dataset

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README

dataset

DOI

dataset is a command line tool, a Go package, and an experimental C shared library for working with JSON objects as collections. Collections are stored on your local disk. JSON objects are stored in collections as plain UTF-8 text files. This means the objects can be accessed with common Unix text processing tools as well as most programming languages. dataset is also available as a Python package, see py_dataset

The dataset command line tool supports common data management operations such as initialization of collections; document creation, reading, updating and deleting; listing keys of JSON objects in the collection.

datasets's enhanced features include

  • aggregate objects into data frames
  • import, export and synchronize JSON objects to and from CSV files
  • generate sample sets of keys and objects

See Getting started with dataset for a tour and tutorial. Both the command line and examples in Python 3 using using py_dataset are included.

Design choices

dataset isn't a database or a replacement for a repository system. It is tool to manage JSON documents in a predictable and structured way. dataset is guided by the idea that you should be able to work with JSON documents as easily as you can any plain text document on Unix. dataset is intended to be simple to use with minimal setup (e.g. dataset init mycollection.ds creates a new collection called 'mycollection.ds'). It is built around the following abstractions

  • dataset stores JSON objects in collections
  • collections are folder(s) containing
    • collection.json metadata file
    • a pairtree of JSON object documents
    • support for attachments to JSON documents

The choice of plain UTF-8 is intended to help future proof reading dataset collections. Care has been taken to keep dataset simple enough and light weight enough that it will run on a machine as small as a Raspberry Pi Zero while being equally comfortable on a more resource rich server or desktop environment. dataset can be re-implement in any programming language supporting file input and output, common string operations and a JSON encoding and decoding.

Example Workflow

A typical processing pattern is to write a "harvester" which then stores it results in a dataset collection. This is often followed by another program that transforms or aggregates harvested material before rendering a prepared output, e.g. web pages or data files. At Caltech Library the harvesters are typically written in Python or Bash storing the results in a dataset collection. Depending on the performance needs transform and aggregates stages are written either in Python or Go and our final rendering stages are typically written in Python or as simple Bash scripts.

Features

dataset supports

  • Basic storage actions (create, read, update and delete)
  • listing of collection keys
  • import/export of CSV files
  • The ability to reshape data by performing simple object joins
  • The ability to create data frames from while collections or based on keys lists
    • frames are defined using dot paths describing what is to be pulled out of a stored JSON objects

You can work with dataset collections via the command line tool, via Go using the dataset package or in Python 3.8 using the py_dataset python package. dataset is useful for general data science applications which need intermediate JSON object management but not a full blown database.

Limitations of dataset

dataset has many limitations, some are listed below

  • it is not a multi-process, multi-user data store (it stores files on disk without locking)
  • it is not a replacement for a repository management system
  • it is not a general purpose database system
  • it does not supply automatic version control on collections, objects or attachments
  • it stores all keys to lower case in order to deal with file systems that are not case sensitive
  • it does not have a built-in query language for filtering or sorting

Explore dataset through A Shell Example, Getting Started with Dataset, How To guides, topics and Documentation.

Releases

Compiled versions are provided for Linux (x86), Mac OS X (x86 and M1), Windows 10 (x86) and Raspberry Pi OS (ARM7). See https://github.com/caltechlibrary/dataset/releases.

You can use dataset from Python via the py_dataset package.

Documentation

Overview

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Package dataset provides a common approach for storing JSON object documents on local disc. It is intended as a single user system for intermediate processing of JSON content for analysis or batch processing. It is not a database management system (if you need a JSON database system I would suggest looking at Couchdb, Mongo and Redis as a starting point).

The approach dataset takes is to store JSON documents in a pairtree structure under the collection folder. The keys are the JSON document names. JSON documents (and possibly their attachments) are then stored based on that assignment in the pairtree. Conversely the collection.json document is used to find and retrieve documents from the collection. The layout of the metadata is as follows

+ Collection - a directory

  • Collection/collection.json - metadata for retrieval
  • Collection/[Pairtree] - holds individual JSON docs and attachments

A key feature of dataset is to be Posix shell friendly. This has lead to storing the JSON documents in a directory structure that standard Posix tooling can traverse. It has also mean that the JSON documents themselves remain on "disc" as plain text. This has facilitated integration with many other applications, programming langauages and systems.

