fsgdb is a graph like database based on the file system. Based on a root folder (or node), you can create subfolders/subnodes and attach data to each node by creating paresable files in each directory.
By allowing to merge data from parent nodes (think of: having a "blog" folder/node which contains metadata about your blog, which is then merged with each blog-entry-folder/sub-node), you can store data efficiently and deduplicated while maintaining a clear folder structure that is easily editable with standard editors.
At the moment, the following parsers are supported:
- markdown: Parses markdown (
*.md
) files and attaches the parsed HTML content to eachnode.markdown.<filename> = "<parsedMarkdown>"
- yaml: Parses yaml (
*.yml
) files and attaches the parsed properties to eachnode.<filename> = { <parsedProperties> }
, with the exception that the properties of the filemetadata.yml
are added directly to the node without the in-between<filename>
object. - images: Parses jpeg (
*.jpg
) files, reads out exif information and creates (if configured withcreateThumbnails: true
) thumbnails. Adds helper functions that return image/thumbnail data. Note that for generating thumbnails, GraphicsMagick/ImageMagick needs to be installed on the system.
Hint: although the examples here are written in coffeescript, the module works with javascript as well.
The database is initialized by specifying a root directory and the list of parsers to use. Then, the directory can be scanned and data loaded.
FileSystemGraphDatabase = require('fsgdb').FileSystemGraphDatabase
graph = new FileSystemGraphDatabase({ path: './sampleApp/sampleData'})
graph.registerParser('MarkdownParser')
graph.registerParser('YamlParser')
loadingPromise = graph.load()
Based on the graph, the root node can be accessed and the tree can be traversed.
loadingPromise.then (rootNode) ->
# Check for a property
boolean = rootNode.hasProperty('propertyName')
# Get a property
value = rootNode.getProperty('propertyName')
# Merge properties with values from parents (useful for deduplication of common data)
mergedProperties = rootNode.flattenProperties()
# use on nodes with children
allLeaves = rootNode.getAllLeaves()
Instead of walking manually through nodes, queries can be used to filter efficiently. Queries are chainable.
Query = require('fsgdb').Query
q = new Query(rootNode)
# The most basic method is the .filter method, which expects a callback.
# This callback should return true or false if the given node passes the filter or not
q = q.filter (properties, node) -> return true
# Helper functions to simplify querying
# Query all nodes that have a property which contains a certain element:
q = q.whichContains('tags', 'technology')
# Or check for the existence of a property
q = q.withProperty('markdown')
#...that also must have a certain value
q = q.withProperty('date', '2015-12-31')
# Results can be given either as the direct results nodes (where the individual nodes
# might have children with different properties that do not match
# the query when properties are flattened)
nodes = q.resultNodes()
# Or get the leaves (nodes without children) with flattened properties to directly continue working with the
# combined data
nodes = q.resultLeaves()