryResult is fully consumed and automatically closed by this operation. |
| rowCount(self) | Returns the number of result items stored in this object. |
A Statement is a client-side triple. It encapsulates the subject, predicate, object and context (subgraph) values of a single triple and makes them available.
Source: /AllegroGraphDirectory/src/franz/openrdf/model/statement.py.
Statement(self, subject, predicate, object, context=None)
Example: Best practice is to allow the RepositoryConnection.createStatement() method to create and return the Statement object. There is no reason for the Python application programmer to create a Statement object directly.
stmt1 = conn.createStatement(alice, age, fortyTwo)
| getContext(self) | Returns the value in the fourth position of the stored tuple (the subgraph URI). |
| getObject(self) | Returns the value in the third position of the stored tuple. |
| getPredicate(self) | Returns the value in the second position of the stored tuple. |
| getSubject(self) | Returns the value in the first position of the stored tuple. |
| setQuad(self, string_tuple) | Stores a string_tuple of a triple or quad. This method is called only by an internal method of the RepositoryResult class. There is no need for a Python application programmer to use it. |
A ValueFactory is a factory for creating URIs, blank nodes, literals and Statements. In the AllegroGraph Python interface, the ValueFactory class would be regarded as obsolete. Its functions have been subsumed by the expanded capability of the RepositoryConnection class. It is documented here for the convenience of the person who is porting an application from Aduma Sesame.
Source: /AllegroGraphDirectory/src/franz/openrdf/model/valuefactory.py.
ValueFactory(self, store)
Example: Best practice is to allow the Repository constructor to generate the ValueFactory automatically at the same time that the Repository object is created. There is no reason for a Python application programmer to attempt this step manually.
| createBNode() | See RepositoryConnection class. |
| createLiteral() | See RepositoryConnection class. |
| createStatement() | See RepositoryConnection class. |
| createURI() | See RepositoryConnection class. |


A restful API describes common behavior for what how resources are requested by the client and how the server responds
In this example i will talk about a REST API which handles users.
each of express' api functions require a url path and a callback function as an argument.
the callback uses the request from the client and the response to send back.
Your API will have 2 endpoints
/users endpoint which is used for retrieving all users from the server
app.get("/users", (req, res) => {
res.send({data: users});
});
/users/id endpoint which is used for retrieving a specific user from the server
app.get("/users/:id", (req, res) => {
const id = Number(req.params.id);
const foundUser = users.find(e => e.id === id);
});
Here we use req.params.id to extract the id parameter from the url and find the requested user based on that
A post endpoint in your API will usually only have 1 endpoint
/users endpoint for the purpose of creating a new user
let AUTOINCREMENT = users.length;
app.post("/users", (req, res) => {
const newUser = req.body;
newUser.id = ++AUTOINCREMENT;
users.push(newUser);
res.send({ data: user});
});
Your API will likely only contain 1 endpoint
/users/id endpoint for updating/changing a user
app.patch("/users/:id", (req, res) => {
users = users.map(user => {
if(user.id === Number(req.params.id)){
user = {...user, ...req.body, id: user.id};
}
return user;
});
res.send({});
});
Your API will most likely only contain 1 endpoint (you don't wan't client to be able to request the deletion of all resources)
/users/id endpoint for deleting a single specific user
app.delete("/users/:id", (req, res) => {
const query = Number(req.params.id);
users = users.filter(user => user.id !== query);
res.send({ });
});
Next up: i will show you how to server HTML files with express


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@()(content: Html)
Usage Instructions: Make sure to include the scrolling-nav.js
, jquery.easing.min.js
,
and scrolling-nav.css
files. To make a link smooth scroll to another section on the
page, give the link the .page-scroll
class and set the link target to a corresponding
ID on the page.


Your browser does not support the audio element.
You Win!!!!
Game Over
Press Any Key to Try Again!
Press A-Z to Make a Guess!
Wins
Word To Guess
Guesses Remaining
Letters Guessed
Sad but True
Teen Spirit
Dream on
Bohemian Rhapsody
Hotel California
English man
Symphony of destruction
Hint