Attachments are non-JSON documents explicitly "attached" that share the same pairtree path but are placed in a sub directory called "_". If the document name is "Jane.Doe.json" and the attachment is photo.jpg the JSON document is "pairtree/Ja/ne/.D/e./Jane.Doe.json" and the photo is in "pairtree/Ja/ne/.D/e./_/photo.jpg".

Additional operations beside storing and reading JSON documents are also supported. These include creating lists (arrays) of JSON documents from a list of keys, listing keys in the collection, counting documents in the collection, indexing and searching by indexes.

The primary use case driving the development of dataset is harvesting API content for library systems (e.g. EPrints, Invenio, ArchivesSpace, ORCID, CrossRef, OCLC). The harvesting needed to be done in such a way as to leverage existing Posix tooling (e.g. grep, sed, etc) for processing and analysis.

Initial use case:

Caltech Library has many repository, catelog and record management systems (e.g. EPrints, Invenion, ArchivesSpace, Islandora, Invenio). It is common practice to harvest data from these systems for analysis or processing. Harvested records typically come in XML or JSON format. JSON has proven a flexibly way for working with the data and in our more modern tools the common format we use to move data around. We needed a way to standardize how we stored these JSON records for intermediate processing to allow us to use the growing ecosystem of JSON related tooling available under Posix/Unix compatible systems.

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Package dataset includes the operations needed for processing collections of JSON documents and their attachments.

Authors R. S. Doiel, <rsdoiel@library.caltech.edu> and Tom Morrel, <tmorrell@library.caltech.edu>

Copyright (c) 2021, Caltech All rights not granted herein are expressly reserved by Caltech.

Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.

THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

Index

Constants

View Source 
const (
	// Asc is used to identify ascending sorts
	Asc = iota
	// Desc is used to identify descending sorts
	Desc = iota
)
View Source 
const (

	// License is a formatted from for dataset package based command line tools
	License = `` /* 1530-byte string literal not displayed */

)
View Source 
const Version = "1.0.1"

Variables

This section is empty.

Functions

func Check added in v0.1.0 

func Check(cName string, verbose bool) error

Check checks a dataset collection and reports error to console. NOTE: Collection objects are locked during check!

func Close added in v0.1.0 

func Close(cName string) error

Close closes a dataset collections previously opened by CMapOpen(). It will also set the internal cMap variable to nil if there are no remaining collections.

func CloseAll added in v0.1.0 

func CloseAll() error

CloseAll goes through the service collection list and closes each one.

func Collections added in v0.1.0 

func Collections() []string

Collections returns a list of collections previously opened with CMapOpen()

func CreateJSON added in v0.1.0 

func CreateJSON(cName string, key string, src []byte) error

CreateJSON takes a collection name, key and JSON object document and creates a new JSON object in the collection using the key.

func DecodeJSON added in v0.1.0 

func DecodeJSON(src []byte, obj *map[string]interface{}) error

DecodeJSON provides a common method for decoding data for use in Dataset.

func DeleteJSON added in v0.1.0 

func DeleteJSON(cName string, key string) error

DeleteJSON takes a collection name and key and removes and JSON object from the collection.

func EncodeJSON added in v0.1.0 

func EncodeJSON(obj map[string]interface{}) ([]byte, error)

EncodeJSON provides a common method for encoding data for use in Dataset.

func FrameClear added in v0.1.0 

func FrameClear(cName string, fName string) error

FrameClear clears the object and key list from a frame

func FrameDelete added in v0.1.0 

func FrameDelete(cName string, fName string) error

FrameDelete deletes a frame from a service collection

func FrameExists added in v0.1.0 

func FrameExists(cName string, fName string) bool

FrameExists returns true if frame found in service collection, otherwise false

func FrameKeys added in v0.1.0 

func FrameKeys(cName string, fName string) []string

FrameKeys returns the ordered list of keys for the frame.

func FrameObjects added in v0.1.0 

func FrameObjects(cName string, fName string) ([]map[string]interface{}, error)

FrameObjects returns a JSON document of a copy of the objects in a frame for the service collection. It is analogous to a dataset.ReadJSON but for a frame's object list

func FrameReframe added in v0.1.0 

func FrameReframe(cName string, fName string, keys []string, verbose bool) error

FrameReframe updates the frame object list. If a list of keys is provided then the object will be replaced with updated objects based on the keys provided.

