Jupyter notebook providing VTL support through Trevas engine
Run mvn package to bundle the VTL Kernel.
TODO
docker build . -t jupyter_vtl
docker run -p 8888:8888 jupyter_vtlCustom functions have been introduced into the Trevas engine.
| Name | Arguments | Returned type | Description |
|---|---|---|---|
| loadParquet | String url | Dataset | Load Parquet dataset |
| loadCSV (1) | String url | Dataset | Load CSV dataset |
| loadSas | String url | Dataset | Load Sas dataset |
| loadSDMXEmptySource | (String sdmxMesUrl, String structureId) | Dataset | Load SDMX empty source |
| loadSDMXSource (2) | (String sdmxMesUrl, String structureId, String dataUrl) | Dataset | Load SDMX source |
| writeParquet | (String url, Dataset ds) | String | Write given dataset in Parquet |
| writeCSV (3) | (String url, Dataset ds) | String | Write given dataset in CSV |
| show | Dataset ds | DisplayData | Display firt rows of a given dataset |
| showMetadata | Dataset ds | DisplayData | Display metadata of a given dataset |
| runSDMXPreview | String sdmxMesUrl | DisplayData | Run SDMX VTL transformations, with empty datasets, to obtain Persitent defined datasets |
| runSDMX (4) | (String sdmxMesUrl, String dataLocations ) | DisplayData | Run SDMX VTL transformations, with sources, to obtain Persitent defined datasets |
| getTransformationsVTL | String sdmxMesUrl | String | Display VTL transformations defined in the SDMX Message file |
| getRulesetsVTL | String sdmxMesUrl | String | Display VTL rulesets defined in the SDMX Message file |
| size | Dataset ds | String | Display size of a given dataset |
Default option values:
| Name | Value |
|---|---|
| header | true |
| delimiter | ; |
| quote | " |
Any CSV option can be defined or overridden thanks to url parameters (values have to be encoded).
For instance, to read a CSV content where delimiter is | and quote is ':
loadCSV(...?delimiter=%7C"e=%27)
Sources has to be .csv files for now.
Default option values:
| Name | Value |
|---|---|
| header | true |
| delimiter | ; |
| quote | " |
Any CSV option can be defined or overridden thanks to url parameters (values have to be encoded).
For instance, to write a CSV with a content delimited by | and quoted by ':
writeCSV(...?delimiter=%7C"e=%27)
Sources has to be .csv files for now.
Second argument, dataLocations has to be a string separated field containing SDMX structure id and source location (ex: structId1,dataLocation1,structId2,dataLocation2)
INIT_PROJECT_URL docker environment variable enable to load a default project in your Trevas Jupyter instance.
Have a look to this project definition for instance.
Fill the INIT_PROJECT_URL environment variable with your script adress and run:
docker pull inseefrlab/trevas-jupyter:latest
docker run -p 8888:8888 -e INIT_PROJECT_URL="https://raw.githubusercontent.com/Making-Sense-Info/Trevas-Jupyter-Training/main/init-notebook.sh" inseefrlab/trevas-jupyter:latest