- File converter.cpp
- License BSD-3-Clause
- File converter.hh
- License BSD-3-Clause
- File device.cpp
- License BSD-3-Clause
- File device.hh
- License BSD-3-Clause
- File device_simulator.cpp
- License BSD-3-Clause
- File device_simulator.hh
- License BSD-3-Clause
- File dg_to_ros.cpp
- License BSD-3-Clause
- File dg_to_ros.hh
- License BSD-3-Clause
- File dynamic_graph_manager.cpp
- License BSD-3-Clause
- File dynamic_graph_manager.hh
- License BSD-3-Clause
- File exception-abstract.cpp
- License BSD-3-Clause
- File exception-abstract.hh
- License BSD-3-Clause
- File exception-dynamic.cpp
- License BSD-3-Clause
- File exception-dynamic.hh
- License BSD-3-Clause
- File exception-factory.cpp
- License BSD-3-Clause
- File exception-factory.hh
- License BSD-3-Clause
- File exception-feature.cpp
- License BSD-3-Clause
- File exception-feature.hh
- License BSD-3-Clause
- File exception-signal.cpp
- License BSD-3-Clause
- File exception-signal.hh
- License BSD-3-Clause
- File exception-task.cpp
- License BSD-3-Clause
- File exception-task.hh
- License BSD-3-Clause
- File exception-tools.cpp
- License BSD-3-Clause
- File exception-tools.hh
- License BSD-3-Clause
- File exception-yaml-cpp.cpp
- License BSD-3-Clause
- File exception-yaml-cpp.hpp
- License BSD-3-Clause
- File main.cpp
- License BSD-3-Clause
- File matrix_geometry.hh
- License BSD-3-Clause
- File periodic-call.cpp
- License BSD-3-Clause
- File periodic-call.hh
- License BSD-3-Clause
- File prologue.py
- License BSD-3-Clause
- File robot.py
- License BSD-3-Clause
- File robot_pose_publisher.py
- License BSD-3-Clause
- File ros.py
- License BSD-3-Clause
- File ros_client.py
- License BSD-3-Clause
- File ros_init.cpp
- License BSD-3-Clause
- File ros_init.hh
- License BSD-3-Clause
- File ros_interpreter.cpp
- License BSD-3-Clause
- File ros_interpreter.hh
- License BSD-3-Clause
- File ros_publish.cpp
- License BSD-3-Clause
- File ros_publish.hh
- License BSD-3-Clause
- File ros_publish.hxx
- License BSD-3-Clause
- File ros_queued_subscribe.cpp
- License BSD-3-Clause
- File ros_queued_subscribe.hh
- License BSD-3-Clause
- File ros_queued_subscribe.hxx
- License BSD-3-Clause
- File ros_robot_state_publisher.cpp
- License BSD-3-Clause
- File ros_robot_state_publisher.hpp
- License BSD-3-Clause
- File ros_robot_state_publisher_mt.cpp
- License BSD-3-Clause
- File ros_robot_state_publisher_mt.hpp
- License BSD-3-Clause
- File ros_subscribe.cpp
- License BSD-3-Clause
- File ros_subscribe.hh
- License BSD-3-Clause
- File ros_subscribe.hxx
- License BSD-3-Clause
- File ros_tf_listener.cpp
- License BSD-3-Clause
- File ros_tf_listener.hh
- License BSD-3-Clause
- File ros_time.cpp
- License BSD-3-Clause
- File ros_time.hh
- License BSD-3-Clause
- File run_command.py
- License BSD-3-Clause
- File setup.py
- License BSD-3-Clause
- File shell_client.py
- License BSD-3-Clause
- File simple_dgm.hpp
- License BSD-3-Clause
- File tools.cpp
- License BSD-3-Clause
- File tools.hh
- License BSD-3-Clause


If you are an aspiring musician or any age and are looking to join an orchestra then The Barrier Reef Orchestra might have a place for you!
We are always looking for new musicians who share our same love and passion of music. If you would like to join simply fill out the information below and leave us a message with what instrument you play and a little information about yourself.


Start a Sanergy micro enterprice
Sanergy builds healthy, prosperous communities by making hygienic sanitation affordable and accessible througout Africa’s informal settlemetns.
Sanergy builds healthy, prosperous communities by making hygienic sanitation affordable and accessible througout Africa’s informal settlemetns.


|
AceTime
0.5.2
Date and time classes for Arduino that support timezones from the TZ Database, and a system clock that can synchronize from an NTP server or an RTC chip.
|
Class that translates a numeric month (1-12) or dayOfWeek (1-7) into a human readable string. More...
#include <DateStrings.h>
Public Member Functions | |
| const char * | monthLongString (uint8_t month) |
| Return the long month name. More... | |
| const char * | monthShortString (uint8_t month) |
| Return the short month name. More... | |
| const char * | dayOfWeekLongString (uint8_t dayOfWeek) |
| Return the short dayOfWeek name. More... | |
| const char * | dayOfWeekShortString (uint8_t dayOfWeek) |
| Return the short dayOfWeek name. More... | |
Static Public Attributes | |
| static const uint8_t | kBufferSize = 10 |
| Length of the longest month or week name, including the '\0' terminator. | |
| static const uint8_t | kShortNameLength = 3 |
| Number of prefix characters to use to create a short name. More... | |
Class that translates a numeric month (1-12) or dayOfWeek (1-7) into a human readable string.
Both long and short versions can be retrieved. The object uses an internal char[] buffer to store the result strings, so the strings must be used before DateStrings object is destroyed. This also means that the object is not thread-safe but Arduino boards are single-threaded currently so we don't have to worry about this.
Inspired by the DateStrings.cpp file in https://github.com/PaulStoffregen/Time/blob/master/DateStrings.cpp.
Definition at line 27 of file DateStrings.h.
|
inline |
Return the short dayOfWeek name.
0=Error, 1=Monday, 7=Sunday.
Definition at line 57 of file DateStrings.h.
|
inline |
|
inline |
Return the long month name.
0=Error, 1=January, 12=December.
Definition at line 41 of file DateStrings.h.
|
inline |
|
static |
Number of prefix characters to use to create a short name.
kShortNameLength < kBufferSize must be true.
Definition at line 38 of file DateStrings.h.