func FrameRefresh added in v0.1.0 

func FrameRefresh(cName string, fName string, verbose bool) error

FrameRefresh updates the frame object list's for the keys provided. Any new keys 

cause a new object to be appended to the end of the list.

func Frames added in v0.1.0 

func Frames(cName string) []string

Frames returns a list of frame names in a service collection

func GetContact added in v0.1.0 

func GetContact(cName string) string

GetContact gets the contact info for the collection.

func GetVersion added in v0.1.0 

func GetVersion(cName string) string

GetVersion gets the version info for the collection.

func GetWhat added in v0.1.0 

func GetWhat(cName string) string

GetWhat get the What metadata value for a collection.

func GetWhen added in v0.1.0 

func GetWhen(cName string) string

GetWhen gets the When value for a collection

func GetWhere added in v0.1.0 

func GetWhere(cName string) string

GetWhere gets the Where value for a collection

func GetWho added in v0.1.0 

func GetWho(cName string) string

GetWho get the Who metadata value for a collection.

func IsCollection added in v0.0.45 

func IsCollection(p string) bool

IsCollection checks to see if a given path contains a collection.json file

func IsOpen added in v0.1.0 

func IsOpen(cName string) bool

IsOpen checks to see if a dataset collection is already opened.

func KeyExists added in v0.1.0 

func KeyExists(cName string, key string) bool

KeyExists returns true if the key exists in the collection or false otherwise

func Keys added in v0.1.0 

func Keys(cName string) []string

Keys returns a list of keys for a collection opened with StartCMap.

func Open 

func Open(cName string) error

Open opens a dataset collection for use in a service like context. CMap collections remain "open" until explicitly closed or closed via CloseAll(). Writes to the collections are run through a mutex to prevent collisions. Subsequent CMapOpen() will open additional collections under the the service.

func ReadJSON added in v0.1.0 

func ReadJSON(cName string, key string) ([]byte, error)

ReadJSON takes a collection name, key and returns a JSON object document.

func Repair added in v0.0.3 

func Repair(cName string, verbose bool) error

Repair repairs a collection NOTE: Collection objects are locked during repair!

func SetContact added in v0.1.0 

func SetContact(cName string, contact string) error

SetContact sets the metadata value for the collection's version.

func SetVersion added in v0.1.0 

func SetVersion(cName string, version string) error

SetVersion sets the metadata value for the collection's version.

func SetWhat added in v0.1.0 

func SetWhat(cName string, what string) error

SetWhat sets the What value for a collection

func SetWhen added in v0.1.0 

func SetWhen(cName string, when string) error

SetWhen sets the When value of a collection

func SetWhere added in v0.1.0 

func SetWhere(cName string, where string) error

SetWhere sets the Where value of a collection

func SetWho added in v0.1.0 

func SetWho(cName string, names string) error

SetWho sets the collection's Who metadata value for a collection

func UpdateJSON added in v0.1.0 

func UpdateJSON(cName string, key string, src []byte) error

UpdateJSON takes a collection name, key and JSON object document and updates the collection.

Types

type Attachment 

type Attachment struct {
	// Name is the filename and path to be used inside the generated tar file
	Name string `json:"name"`

	// Size remains to to help us migrate pre v0.0.61 collections.
	// It should reflect the last size added.
	Size int64 `json:"size"`

	// Sizes is the sizes associated with the version being attached
	Sizes map[string]int64 `json:"sizes"`

	// Current holds the semver to the last added version
	Version string `json:"version"`

	// Checksum, current implemented as a MD5 checksum for now
	// You should have one checksum per attached version.
	Checksums map[string]string `json:"checksums"`

	// HRef points at last attached version of the attached document, e.g. v0.0.0/photo.png
	// If you moved an object out of the pairtree it should be a URL.
	HRef string `json:"href"`

	// VersionHRefs is a map to all versions of the attached document
	// {
	//    "v0.0.0": "... /photo.png",
	//    "v0.0.1": "... /photo.png",
	//    "v0.0.2": "... /photo.png"
	// }
	VersionHRefs map[string]string `json:"version_hrefs"`

	// Created a date string in RTC3339 format
	Created string `json:"created"`

	// Modified a date string in RFC3339 format
	Modified string `json:"modified"`

	// Metadata is a map for application specific metadata about attachments.
	Metadata map[string]interface{} `json:"metadata,omitempty"`
}

