Title: A 'Neo4J' Driver
Version: 0.1.1
Description: A Modern and Flexible 'Neo4J' Driver, allowing you to query data on a 'Neo4J' server and handle the results in R. It's modern in the sense it provides a driver that can be easily integrated in a data analysis workflow, especially by providing an API working smoothly with other data analysis and graph packages. It's flexible in the way it returns the results, by trying to stay as close as possible to the way 'Neo4J' returns data. That way, you have the control over the way you will compute the results. At the same time, the result is not too complex, so that the "heavy lifting" of data wrangling is not left to the user.
License: MIT + file LICENSE
URL: https://github.com/neo4j-rstats/neo4r
BugReports: https://github.com/neo4j-rstats/neo4r/issues
Imports: attempt, data.table, glue, httr, igraph, jsonlite, magrittr, purrr, R6, rlang, rstudioapi, shiny, tibble, tidyr, tidyselect, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-02-15 22:04:51 UTC; colin
Author: Colin Fay ORCID iD [cre, aut], ThinkR [cph], Neo4J [spn]
Maintainer: Colin Fay <contact@colinfay.me>
Repository: CRAN
Date/Publication: 2019-02-15 22:20:03 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Call Neo4J API

Description

Call Neo4J API

Usage

call_neo4j(query, con, type = c("row", "graph"), output = c("r",
  "json"), include_stats = FALSE, include_meta = FALSE)

Arguments

query

The cypher query

con

A NEO4JAPI connection object

type

Return the result as row or as graph

output

Use "json" if you want the output to be printed as JSON

include_stats

tShould the stats about the transaction be included?

include_meta

tShould the stats about the transaction be included?

Value

the result from the Neo4J Call

Extract nodes or relationships

Description

Extract nodes or relationships

Usage

extract_nodes(x)

extract_relationships(x)

Arguments

x

a result from Neo4J

Value

a tibble

Launch Neo4J Connection Pane

Description

Launch Neo4J Connection Pane

Usage

launch_con_pane(con)

Arguments

con

a connection object

Value

an opened Connection Pane

Load a CSV to Neo4J

Description

Load a CSV to Neo4J

Usage

load_csv(on_load = "", con, url, header = TRUE,
  periodic_commit = 1000, as = "csv", type = c("row", "graph"),
  output = c("r", "json"), include_stats = TRUE,
  include_meta = FALSE)

Arguments

on_load

the code to execute on load

con

A NEO4JAPI connection object

url

the url of the csv

header

does the csv have a header?

periodic_commit

the PERIODIC COMMIT cypher arg

as

the AS cypher arg

type

Return the result as row or as graph

output

Use "json" if you want the output to be printed as JSON

include_stats

tShould the stats about the transaction be included?

include_meta

tShould the stats about the transaction be included?

Value

a csv loaded to Neo4J

A Neo4J Connexion

Description

A Neo4J Connexion

Usage

neo4j_api

Format

An object of class R6ClassGenerator of length 24.

Value

A Neo4J Connexion

Methods

access

list url, user and password

ping

test your connexion

version

Neo4J version

get

Get a list of either relationship, labels,

get

Get a list of either relationship, labels,

get

Get a list of either relationship, labels,

get

Get a list of either relationship, labels,

get

Get a list of either relationship, labels,

Data

url

list url, user and password

user

test your connexion

Examples

## Not run: 
con <- neo4j_api$new(url = "http://localhost:7474", user = "neo4j", password = "password")

## End(Not run)

Opening the Neo4J connection Pane

Description

For intenral use

Usage

on_connection_opened(con, url, auth)

Arguments

con

A connection object

url

The url of the database

auth

The auth token

Read a cypher file

Description

Read a cypher file

Usage

read_cypher(file)

Arguments

file

the path to the cypher file

Value

a tibble with the queries

Examples

## Not run: 
read_cypher("random/create.cypher")

## End(Not run)

Run the connection app

Description

For internal use

Usage

run_app()

Send a cypher file to be executed

Description

Send a cypher file to be executed

Usage

send_cypher(path, con, type = c("row", "graph"), output = c("r",
  "json"), include_stats = TRUE, meta = FALSE)

Arguments

path

the path to the cypher file

con

a connexion object created with neo4j_api$new()

type

the type of the format to query for (row or graph)

output

the printing method (r or json)

include_stats

whether of not to include stats

meta

whether of not to include meta info

Value

a cypher call

Examples

## Not run: 
send_cypher("random/create.cypher")
path <- "data-raw/constraints.cypher"

## End(Not run)

Unnest both relationships and nodes

Description

Unnest both relationships and nodes

Usage

unnest_graph(res)

Arguments

res

an api graph result

Value

a list of two unnested data.frames

Unnest a node data.frame

Description

Unnest a node data.frame

Usage

unnest_nodes(nodes_tbl, what = c("all", "label", "properties"))

Arguments

nodes_tbl

the node table

what

what to unnest

Value

a new dataframe

Unnest a Relationships table

Description

Unnest a Relationships table

Usage

unnest_relationships(relationships_tbl)

Arguments

relationships_tbl

a relationship table

Value

an unnested table

Note

Please note that the properties will be converted to character if the class is not unique.

Turn a named vector into a cypher list

Description

'vec_to_cypher()' creates a list, and 'vec_to_cypher_with_var()' creates a cypher call starting with a variable.

Usage

vec_to_cypher(vec, label)

vec_to_cypher_with_var(vec, label, variable)

Arguments

vec

the vector

label

the label of each vector

variable

the variable to use (for 'vec_to_cypher()')

Details

This function can be used with small vectors you want to send to the server. It can for example be used this way : “' paste("MERGE", vec_to_cypher(iris[1, 1:3], "Species")) “' to create a cypher call.

Value

a character vector

Examples


vec_to_cypher(iris[1, 1:3], "Species")
vec_to_cypher_with_var(iris[1, 1:3], "Species", a)