{include file="common/header"} {__CONTENT__} {include file="common/right"} {include file="common/footer"}


Sample field
This field will only show the fancyplaceholder when the field has focus:
This field will retain the fancyplaceholder after focus is lost if there is text in the field:


A typical flyover
workflow has the following steps:
This vignette will introduce step 1: how flyover
’s helper functions can be used to prepare multiple data sets for comparison.
This package generally relies on the conscientiousness of the user to clean up data sets prior to plotting, but the helper functions are provided for convenience as part of the flyover
workflow.
If your goal is to compare distributions of variables across multiple data sets, you must first collect those data sets into a single table prior to plotting. flyover
provides basic functions to accomplish this.
Let’s say we have two data sets we would like to compare, one from an old data process and one from a new one. They consist of numeric and categorical data, and they don’t share all the same columns.
old <- data.frame(num1 = rnorm(5), num2 = rexp(5), cat1 = letters[1:5], cat2 = rep("z", 5)) new <- data.frame(num1 = rnorm(5), num2 = rexp(5), cat1 = letters[1:5])
The first step is to create a named list of the data. The names will be used as the levels of a grouping variable to identify observations in later plots, so you want them to be meaningful. By default the names are taken to be the object names you pass, but you can supply a character vector of names to make them more descriptive.
data_list <- enlist_data(old, new, names = c("my old data", "my new data")) str(data_list)
## List of 2
## $ my old data: tibble [5 × 4] (S3: tbl_df/tbl/data.frame)
## ..$ num1: num [1:5] 0.586 0.709 -0.109 -0.453 0.606
## ..$ num2: num [1:5] 2.878 1.605 0.471 6.402 1.258
## ..$ cat1: chr [1:5] "a" "b" "c" "d" ...
## ..$ cat2: chr [1:5] "z" "z" "z" "z" ...
## $ my new data: tibble [5 × 3] (S3: tbl_df/tbl/data.frame)
## ..$ num1: num [1:5] -0.0942 -0.2469 1.6612 -0.4489 0.546
## ..$ num2: num [1:5] 1.2525 0.3971 0.0881 1.7222 5.3849
## ..$ cat1: chr [1:5] "a" "b" "c" "d" ...
All that is left is to stack the data in the list together to create one table. In the process, a grouping variable is created, whose name defaults to flyover_id_
.
data_stack <- stack_data(data_list) data_stack
## # A tibble: 10 x 5
## flyover_id_ num1 num2 cat1 cat2
## <chr> <dbl> <dbl> <chr> <chr>
## 1 my old data 0.586 2.88 a z
## 2 my old data 0.709 1.61 b z
## 3 my old data -0.109 0.471 c z
## 4 my old data -0.453 6.40 d z
## 5 my old data 0.606 1.26 e z
## 6 my new data -0.0942 1.25 a <NA>
## 7 my new data -0.247 0.397 b <NA>
## 8 my new data 1.66 0.0881 c <NA>
## 9 my new data -0.449 1.72 d <NA>
## 10 my new data 0.546 5.38 e <NA>
Notice that the variable cat2
appears in the old data set but not the new one, so the values for this variable are NA
in the records corresponding to the new data. Plotting this field may not be useful to you, since the plot would give you no information about how the distribution changed, and you may already be aware of the column’s absense in newer data. You can remove columns that don’t appear in every data set (and you can also change the grouping variable name):
data_stack_drop <- stack_data(data_list, drop_mismatches = TRUE, group_var = "grp") data_stack_drop
## # A tibble: 10 x 4
## grp num1 num2 cat1
## <chr> <dbl> <dbl> <chr>
## 1 my old data 0.586 2.88 a
## 2 my old data 0.709 1.61 b
## 3 my old data -0.109 0.471 c
## 4 my old data -0.453 6.40 d
## 5 my old data 0.606 1.26 e
## 6 my new data -0.0942 1.25 a
## 7 my new data -0.247 0.397 b
## 8 my new data 1.66 0.0881 c
## 9 my new data -0.449 1.72 d
## 10 my new data 0.546 5.38 e


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Charts and trends of what politicians say and/or do with analysis so that you can put your vote where it counts.
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See where your fellow citizens stand on the issues. Create coalitions and share your insights so that together we can see real policy change.
Customize Your Relationship With Government!


