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Python Algorithmic Trading Cookbook

You're reading from   Python Algorithmic Trading Cookbook All the recipes you need to implement your own algorithmic trading strategies in Python

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781838989354
Length 542 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Pushpak Dagade Pushpak Dagade
Author Profile Icon Pushpak Dagade
Pushpak Dagade
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Toc

Table of Contents (16) Chapters Close

Preface 1. Handling and Manipulating Date, Time, and Time Series Data 2. Stock Markets - Primer on Trading FREE CHAPTER 3. Fetching Financial Data 4. Computing Candlesticks and Historical Data 5. Computing and Plotting Technical Indicators 6. Placing Regular Orders on the Exchange 7. Placing Bracket and Cover Orders on the Exchange 8. Algorithmic Trading Strategies - Coding Step by Step 9. Algorithmic Trading - Backtesting 10. Algorithmic Trading - Paper Trading 11. Algorithmic Trading - Real Trading 12. Other Books You May Enjoy Appendix I
1. Appendix II
2. Appendix III

Creating datetime objects

The datetime module provides a datetime class, which can be used to accurately capture information relating to timestamps, dates, times, and time zones. In this recipe, you will create datetime objects in multiple ways and introspect their attributes.

How to do it…

Follow these steps to execute this recipe:

  1. Import the necessary module from the Python standard library:
>>> from datetime import datetime
  1. Create a datetime object holding the current timestamp using the now() method and print it:
>>> dt1 = datetime.now()
>>> print(f'Approach #1: {dt1}')

We get the following output. Your output will differ:

Approach #1: 2020-08-12 20:55:39.680195
  1. Print the attributes of dt1 related to date and time:
>>> print(f'Year: {dt1.year}')
>>> print(f'Month: {dt1.month}')
>>> print(f'Day: {dt1.day}')
>>> print(f'Hours: {dt1.hour}')
>>> print(f&apos...
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