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moneyman

Automatically add transactions from all major Israeli banks and credit card companies to a online worksheet

Internally we use israeli-bank-scrapers to scrape the data.

Why?

Having all your data in one place lets you view all of your expenses in a beautiful dashboard like Google Data Studio, Azure Data Explorer dashboards and Microsoft Power BI

Important notes

This app requires some technical skills, if you prefer a GUI app you can use Caspion instead.

Important: The current implementation assumes that you run the code on secure and trusted computers.

It’s a bad idea to put all your financial data and passwords in one place, especially with more than read-only access.

By using moneyman, you acknowledge that you are taking full responsibility for the code quality and will use it only after you review the code and validate that it’s secure.

Please use a proper secret management solution to save and pass the environment variables

How to run

Cloud

Moneyman can be configured to periodically run automatically, using the scrape github workflow.

By default, this workflow will run every other day.

Since logs are public for public repos, most logs are off by default and the progress and error messages will be sent in telegram.

Setup

  1. Fork the moneyman repo to your account
  2. Add the following secrets to the actions secrets of the forked repo
    1. ACCOUNTS_JSON - So moneyman can login to your accounts
    2. TELEGRAM_API_[KEY, CHAT_ID] - So moneyman can send private logs and errors
    3. The environment variables of the storage you want to use
  3. Wait for the workflow to be triggered by github

locally

From code

  1. Clone this repo
  2. Run npm install
  3. Run npm run build
  4. Add your env variables (you can add them in a .env file in the project's root directory)
  5. Run npm run start

From docker

  1. Define the environment variables in a .env file
  2. docker run --rm --env-file ".env" ghcr.io/daniel-hauser/moneyman:latest.
Note

docker doesn't support multiline environment variables (i.e. GOOGLE_SERVICE_ACCOUNT_PRIVATE_KEY), in that case you can run docker-compose up instead

Debug

We use the debug package for debug messages under the moneyman: namespace.

If you want to see them, use the DEBUG environment variable with the value moneyman:*

Settings

Add accounts and scrape

Use the following env vars to setup the data fetching:

ACCOUNTS_JSON

A json array of accounts following this schema with an additional companyId field with a companyType as the value.

Example:

[
  { "companyId": "hapoalim", "userCode": "AB1234", "password": "p@ssword" },
  { "companyId": "visaCal", "username": "Ploni Almoni", "password": "p@ssword" }
]

Other configurations

env variable name default description
ACCOUNTS_TO_SCRAPE [] A comma separated list of providers to take from ACCOUNTS_JSON. if empty, all accounts will be used
DAYS_BACK 10 The amount of days back to scrape
TZ 'Asia/Jerusalem' A timezone for the process - used for the formatting of the timestamp
FUTURE_MONTHS 1 The amount of months that will be scrapped in the future, starting from the day calculated using DAYS_BACK

Get notified in telegram

We use telegram to send you the update status.

  1. Create your bot following this
  2. Open this url https://api.telegram.org/bot<TELEGRAM_API_KEY>/getUpdates
  3. Send a message to your bot and fnd the chat id

Use the following env vars to setup:

env variable name description
TELEGRAM_API_KEY The super secret api key you got from BotFather
TELEGRAM_CHAT_ID The chat id

TODO: Add a way to send a message to the bot to connect?

Export to Azure Data Explorer

  1. Create a new data explorer cluster (can be done for free here)

  2. Create a database within your cluster

  3. Create a azure Service Principal following steps 1-7 here

  4. Allow the service to ingest data to the database by running this:

    .execute database script <|
.add database ['<ADE_DATABASE_NAME>'] ingestors ('aadapp=<AZURE_APP_ID>;<AZURE_TENANT_ID>')

  5. Create a table and ingestion mapping by running this: (Replace <ADE_TABLE_NAME> and <ADE_INGESTION_MAPPING>)

    .execute database script <|
.drop table <ADE_TABLE_NAME> ifexists
.create table <ADE_TABLE_NAME> (
   metadata: dynamic,
   transaction: dynamic
)
.create table <ADE_TABLE_NAME> ingestion json mapping '<ADE_INGESTION_MAPPING>' ```
[
   { "column": "transaction", "path": "$.transaction" },
   { "column": "metadata", "path": "$.metadata" }
]
```

    Feel free to add more columns to the table and ingestion json mapping

Use the following env vars to setup:

env variable name description
AZURE_APP_ID The azure application ID
AZURE_APP_KEY The azure application secret key
AZURE_TENANT_ID The tenant ID of your azure application
ADE_DATABASE_NAME The name of the database
ADE_TABLE_NAME The name of the table
ADE_INGESTION_MAPPING The name of the JSON ingestion mapping
ADE_INGEST_URI The ingest URI of the cluster

Export JSON files

Export transactions to json file.

Use the following env vars to setup:

env variable name description
LOCAL_JSON_STORAGE If truthy, all transaction will be saved to a <process cwd>/output/<ISO timestamp>.json file

Export to excel on OneDrive

WIP

Export to google sheets

  1. Follow the instructions here to create a google service account.
  2. Create a new sheet and share it with your service account using the GOOGLE_SERVICE_ACCOUNT_EMAIL.

Use the following env vars to setup:

env variable name description
GOOGLE_SERVICE_ACCOUNT_PRIVATE_KEY The super secret api key of your service account
GOOGLE_SERVICE_ACCOUNT_EMAIL The service account's email address
GOOGLE_SHEET_ID The id of the spreadsheet you shared with the service account
WORKSHEET_NAME The name of the sheet you want to add the transactions to