note: this collection of scripts is unmaintained, and most were written using significantly older versions of their component libraries than currently available. A number are also still Python2.x and unlikely to be updated.
SCRIPT: ia_check_missing_metadata.py
DEPENDS ON: https://github.com/jjjake/internetarchive
PURPOSE: Checks for a given metadata element in Internet Archive item records. Returns a list of item identifiers for records in which the element DOES NOT appear.
USAGE: python ia_check_missing_metadata.py [list-of-identifiers.txt] [metadata element label]
SCRIPT: ia-search.py
DEPENDS ON: https://github.com/jjjake/internetarchive
PURPOSE: Returns a list of item identifiers in an Internet Archive collection.
USAGE: python ia-search.py [collection_to_search]
SCRIPT: ia-file-list.py
DEPENDS ON: https://github.com/jjjake/internetarchive
PURPOSE: Searches an Internet Archive collection for a string in identifier, returns first filename associated with identifier.
USAGE: python ia-file-list.py [collection_to_search] [search_string]
SCRIPT: ia-json.py
DEPENDS ON: https://github.com/jjjake/internetarchive
PURPOSE: Dumps JSON to for items within an Internet Archive collection
USAGE: python ia-json.py [collection_to_scrape] [outfile.json]
SCRIPT: iaCollectionCSVer.py
DEPENDS ON: https://github.com/jjjake/internetarchive
PURPOSE: to facilitate bulk update of extant Internet Archive items to a include a new collection.
PERFORMS THE FOLLOWING:
- Searches an existing IA collection for items with matching [search_string] in "title", "description", or "subject" fields.
- Fetches object metadata and appends a new collection field
- Outputs a CSV intended for re-upload with the internetarchive command line tool.
USAGE: python iaCollectionCSVer.py [search_string] [name_of-collection_to_search] [name_of_new_collection] [outfile.csv]
SCRIPT: ia-fetch-subjects.py
DEPENDS ON: https://github.com/jjjake/internetarchive
PURPOSE: Outputs a CSV containing [IDENTIFIER, TITLE, SUBJECT[0], SUBJECT[1], etc...]
USAGE: python ia-fetch-subjects.py [collection_to_search] [outfile.csv]
SCRIPT(s): cdm_x_dump.py
PURPOSE: Fetches & dumps objects from CONTENTdm via an XML file created with pyoaiharvester.
SEE: https://github.com/vphill/pyoaiharvester
XML File Creation: python pyoaiharvest.py -l [http://server.domain.edu:port/oai/oai.php] -o [outfile.xml] -m [CONTENTdm_collectionID]
DEPENDS ON:
- urllib2
- etree
USAGE: python script.py [IA_collection_ID] [outfile.csv]
NOTE: The Omeka CSV importer wants only items of a single type (e.g., still images, documents, etc). This script presumes all items in a collection are of mediatype:image (i.e., still images in jpg format).
SCRIPT: ia2omeka.py
DEPENDS ON: https://github.com/jjjake/internetarchive
PURPOSE: Outputs a CSV from an Internet Archive suitable for ingest into Omeka. Allows for easy migration/generation of Omeka collections from items in IA.
USAGE: python ia2omeka.py [IA_collection_ID] [outfile.csv]
SCRIPT: rm2mp4.py
DEPENDS ON:
- ffmpeg (or avconv)
- mplayer
- libx264
- libfaac
- a plaintext list of URLs for the RealMedia streams
PURPOSE: Dump RealMedia streeams from server and convert to mp4 audio
USAGE: python script.py [urllist.txt]
NOTE: this method is SLOOOOOOW and wonky and resource-heavy. The time to download and convert a .rm video is around 130% of the playback duration.
SCRIPT: fastimagecat.py
DEPENDS ON:
- feh, PIL, or TerminalImageViewer (https://github.com/stefanhaustein/TerminalImageViewer) depending on preference
- json
PURPOSE: To speed descriptive data entry for large image batches. Reads "default.json" (see example below) and queries empty values (i.e., reads each key, if key = "" asks for user input). Creates descriptive metadata for each image in a directory as individual JSON files based on user input.
USAGE: python script.py [working_directory]
EXAMPLE CONFIG (named "defaults.json", will ask user for title, creator, and date): { "collection" : "this collection", "rights" : "This image licesed under a CC-4.0-By license." "title" : "" "creator" : "" "date" : "" }
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent