digikuery


Namedigikuery JSON
Version 20230529.post2 PyPI version JSON
download
home_page
SummaryDigikam database query tool
upload_time2023-05-29 19:20:48
maintainer
docs_urlNone
author
requires_python>=3.0
licenseBSD-3-Clause
keywords digikam database query
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            digikuery is a script to perform queries in [digikam](https://www.digikam.org/) (photo manager) database.

It can
* Query albums which contains tags matching a given regex
* Query most used tags and corresponding albums
* Print other tags present in matching albums
* List digikam database structure
* Provide an interactive python shell for manual queries

## Usage

``` bash
usage: digikuery.py [-h] [-d DBPATH] [-F] [-R ROOT] [-T [FILTER_TAGS]] {shell,schema,album,tag,stats} ...

digikuery - Digikam database query tool - v20230529

positional arguments:
  {shell,schema,album,tag,stats}
    shell                       spawn ipython shell to explor digikam database
    schema                      dump digikam database schema
    album               [album] list tags for one or all albums
    tag                 [tag]   list all tags or query single tag
                        -C      sort by result count
                        -I      show image details
    stats                       show digikam database statistics (default)

options:
  -h, --help            show this help message and exit
  -d DBPATH, --dbpath DBPATH
                        database path
  -F, --full-tagname    display full tag name
  -R ROOT, --root ROOT  restrict query to this root album
  -T [FILTER_TAGS], --filter-tags [FILTER_TAGS]
                        show and filter tags for displayed albums

examples:
List albums when tag 'Paquerette' is present, together with other tags of this album
$ digikuery tag Paquerette
```

## Install

``` bash
$ pip install digikuery
```

## Example: Query which albums contain given tag expression

Bellow we look for the "semaphore" name in all tags.

The query returns 2 tags "TagCommunication/Semaphore/Bleu" and "TagAlphabet/Semaphore", listing for each tag the albums containing tagged pictures.

``` bash
$ digikuery tag semaphore
  3 TagCommunication/Semaphore/Bleu
      album_albanie
      album_france
      album_grece
  1 TagAlphabet/Semaphore
      album_photos_19e_siecle
```

Providing -I option would list the picture names.

Let's just sort them by picture count:

```
$ digikuery tag -C semaphore
  3 TagCommunication/Semaphore/Bleu
      3 album_france
      2 album_grece
      2 album_albanie
  1 TagAlphabet/Semaphore
      19 album_photos_19e_siecle
```

For each matching album we can show if it contains other tags, for example tags maching "access"

``` bash
$ digikuery -T access tag semaphore
  3 TagCommunication/Semaphore/Bleu
      album_france
        TagAccess/Walking (9), TagAccess/Train(1)
      album_grece
		TagAccess/Car(6), TagAccess/Walking (3)
      album_albanie
		TagAccess/Walking (5)
```

## Interactive shell in database

```
$ digikuery shell
Interactive mode help:
   available objects
      dk.session
         dk.session.query(Album).count()
         dk.session.query(AlbumRoot).all()
         dk.session.query(Image).filter(Image.name == 'example.png').all()
         dk.session.query(Album, Tag, sqlalchemy.func.count(Tag.name)).join(imagetag).join(Image).join(Album)
      dk.engine
         access sqlalchemy engine
      dk.metadata
         access sqlalchemy metadata
   available functions
      help()
         print this message
      dk.query_album(album)
      dk.query_tag(tag)
      dk.schema()
      dk.stats()
running ipython...

In [1]:
```

## Internals

digikuery uses sqlalchemy to map digikam database to python objects.

            

