Initial commit

.github/workflows/tests.yml

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+name: Unit and integration tests
+on:
+  workflow_dispatch:
+  push:
+    branches:
+      - main
+  pull_request:
+
+jobs:
+  build:
+    runs-on: ${{ matrix.os }}
+
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest, windows-latest]
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: |
+            3.11
+            3.12
+      - name: Install the latest version of uv
+        uses: astral-sh/setup-uv@v2
+      - name: Install project
+        run: uv sync --dev
+      - name: Run tests
+        run: uv run pytest --cov
+
+
+    # - name: Upload coverage reports to Codecov
+    #   uses: codecov/[email protected]
+    #   if: ${{ matrix.os == 'ubuntu-latest' }}
+    #   with:
+    #     token: ${{ secrets.CODECOV_TOKEN }}

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+*.DS_Store

.pre-commit-config.yaml

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+# See https://pre-commit.com for more information
+# See https://pre-commit.com/hooks.html for more hooks
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v5.0.0
+    hooks:
+      - id: trailing-whitespace
+      - id: end-of-file-fixer
+      - id: check-yaml
+      - id: check-added-large-files
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.6.9
+    hooks:
+      - id: ruff
+      - id: ruff-format
+        args: ['--exclude', 'src/autoparser/toml_writer.py']

README.md

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+# autoparser
+
+[![](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)
+[![tests](https://github.com/globaldothealth/autoparser/actions/workflows/tests.yml/badge.svg)](https://github.com/globaldothealth/autoparser/actions/workflows/tests.yml)
+<!-- [![codecov](https://codecov.io/gh/globaldothealth/autoparser/graph/badge.svg?token=AINU8PNJE3)](https://codecov.io/gh/globaldothealth/autoparser) -->
+[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
+
+autoparser helps in the generation of ADTL parsers as
+TOML files, which can then be processed by
+[adtl](https://github.com/globaldothealth/adtl) to transform files from the
+source schema to a specified schema.
+
+Contains functionality to:
+1. Create a basic data dictionary from a raw data file (`create-dict`)
+2. Use an LLM (currently only ChatGPT via the OpenAI API) to add descriptions to the 
+    data dictionary, to enable better parser auto-generation (`add-descriptions`)
+3. Create a mapping csv file linking source to target data fields and value mappings 
+    using the LLM, which can be edited by a user (`create-mapping`)
+4. Create a TOML parser file ready for use with ADTL, based on a JSON schema
+    (rules-based from the mapping file; `create-parser`).
+
+All 4 functions have both a command-line interface, and a python function associated.
+
+## Parser construction process (CLI)
+
+1. **Data**: Get the data as CSV or Excel and the data dictionary if available.
+
+2. **Creating autoparser config**: Optional step if the data is not in REDCap
+   (English) format. The autoparser config ([example](src/autoparser/config/redcap-en.toml))
+    specifies most of the variable configuration settings for autoparser.
+
+3. **Preparing the data dictionary**: If the data dictionary is not in CSV, or
+   split across multiple Excel sheets, then it needs to be combined to a single
+   CSV. If a data dictionary does not already exist, one can be created using
+
+   ```shell
+    autoparser create-dict <path to data> -o <parser-name>
+   ```
+
+   Here, `-o` sets the output name, and will create
+   `<parser-name>.csv`. For optional arguments (such as using a custom configuration
+   which was created in step 2), see `autoparser create-dict --help`.
+
+4. **Generate intermediate mappings (CSV)**: Run with config and data dictionary
+   to generate mappings:
+
+   ```shell
+   autoparser create-mapping <path to data dictionary> <path to schema> <language> <api key> -o <parser-name>
+   ```
+
+   Here `language` refers to the language of the original data, e.g. "fr" for french 
+   language data. `autoparser` defaults to using OpenAI as the LLM API, so the api key 
+   provided should be for the OpenAi platform. In future, alternative API's and/or a 
+   self-hosted llm are planned to be provided as options.
+
+5. **Curate mappings**: The intermediate mappings must be manually curated, as
+   the LLM may have generated false matches, or missed certain fields or value mappings.
+
+6. **Generate TOML**: This step is automated and should produce a TOML file that
+   conforms to the parser schema. 
+
+   For example:
+
+   ```shell
+   autoparser create-toml parser.csv <path to schema> -n parser
+   ```
+
+   will create `parser.toml` (specified using the `-n` flag) from the
+   intermediate mappings `parser.csv` file.
+
+7. **Review TOML**: The TOML file may contain errors, so it is recommended to
+   check it and alter as necessary.
+
+8. **Run adtl**: Run adtl on the TOML file and the data source. This process
+   will report validation errors, which can be fixed by reviewing the TOML file
+   and looking at the source data that is invalid.
+
+## Parser construction process (Python)
+
+An [example notebook](example.ipynb) has been provided using the test data to demonstrate
+the process of constructing a parser using the Python functions of `autoparser`.
+
+## Troubleshooting autogenerated parsers
+
+1. "I get validation errors like "'x' must be date":
+ADTL expects dates to be provided in ISO format (i.e. YYY-MM-DD). If your dates are
+formatted differently, e.g. "dd/mm/yyyy", you can add a line in the header
+of the TOML file (e.g. underneath the line "returnUnmatched=True") like this:
+
+```TOML
+defaultDateFormat = "%d/%m/%Y"
+```
+which should automatically convert the dates for you.
+
+2. ADTL can't find my schema (error: No such file or directory ..../x.schema.json)
+autoparser puts the path to the schema at the top of the TOML file, relative to the
+*current location of the parser* (i.e, where you ran the autoparser command from).
+If you have since moved the parser file, you will need to update the schema path at the
+top of the TOML parser.