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Python Libraray to provide a wrapper for accessing the API for the german newspaper portal

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Deutsche-Digitale-Bibliothek/ddblabs-ddbapi

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Wrapper for the DDB API

  • Query the DDB API for Newspapers
  • returns a Pandas Dataframe Object

Usage:

from ddbapi import zp_issues, zp_pages, list_column, filter

df = zp_issues(publication_date='[1600-09-01T12:00:00Z TO 1699-12-31T12:00:00Z]')
print(df)

zp_issues

  • Returns a DataFrame containing Data on Newspaper-Issues.
  • Use any combination of these keyword arguments:
    • language: Use ISO Codes, currently ger, eng, fre, spa, ita
    • place_of_distribution: Search inside "Verbreitungsort", use a list for multiple search-words
    • publication_date: Get newspapers by publication date. Use the following format: 1900-12-31T12:00:00Z for a specific date, use square brackets and TO between two dates to get a daterange like so: publication_date='[1935-09-01T12:00:00Z TO 1935-09-22T12:00:00Z]' - time is always 12:00:00Z.
    • zdb_id: Search by ZDB-ID
    • provider: Search by Data Provider
    • paper_title: Search inside the title of the Newspaper

zp_pages

  • Returns a DataFrame containing Data on Newspaper-Pages.
  • Use any combination of these keyword arguments:
    • plainpagefulltext: Search inside the OCR Fulltext (Use a list for multiple search-words)
    • language: Use ISO Codes, currently ger, eng, fre, spa, ita
    • place_of_distribution: Search inside "Verbreitungsort", use a list for multiple search-words
    • publication_date: Get newspapers by publication date. Use the following format: 1900-12-31T12:00:00Z for a specific date, use square brackets and TO between two dates to get a daterange like so: publication_date='[1935-09-01T12:00:00Z TO 1935-09-22T12:00:00Z]' - time is always 12:00:00Z.
    • zdb_id: Search by ZDB-ID
    • provider: Search by Data Provider
    • paper_title: Search inside the title of the Newspaper

  • Values of keyword arguments may contain lists to combine queries.
  • Use list_column and filter to perform usual Pandas Operations on list-containing Columns (eg. list_column(df['place_of_distribution']).value_counts() or filter('Altona', 'place_of_distribution', df))

Example

See this Notebook for a usage example.

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