| vec_match {vctrs} | R Documentation |
vec_in()
returns a logical vector based on whether needle
is found in
haystack. vec_match()
returns an integer vector giving location of
needle
in haystack
, or NA
if it's not found.
vec_match( needles, haystack, ..., na_equal = TRUE, needles_arg = "", haystack_arg = "" ) vec_in( needles, haystack, ..., na_equal = TRUE, needles_arg = "", haystack_arg = "" )
needles, haystack |
Vector of
|
... |
These dots are for future extensions and must be empty. |
na_equal |
If |
needles_arg, haystack_arg |
Argument tags for |
vec_in()
is equivalent to %in%; vec_match()
is equivalent to match()
.
A vector the same length as needles
. vec_in()
returns a
logical vector; vec_match()
returns an integer vector.
In most cases places in R, missing values are not considered to be equal,
i.e. NA == NA
is not TRUE
. The exception is in matching functions
like match()
and merge()
, where an NA
will match another NA
.
By vec_match()
and vec_in()
will match NA
s; but you can control
this behaviour with the na_equal
argument.
vec_cast_common()
with fallback
hadley <- strsplit("hadley", "")[[1]] vec_match(hadley, letters) vowels <- c("a", "e", "i", "o", "u") vec_match(hadley, vowels) vec_in(hadley, vowels) # Only the first index of duplicates is returned vec_match(c("a", "b"), c("a", "b", "a", "b"))


why charms and slime is a really good website is because some people cant afford to buy the ingredients to make slime so on my webpage you can look for slimes that are on sale or dont cost alot of money as other slime online sites or shops
different types of slimes
- original slime
- fishbowl slime
- floam slime
- jiggly slime
this site helps people who are interested in makeing slime and buying slime
It will Cost: $7.00
im Kurrin i created this website im from michigan and my birthday is june 1 also im 10 years old


