cryptocurrency_data

Fetch and chart historical & current cryptocurrency prices from the CryptoCompare API in a Jupyter notebook, with an optional (legacy) Google Sheets export.

The core price-fetching helpers live in api_functions.py and are driven interactively from historic_data.ipynb.

What it does

• Pulls historical daily prices for a list of coins (get_price_history).
• Pulls current prices for a list of coins (get_current_prices).
• Looks up the list of supported coins (get_coin_list, see coin_list.ipynb).
• Plots price history with matplotlib (get_graph / plot_graphs).
• Optionally pushes current prices to a Google Sheet (gsheets.py, see the caveat below).

Requirements

• Python 3.6+ (this project was originally built and last updated in 2018).
• The packages in requirements.txt (numpy, pandas, matplotlib, ipython, jupyter, requests, pyyaml, and google-api-python-client).
• No CryptoCompare API key is strictly required for the endpoints used here, but CryptoCompare now encourages an api_key and applies tighter rate limits, so heavy or bulk unauthenticated use may be throttled.

Getting Started

1. Clone Repo

git clone https://github.com/andrebrener/cryptocurrency_data.git

2. Install Packages Required

Go in the directory of the repo and run: pip install -r requirements.txt

3. Open Jupyter Notebook

To open the notebook run:

jupyter notebook

This should open a tab in your browser displaying information like a finder.

Brief tutorial to Jupyter Notebook

The notebook is divided into blocks. The different blocks with code can be identified in the following screenshot.

Each block is run separately by pressing the Play button (screenshot below) or with shortcut Shift+Enter.

To delete all content and start from scratch press Kernel and then Restart & Clear Output

4. Get historic Data

Data

• Open the file historic_data.ipynb.
• Run the first block of code to import dependencies.
• In the second block of code insert:
  • The Coins you like by adding them to the list. Make sure that the Coin is included in the supported coins list.
  • The last day of your report.
  • How many days before the end date you want the data from.
  • The type of price from close, high, low, open.
  • The currency for the prices.
• Run the 2nd & 3rd blocks of code.

Graph

• In the 4th block of code:
  • Choose the time interval for the dates in the x-axis to be shown.
• Run the block.

Export CSV

• In the 5th block of code:
  • Select File Name. Run the block.
• Run the 6th block. The file should now be saved in the directory printed below. Note that the directory is relative to the repo path.

Google Sheets export (legacy / unsupported)

gsheets.py can push the current prices into a Google Sheet. This path is legacy and is not expected to run as-is today. It relies on the deprecated oauth2client / apiclient authentication libraries (end-of-life, no longer bundled with the current google-api-python-client) and on a local google_credentials.py module that is intentionally not committed to this repo.

If you want to use it, you would need to:

1. Create a Google Cloud project, enable the Google Sheets API, and download the OAuth client secrets as client_secret.json.
2. Create a google_credentials.py file (kept out of version control by .gitignore) that defines at least:

   PRICES_SHEET_LINK = "<your spreadsheet id>"
   RANGE_NAME = "<sheet!A1:B100>"

3. Modernise the auth stack (e.g. migrate to google-auth / google-auth-oauthlib), since oauth2client/apiclient are no longer installable in a modern environment.

These credential files (google_credentials.py, client_secret.json) and any generated *.log / data/*.csv files are ignored via .gitignore and should never be committed.

License

MIT