Retrieving All Cryptocurrencies by using Requests

Hello dear Reader!

The next post is again a simple one, where the goal is to retrieve all the cryptocurrencies available in https://www.coingecko.com/en

For this Script we will need some libraries. We are going to access the CoinGecko API so the Requests library is needed! The information is retrieved in JSON format and saved into a Dataframe. Also, Modules like the Datetime and OS (operating system dependent functionality) are going to be used for easier management of the final Outputs.

import json
import requests
import pandas as pd
from datetime import datetime
import os

Let’s define our base_url for the request call to the API and a variable for our Output folder. P.S. I chosed to call my folder “Output” but you can change this just by changing the variable

base_url = "https://api.coingecko.com/api/v3/"
output_folder= "Output"

Now to create a function, let’s define it and print the beginning to the console.

def get_coins_list_coingecko():
    print("Getting the List with all the Coins under CoinGecko")

For the request we need to merge the base_url with “coins/list”, that’s the place where the list that we require is. Let’s print the URL Request to see what we are going to retrieve.

    response = requests.get(base_url + "coins/list")
    print("Request Url = {}".format(response.url))

If we access the link given by the Print command, we get the following output.

Seems confusing but in fact is very simple, this is in JSON format, and the first bracket means we are starting a list, next we have a curly bracket, that means we are starting a dictionary, notice we have one dictionary for each coin, and that coin contains an ID, a Symbol and a Name, each different coin/dictionary are separated by commas.

We now need to retrieve this text to Json and load it into a Dataframe called all_coins.

    response_json = json.loads(response.text)
    all_coins = pd.DataFrame.from_dict(response_json)
    all_coins.index.name = 'index'

We want to give a name to the index column, so it won’t be Blank. Let’s print the Dataframe to see the output that we already have.

Now we just need to save our List!

    if not os.path.exists(output_folder):
        os.mkdir(output_folder)

The OS Module is very useful, it helps to interact with the Operating System. In this case we have an IF condition, it is going to check if the folder(the one we defined at the beginning) exists!

Keep in mind that you need to run the Script on the Parent Folder of your output Variable, if in your Parent Folder doesn’t exist any folder with the same name as the variable output_folder then in that same folder a new folder be created under the command mkdir.

For the last step, we need to save the file.

    try:
        all_coins.to_csv(os.path.join(output_folder, 'AllCoins_CoinGecko_{}.csv'.format(str(datetime.today().strftime('%Y%m%d'))) ))
    except:
        print("It was not possible to save/create the file")

We are going to use the try command, it means that the program will try to execute what we have under the try command, if it fails than the except command will be raised. In this case we are taking the dataframe that we previously created and using the to_csv method we are going to export it to an CSV file. As for the arguments, we are joining two things:

1. The path where we want to save the CSV file.
2. The file name, “AllCoins_CoinGecko_CURRENT_DATE.csv”

To calculate the current date, we are using the Module Datetime from the library Datetime and converting the date to a desired string format.

At the end we return the Dataframe so anytime we need to access the List we just need to call the function!

To see the full Script please visit the repository.

Thanks for the reading!