Program
The program of the conference is the following. Times are shown in CEST (left) and EDT (right) timezones.
| Tue 22 | Wed 23 | Thu 24 | Fri 25 | ||
|---|---|---|---|---|---|
| 10:30 AM (CEST) |
Hong-Yan Shih Emergence of collective evolution, ecological stability and diversity in bacteria and viruses from multi-scale feedback |
Jonathan Friedman Community composition of microbial microcosms follows simple assembly rules at evolutionary timescales |
Ville Laitinen Robust detection of early warning signals in limited time series |
Vishwesha Guttal Intrinsic noise, order and bistability in ecological systems |
4:30 AM (EDT) |
| 10:45 AM (CEST) |
Shane Hogle Co-evolution reorganizes the consumer competitive hierarchy in a two-consumer microbial ecosystem |
Enrico Gavagnin Synchronised oscillations in growing cell populations are explained by demographic noise |
Ada Altieri Evidence of glassy phases in large interacting ecosystems with finite demographic noise |
Lorenzo Fant Eco-evolutionary dynamics lead to functionally robust and redundant communities |
4:45 AM (EDT) |
| 11:00 AM (CEST) |
Marta Biondo The collective dynamics of aerotaxis in an eukaryotic simple model |
Philipp Thomas Stochasticity in cellular growth: sources, propagation and consequences |
Andrea Riba A Model-Driven Quantitative Analysis of Retrotransposon Distributions in the Human Genome |
Andrea Mazzolini Evolutionary regularities in models with generic demographic dynamics |
5:00 AM (EDT) |
| 11:15 AM (CEST) |
Michael Manhart Predictability of bacterial adaptation at high resolution under antibiotic stress |
Julien Tailleur Motility regulation as a self-organization principle |
Stefano Garlaschi An Effective Resource-Competition Model for Species Coexistence |
Jean-François Arnoldi Fitness and community feedbacks: the two axis that drive long-term invasion impacts |
5:15 AM (EDT) |
| 11:30 AM (CEST) |
Lukas Eigentler Founder cell locations predict outcome of competitive interactions within colony biofilms |
Silvia Zaoli A macroecological description of gut microbial community dynamics |
Valentina Ros Counting equilibria of large well-mixed ecosystems with asymmetric interactions |
Luigi Esercito Lines of descent in a Moran model with frequency-dependent selection and mutation |
5:30 AM (EDT) |
| 11:45 AM (CEST) |
Marco Mauri Conditions and trade-offs to enhance protein production in synthetic bacterial communities |
Maria Ruiz Ortega Statistical analysis on antibody sharing repertoires |
Mike Fowler Emergent Dynamics in Evolutionary Games Played in Small World and Random Networks |
Enrico Di Gaspero Phylogeny and population genetics: The mutation process on the ancestral line |
5:45 AM (EDT) |
| 12:00 PM (CEST) |
Maaike Sangster Conditions and trade-offs to enhance protein production in synthetic bacterial communities - Poster |
Giorgio Nicoletti Modeling the emergence of scale-free fire outbreaks in Australia |
Francesco Puccioni Stochastic agent-based models of cell population growth |
David Alonso Rule-based disease dynamics, long-term predictions, and stochasticity in COVID19 |
6:00 AM (EDT) |
| 12:05 PM (CEST) |
Alex Samoletov Statistical approach to mathematical modeling in population dynamics and ecology |
Benjamin Planque Possibilistic modelling of food-web dynamics based on Chance and Necessity (CaN) |
Chandler Ross Stationary Density Predictions Based on Simulations and Real Data |
6:05 AM (EDT) |
|
| 12:10 PM (CEST) |
Maksim Mazuryn Mean Field Game Model for Diel Vertical Migration |
Thibaut Morel-Journel When expansion flounders: an extension of the concept of range pinning in ecology |
Discussion | 6:10 AM (EDT) |
|
| 12:15 PM (CEST) |
Discussion | Discussion | Break | 6:15 AM (EDT) |
|
| 12:45 PM (CEST) |
Break | Break | Break | 6:45 AM (EDT) |
|
| 1:00 PM (CEST) |
Break | Break | Break | Break | 7:00 AM (EDT) |
| 2:30 PM (CEST) |
Rosalind Allen Modelling the establishment of marine biofouling communities |
Eric Dykeman Towards a whole cell stochastic model of the ribosome in the cell |
Agnese Seminara Sensory navigation in turbulent environments |
Amandine Véber The effects of a weak selection pressure in a spatially structured population |
8:30 AM (EDT) |
| 3:30 PM (CEST) |
Alvaro Sanchez Engineering microbial communities by artificial selection |
David Nelson On Growth and Form of Microorganisms on Liquid Substrates |
Nigel Goldenfeld Topological scaling laws and the statistical mechanics of evolution |
Corina Tarnita Lack of synchronization: a key for collective systems robustness? |
9:30 AM (EDT) |
| 4:30 PM (CEST) |
Break | Break | Break | Break | 10:30 AM (EDT) |
| 5:00 PM (CEST) |
Terence Hwa Extensive cross-feeding as a general mechanism of microbial cooperation |
Susan Holmes Latent factors and microbial communities in the human microbiome |
Daniel Fisher Ecology, Continual Evolution, and Fine-Scale Microbial Diversity: What should — or should not — be surprising? |
Eleni Katifori Coarse grained models for transport in spatially embedded contact networks |
11:00 AM (EDT) |
| 6:00 PM (CEST) |
Martina Dal Bello Resource-diversity relationships in bacterial communities reflect the network structure of microbial metabolism |
Filippo Valle Emergent statistical laws in single-cell transcriptomic data |
Matteo Sireci A macroecological law of species interaction in microbial communities |
Lorenzo Masoero More for less: Predicting and maximizing genetic variant discovery via Bayesian nonparametrics |
12:00 PM (EDT) |
| 6:15 PM (CEST) |
Matti Gralka Niche partitioning and community assembly in marine microbes |
Connah Johnson Modelling environmental-metabolic feedback in spatially distributed populations of chemically coupled cells |
Nicola Rigolli Robust prediction of target location using turbulent odor plumes |
Hardik Rajpal Causal emergence and top-down control in Tangled Nature Model |
12:15 PM (EDT) |
| 6:30 PM (CEST) |
Sylvie Estrela Functional attractors in microbial community assembly |
Ricardo Martinez-Garcia Species exclusion and coexistence in stochastic models with a competition-colonization tradeoff |
Sophie De Buyl Heavy-tailed abundance distributions from stochastic Lotka-Volterra models |
Leonardo Miele Control strategies for heterogeneous plant pathogens: evolutionary and agricultural consequences |
12:30 PM (EDT) |
| 6:45 PM (CEST) |
Marco Saltini Ontogenetic niche shifts and the potential for adaptive diversification |
Moein Khalighi The impact of ecological memory on a microbial community model |
Gian Marco Palamara The Stochastic Nature of Functional Responses |
Georgios Gounaris The vasculature as an optimal perfusion network |
12:45 PM (EDT) |
| 6:50 PM (CEST) |
Amit Sharma Modelling and simulation to suppress the spread of COVID19 with impulsive vaccination |
12:50 PM (EDT) |
|||
| 6:55 PM (CEST) |
Pedro Henrique Cintra Evaluating the effect of non pharmaceutical interventions on COVID-19 infection dynamics through agent based models |
12:55 PM (EDT) |
|||
| 7:00 PM (CEST) |
Zoë Lange Resolving Energy Storage in Extra-Embryonic Membranes |
Discussion | Discussion | Conclusion | 1:00 PM (EDT) |
| 7:05 PM (CEST) |
Discussion | 1:05 PM (EDT) |
Green cells indicate contributed talks, red cells indicate invited talks and yellow cells indicate posters.


