swegram 2.1.2

CLI library for Swegram

Copyright (c) 2021 bmegyesi

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

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Description: # Swegram

## Introduction

Swegram is a tool that offers the ability to annotate and analyse Swedish and English texts. You can upload one or more texts and have them linguistically analysed with morphological and syntactic features. These linguistically annotated texts can then be used to perform quantitative linguistic text analysis; for example, the tool provides statistics about sentence lengths, total number of words, various readability metrics, part-of-speech (PoS) distribution, as well as frequency of lemmas, PoS, or misspelled words. The tool also visualize the syntactic relations between words in sentences and give detailed information about the distribution of various syntactic functions and relations in the text.

## Setup ENVIRONMENT VARIABLES `bash export SWEGRAM_WORKSPACE=$(pwd) `

## Install swegram command line interface

Before installation, it is strongly recommended to use a virtual environment `bash # Create virtual environment (Highly recommended) python3 -m venv venv source venv/bin/activate # Install swegram package pip install swegram --upgrade # Build dependencies swegram-build # Export pythonpath export PYTHONPATH="$PYTHONPATH:$(pwd):$(pwd)/tools/efselab" `

Check the usage of swegram cli

• swegram -h

`console usage: SWGRAM 1.0 [-h] -l {en,sv} -i INPUT_PATH [-o OUTPUT_DIR] [--output-format {txt,xlsx,json,csv}] {annotate,statistic} ... Swegram command line interface description positional arguments: {annotate,statistic} Swegram subparser annotate Annotation parser help statistic Statistic parser help `

` optional arguments: -h, --help show this help message and exit -l {en,sv}, --language {en,sv} choose the language for annotation -i INPUT_PATH, --input-path INPUT_PATH The input path to files/directory where working files are stored -o OUTPUT_DIR, --output-dir OUTPUT_DIR The output directory where working files are stored --save-as {txt,xlsx,json} The output format `

swegram annotate -h ` --normalize Process spelling checker after tokenization and normalized tokens will be used for upcoming annotation actions. --tokenize Process sentence segmentation and tokenization. --tag Process part-of-speech tagging. --parse Process syntactic dependency parsing. --aggregate Aggregate all annotated texts into one file. `

swegram statistic -h `console --include-metadata Include certain texts by selecting metadata. For instance, "--include-metadata key1 key2:value2" only selects the texts that contain key1 or key2:value2 in the metadata -- exclude-metadata Exclude certain texts by deselecting metadata -u --units Checking statistics of features given certain linguistic unit(s). The following units are valid to be chosen: corpus, text, paragraph, sentence --aspects Checking statistics on the basis of selection of certain aspect(s). The following aspects are valid to be chosen: general, readability, morph, lexical, syntactic --include-features Only certain features will be included --exclude-features Certain features will be excluded --print Flag to print the result on console `

## Run annotate and statistic actions with swegram

• For example, if you want to annotate one text file called “10-sv.txt” in the existing Resource folder named “resources/corpus/raw”, the final conll file will be generated in a folder called output-folder, type the following command

`bash swegram --language sv --input-path resources/corpus/raw/10-sv.txt --output-dir output-folder annotate `

• If you have executed the command above and have the annotated file in the folder named output-folder, you can use the following command to analyze the annotated text(s) and get statistics.

`tips Please remove all metafiles in the output folder, namely all files do not end up with ".conll". rm output/*.tok output/*.tag output/*.txt `

Now, type the following command: `bash swegram --language sv --input-path output statistic `

## Dependencies

• [udpipe](https://ufal.mff.cuni.cz/udpipe/1/install)

` g++ 4.7 or newer, clang 3.2 or newer, Visual C++ 2015 or newer make SWIG 3.0.8 or newer for language bindings other than C++ `

• [efselab](https://github.com/robertostling/efselab)

• [pandoc](https://pandoc.org)

## Run swegram desktop version

Tested with following requirements on ubuntu:20.04

• docker (Docker version 20.10.22)

Run desktop under the root of repository locally: `bash bash run.sh `

## Run swegram with Docker Desktop on macOS ### Preparation

• Docker Desktop is installed. If not, please check [here](https://docs.docker.com/desktop/install/mac-install/) for installation. Only recent macOS versions are supported. It may be reuqired to update macOS. For our use case, please install according to the recommended setting.

• These ports are supposed to be available for Swegram desktop.

  • 80 (nginx proxy to serve frontend)

  • 8000 (fastapi app as backend to handle requests)

  • 3306 (mysql database)

• [Docker hub](https://hub.docker.com/) account

  This is used due to backend image is stored in docker hub.

### Guideline to start swegram desktop on your mac.

1. Generate static files to serve frontend pages:

`bash cd frontend docker build -t vue-builder -f Dockerfile.build . docker run --rm -v $(pwd)/dist:/root/dist vue-bulder `

2. Go to the repository root path, and run the following command to spin up the container

`bash docker compose --profile client up -d ` When the containers are up, go to the following [link](http://localhost/#/en)

### Good to know when using swegram desktop on macOS

• It is not able to build the docker image locally on macOS due to limitation of udpipe binary. The image will be pulled from [docker hub](https://hub.docker.com/)

• It takes a while before database is ready. Therefore, backend server will be up after 30 seconds sleep.

• To exit swegram desktop. You can do docker compose –profile client down

Platform: UNKNOWN Classifier: Framework :: Fastapi Classifier: Programming Language :: Python :: 3 Description-Content-Type: text/markdown