EOD Historical Data Python Library (Unofficial)

Overview

EOD Historical Data Python Library (Unofficial)

https://eodhistoricaldata.com

Installation

python3 -m pip install eodhistoricaldata

Note

Demo API key below is provided by EOD Historial Data for testing purposes https://eodhistoricaldata.com/financial-apis/new-real-time-data-api-websockets

Usage

None: """Main""" websocket = WebSocketClient( # Demo API key for testing purposes api_key="OeAFFmMliFG5orCUuwAKQ8l4WWFQ67YX", endpoint="crypto", symbols=["BTC-USD"] #api_key="OeAFFmMliFG5orCUuwAKQ8l4WWFQ67YX", endpoint="forex", symbols=["EURUSD"] #api_key="OeAFFmMliFG5orCUuwAKQ8l4WWFQ67YX", endpoint="us", symbols=["AAPL"] ) websocket.start() message_count = 0 while True: if websocket: if ( message_count != websocket.message_count ): print(websocket.message) message_count = websocket.message_count sleep(0.25) # output every 1/4 second, websocket is realtime if __name__ == "__main__": main() ">
"""Sample script"""

from time import sleep
from eodhistoricaldata import WebSocketClient

def main() -> None:
    """Main"""

    websocket = WebSocketClient(
        # Demo API key for testing purposes
        api_key="OeAFFmMliFG5orCUuwAKQ8l4WWFQ67YX", endpoint="crypto", symbols=["BTC-USD"]
        #api_key="OeAFFmMliFG5orCUuwAKQ8l4WWFQ67YX", endpoint="forex", symbols=["EURUSD"]
        #api_key="OeAFFmMliFG5orCUuwAKQ8l4WWFQ67YX", endpoint="us", symbols=["AAPL"]
    )
    websocket.start()

    message_count = 0
    while True:
        if websocket:
            if (
                message_count != websocket.message_count
            ):
                print(websocket.message)
                message_count = websocket.message_count
                sleep(0.25)  # output every 1/4 second, websocket is realtime

if __name__ == "__main__":
    main()
You might also like...
TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI) data
TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI) data

tedana: TE Dependent ANAlysis TE-dependent analysis (tedana) is a Python library for denoising multi-echo functional magnetic resonance imaging (fMRI)

Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data.
Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data.

Hatchet Hatchet is a Python-based library that allows Pandas dataframes to be indexed by structured tree and graph data. It is intended for analyzing

 🧪 Panel-Chemistry - exploratory data analysis and build powerful data and viz tools within the domain of Chemistry using Python and HoloViz Panel.
🧪 Panel-Chemistry - exploratory data analysis and build powerful data and viz tools within the domain of Chemistry using Python and HoloViz Panel.

🧪📈 🐍. The purpose of the panel-chemistry project is to make it really easy for you to do DATA ANALYSIS and build powerful DATA AND VIZ APPLICATIONS within the domain of Chemistry using using Python and HoloViz Panel.

Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code

Tuplex is a parallel big data processing framework that runs data science pipelines written in Python at the speed of compiled code. Tuplex has similar Python APIs to Apache Spark or Dask, but rather than invoking the Python interpreter, Tuplex generates optimized LLVM bytecode for the given pipeline and input data set.

Python data processing, analysis, visualization, and data operations

Python This is a Python data processing, analysis, visualization and data operations of the source code warehouse, book ISBN: 9787115527592 Descriptio

Catalogue data - A Python Scripts to prepare catalogue data

catalogue_data Scripts to prepare catalogue data. Setup Clone this repo. Install

fds is a tool for Data Scientists made by DAGsHub to version control data and code at once.
fds is a tool for Data Scientists made by DAGsHub to version control data and code at once.

Fast Data Science, AKA fds, is a CLI for Data Scientists to version control data and code at once, by conveniently wrapping git and dvc

A data parser for the internal syncing data format used by Fog of World.
A data parser for the internal syncing data format used by Fog of World.

A data parser for the internal syncing data format used by Fog of World. The parser is not designed to be a well-coded library with good performance, it is more like a demo for showing the data structure.