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| < Day Day Up > |
6.2 Breadcrumb PathfindingBreadcrumb pathfinding can make computer-controlled characters seem very intelligent because the player is unknowingly creating the path for the computer-controlled character. Each time the player takes a step, he unknowingly leaves an invisible marker, or breadcrumb, on the game world. When a game character comes in contact with a breadcrumb, the breadcrumb simply begins following the trail. The game character will follow in the footsteps of the player until the player is reached. The complexity of the path and the number of obstacles in the way are irrelevant. The player already has created the path, so no serious calculations are necessary. The breadcrumb method also is an effective and efficient way to move groups of computer-controlled characters. Instead of having each member of a group use an expensive and time-consuming pathfinding algorithm, you can simply have each member follow the leader's breadcrumbs. Figure 6-8 shows how each step the player takes is marked with an integer value. In this case, a maximum of 15 steps are recorded. In a real game, the number of breadcrumbs dropped will depend on the particular game and how smart you want the game-controlled characters to appear. In this example, a troll randomly moves about the tile-based environment until it detects a breadcrumb on an adjacent location. Figure 6-8. Breadcrumb trailOf course, in a real game, the player never sees the breadcrumb trail. It's there exclusively for the game AI. Example 6-3 shows the class we use to track the data associated with each game character. Example 6-3. ai_Entity class#define kMaxTrailLength 15 class ai_Entity { public: int row; int col; int type; int state; int trailRow[kMaxTrailLength]; int trailCol[kMaxTrailLength]; ai_Entity(); ~ai_Entity(); }; The initial #define statement sets the maximum number of player steps to track. We then use the kMaxTrailLength constant to define the bounds for the trailRow and trailCol arrays. The trailRow and trailCol arrays store the row and column coordinates of the previous 15 steps taken by the player. As Example 6-4 shows, we begin by setting each element of the trailRow and trailCol arrays to a value of -1. We use -1 because it's a value outside of the coordinate system we are using for this tile-based demo. When the demo first starts, the player hasn't taken any steps, so we need a way to recognize that some of the elements in the trailRow and trailCol arrays haven't been set yet. Example 6-4. Trail array initializationint i; for (i=0;i<kMaxTrailLength;i++) { trailRow[i]=-1; trailCol[i]=-1; } As you can see in Example 6-4, we traverse the entire trailRow and trailCol arrays, setting each value to -1. We are now ready to start recording the actual footsteps. The most logical place to do this is in the function that changes the player's position. Here we'll use the KeyDown function. This is where the demo checks the four direction keys and then changes the player's position if a key-down event is detected. The KeyDown function is shown in Example 6-5. Example 6-5. Recording the player positionsvoid ai_World::KeyDown(int key) { int i; if (key==kUpKey) for (i=0;i<kMaxEntities;i++) if (entityList[i].state==kPlayer) if (entityList[i].row>0) { entityList[i].row--; DropBreadCrumb(); } if (key==kDownKey) for (i=0;i<kMaxEntities;i++) if (entityList[i].state==kPlayer) if (entityList[i].row<(kMaxRows-1)) { entityList[i].row++; DropBreadCrumb(); } if (key==kLeftKey) for (i=0;i<kMaxEntities;i++) if (entityList[i].state==kPlayer) if (entityList[i].col>0) { entityList[i].col--; DropBreadCrumb(); } if (key==kRightKey) for (i=0;i<kMaxEntities;i++) if (entityList[i].state==kPlayer) if (entityList[i].col<(kMaxCols-1)) { entityList[i].col++; DropBreadCrumb(); } } The KeyDown function shown in Example 6-5 determines if the player has pressed any of the four direction keys. If so, it traverses the entityList array to search for a character being controlled by the player. If it finds one, it makes sure the new desired position is within the bounds of the tile world. If the desired position is legitimate, the position is updated. The next step is to actually record the position by calling the function DropBreadCrumb. The DropBreadCrumb function is shown in Example 6-6. Example 6-6. Dropping a breadcrumbvoid ai_World::DropBreadCrumb(void) { int i; for (i=kMaxTrailLength-1;i>0;i--) { entityList[0].trailRow[i]=entityList[0].trailRow[i-1]; entityList[0].trailCol[i]=entityList[0].trailCol[i-1]; } entityList[0].trailRow[0]=entityList[0].row; entityList[0].trailCol[0]=entityList[0].col; } The DropBreadCrumb function adds the current player position to the trailRow and trailCol arrays. These arrays maintain a list of the most recent player positions. In this case, the constant kMaxTrailLength sets the number of positions that will be tracked. The longer the trail, the more likely a computer-controlled character will discover it and pathfind its way to the player. The DropBreadCrumb function begins by dropping the oldest position in the trailRow and trailCol arrays. We are tracking only kMaxTrailLength positions, so each time we add a new position we must drop the oldest one. We do this with the initial for loop. In effect, this loop shifts all the positions in the array. It deletes the oldest position and makes the first array element available for the current player position. Next, we store the player's current position in the first element of the trailRow and trailCol arrays. The next step is to actually make the computer-controlled character detect and follow the breadcrumb trail that the player is leaving. The demo begins by having the computer-controlled troll move randomly about the tiled environment. Figure 6-9 illustrates how the troll moves about the tiled environment in any one of eight possible directions. Figure 6-9. Finding the breadcrumbsExample 6-7 goes on to show how the troll detects and follows the breadcrumb trail. Example 6-7. Following the breadcrumbsfor (i=0;i<kMaxEntities;i++) { r=entityList[i].row; c=entityList[i].col; foundCrumb=-1; for (j=0;j<kMaxTrailLength;j++) { if ((r==entityList[0].trailRow[j]) && (c==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r-1==entityList[0].trailRow[j]) && (c-1==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r-1==entityList[0].trailRow[j]) && (c==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r-1==entityList[0].trailRow[j]) && (c+1==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r==entityList[0].trailRow[j]) && (c-1==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r==entityList[0].trailRow[j]) && (c+1==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r+1==entityList[0].trailRow[j]) && (c-1==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r+1==entityList[0].trailRow[j]) && (c==entityList[0].trailCol[j])) { foundCrumb=j; break; } if ((r+1==entityList[0].trailRow[j]) && (c+1==entityList[0].trailCol[j])) { foundCrumb=j; break; } } if (foundCrumb>=0) { entityList[i].row=entityList[0].trailRow[foundCrumb]; entityList[i].col=entityList[0].trailCol[foundCrumb]; } else { entityList[i].row=entityList[i].row+Rnd(0,2)-1; entityList[i].col=entityList[i].col+Rnd(0,2)-1; } if (entityList[i].row<0) entityList[i].row=0; if (entityList[i].col<0) entityList[i].col=0; if (entityList[i].row>=kMaxRows) entityList[i].row=kMaxRows-1; if (entityList[i].col>=kMaxCols) entityList[i].col=kMaxCols-1; } the trailRow and trailCol arrays are ordered from the most recent player position to the oldest player position. Starting the search from the most recent player position also ensures that the troll will follow the breadcrumbs to, rather than away from, the player. It's quite probable that the troll will first detect a breadcrumb somewhere in the middle of the trailRow and trailCol arrays. We want to make sure the troll follows the breadcrumbs to the player. Once the for loop is finished executing, we check whether a breadcrumb has been found. The foundCrumb variable stores the array index of the breadcrumb found. If no breadcrumb is found, it contains its initial value of -1. If foundCrumb is greater than or equal to 0, we set the troll's position to the value stored at array index foundCrumb in the trailRow and trailCol arrays. Doing this each time the troll's position needs to be updated results in the troll following a trail to the player's position. If foundCrumb is equal to a value of -1 when we exit the for loop, we know that no breadcrumbs were found. In this case, we simply select a random direction in which to move. Hopefully, this random move will put the troll adjacent to a breadcrumb which can be detected and followed the next time the troll's position needs to be updated. There is another benefit to storing the most recent player positions in the lower trailRow and trailCol array elements. It is not unusual for a player to backtrack or to move in such a way that his path overlaps with or is adjacent to a previous location. This is illustrated in Figure 6-10. Figure 6-10. Following the shortest pathIn this case, the troll isn't going to follow the exact footsteps of the player. In fact, doing so would be rather unnatural. It would probably be obvious to the player that the troll was simply moving in the player's footsteps rather than finding its way to the player in an intelligent way. In this case, however, the troll will always look for the adjacent tile containing the most recent breadcrumb. The end result is that the troll will skip over breadcrumbs whenever possible. For example, in Figure 6-10, the troll would follow array elements {12,11,10,9,8,7,6,2} as it moves to the player's position. |
| < Day Day Up > |


