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CME Group Datamine Package.

Project description

CME Datamine

Overview

CME Datamine is offered via a self-service cloud solution, where you can access more than 450 terabytes of historical data almost instantaneously, using some of the most flexible data delivery methods available. Extensively back-test strategies using real benchmark markets that date back as far as the 1970s, to help you gauge profitability and risk.

This python package will support your rapid analysis by supplying a basic framework for direct iteration with CME Datamine cloud system to accomplish the following tasks.

  1. Load your data item catalog which you have subscribed
  2. Download your data items to your local machines from the cloud
  3. Specific data items automatically structured into a Pandas dataframe from your local copy. This includes correct typing and other generic routines to support your analysis needs.
  4. Examples of working with this data in Pandas via a collection of Ipyhon Notebook files.

Installation

Conda

The easiest way to install this package is to do so in a Python environment created with Anaconda or its minimalist alternative Miniconda. Once this environment is installed and activated, simply run this command:

conda install -c cmegroup datamine_python

PyPi

Installation from PyPi via pip is coming soon.

From source

To install from source, clone this repository and execute

pip install .

If you wish to install the package in writable mode for development, do

pip install -e .

Example usage

The following sections quickly outline some of the simple methods to access CME Datamine data. For interactive use, we recommend the use of a Jupyter notebook or the JupyterLab platform.

Load My Data Catalog Items

myDatamine = dm.DatamineCon(username='YOUR_CME_APP_ID', password='YOUR_CME_APP_PASSWORD', path='./data/')
#Get My Datamine Data Catalog
myDatamine.get_catalog(limit=1000)
# Review one of the data catalog items as supplied in dict format.  
myDatamine.data_catalog.popitem()

Download Specific Data Products

You can request specific data products. Current data products supported are as follows. When requesting your data, you must specify the dataset tag or leave it blank will request all items in your catalog.

CME Data Products

Data Set Name Data Type dataset Tag
CME Time and Sales Price TICK
CME Market Depth MBO Price MBO
CME CF Crypto Currency Index CRYPTOCURRENCY
BrokerTech Top of Book Price NEXBROKERTECTOB
BrokerTech Depth of Book Price NEXBROKERTECDOB
BrokerTech Full Book Price NEXBROKERTECFOB
Eris PAI Market Analytics ERIS

Third Party Data

Data Set Name Data Type dataset Tag
TellusLabs Alternative - Ags TELLUSLABS
Orbital Insight Alternative - Energy ORBITALINSIGHT
Bantix Technologies Market Analytics - Options BANTIX
RS Metrics Alternative - Metals RSMETRICS

A complete list of data products can be reviewed on CME Datamine

Example request for specific Data Sets using the dataset tag.

myDatamine.get_catalog(dataset='CRYPTOCURRENCY', limit=1000)
myDatamine.get_catalog(dataset='TICK', limit=1000)
myDatamine.get_catalog(dataset='TELLUSLABS', limit=1000)
myDatamine.get_catalog(dataset='RSMETRICS', limit=1000)

Use Bitcoin Information in Analysis

The following example can be found in the Load Datamine Data Locally Example Notebook

myDatamine.get_catalog(dataset='CRYPTOCURRENCY', limit=1000)
myDatamine.crypto_load()

#plot second interval index values for Bitcoin
indexValue = myDatamine.crypto_DF.loc[myDatamine.crypto_DF['symbol'] =='BRTI','mdEntryPx'].plot(figsize=[15,5]);
plt.title('Historical Bitcoin Intraday Reference Rate')
plt.xlabel('Date')
plt.ylabel('USD/BTC')
plt.style.use('fivethirtyeight')
plt.show()

Bitcoin RT Index Plot Example

Questions and Comments?

Please use the Issues feature.

Notice

The information herein has been complied by CME Group for general informational and education purposes only and does not constitute trading advice or the solicitation of purchases or sale of futures, options, or swaps. The views in this video reflect solely those of the author and not necessarily those of CME Group or its affiliated institutions. All examples discussed are hypothetical situations, used for explanation purposes only, and should not be considered investment advice of the results of actual market experience. Although every attempt has been made to ensure the accuracy of the information herein, CME Group and its affiliates assume no responsibility for any errors or omissions. All data is sourced by CME Group unless otherwise stated. All matters pertaining to rules and specification herein are made subject to and are superseded by official CME, CBOT, NYMEX, and COMEX rules. Current rules should be consulted in all cases concerning contact specifications.

CME Group, the Globe Logo, CME, Globex, E-Mini, CME Direct, CME Datamine and Chicago Mercantile Exchange are trademarks of Chicago Mercantile Exchange Inc. CBOT is a trademark of the Board of Trade of the City of Chicago, Inc. NYMEX is a trademark of New York Mercantile Exchange, Inc. COMEX is a trademark of Commodity Exchange, Inc. All other trademarks are the property of their respective owners.

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0.1

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