sppcls 0.1.0

Accessing and processing data from the DFG-funded SPP Computational Literary Studies

Python code for working with the data of the DFG-funded SPP Computational Literary Studies.

• sppcls.py: the sppcls Python module to access the data:
  • blocking:

  from sppcls import sppcls
  df = sppcls.load_df(work="judenbuche", projects=["keypassages"])
  print(df.describe())
  

  • non blocking:

  from sppcls import sppcls
  df = await sppcls.load_df_async(work="judenbuche", projects=["keypassages"])
  print(df.describe())
  

Installation

PyPI

pip install sppcls

or with spacy

pip install sppcls[spacy]

From source

Setup an virtual environment, if necessary:

python3 -m venv env
source env/bin/activate

Install dependencies:

pip install -r requirements.txt

Note

For tokenization, the spacy model is required:

python -m spacy download de_core_news_lg

Usage

The package offers a command line interface, either by using the command sppcls after installing using PyPI or python -m sppcls.cli.sppclscli when running from source.

usage: sppclscli.py [-h] {tokenise,check} ...

Accessing and processing data from the DFG-funded SPP Computational Literary
Studies

positional arguments:
  {tokenise,check}
    tokenise        Tokenize text file and create output tsv.
    check           Compare two tsv files and check that the structures
                    matches.

optional arguments:
  -h, --help        show this help message and exit

tokenise

Tokenise takes a txt file, e.g. work.txt, and produces a tsv file containing the tokenized text, e.g. work.tsv. This base tsv file is then extended by the individual projects.

usage: sppclscli.py tokenise [-h] input_file output_folder

Tokenize text file and create output tsv.

positional arguments:
  input_file     Path to the input txt file.
  output_folder  Path to the output folder where the output tsv will be saved.

optional arguments:
  -h, --help     show this help message and exit

TODO: fix character offset to be byte instead

check

check.py takes two tsv files, e.g. work.tsv and keypassages.tsv, and makes sure that the project tsv file matches the structure of the base work tsv file.

usage: sppclscli.py check [-h] org-tokens-file-path project-tokens-file-path

Compare two tsv files and check that the structures matches.

positional arguments:
  org-tokens-file-path  Path to the original tokens tsv file
  project-tokens-file-path
                        Path to the project tokens tsv file

optional arguments:
  -h, --help            show this help message and exit