The base api client class and its documentation are automatically generated with swagger-codegen
from the OpenAPI specification available here on the coingecko website.
The documentation for the api client can be found here.
This ensures that all endpoints and their corresponding parameters are 100% correct. Furthermore, the "Client Updated" badge you see at the top of this README is a live check that the spec used to generate the client code matches the latest version of the spec available on the coingecko website. This badge is updated once a day as a part of the CICD pipeline.
Additionally, the base api client has been extended to provide additional functionality like
Advanced Features - Mitigate Rate Limiting
Advanced Features - Page Range Queries
This package is currently only available through PyPI. You can install it by running
pip install coingecko_py
This package exposes a single class called CoingeckoApi
. To import and
initialize this class, do the following
from coingecko_py import CoingeckoApi
cg = CoingeckoApi()
Check out the API Reference for more details on how to use this object.
This section includes usage examples for advanced features that have been added to the base api client.
Note: This functionality is available for all endpoints available on the base client.
Imagine you wanted to get price data for the last year on the top 1000 market cap coins.
First, we get the data for the top 1000 market cap coins. Each page returns 100 results and pages are already sorted by market cap.
# np.ravel flattens a list of lists
import numpy as np
coins = np.ravel([cg.coins_markets_get('usd', page=i) for i in range(1, 11)])
Next, we iterate over coins
and use each coin id to query for it's price data.
ndays = 365
prices = dict()
for c in coins:
cid = c['id']
prices[cid] = cg.coins_id_market_chart_get(cid, 'usd', ndays)['prices']
The issue here is that the coingecko api performs server side rate limiting. If you are using the free tier, it's about 50 api calls per second. Paid tiers have higher limits, but there is still a limit.
Since the above code block would be sending 1000 api requests synchronously, it is likely to fail at some point if you have a decent internet connection. In order to get around this, you would have to add error detection and call management logic. If you are writing a complex app with many api calls, this can be really annoying.
The coingecko_py client introduces a mechanism to queue api calls and execute a series of queued calls while performing client side exponential backoff retries. See here for an explanation of this strategy.
This allows you to write code without worrying about rate limiting! Here is a block of code that is equivalent to the above code block that won't error out due to rate limiting.
ndays = 365
for c in coins:
cid = c['id']
cg.coins_id_market_chart_get(cid, 'usd', ndays, qid=cid)
prices = cg.execute_queued()
prices = {k: v['prices'] for k, v in prices.items()}
The key differences here are
The inclusion of the qid
keyword argument in the api call signature.
qid
stands for queue id. qid
must be a string. qid
is present as a keyword argument in an api call, the client will queue the call instead of executing it. qid
can be used as a lookup key for the result of this api call once it is executed. The line containing the api call (cg.coins_id_market_chart_get(...)
) does not return anything.
qid
is not a kwarg, an api call behaves exactly the same as the base api client. qid
is a kwarg, an api call returns nothing, as it was queued. The function execute_queued
must be invoked in order to execute all queued calls.
qid
values from queued calls and the values are the data parsed from responses of the corresponding api calls. execute_queued
is successful, the internal call queue is cleared. execute_queued
on line 1 then again on line 2, the second call would return an empty dictionary. These two blocks of code both produce a dictionary prices
with the same exact structure (assuming the first code block doesn't error out because of rate limiting).
prices = {
'bitcoin': {
'prices': [
[1610236800000, 40296.5290038294],
[1610323200000, 38397.895985418174],
[1610409600000, 35669.90668663349],
...
]
},
'ethereum': {
'prices': [
[1610236800000, 1282.979575527323],
[1610323200000, 1267.7310031512136],
[1610409600000, 1092.9143378806064],
...
]
},
...
}
Note: This functionality is available for all endpoints the base client that support paging.
The coingecko api has a number of endpoints that support pagination. Pagination is a common api feature where you can request a specific page of data from an api. This is often necessary as some data objects are too large to return in a single api response. If you want all the data for a particular api call you are executing, you must request data from all pages.
Here is an example that uses the client to query for a single page of data
cg.coins_id_tickers_get('bitcoin', page=2, per_page=50)
Page range queries allow you to request a range of pages in a single client call. The api client supports bounded and unbounded page range queries.
[page_start, page_end]
. page_start
and will return
data from all available pages from page_start
onwards. For the code blocks below, let's assume we magically know there are 100 data pages for the coins_id_tickers_get
endpoint for the given set of parameters. In reality, if you wanted
to determine the number of data pages for a client call, you would need to make the call,
inspect the HTTP headers, perform a calculation to determine the total number of pages,
then loop over the page range and make a request per each page.
Here is an example of doing pagination manually using the base api client functionality
data = []
for i in range(1, 101):
res = cg.coins_id_tickers_get('bitcoin', page=i)
data.append(res)
Here is an example of doing a bounded page range query with the extended client.
cg.coins_id_tickers_get('bitcoin', qid="data", page_start=1, page_end=100)
data = cg.execute_queued()['data']
Here is an example of doing an unbounded page range query with the extended client.
cg.coins_id_tickers_get('bitcoin', qid="data", page_start=1)
data = cg.execute_queued()['data']
All code blocks will produce equivalent output. The return value of a page range query is a list of response data from each individual api call. So data[0]
contains the result for page 1, data[49]
contains the result for page 50.
It's important to note that qid
must be included as a keyword argument for page range queries.
Thus, page range queries will also automatically deal with rate limiting as detailed in the
rate limiting section.
The extended client supports multiple configuration options which impact its behavior.
Kwarg | Default | Description |
---|---|---|
exp_limit | 8 |
Max exponent (2exp_limit) for exponential backoff retries |
progress_interval | 10 |
Min percentage interval at which to log progress of queued api calls |
log_level | logging.INFO |
python logging log level for client log messages |
The API client doesn't print any messages, but has logs at the following levels.
logging.DEBUG
) will provide logs about internal state of client. logging.INFO
) progress logs and other useful info exists at this level. logging.WARNING
) useful warnings. I don't recommend any level higher than this.
See here for more info on log levels. Here's an example of how to configure the client with non-default values.
cg = CoingeckoApi(log_level=10, exp_limit=6, progress_interval=5)
A quick summary of the functionality offered by this package
cg.execute_queued
is the only public method added to the client. It takes no input arguments and returns a dictionary that maps qid
values to the corresponding queued api call. qid
in a client call. When you include the kwarg qid
the function call does not return anything (as it was queued for later execution). page_start
and page_end
are both defined, it will return all data pages in range. page_start
is defined and page_end
is not, it will return all data pages from page_start
onwards.qid
in their call signature). This package is packaged with poetry
If you have poetry installed, you can perform the following steps to set up the development environment.
git clone https://github.com/brycemorrow4564/coingecko_py.git
cd coingecko_py
poetry shell
poetry update
poetry install
If you want to run the tests (within the dev environment), do the following
poetry run test