.. Messari documentation master file, created by
   sphinx-quickstart on Sun Feb 21 13:13:45 2021.
   You can adapt this file completely to your liking, but it should at least
   contain the root `toctree` directive.

Welcome to Messari's Documentation!
===================================

Messari provides a free API for crypto prices, market data metrics, on-chain metrics,
and qualitative information (asset profiles).

This documentation will provide the basic steps to start using messari's python library.

Installing messari
==================

The first step is installing messari. messari is a python project, so it can be installed like any
other python library. Every Operating System should have Python pre-installed,
so you should just have to run::

   $> pip install git+https://github.com/messari/messari-python-api.git

Authentication
==============

Once the python library is installed, the next step is to create an API key. To do this sign up for an
account at https://messari.io/ and navigate to https://messari.io/account/api to generate a key.

.. note::
   Without an API key, requests are rate limited to 20 requests per minute and 1000 requests
   per day. Users that create an account will have slightly higher limits of 30 requests per
   minute and 2000 requests per day. PRO users have the highest limit at 60 requests per minute
   up to a maximum of 4000 requests per day. Contact us at api@messsari.io if you need a higher limit.


Once you generate an API key, import messari then set your API key by running::

   # Import Messari API wrapper
   from messari.messari import Messari

   # Set up Messari instance
   MESSARI_API_KEY = 'add_your_api_key'
   messari = Messari(api_key=MESSARI_API_KEY)

   # Run a quick demo
   markets_df = messari.get_all_markets()
   markets_df.head()


.. note::
   We recommend using the library with `JupyterLab <https://jupyterlab.readthedocs.io/en/stable/>`_. Detailed
   installation instructions can be found `here <https://jupyterlab.readthedocs.io/en/stable/getting_started/installation.html>`_.

   Using ``conda``, you can install JupyterLab by running::

      conda install -c conda-forge jupyterlab

   With ``pip``, you can install it with::

      pip install jupyterlab

Integrations
============
Messari API
 Data aggregator
DeFi Llama API
 Data for chain & protocol TVL
Token Terminal API
 Crypto Analytics Platform with Advanced Metrics & Tools
Deep DAO API
 DAO analytics insights for a decentralized world
Etherscan, Polygonscan, Arbiscan, FTMscan, BSCscan, & SnowTrace
 EVM Block Explorers
Solscan API
 Solana Block Explorer
Upshot API
 Where NFTs meet DeFi
NonFungible API
 Real time digital asset tracking to help you to navigate NFT markets with transparency and confidence
OpenSea API
 A peer-to-peer marketplace for NFTs, rare digital items and crypto collectibles
NFT Floor Price API
 Track top NFT collections: price floor, historical price chart, sales data & trade volume
EVM Live Event Monitoring
 Monitor and gather on-chain events

Usage
=====

Check out our examples `here <https://github.com/messari/messari-python-api/blob/master/examples/Messari%20API%20Tutorial.ipynb>`_ for detailed usage.

:ref:`Here<genindex>` is detailed description of all the available functions in the library.

.. toctree::
   :maxdepth: 2
   :caption: Contents:

   notebooks/Messari API Tutorial.ipynb
   notebooks/DeFiLlama API Tutorial.ipynb
   notebooks/TokenTerminal API Tutorial.ipynb
   notebooks/DeepDAO API Tutorial.ipynb
   notebooks/Etherscan API Tutorial.ipynb
   notebooks/Solscan API Tutorial.ipynb
   notebooks/Upshot API Tutorial.ipynb
   notebooks/OpenSea API Tutorial.ipynb
   notebooks/NonFungible API Tutorial.ipynb
   notebooks/NFT Price Floor API Tutorial.ipynb
   notebooks/Event Monitor Tutorial.ipynb


Indices and tables
==================

* :ref:`genindex`
* :ref:`modindex`