Raw data

            {
    "_id": null,
    "home_page": "",
    "name": "digikuery",
    "maintainer": "",
    "docs_url": null,
    "requires_python": ">=3.0",
    "maintainer_email": "",
    "keywords": "digikam,database,query",
    "author": "",
    "author_email": "Laurent Ghigonis <ooookiwi@gmail.com>",
    "download_url": "https://files.pythonhosted.org/packages/90/3a/24527dff32f73c8f4a176bc6d11066324a90323e12743d1059d1933e6d6d/digikuery-20230529.post2.tar.gz",
    "platform": null,
    "description": "digikuery is a script to perform queries in [digikam](https://www.digikam.org/) (photo manager) database.\n\nIt can\n* Query albums which contains tags matching a given regex\n* Query most used tags and corresponding albums\n* Print other tags present in matching albums\n* List digikam database structure\n* Provide an interactive python shell for manual queries\n\n## Usage\n\n``` bash\nusage: digikuery.py [-h] [-d DBPATH] [-F] [-R ROOT] [-T [FILTER_TAGS]] {shell,schema,album,tag,stats} ...\n\ndigikuery - Digikam database query tool - v20230529\n\npositional arguments:\n  {shell,schema,album,tag,stats}\n    shell                       spawn ipython shell to explor digikam database\n    schema                      dump digikam database schema\n    album               [album] list tags for one or all albums\n    tag                 [tag]   list all tags or query single tag\n                        -C      sort by result count\n                        -I      show image details\n    stats                       show digikam database statistics (default)\n\noptions:\n  -h, --help            show this help message and exit\n  -d DBPATH, --dbpath DBPATH\n                        database path\n  -F, --full-tagname    display full tag name\n  -R ROOT, --root ROOT  restrict query to this root album\n  -T [FILTER_TAGS], --filter-tags [FILTER_TAGS]\n                        show and filter tags for displayed albums\n\nexamples:\nList albums when tag 'Paquerette' is present, together with other tags of this album\n$ digikuery tag Paquerette\n```\n\n## Install\n\n``` bash\n$ pip install digikuery\n```\n\n## Example: Query which albums contain given tag expression\n\nBellow we look for the \"semaphore\" name in all tags.\n\nThe query returns 2 tags \"TagCommunication/Semaphore/Bleu\" and \"TagAlphabet/Semaphore\", listing for each tag the albums containing tagged pictures.\n\n``` bash\n$ digikuery tag semaphore\n  3 TagCommunication/Semaphore/Bleu\n      album_albanie\n      album_france\n      album_grece\n  1 TagAlphabet/Semaphore\n      album_photos_19e_siecle\n```\n\nProviding -I option would list the picture names.\n\nLet's just sort them by picture count:\n\n```\n$ digikuery tag -C semaphore\n  3 TagCommunication/Semaphore/Bleu\n      3 album_france\n      2 album_grece\n      2 album_albanie\n  1 TagAlphabet/Semaphore\n      19 album_photos_19e_siecle\n```\n\nFor each matching album we can show if it contains other tags, for example tags maching \"access\"\n\n``` bash\n$ digikuery -T access tag semaphore\n  3 TagCommunication/Semaphore/Bleu\n      album_france\n        TagAccess/Walking (9), TagAccess/Train(1)\n      album_grece\n\t\tTagAccess/Car(6), TagAccess/Walking (3)\n      album_albanie\n\t\tTagAccess/Walking (5)\n```\n\n## Interactive shell in database\n\n```\n$ digikuery shell\nInteractive mode help:\n   available objects\n      dk.session\n         dk.session.query(Album).count()\n         dk.session.query(AlbumRoot).all()\n         dk.session.query(Image).filter(Image.name == 'example.png').all()\n         dk.session.query(Album, Tag, sqlalchemy.func.count(Tag.name)).join(imagetag).join(Image).join(Album)\n      dk.engine\n         access sqlalchemy engine\n      dk.metadata\n         access sqlalchemy metadata\n   available functions\n      help()\n         print this message\n      dk.query_album(album)\n      dk.query_tag(tag)\n      dk.schema()\n      dk.stats()\nrunning ipython...\n\nIn [1]:\n```\n\n## Internals\n\ndigikuery uses sqlalchemy to map digikam database to python objects.\n",
    "bugtrack_url": null,
    "license": "BSD-3-Clause",
    "summary": "Digikam database query tool",
    "version": "20230529.post2",
    "project_urls": {
        "Homepage": "https://github.com/looran/digikuery"
    },
    "split_keywords": [
        "digikam",
        "database",
        "query"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "b3e187734793633aaaf6991aacc46f0e41b5487af2888e9aa9a8aa8466a09094",
                "md5": "b2ee11aeaea8761d84733525179057d0",
                "sha256": "5b5dc5b9d11b75e24e45285ef1fd38456e9a3705117843a162c367c1edcf3725"
            },
            "downloads": -1,
            "filename": "digikuery-20230529.post2-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "b2ee11aeaea8761d84733525179057d0",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.0",
            "size": 6882,
            "upload_time": "2023-05-29T19:20:46",
            "upload_time_iso_8601": "2023-05-29T19:20:46.928365Z",
            "url": "https://files.pythonhosted.org/packages/b3/e1/87734793633aaaf6991aacc46f0e41b5487af2888e9aa9a8aa8466a09094/digikuery-20230529.post2-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "903a24527dff32f73c8f4a176bc6d11066324a90323e12743d1059d1933e6d6d",
                "md5": "0ed037a0cac2cbb71de8bb35ea6a2ba7",
                "sha256": "475c1fe80a58a50bf7516cb0fa86056619fd69ee8cf2375a8a32ab878a505e4f"
            },
            "downloads": -1,
            "filename": "digikuery-20230529.post2.tar.gz",
            "has_sig": false,
            "md5_digest": "0ed037a0cac2cbb71de8bb35ea6a2ba7",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.0",
            "size": 6124,
            "upload_time": "2023-05-29T19:20:48",
            "upload_time_iso_8601": "2023-05-29T19:20:48.252597Z",
            "url": "https://files.pythonhosted.org/packages/90/3a/24527dff32f73c8f4a176bc6d11066324a90323e12743d1059d1933e6d6d/digikuery-20230529.post2.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2023-05-29 19:20:48",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "looran",
    "github_project": "digikuery",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "digikuery"
}
        
Elapsed time: 0.08568s