Personal Investments Dashboard

Personal web application to manage a diverse investment portfolio in multiple currencies, including crypto and market indexes. Delivered as a Streamlit app. Includes also a module to hack your investments in Jupyter notebooks.

Dashboards reads your ledger and balances from an online Google Spreadsheet (see example), gets historical benchmarks and currency convertion tables from multiple configurabe internet sources, and created a rich explorable dashboard.

All or some or each of your investments are internally normalized into a single “fund” with number of shares and share value. From there, multiple visualizations are possible.

Install and Run

Runs on macOS, Windows, Linux or anywhere Python, Pandas and Streamlit can be installed. Here is a video I put in place that shows Investorzilla getting installed on a Mac and run for the first time with its example portfolio file.

install and use Investorzilla

Install

After getting Python 3 installed, install Investorzilla with pip:

pip install investorzilla --user

Configure

Create a folder and then build your investorzilla.yaml file with information about data sources, benchmarks and currencies.

Start with the examples from https://github.com/avibrazil/investorzilla/blob/main/config_examples/

Run

After installing your API keys (in case of using CryptoCompare data), run it like the following from the same folder containing investorzilla.yaml:

investorzilla

Access the dashboard on http://localhost:8501 (or remotelly if your browser is in a different machine)

Features

Virtual Funds

Create a unified virtual fund with only some of the investments found in your portfolio spreadsheet.

Your whole porfolio will be used if left balnk. Then you might exclude some to match the particular visualization you are trying to attain.

Currency and Benchmarks

You may track your investments using multiple currencies, inluding crypto. I have investments in USD and BRL. You can create virtual funds that mix different currencies, in this case you must select a currency under which you’ll view that (virtual) fund. Values from your spreadsheet will be converted to the target currency on a daily basis.

Also, you might compare your investment performance with market benchmarks as S&P 500, NASDAQ index etc. Just remember to use a benchmark that matches the current currency, otherwise comparisons won’t make sense.

Period Selector

If you have enough or high frequency data, you can divide time in more granular regular periods. Default is monthy view with an anual summary.

Graphs and Reports

Currently supports 4 graphs, from left to right, top to bottom:

  1. Virtual share value performance compared to a selected benchmark
  2. Periodic (monthly, weekly) gain, along with 12M moving average and moving median
  3. Frequency histogram of percent return rate per period (default is per month)
  4. Fund savings, balance and gains (which is pure balance minus savings)

There is also numerical reports showing:

  1. Performance
    1. Periodic (monthly) rate of return with an macro-period (yearly) accumulated value
    2. Same for selecte benchmark
    3. Excess return over benchmark
    4. Periodic and accumulated gain
  2. Wealth Evolution
    1. Current balance
    2. Balance over savings
    3. Cumulated gains
    4. Cumulated savings
    5. Movements on the periods, which is the sum of money added to and removed from virtual fund

Usage Tips

  1. Select a custom period on the slider
  2. View your main metrics on top of report
  3. To optimize screen usage, on the the top right menu, select Settings and then Wide mode
  4. Hide the left panel to gain even more screen real estate
  5. Use Refresh data buttons to update local cache with latest info from your porfolio spreadsheet, market data or both.

Project links

Data verified by PyPI on Sep 4, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for avibrazil from gravatar.com avibrazil

Credits

Author: Avi Alkalay

License

GNU Library or Lesser General Public License (LGPL) (GNU GENERAL PUBLIC LICENSE)

Requires

Python >=3.9

Provides Extra

docs

Tags

investments

Classifiers

Report project as malware

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

investorzilla-6.3.4.tar.gz (107.1 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

investorzilla-6.3.4-py3-none-any.whl (100.6 kB view details)

Uploaded Python 3

File details

Details for the file investorzilla-6.3.4.tar.gz.

File metadata

  • Download URL: investorzilla-6.3.4.tar.gz
  • Upload date:
  • Size: 107.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.14.7

File hashes

Hashes for investorzilla-6.3.4.tar.gz
Algorithm Hash digest
SHA256 784f4f52202ab2d9c40d526e2052e691db47e1263525e945b14dd72fbd8845ac
MD5 b486de86c67b4a51ce770d3fc091ef73
BLAKE2b-256 45934dbb0913cf66cc38a7be14a615ddc55c5171e5ea1407ad4f63ae839f4002

See more details on using hashes here.

File details

Details for the file investorzilla-6.3.4-py3-none-any.whl.

File metadata

  • Download URL: investorzilla-6.3.4-py3-none-any.whl
  • Upload date:
  • Size: 100.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/7.0.0 CPython/3.14.7

File hashes

Hashes for investorzilla-6.3.4-py3-none-any.whl
Algorithm Hash digest
SHA256 1786cf7ecad0b73156a9bcf2f1c565ccd37d3f18130ede2a54b4593cfc64c05a
MD5 dadd7ba14e5db1958e73736e32bfe363
BLAKE2b-256 f485618c5d1161990d81825ba9a61bf4a1fb622c83a2e1bf2bb1e2362efda46e

See more details on using hashes here.

Release history Release notifications | RSS feed

This release

6.3.4 This release

2 files

6.3.3

2 files

6.3.2

2 files

6.3.1

2 files

6.3

2 files

6.2.1

2 files

6.2

2 files

6.1

2 files

6.0.10

2 files

6.0.9

2 files

6.0.8

2 files

6.0.7

2 files

6.0.6

2 files

6.0.5

2 files

6.0.4

2 files

6.0.3

2 files

6.0.2

2 files

6.0.1

2 files

6.0

2 files

5.4.1

2 files

5.4

2 files

5.3

2 files

5.2.1

2 files

5.2

2 files

5.1

2 files

5.0.1

2 files

5.0

2 files

4.5

2 files

4.4

2 files

4.3

2 files

4.2

2 files

4.1

2 files

4.0

2 files

3.7

2 files

3.6

2 files

3.5

2 files

3.4

2 files

3.3

2 files

3.2.3

2 files

3.2.2

2 files

3.2.1

2 files

3.2.0

2 files

3.1.3

2 files

3.1.2

2 files

3.1

2 files

3

2 files

2.6

2 files

2.5.1

2 files

2.5

2 files

2.4.10

2 files

2.4.9

2 files

2.4.8

2 files

2.4.7

2 files

2.4.6

2 files

2.4.5

2 files

2.4.4

2 files

2.4.3

2 files

2.4.2

2 files

2.4.1

2 files

2.4

2 files

2.3.7

2 files

2.3.6

2 files

2.3.4

2 files

2.3.3

2 files

2.3.2

2 files

2.3.1

2 files

2.3

2 files

2.2

2 files

2.1.1

2 files

2.1

2 files

2.0.1

2 files

2.0.0

2 files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page