Attachment is a structure for holding non-JSON content metadata you wish to store alongside a JSON document in a collection

type CMap added in v0.1.0 

type CMap struct {
	// contains filtered or unexported fields
}

CMap holds a map of collection names to *Collection

type Collection 

type Collection struct {
	// DatasetVersion of the collection
	DatasetVersion string `json:"dataset_version"`

	// Name (filename) of collection
	Name string `json:"name"`

	// KeyMap holds the document key to path in the collection
	KeyMap map[string]string `json:"keymap"`

	// FrameMap is a list of frame names and with rel path to the frame defined in the collection
	FrameMap map[string]string `json:"frames"`

	// Created is the date/time the init command was run in
	// RFC1123 format.
	Created string `json:"created,omitempty"`

	// Version of collection being stored in semvar notation
	Version string `json:"version,omitempty"`

	// Contact info
	Contact string `json:"contact,omitempty"`

	// CodeMeta is a relative path or URL to a Code Meta
	// JSON document for the collection.  Often it'll be
	// in the collection's root and have the value "codemeta.json"
	// but also may be stored someplace else. It should be
	// an empty string if the codemeta.json file has not been
	// created.
	CodeMeta string `json:"codemeta,omitempty"`

	// Who is the person(s)/organization(s) that created the collection
	Who []string `json:"who,omitempty"`
	// What - description of collection
	What string `json:"what,omitempty"`
	// When - date associated with collection (e.g. 2021,
	// 2021-10, 2021-10-02), should map to an approx date like in
	// archival work.
	When string `json:"when,omitempty"`
	// Where - location (e.g. URL, address) of collection
	Where string `json:"where,omitempty"`
	// contains filtered or unexported fields
}

Collection is the container holding a pairtree containing JSON docs

func GetCollection added in v0.1.0 

func GetCollection(cName string) (*Collection, error)

GetCollection takes a collection name, opens it if necessary and returns a handle to the CMapCollection struct and error value.

func InitCollection added in v0.0.8 

func InitCollection(name string) (*Collection, error)

InitCollection - creates a new collection.

func (*Collection) AttachFile added in v0.0.33 

func (c *Collection) AttachFile(keyName, semver string, fullName string) error

AttachFile is for attaching a single non-JSON document to a dataset record. It will replace ANY existing attached content with the same semver and basename.

func (*Collection) AttachFiles 

func (c *Collection) AttachFiles(keyName string, semver string, fileNames ...string) error

AttachFiles attaches non-JSON documents to a JSON document in the collection. Attachments are stored in a tar file, if tar file exits then attachment(s) are appended to tar file.

func (*Collection) AttachStream added in v0.0.63 

func (c *Collection) AttachStream(keyName, semver, fullName string, buf io.Reader) error

AttachStream is for attaching open a non-JSON file buffer (via an io.Reader).

func (*Collection) Attachments 

func (c *Collection) Attachments(keyName string) ([]string, error)

Attachments returns a list of files and size attached for a key name in the collection

func (*Collection) Clone added in v0.0.39 

func (c *Collection) Clone(cloneName string, keys []string, verbose bool) error

Clone copies the current collection records into a newly initialized collection given a list of keys and new collection name. Returns an error value if there is a problem. Clone does NOT copy attachments, only the JSON records.

func (*Collection) CloneSample added in v0.0.39 

func (c *Collection) CloneSample(trainingCollectionName string, testCollectionName string, keys []string, sampleSize int, verbose bool) error

CloneSample takes the current collection, a sample size, a training collection name and a test collection name. The training collection will be created and receive a random sample of the records from the current collection based on the sample size provided. Sample size must be greater than zero and less than the total number of records in the current collection.

