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in-fin-neat / in-fin-neat-core

Personal Finances tool
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Personal Finances

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Using

Fetching transactions from banks

This command collects transactions in the past 90 days from configured bank accounts, and creates a new transactions file in the data/ folder. Browser tabs will be open for bank authentication and authorization.

Command

pipenv run fetch_transactions

Merging saved transactions

This command merges all transactions previously saved into a single file to be processed by other commands.

Command

pipenv run merge_transactions

Generating reports

Reports are generated for a given time period selected using two parameters --start-time <ISO8061 DATETIME> and --end-time <ISO8061 DATETIME>.

Additionally, a user configuration file[^user_config] path is necessary. For convenience, a default file path is set to be config/user_config.yaml, however you can override it using --user-configuration-file-path <file_path>.

Three reports will be saved into /reports folder:

  1. Balance report, showing total income, total expenses and the final balance.
  2. A income report by category
  3. An expense report by category

Command

pipenv run generate_reports --start-time <ISO8061 DATETIME> --end-time <ISO8061 DATETIME> --user-config-file-path

eg: pipenv run generate_reports --start-time 2023-12-01T00:00+0100 --end-time 2024-02-29T00:00+0100 --user-config-file-path user_configuration_file.yaml

Configuring

Config Nordigen Credentials

The personal finances application connects to GoCardless Bank Account Data API using their official python client. Two secret values are needed to connect to their API, a secret id and a secret key. These values are read by the personal_finances application through OS environment variables named respectively, GOCARDLESS_SECRET_ID and GOCARDLESS_SECRET_KEY.

Using environment variables

The current recommended way of using this application is through the pipenv command. pipenv automatically inherits the parent global environment variables, therefore setting GoCardless credentials as env vars on the parent environment is one option.[^env_vars]

Using .env file

An alternative option is to set it in a .env file, pipenv loads .env into environment variables.

  1. echo GOCARDLESS_SECRET_ID=SecretIdFromGoCardless >.env
  2. echo GOCARDLESS_SECRET_KEY=SecretKeyFromGoCardless >>.env
  3. echo TOKEN_DISK_PATH_PREFIX=/path/to/token/folder >>.env
  4. echo REQUISITION_DISK_PATH_PREFIX=/path/to/token/folder >>.env
  5. pipenv run <command> <arguments>

Developing

  1. gh repo clone diegotsutsumi/personal_finances
  2. pipenv install --dev
  3. pipenv run bash -c 'mypy .; mypy --install-types --non-interactive'
  4. pipenv run build
  5. pipenv run tests
  6. pipenv run format
  7. pipenv run aws_lambda_pack
  8. gh pr create --title "brand new feature"

Writing Tests

This repository implments tests using pytest, the test files are in the folder personal_finances/tests/, it has one test file per source file and the file structure follows the source file structure in personal_finances/personal_finances/.

[^env_vars]: For linux you can either prepend as in NAME=value pipenv ... or use export NAME=value, for windows you can use set. [^user_config]: A more detailed documentation on the user configuration file can be found here.

AWS Lambda Packing

In-fin-neat-core code runs on AWS Lambda and a "packing" command (aws_lambda_pack) is defined for generating a zip file with python dependencies (defined in Pipfile) installed to run on the AWS Lambda runtime.

The aws_lambda_pack command can be run using pipenv: 

pipenv run aws_lambda_pack

This script generates a requirements file using pipenv and install all dependencies in the in_fin_core_package zip file, created inside the package folder. This zip can be uploaded to aws lambda function.