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
TextDescriptives - A Python library for calculating a large variety of statistics from text

A Python library for calculating a large variety of statistics from text(s) using spaCy v.3 pipeline components and extensions. TextDescriptives can be used to calculate several descriptive statistic

150 Dec 30, 2022
Exploratory data analysis

Exploratory data analysis An Exploratory data analysis APP TAPIWA CHAMBOKO 🚀 About Me I'm a full stack developer experienced in deploying artificial

tapiwa chamboko 1 Nov 07, 2021
Open-source Laplacian Eigenmaps for dimensionality reduction of large data in python.

Fast Laplacian Eigenmaps in python Open-source Laplacian Eigenmaps for dimensionality reduction of large data in python. Comes with an wrapper for NMS

17 Jul 09, 2022
This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

This program analyzes a DNA sequence and outputs snippets of DNA that are likely to be protein-coding genes.

1 Dec 28, 2021
InDels analysis of CRISPR lines by NGS amplicon sequencing technology for a multicopy gene family.

CRISPRanalysis InDels analysis of CRISPR lines by NGS amplicon sequencing technology for a multicopy gene family. In this work, we present a workflow

2 Jan 31, 2022
Import, connect and transform data into Excel

xlwings_query Import, connect and transform data into Excel. Description The concept is to apply data transformations to a main query object. When the

George Karakostas 1 Jan 19, 2022
Python Implementation of Scalable In-Memory Updatable Bitmap Indexing

PyUpBit CS490 Large Scale Data Analytics — Implementation of Updatable Compressed Bitmap Indexing Paper Table of Contents About The Project Usage Cont

Hyeong Kyun (Daniel) Park 1 Jun 28, 2022
Open source platform for Data Science Management automation

Hydrosphere examples This repo contains demo scenarios and pre-trained models to show Hydrosphere capabilities. Data and artifacts management Some mod

hydrosphere.io 6 Aug 10, 2021
BIGDATA SIMULATION ONE PIECE WORLD CENSUS

ONE PIECE is a Japanese manga of great international success. The story turns inhabited in a fictional world, tells the adventures of a young man whose body gained rubber properties after accidentall

Maycon Cypriano 3 Jun 30, 2022
MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.

MetPy MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data. MetPy follows semantic versioni

Unidata 971 Dec 25, 2022
Monitor the stability of a pandas or spark dataframe ⚙︎

Population Shift Monitoring popmon is a package that allows one to check the stability of a dataset. popmon works with both pandas and spark datasets.

ING Bank 403 Dec 07, 2022
vartests is a Python library to perform some statistic tests to evaluate Value at Risk (VaR) Models

gg I wasn't satisfied with any of the other available Gemini clients, so I wrote my own. Requires Python 3.9 (maybe older, I haven't checked) and opti

RAFAEL RODRIGUES 5 Jan 03, 2023
The Spark Challenge Student Check-In/Out Tracking Script

The Spark Challenge Student Check-In/Out Tracking Script This Python Script uses the Student ID Database to match the entries with the ID Card Swipe a

1 Dec 09, 2021
Randomisation-based inference in Python based on data resampling and permutation.

Randomisation-based inference in Python based on data resampling and permutation.

67 Dec 27, 2022
PyClustering is a Python, C++ data mining library.

pyclustering is a Python, C++ data mining library (clustering algorithm, oscillatory networks, neural networks). The library provides Python and C++ implementations (C++ pyclustering library) of each

Andrei Novikov 1k Jan 05, 2023
CRISP: Critical Path Analysis of Microservice Traces

CRISP: Critical Path Analysis of Microservice Traces This repo contains code to compute and present critical path summary from Jaeger microservice tra

Uber Research 110 Jan 06, 2023
Geospatial data-science analysis on reasons behind delay in Grab ride-share services

Grab x Pulis Detailed analysis done to investigate possible reasons for delay in Grab services for NUS Data Analytics Competition 2022, to be found in

Keng Hwee 6 Jun 07, 2022
Pipeline and Dataset helpers for complex algorithm evaluation.

tpcp - Tiny Pipelines for Complex Problems A generic way to build object-oriented datasets and algorithm pipelines and tools to evaluate them pip inst

Machine Learning and Data Analytics Lab FAU 3 Dec 07, 2022
Candlestick Pattern Recognition with Python and TA-Lib

Candlestick-Pattern-Recognition-with-Python-and-TA-Lib Goal Look at the S&P500 to try and get a better understanding of these candlestick patterns and

Ganesh Jainarain 11 Oct 07, 2022
NumPy aware dynamic Python compiler using LLVM

Numba A Just-In-Time Compiler for Numerical Functions in Python Numba is an open source, NumPy-aware optimizing compiler for Python sponsored by Anaco

Numba 8.2k Jan 07, 2023