If the test collection name is not an empty string it will be created and any records not in the training collection will be cloned from the current collection into the test collection.

func (*Collection) Close 

func (c *Collection) Close() error

Close closes a collection, writing the updated keys to disc

func (*Collection) Create 

func (c *Collection) Create(name string, data map[string]interface{}) error

Create a JSON doc from an map[string]interface{} and adds it to a collection, if problem returns an error name must be unique. Document must be an JSON object (not an array).

func (*Collection) CreateJSON added in v0.0.33 

func (c *Collection) CreateJSON(key string, src []byte) error

CreateJSON adds a JSON doc to a collection, if a problem occurs it returns an error

func (*Collection) CreateObjectsJSON added in v0.0.70 

func (c *Collection) CreateObjectsJSON(keyList []string, src []byte) error

CreateObjectsJSON takes a list of keys and creates a default object for each key as quickly as possible. NOTE: if object already exist creation is skipped without reporting an error.

func (*Collection) Delete 

func (c *Collection) Delete(name string) error

Delete removes a JSON doc from a collection

func (*Collection) DocPath 

func (c *Collection) DocPath(name string) (string, error)

DocPath returns a full path to a key or an error if not found

func (*Collection) ExportCSV added in v0.0.3 

func (c *Collection) ExportCSV(fp io.Writer, eout io.Writer, f *DataFrame, verboseLog bool) (int, error)

ExportCSV takes a reader and frame and iterates over the objects generating rows and exports then as a CSV file

func (*Collection) ExportTable added in v0.0.47 

func (c *Collection) ExportTable(eout io.Writer, f *DataFrame, verboseLog bool) (int, [][]interface{}, error)

ExportTable takes a reader and frame and iterates over the objects generating rows and exports then as a CSV file

func (*Collection) FrameClear added in v0.1.0 

func (c *Collection) FrameClear(name string) error

FrameClear empties the frame's object and key lists but leaves in place the Frame definition. Use Reframe() to re-populate a frame based on a new key list.

func (*Collection) FrameCreate added in v0.1.0 

func (c *Collection) FrameCreate(name string, keys []string, dotPaths []string, labels []string, verbose bool) (*DataFrame, error)

FrameCreate takes a set of collection keys, dot paths and labels builds an ObjectList and assembles additional metadata returning a new Frame associated with the collection as well as an error value. If there is a mis-match in number of labels and dot paths an an error will be returned. If the frame already exists an error will be returned.

Conceptually a frame is an ordered list of objects. Frames are associated with a collection and the objects in a frame can easily be refreshed. Frames also serve as the basis for indexing a dataset collection and provide the data paths (expressed as a list of "dot paths"), labels (aka attribute names), and type information needed for indexing and search.

If you need to update a frame's objects use FrameRefresh(). If you need to change a frame's objects or ordering use FrameReframe().

func (*Collection) FrameDelete added in v0.1.0 

func (c *Collection) FrameDelete(name string) error

FrameDelete removes a frame from a collection, returns an error if frame can't be deleted.

func (*Collection) FrameExists added in v0.1.0 

func (c *Collection) FrameExists(name string) bool

FrameExists checkes to see if a frame is already defined. Returns true if it exists otherwise false

func (*Collection) FrameObjects added in v0.1.0 

func (c *Collection) FrameObjects(fName string) ([]map[string]interface{}, error)

FrameObjects returns a copy of a DataFrame's object list given a collection's frame name.

func (*Collection) FrameRead added in v0.1.0 

func (c *Collection) FrameRead(name string) (*DataFrame, error)

FrameRead retrieves a frame from a collection. Returns the DataFrame and an error value

func (*Collection) FrameReframe added in v0.1.0 

func (c *Collection) FrameReframe(name string, keys []string, verbose bool) error

FrameReframe **replaces** a frame's object list based on the keys provided.

func (*Collection) FrameRefresh added in v0.1.0 

func (c *Collection) FrameRefresh(name string, verbose bool) error

FrameRefresh updates a DataFrames' object list based on the existing keys in the frame. It doesn't change the order of objects. NOTE: If an object is missing in the collection it gets pruned from the object list.

func (*Collection) Frames added in v0.0.41 

func (c *Collection) Frames() []string

Frames retrieves a list of available frames associated with a collection

func (*Collection) GetAttachedFiles 

func (c *Collection) GetAttachedFiles(keyName string, semver string, filterNames ...string) error

GetAttachedFiles returns an error if encountered, a side effect is the file(s) are written to the current work directory If no filterNames provided then return all attachments are written out An error value is always returned.

func (*Collection) ImportCSV added in v0.0.3 

func (c *Collection) ImportCSV(buf io.Reader, idCol int, skipHeaderRow bool, overwrite bool, verboseLog bool) (int, error)