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A collection of modules for building clientless applications for Realm of the Mad God.
This project is still in early development. First and foremost, this means that breaking changes are going to be quite common. While the project is still on v0, a breaking change will only constitute a minor version increment. When v1.0.0 is released, all breaking changes will go back to being a major version increment.
Being in early development also means that documentation (including usage guides) may not be as comprehensive until later in the development process.
As always, feel free to report bugs or submit feature requests on the GitHub issues page.
First, clone this repository.
git clone https://github.com/thomas-crane/n2
Change the current working directory of the console to the n2 folder.
cd n2
Then install the dependencies.
npm install
npm run gulp
Note that if gulp-cli
is globally installed, this, and subsequent mentions of npm run gulp
can simply be replaced with
gulp
This will clean and rebuild all n2 modules. To rebuild or clean an individual module, its name can be provided in the build
gulp script.
npm run gulp build:core
Will rebuild just the n2/core module.
There are several other gulp tasks which the main build tasks are composed of.
gulp clean
Will delete the build artifacts in every module. A single module can be cleaned by providing its name, e.g. gulp clean:net
.
gulp compile
Will compile all modules. Like the other commands, a single module can be compiled by using its name. e.g. gulp compile:common
.
Note that because of dependencies, the build order is
n2/updater and n2/core are able to compile in parallel, however they both depend on n2/common and n2/net.
Each module, except for n2/updater, hs an npm script which is used to generate the index.ts
files. It can be invoked by using
npm run index
From the module's root folder.
The gulp commands are mirrored in package.json
to provide npm script commands to invoke the gulp tasks. This means that
npm run clean
is the same as npm run gulp clean
npm run compile
is the same as npm run gulp compile
npm run build
is the same as npm run gulp build
The only difference is that module names cannot be provided with the npm script commands, e.g. npm run build:net
will not work.
There are also a few other scripts in the package.json
scripts,
npm run docs
- This runs TypeDoc to generate the API documentation.npm test
- This runs all of the unit tests with Mocha.n2 contains several modules which can be used separately or in combination with one another to build clientless applications.
@n2/updater
The updater module contains a utility class for downloading assets, and extracting packet IDs from the game client.
@n2/core
The core module is a good starting point for a clientless application. It contains a lightweight client class which can be extended.
@n2/net
The net module contains all networking related code for clientless applications. This includes packets and a packet IO class.
@n2/common
The common module contains interfaces and other classes which are used throughout other n2 modules.
Each module has its own readme where you will find more information about using the specific modules. As a brief overview,
This project uses the following open source software
Generated using TypeDoc


