Python data processing based on existing Matlab Code -
Budget: $30 – $250 USD
Job Description:
We are seeking an experienced freelancer proficient in both Matlab and Python to translate existing Matlab code into Python. The task involves translating all functionality of the code while improving the structure of the code and adding a comprehensive set of sensible unit tests.
Project Details:
1. Translate existing Matlab code (~200 lines of code) into Python. The new code must produce the same outputs as the old (though in Parquet file format)
2. Improve the code's structure. The new Python code should follow coding best practices. I.e. introduce separate classes where it makes sense, break down logic into methods etc.
3. Add comprehensive suite of unit tests. All relevant business logic must be covered by a set of granular, sensible unit tests.
4. Coding guidelines: Python code must follow the PEP 8 standard, be formatted with black and isort.
5. Python environment: Code must use the following Python environment:
Python 3.11.9
pandas==2.2.2
pyarrow==17.0.0
jupyter==1.0.0
black==24.4.2
isort==5.13.2
flake8==7.1.0
No additional requirements may be added.
6. Input files: There are 6 input data files in ".mat" format. They must be translated to Parquet files.
7. Output file: The Python code should produce the same output as the Matlab code, but stored in Parquet format.
Provided Materials:
• Matlab Code: Current implementation in Matlab.
• Input files: 6 input data files in the formats used by the Matlab code (".mat" format)
• Example output file: Example outputs from the Matlab code for verification purposes (".mat" format).
• Documentation: No additional documentation apart from the Matlab code.
Deliverables:
1. Python Code: Fully functional Python version of the Matlab code, following all requirements laid out in "Project Details" above.
2. Unit test: Comprehensive suite of unit tests covering all relevant business logic.
3. Documentation: Instructions for running the Python code, including a list of dependencies and any setup required.
4. Verification: Demonstration that the Python code produces results consistent with the Matlab code using the provided input files and example outputs.
We are seeking an experienced freelancer proficient in both Matlab and Python to translate existing Matlab code into Python. The task involves translating all functionality of the code while improving the structure of the code and adding a comprehensive set of sensible unit tests.
Project Details:
1. Translate existing Matlab code (~200 lines of code) into Python. The new code must produce the same outputs as the old (though in Parquet file format)
2. Improve the code's structure. The new Python code should follow coding best practices. I.e. introduce separate classes where it makes sense, break down logic into methods etc.
3. Add comprehensive suite of unit tests. All relevant business logic must be covered by a set of granular, sensible unit tests.
4. Coding guidelines: Python code must follow the PEP 8 standard, be formatted with black and isort.
5. Python environment: Code must use the following Python environment:
Python 3.11.9
pandas==2.2.2
pyarrow==17.0.0
jupyter==1.0.0
black==24.4.2
isort==5.13.2
flake8==7.1.0
No additional requirements may be added.
6. Input files: There are 6 input data files in ".mat" format. They must be translated to Parquet files.
7. Output file: The Python code should produce the same output as the Matlab code, but stored in Parquet format.
Provided Materials:
• Matlab Code: Current implementation in Matlab.
• Input files: 6 input data files in the formats used by the Matlab code (".mat" format)
• Example output file: Example outputs from the Matlab code for verification purposes (".mat" format).
• Documentation: No additional documentation apart from the Matlab code.
Deliverables:
1. Python Code: Fully functional Python version of the Matlab code, following all requirements laid out in "Project Details" above.
2. Unit test: Comprehensive suite of unit tests covering all relevant business logic.
3. Documentation: Instructions for running the Python code, including a list of dependencies and any setup required.
4. Verification: Demonstration that the Python code produces results consistent with the Matlab code using the provided input files and example outputs.