ImportCSV takes a reader and iterates over the rows and imports them as a JSON records into dataset. BUG: returns lines processed should probably return number of rows imported

func (*Collection) ImportTable added in v0.0.4 

func (c *Collection) ImportTable(table [][]interface{}, idCol int, useHeaderRow bool, overwrite, verboseLog bool) (int, error)

ImportTable takes a [][]interface{} and iterates over the rows and imports them as a JSON records into dataset.

func (*Collection) IsKeyNotFound added in v0.0.69 

func (c *Collection) IsKeyNotFound(e error) bool

IsKeyNotFound checks an error message and returns true if it is a key not found error.

func (*Collection) Join added in v0.0.47 

func (c *Collection) Join(key string, obj map[string]interface{}, overwrite bool) error

Join takes a key, a map[string]interface{}{} and overwrite bool and merges the map with an existing JSON object in the collection. BUG: This is a naive join, it assumes the keys in object are top level properties.

func (*Collection) KeyExists added in v0.1.0 

func (c *Collection) KeyExists(key string) bool

KeyExists returns true if key is in collection's KeyMap, false otherwise

func (*Collection) KeySortByExpression added in v0.0.33 

func (c *Collection) KeySortByExpression(keys []string, expr string) ([]string, error)

KeySortByExpression takes a array of keys and a sort expression and turns a sorted list of keys.

func (*Collection) Keys 

func (c *Collection) Keys() []string

Keys returns a list of keys in a collection

func (*Collection) Length added in v0.0.6 

func (c *Collection) Length() int

Length returns the number of keys in a collection

func (*Collection) MergeFromTable added in v0.0.47 

func (c *Collection) MergeFromTable(frameName string, table [][]interface{}, overwrite bool, verbose bool) error

MergeFromTable - uses a DataFrame associated in the collection to map columns from a table into JSON object attributes saving the JSON object in the collection. If overwrite is true then JSON objects for matching keys will be updated, if false only new objects will be added to collection. Returns an error value

func (*Collection) MergeIntoTable added in v0.0.47 

func (c *Collection) MergeIntoTable(frameName string, table [][]interface{}, overwrite bool, verbose bool) ([][]interface{}, error)

MergeIntoTable - uses a DataFrame associated in the collection to map attributes into table appending new content and optionally overwriting existing content for rows with matching ids. Returns a new table (i.e. [][]interface{}) or error.

func (*Collection) ObjectList added in v0.0.61 

func (c *Collection) ObjectList(keys []string, dotPaths []string, labels []string, verbose bool) ([]map[string]interface{}, error)

ObjectList (on a collection) takes a set of collection keys and builds an ordered array of objects from the array of keys, dot paths and labels provided.

func (*Collection) Prune added in v0.0.33 

func (c *Collection) Prune(keyName string, semver string, filterNames ...string) error

Prune a non-JSON document from a JSON document in the collection.

func (*Collection) Read 

func (c *Collection) Read(name string, data map[string]interface{}, cleanObject bool) error

Read finds the record in a collection, updates the data interface provide and if problem returns an error name must exist or an error is returned

func (*Collection) ReadJSON added in v0.0.33 

func (c *Collection) ReadJSON(name string) ([]byte, error)

ReadJSON finds a the record in the collection and returns the JSON source

func (*Collection) SaveFrame added in v0.0.47 

func (c *Collection) SaveFrame(name string, f *DataFrame) error

SaveFrame saves a frame in a collection or returns an error

func (*Collection) Update 

func (c *Collection) Update(name string, data map[string]interface{}) error

Update JSON doc in a collection from the provided data interface (note: JSON doc must exist or returns an error )

func (*Collection) UpdateJSON added in v0.0.33 

func (c *Collection) UpdateJSON(name string, src []byte) error

UpdateJSON a JSON doc in a collection, returns an error if there is a problem

type DataFrame added in v0.0.41 

type DataFrame struct {
	// Explicit at creation
	Name string `json:"frame_name"`

	// CollectionName holds the name of the collection the frame was generated from. In theory you could
	// define a frame in one collection and use its results in another. A DataFrame can be rendered as a JSON
	// document.
	CollectionName string `json:"collection_name"`

	// DotPaths is a slice holding the definitions of what each Object attribute's data source is.
	DotPaths []string `json:"dot_paths"`