Honda City BS6 Petrol Launching Very Soon; To Be Priced From Rs. 10.22 Lakh
by Surendhar MThe existing City will continue on sale till the arrival of the next generation model towards the end of next year reportedly
According to several reports emerged on the internet, Honda Cars India is preparing to introduce the BSVI compliant City in the domestic market in the coming days. The petrol engined City sticking by the more stringent emission standards will reportedly be priced from Rs. 10.22 lakh and it goes all the way up to Rs. 14.68 lakh (ex-showroom, Mumbai).
In comparison to the current BSIV petrol variants, the price increase for the base SV manual is only Rs. 10,000 and for other variants, it costs Rs. 15,000 reportedly. The 1.5-litre i-VTEC petrol four-cylinder engine with BSVI updates will continue to produce 119 horsepower and it will be connected to either a six-speed manual or a CVT automatic transmission as in the current state.
The Japanese manufacturer employs the 1.5-litre i-DTEC diesel powertrain across its portfolio and it will be upgraded to meet BSVI norms ahead of the April 2020 deadline. Moreover, the smaller 1.2-litre petrol unit will also undergo updates to conform with the BSVI regulations in the coming months.
The major implication of the arrival of the updated petrol engine in the current generation City sedan is that the much-awaited next-gen model will likely take a little longer than anticipated to debut in the domestic market. Honda may continue to sell the existing City without any further updates.
| Variants | BS6 Honda City | BS4 Honda City |
| SV MT | Rs 10.22 lakh | Rs 10.12 lakh |
| V MT | Rs 11.13 lakh | Rs 10.98 lakh |
| V CVT | Rs 12.34 lakh | Rs 12.19 lakh |
| VX MT | Rs 12.17 lakh | Rs 12.01 lakh |
| VX CVT | Rs 13.48 lakh | Rs 13.33 lakh |
| ZX MT | Rs 13.35 lakh | Rs 13.20 lakh |
| ZX CVT | Rs 14.68 lakh | Rs 14.53 lakh |
The fifth generation Honda City will be unveiled on November 25 in Thailand and it will go on sale there before reaching other ASEAN markets. It is subjected to a range of exterior and interior changes and all of them are expected to up the ante in the segment and revive the sluggish sales numbers.
On the mechanical side, the diesel engine is said to get CVT gearbox in the fifth-gen City while a mild-hybrid system introduced in the latest Jazz sold globally will make it’s way into the Indian lineup sometime during the course of 2021.


A cookie is a baked or cooked food that is typically small, flat and sweet. It usually contains flour, sugar and some type of oil or fat. It may include other ingredients such as raisins, oats, chocolate chips, nuts
Our favorite Cookies that can be for all your family
We have multiple location a round the world
| Location | Opened | Closed |
|---|---|---|
| Seatle | 6:00 am | 8:00 pm |
| Dubai | 6:00 am | 8:00 pm |
| Tokyo | 6:00 am | 8:00 pm |
| Paris | 6:00 am | 8:00 pm |
| Lima | 6:00 am | 8:00 pm |


--- layout: page title: About Me description: This is what I do. background: '/img/bg-about.jpg' ---
Hi, I am Alexander Villasoto from the Philippines. I graduated with the degree in Information Technology, specializing in Web and Mobile Applications Development. Aside from being a software developer, I have also interests in Data Science, Machine Learning and Artificial Intelligence.
This blog is meant for sharing stuff that I currently explore, be it in the face of technology, books, movies, games, online courses or anything that interests me, posting them from time to time. Aside from these, I also think of this blog as my motivation towards completing something. For me to have a "written" record of what I am exploring.
I will also be available for discussion for every blog. Comments and suggestions are welcome and I will do my best to reply to you as soon as possible. You may also email me at<EMAIL_ADDRESS>Or fill up the form here and send me your message.