With your Decision Optimization model, you can use the following input and output data identifiers and extension combinations.
Model type | Input file type | Output file type | Comments |
---|---|---|---|
cplex |
.lp .mps .sav .feasibility .prm .jar for Java™models |
.xml .json The name of the output file must be solution |
The output format can be specified by using the API. Files of type The schemas for the CPLEX formats for solutions, conflicts, and feasibility files are available for you to download in the cplex_xsds.zip archive from the Decision Optimization github. |
cpo |
.cpo .jar for Javamodels |
.xml .json The name of the output file must be solution |
The output format can be specified by using a run parameter. For the native file format for CPO models, see: CP Optimizer file format syntax. |
opl |
.mod .dat .oplproject .xlsx (deprecated) .json .csv .jar for Javamodels |
.xml .json .txt .csv .xlsx (deprecated) |
The output format is consistent with the input type, but can be specified by using a run
parameter if needed. To connect to Microsoft Excel files, use a data-connector. The data-connector
transforms your Excel file into a Only models that are defined with tuple sets can be deployed; other OPL structures are not supported. To read and write input and output in OPL, see OPL models. |
docplex |
.py *.* (input data) |
Any output file type that is specified in the model. | Any format can be used in your Python code, but to take advantage of data connectors, use
the .csv format.To read and write input and output in Python, use the commands
|
- Data identifier restrictions
- A file name has the following restrictions:
- Is limited to 255 characters
- Can include only ASCII characters
- Cannot include the characters
/\?%*:|"<>
, the space character, or the null character - Cannot include _ as the first character
- Referenced data
- When using data assets or connection assets for tabular data, use
.csv
as the data-identifier extension in theid
field, regardless of the asset type. The data-connector makes the necessary transformations, so that you can load or save data without needing to change the format of the data. You can thus use the same Decision Optimization model with many different data-source types and formats by using a data-connector to reference both the source and target data. If you use other data-identifier extensions, the data is loaded or saved as a raw-data binary-file without any transformation. For more information, see Input data sources for Decision Optimization deployment jobs and Output data for Decision Optimization deployment jobs.