	// Labels are new attribute names for fields create from the provided
	// DotPaths.  Typically this is used to surface a deeper dotpath's
	// value as something more useful in the frame's context (e.g.
	// first_title from an array of titles might be labeled "title")
	Labels []string `json:"labels"`

	// NOTE: Keys is an orded list of object keys in the frame.
	Keys []string `json:"keys"`

	// NOTE: Object map privides a quick index by key to object index.
	ObjectMap map[string]interface{} `json:"object_map"`

	// Created is the date the frame is originally generated and defined
	Created time.Time `json:"created"`

	// Updated is the date the frame is updated (e.g. reframed)
	Updated time.Time `json:"updated"`
}

DataFrame is the basic structure holding a list of objects as well as the definition of the list (so you can regenerate an updated list from a changed collection). It persists with the collection.

func FrameCreate added in v0.1.0 

func FrameCreate(cName string, fName string, keys []string, dotPaths []string, labels []string, verbose bool) (*DataFrame, error)

FrameCreate creates a frame in a service collection

func (*DataFrame) Grid added in v0.0.41 

func (f *DataFrame) Grid(includeHeaderRow bool) [][]interface{}

Grid returns a Grid representaiton of a DataFrame's ObjectList

func (*DataFrame) Objects added in v0.0.64 

func (f *DataFrame) Objects() []map[string]interface{}

Objects returns a copy of DataFrame's object list (an array of map[string]interface{})

func (*DataFrame) String added in v0.0.41 

func (f *DataFrame) String() string

String renders the data structure DataFrame as JSON to a string

type Err added in v0.0.62 

type Err struct {
	Msg string
}

Err holds Semver's error messages

func (*Err) Error added in v0.0.62 

func (err *Err) Error() string

type KeyValue added in v0.0.7 

type KeyValue struct {
	// JSON Record ID in collection
	ID string
	// The value of the field to be sorted from record
	Value interface{}
}

KeyValue holds an ID string and value interface, this lets us work with numeric keys and to sort them.

type KeyValues added in v0.0.7 

type KeyValues []KeyValue

KeyValues is a list of keys (strings) to records. This type exists to allow easy sorting.

func (KeyValues) Len added in v0.0.7 

func (a KeyValues) Len() int

func (KeyValues) Less added in v0.0.7 

func (a KeyValues) Less(i, j int) bool

func (KeyValues) Swap added in v0.0.7 

func (a KeyValues) Swap(i, j int)

type Semver added in v0.0.62 

type Semver struct {
	// Major version number (required, must be an integer as string)
	Major string `json:"major"`
	// Minor version number (required, must be an integer as string)
	Minor string `json:"minor"`
	// Patch level (optional, must be an integer as string)
	Patch string `json:"patch,omitempty"`
	// Suffix string, (optional, any string)
	Suffix string `json:"suffix,omitempty"`
}

Semver holds the information to generate a semver string

func ParseSemver added in v0.0.62 

func ParseSemver(src []byte) (*Semver, error)

ParseSemver takes a byte slice and returns a version struct, and an error value.

func (*Semver) IncMajor added in v0.0.64 

func (sv *Semver) IncMajor() error

IncMajor increments a major version number, zeros minor and patch values. Returns an error if increment fails.

func (*Semver) IncMinor added in v0.0.64 

func (sv *Semver) IncMinor() error

IncMinor increments a minor version number and zeros the patch level or returns an error. Returns an error if increment fails.

func (*Semver) IncPatch added in v0.0.64 

func (sv *Semver) IncPatch() error

IncPatch increments the patch level if it is numeric or returns an error.

func (*Semver) String added in v0.0.62 

func (sv *Semver) String() string

func (*Semver) ToJSON added in v0.0.62 

func (sv *Semver) ToJSON() []byte

ToJSON takes a version struct and returns JSON as byte slice

Source Files

View all Source files

Directories

Path Synopsis
cmd
dataset
dataset is a command line tool, Go package, shared library and Python package for working with JSON objects as collections on local disc.
 dataset is a command line tool, Go package, shared library and Python package for working with JSON objects as collections on local disc.
tbl.go provides some utility functions to move string one and two demensional slices into/out of one and two deminsional slices.
 tbl.go provides some utility functions to move string one and two demensional slices into/out of one and two deminsional slices.

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