Functional Data Analysis, or FDA, is the field of Statistics that analyses data that depend on a continuous parameter.
Comments
  • Syntax issue with query Parameter in get_calendar_ functions

    Syntax issue with query Parameter in get_calendar_ functions

    Hello,

    When using the get_calendar_XXX, functions we cannot use the query parameters defined by EOD as the word "from" is forbidden by Python, for instance : earning=client.get_calendar_earnings(from='2022-11-01', to='2022-11-30')

    will raise an issue.

    Should I pass the argument differently ?

    opened by ATCBGroup 1
  • dependency on matplotlib but it is not installed with pip

    dependency on matplotlib but it is not installed with pip

    dependency on matplotlib but it is not installed with pip

    [email protected]:~/git/traderai/eod$ cat test.py
    from eodhd import APIClient
    api = APIClient("DEMO")
    
    [email protected]:~/git/traderai/eod$ python3 test.py
    Traceback (most recent call last):
      File "/home/mshamber/.local/lib/python3.8/site-packages/eodhd/eodhdgraphs.py", line 5, in <module>
        import matplotlib.pyplot as plt
    ModuleNotFoundError: No module named 'matplotlib'
    
    [email protected]:~/git/traderai/eod$ python3 -m pip install eodhd
    Requirement already satisfied: eodhd in /home/mshamber/.local/lib/python3.8/site-packages (1.0.8)
    Requirement already satisfied: websocket-client==1.3.3 in /home/mshamber/.local/lib/python3.8/site-packages (from eodhd) (1.3.3)
    Requirement already satisfied: rich==12.5.1 in /home/mshamber/.local/lib/python3.8/site-packages (from eodhd) (12.5.1)
    Requirement already satisfied: websockets==10.3 in /home/mshamber/.local/lib/python3.8/site-packages (from eodhd) (10.3)
    Requirement already satisfied: numpy==1.21.6 in /home/mshamber/.local/lib/python3.8/site-packages (from eodhd) (1.21.6)
    Requirement already satisfied: pandas==1.3.5 in /home/mshamber/.local/lib/python3.8/site-packages (from eodhd) (1.3.5)
    Requirement already satisfied: requests==2.28.1 in /home/mshamber/.local/lib/python3.8/site-packages (from eodhd) (2.28.1)
    Requirement already satisfied: commonmark<0.10.0,>=0.9.0 in /home/mshamber/.local/lib/python3.8/site-packages (from rich==12.5.1->eodhd) (0.9.1)
    Requirement already satisfied: typing-extensions<5.0,>=4.0.0; python_version < "3.9" in /home/mshamber/.local/lib/python3.8/site-packages (from rich==12.5.1->eodhd) (4.3.0)
    Requirement already satisfied: pygments<3.0.0,>=2.6.0 in /home/mshamber/.local/lib/python3.8/site-packages (from rich==12.5.1->eodhd) (2.13.0)
    Requirement already satisfied: python-dateutil>=2.7.3 in /home/mshamber/.local/lib/python3.8/site-packages (from pandas==1.3.5->eodhd) (2.8.2)
    Requirement already satisfied: pytz>=2017.3 in /home/mshamber/.local/lib/python3.8/site-packages (from pandas==1.3.5->eodhd) (2022.5)
    Requirement already satisfied: charset-normalizer<3,>=2 in /home/mshamber/.local/lib/python3.8/site-packages (from requests==2.28.1->eodhd) (2.1.1)
    Requirement already satisfied: idna<4,>=2.5 in /usr/lib/python3/dist-packages (from requests==2.28.1->eodhd) (2.8)
    Requirement already satisfied: certifi>=2017.4.17 in /usr/lib/python3/dist-packages (from requests==2.28.1->eodhd) (2019.11.28)
    Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/lib/python3/dist-packages (from requests==2.28.1->eodhd) (1.25.8)
    Requirement already satisfied: six>=1.5 in /home/mshamber/.local/lib/python3.8/site-packages (from python-dateutil>=2.7.3->pandas==1.3.5->eodhd) (1.16.0)
    
    opened by opme 1
Releases(1.0.8)
Owner
Michael Whittle
Solution Architect
Michael Whittle
📊 Python Flask game that consolidates data from Nasdaq, allowing the user to practice buying and selling stocks.

Web Trader Web Trader is a trading website that consolidates data from Nasdaq, allowing the user to search up the ticker symbol and price of any stock

Paulina Khew 21 Aug 30, 2022
Python tools for querying and manipulating BIDS datasets.

