# antlr-tsql
[](https://travis-ci.org/datacamp/antlr-tsql)
[](https://badge.fury.io/py/antlr-tsql)
## Development
ANTLR requires Java, so we suggest you use Docker when building grammars. The `Makefile` contains directives to clean, build, test and deploy the ANTLR grammar. It does not run Docker itself, so run `make` inside Docker.
### Build the grammar
```bash
# Build the docker container
docker build -t antlr_tsql .
# Run the container to build the python grammar
# Write parser files to local file system through volume mounting
docker run -it -v ${PWD}:/usr/src/app antlr_tsql make build
```
### Set up the Python module
Now that the Python parsing files are available, you can install them with `pip`:
```bash
pip install -r requirements.txt
pip install -e .
```
And parse SQL code in Python:
```python
from antlr_tsql import ast
ast.parse("SELECT a from b")
```
### Using the AST viewer
If you're actively developing on the ANLTR grammar or the tree shaping, it's a good idea to set up the [AST viewer](https://github.com/datacamp/ast-viewer) locally so you can immediately see the impact of your changes in a visual way.
- Clone the ast-viewer repo and build the Docker image according to the instructions.
- Spin up a docker container that volume mounts the Python package, symlink-installs the package and runs the server on port 3000:
```bash
docker run -it \
-u root \
-v ~/workspace/antlr-tsql:/app/app/antlr-tsql \
-p 3000:3000 \
ast-viewer \
/bin/bash -c "echo 'Install development requirements in development:' \
&& pip install --no-deps -e app/antlr-tsql \
&& python3 run.py"
```
When simultaneously developing other packages, volume mount and install those too:
```bash
docker run -it \
-u root \
-v ~/workspace/antlr-ast:/app/app/antlr-ast \
-v ~/workspace/antlr-plsql:/app/app/antlr-plsql \
-v ~/workspace/antlr-tsql:/app/app/antlr-tsql \
-p 3000:3000 \
ast-viewer \
/bin/bash -c "echo 'Install development requirements in development:' \
&& pip install --no-deps -e app/antlr-ast \
&& pip install --no-deps -e app/antlr-plsql \
&& pip install --no-deps -e app/antlr-tsql \
&& python3 run.py"
```
- If you update the tree shaping logic in this repo, the app will auto-update.
- If you change the grammar, you will have to first rebuild the grammar (with the `antlr_tsql` docker image) and restart the `ast-viewer` container.
### Run tests
```bash
# Similar to building the grammar, but running tests
# and not saving the generated files
docker build -t antlr_tsql .
docker run -t antlr_tsql make build test
```
Or run the test locally, first build the grammar then run:
```python
pytest
```
## Travis deployment
- Builds the Docker image.
- Runs the Docker image to build the grammar and run the unit tests.
- Deploys the resulting python files to PyPi when a new release is made, so they can be installed easily.
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"description": "# antlr-tsql\n\n[](https://travis-ci.org/datacamp/antlr-tsql)\n[](https://badge.fury.io/py/antlr-tsql)\n\n## Development\n\nANTLR requires Java, so we suggest you use Docker when building grammars. The `Makefile` contains directives to clean, build, test and deploy the ANTLR grammar. It does not run Docker itself, so run `make` inside Docker.\n\n### Build the grammar\n\n```bash\n# Build the docker container\ndocker build -t antlr_tsql .\n\n# Run the container to build the python grammar\n# Write parser files to local file system through volume mounting\ndocker run -it -v ${PWD}:/usr/src/app antlr_tsql make build\n```\n\n### Set up the Python module\n\nNow that the Python parsing files are available, you can install them with `pip`:\n\n```bash\npip install -r requirements.txt\npip install -e .\n```\n\nAnd parse SQL code in Python:\n\n```python\nfrom antlr_tsql import ast\nast.parse(\"SELECT a from b\")\n```\n\n### Using the AST viewer\n\nIf you're actively developing on the ANLTR grammar or the tree shaping, it's a good idea to set up the [AST viewer](https://github.com/datacamp/ast-viewer) locally so you can immediately see the impact of your changes in a visual way.\n\n- Clone the ast-viewer repo and build the Docker image according to the instructions.\n- Spin up a docker container that volume mounts the Python package, symlink-installs the package and runs the server on port 3000:\n\n```bash\ndocker run -it \\\n -u root \\\n -v ~/workspace/antlr-tsql:/app/app/antlr-tsql \\\n -p 3000:3000 \\\n ast-viewer \\\n /bin/bash -c \"echo 'Install development requirements in development:' \\\n && pip install --no-deps -e app/antlr-tsql \\\n && python3 run.py\"\n```\n\nWhen simultaneously developing other packages, volume mount and install those too:\n\n```bash\ndocker run -it \\\n -u root \\\n -v ~/workspace/antlr-ast:/app/app/antlr-ast \\\n -v ~/workspace/antlr-plsql:/app/app/antlr-plsql \\\n -v ~/workspace/antlr-tsql:/app/app/antlr-tsql \\\n -p 3000:3000 \\\n ast-viewer \\\n /bin/bash -c \"echo 'Install development requirements in development:' \\\n && pip install --no-deps -e app/antlr-ast \\\n && pip install --no-deps -e app/antlr-plsql \\\n && pip install --no-deps -e app/antlr-tsql \\\n && python3 run.py\"\n```\n\n- If you update the tree shaping logic in this repo, the app will auto-update.\n- If you change the grammar, you will have to first rebuild the grammar (with the `antlr_tsql` docker image) and restart the `ast-viewer` container.\n\n### Run tests\n\n```bash\n# Similar to building the grammar, but running tests\n# and not saving the generated files\ndocker build -t antlr_tsql .\ndocker run -t antlr_tsql make build test\n```\n\nOr run the test locally, first build the grammar then run:\n\n```python\npytest\n```\n\n## Travis deployment\n\n- Builds the Docker image.\n- Runs the Docker image to build the grammar and run the unit tests.\n- Deploys the resulting python files to PyPi when a new release is made, so they can be installed easily.",
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