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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

Converting a datetime object to a string

This recipe demonstrates the conversion of the datetime objects into strings which finds application in printing and logging. Also, this is helpful while sending timestamps as JSON data over web APIs.

How to do it…

Execute the following steps for this recipe:

  1. Import the necessary modules from the Python standard library:
>>> from datetime import datetime
  1. Fetch the current timestamp along with time zone information. Assign it to now and print it:
>>> now = datetime.now().astimezone()
  1. Cast now to a string and print it::
>>> print(str(now))

We get the following output. Your output may differ:

2020-08-12 20:55:48.366130+05:30
  1. Convert now to a string with a specific date-time format using strftime() and print it:
>>> print(now.strftime("%d-%m-%Y %H:%M:%S %Z"))

We get the following output. Your output may differ:

12-08-2020 20:55:48 +0530

How it works...

In step 1, you import the datetime class...

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