PyBIDS is a Python library to centralize interactions with datasets conforming BIDS (Brain Imaging Data Structure) format.

Brain Imaging Data Structure 180 Dec 18, 2022
Bearsql allows you to query pandas dataframe with sql syntax.

Bearsql adds sql syntax on pandas dataframe. It uses duckdb to speedup the pandas processing and as the sql engine

14 Jun 22, 2022
Zipline, a Pythonic Algorithmic Trading Library

Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. Zipline is currently used in production as the backte

Quantopian, Inc. 15.7k Jan 07, 2023
Generates a simple report about the current Covid-19 cases and deaths in Malaysia

Generates a simple report about the current Covid-19 cases and deaths in Malaysia. Results are delay one day, data provided by the Ministry of Health Malaysia Covid-19 public data.

Yap Khai Chuen 7 Dec 15, 2022
Supply a wrapper ``StockDataFrame`` based on the ``pandas.DataFrame`` with inline stock statistics/indicators support.

Stock Statistics/Indicators Calculation Helper VERSION: 0.3.2 Introduction Supply a wrapper StockDataFrame based on the pandas.DataFrame with inline s

Cedric Zhuang 1.1k Dec 28, 2022
A data analysis using python and pandas to showcase trends in school performance.

A data analysis using python and pandas to showcase trends in school performance. A data analysis to showcase trends in school performance using Panda

Jimmy Faccioli 0 Sep 07, 2021
A real data analysis and modeling project - restaurant inspections

A real data analysis and modeling project - restaurant inspections Jafar Pourbemany 9/27/2021 This project represents data analysis and modeling of re

Jafar Pourbemany 2 Aug 21, 2022
Weather Image Recognition - Python weather application using series of data

Weather Image Recognition - Python weather application using series of data

Kushal Shingote 1 Feb 04, 2022
Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python

Driver Analysis with Factors and Forests: An Automated Data Science Tool using Python 📊

Thomas 2 May 26, 2022
This repo contains a simple but effective tool made using python which can be used for quality control in statistical approach.

📈 Statistical Quality Control 📉 This repo contains a simple but effective tool made using python which can be used for quality control in statistica

SasiVatsal 8 Oct 18, 2022
Advanced Pandas Vault — Utilities, Functions and Snippets (by @firmai).

PandasVault ⁠— Advanced Pandas Functions and Code Snippets The only Pandas utility package you would ever need. It has no exotic external dependencies

Derek Snow 374 Jan 07, 2023
DataPrep — The easiest way to prepare data in Python

DataPrep — The easiest way to prepare data in Python

SFU Database Group 1.5k Dec 27, 2022
Project under the certification "Data Analysis with Python" on FreeCodeCamp

Sea Level Predictor Assignment You will anaylize a dataset of the global average sea level change since 1880. You will use the data to predict the sea

Bhavya Gopal 3 Jan 31, 2022
Used for data processing in machine learning, and help us to construct ML model more easily from scratch

Used for data processing in machine learning, and help us to construct ML model more easily from scratch. Can be used in linear model, logistic regression model, and decision tree.

ShawnWang 0 Jul 05, 2022
Feature Detection Based Template Matching

Feature Detection Based Template Matching The classification of the photos was made using the OpenCv template Matching method. Installation Use the pa

Muhammet Erem 2 Nov 18, 2021
Important dataframe statistics with a single command

quick_eda Receiving dataframe statistics with one command Project description A python package for Data Scientists, Students, ML Engineers and anyone

Sven Eschlbeck 2 Dec 19, 2021
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)

Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext

Benedek Rozemberczki 1.8k Jan 09, 2023
PostQF is a user-friendly Postfix queue data filter which operates on data produced by postqueue -j.

PostQF Copyright © 2022 Ralph Seichter PostQF is a user-friendly Postfix queue data filter which operates on data produced by postqueue -j. See the ma

Ralph Seichter 11 Nov 24, 2022
Data and code accompanying the paper Politics and Virality in the Time of Twitter

Politics and Virality in the Time of Twitter Data and code accompanying the paper Politics and Virality in the Time of Twitter. In specific: the code

Cardiff NLP 3 Jul 02, 2022