Skip to main content

DatExtractor - It is a very useful tool to extract data from text

DatExtractor - Extract date from text

pypi version supported Python version licence

Read the documentation at https://datextractor.readthedocs.io/en/latest/

The DatExtractor module provides the most efficient way of extracting date from text in the required format you need, available in Python.

Installation

DatExtractor can be installed from PyPI using pip (note that the package name is different from the importable name):

pip install DatExtractor

Download

DatExtractor is available on PyPI https://pypi.org/project/DatExtractor/1.0/

The documentation is hosted at: https://datextractor.readthedocs.io/en/latest/

Code

The code and issue tracker are hosted on GitHub: https://github.com/subbu-art/DatExtractor

Features

  • This Package help you to extract date from the text.

  • You can get the date in what ever format you actually want it.

  • Currently the package can handle formats seperated by [/.-].

  • Generic parsing of dates in almost any string format.

  • You can extract multiple dates as well and you can use it as per the requirement.

Quick example

Here’s a snapshot, just to give an idea about the power of the package. For more examples, look at the documentation.

Suppose you want to extract date from a text. you need to provide the text to the function as an argument. the default format of date you get is (mm/dd/yyyy). However you can modify the date format by passing the date format argument, so that you get the date in expected format.:

from DatExtractor import date_parser date_parser(“Please extract date:- 29/10/2020.”) [‘10/29/2020’] date_parser(“Please extract date:- 29/10/2020.”,”%Y/%d/%m”) [‘2020/29/10’] date_parser(“Please extract dates:- 29/10/2020, 12/21/2018”,”%d/%Y/%m”) [‘29/2020/10’,’21/2018/12’]

Author

The DatExtractor module was written by Sri Phani Subramanyam subbu27498@gmail.com in 2021.

It is maintained by:

Contact

For queries please contact subbu27498@gmail.com.

License

Copyright (C) 2007 Free Software Foundation, Inc. https://fsf.org/ Everyone is permitted to copy and distribute verbatim copies of this license document, but changing it is not allowed. GNU General Public License v3.0 https://choosealicense.com/licenses/gpl-3.0/#>.

Metadata

Release files for DatExtractor 1.0.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for DatExtractor 1.0.1
File Size Uploaded
DatExtractor-1.0.1.tar.gz 371.9 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for DatExtractor 1.0.1
File Interpreter ABI Platform
DatExtractor-1.0.1-py3-none-any.whl Python 3 none any Details

Total release size: 387.5 kB

Release files / DatExtractor-1.0.1.tar.gz

Download URL DatExtractor-1.0.1.tar.gz
Size 371.9 kB
Tags Source
SHA-256 checksum
How to use checksums
4da977727b70fb11c98c33d7011c08e3dce4d39f5881a86acf6106556e710809
BLAKE2b-256 checksum
How to use checksums
71520b3127f93b13d9df64b8920411a4b737a4c4f9480511081671bcab7ef16b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/3.1.1 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.4

Release files / DatExtractor-1.0.1-py3-none-any.whl

Download URL DatExtractor-1.0.1-py3-none-any.whl
Size 15.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
289183cc92f6bd5147d8f8fa339f5a9e1c87ca403d7ff91fca0033e86b6d8d20
BLAKE2b-256 checksum
How to use checksums
44edfd84ee35df257c21c7979ba536831ef2e5646fb5cb85f6d73adcac3f4aab
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.4.2 importlib_metadata/3.1.1 pkginfo/1.7.1 requests/2.22.0 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.4

Release history Release notifications | RSS feed

This release

1.0.1 This release

2 release files

1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page