Asset Allocation project
Project description
ToC:
- [Asset-Allocation](#asset-allocation)
- [Introduction](#introduction)
- [Development](#development)
- [Configuration](#configuration)
- [Data Store](#data-store)
- [Tests](#tests)
# Asset-Allocation
Asset Allocation implementation in Python
## Introduction
The idea here is to encapsulate Asset Allocation logic into a separate component and make it available to other projects (GnuCash Portfolio, and Android apps).
This will include its own data storage.
Dependencies will include:
- price database, for calculation of current value
- transaction database for securities, for calculation of current value
# Development
Requirements are generated with _pipreqs_. Install requirements from requirements.txt.
## Configuration
On the first run, a config file will be created in the user's directory, based on the template in project's data directory.
## Data Store
Data storage is in a SQLite database, which allows for portability, easy queries and relatively easy editing.
The sample data file is in "data" folder.
# Tests
To lint the code, execute `pylint` from the project root directory.
To run tests, execute `pytest` from the project root directory.
- [Asset-Allocation](#asset-allocation)
- [Introduction](#introduction)
- [Development](#development)
- [Configuration](#configuration)
- [Data Store](#data-store)
- [Tests](#tests)
# Asset-Allocation
Asset Allocation implementation in Python
## Introduction
The idea here is to encapsulate Asset Allocation logic into a separate component and make it available to other projects (GnuCash Portfolio, and Android apps).
This will include its own data storage.
Dependencies will include:
- price database, for calculation of current value
- transaction database for securities, for calculation of current value
# Development
Requirements are generated with _pipreqs_. Install requirements from requirements.txt.
## Configuration
On the first run, a config file will be created in the user's directory, based on the template in project's data directory.
## Data Store
Data storage is in a SQLite database, which allows for portability, easy queries and relatively easy editing.
The sample data file is in "data" folder.
# Tests
To lint the code, execute `pylint` from the project root directory.
To run tests, execute `pytest` from the project root directory.
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