Please note, this is a STATIC archive of website www.w3schools.com from 05 May 2020, cach3.com does not collect or store any user information, there is no "phishing" involved.
THE WORLD'S LARGEST WEB DEVELOPER SITE
HTML CSS JAVASCRIPT SQL PYTHON PHP BOOTSTRAP HOW TO W3.CSS JQUERY JAVA MORE FORUM EXERCISES REFERENCES

Python Tutorial

Python HOME Python Intro Python Get Started Python Syntax Python Comments Python Variables Python Data Types Python Numbers Python Casting Python Strings Python Booleans Python Operators Python Lists Python Tuples Python Sets Python Dictionaries Python If...Else Python While Loops Python For Loops Python Functions Python Lambda Python Arrays Python Classes/Objects Python Inheritance Python Iterators Python Scope Python Modules Python Dates Python JSON Python RegEx Python PIP Python Try...Except Python User Input Python String Formatting

File Handling

Python File Handling Python Read Files Python Write/Create Files Python Delete Files

Python NumPy

NumPy Intro NumPy Getting Started NumPy Creating Arrays NumPy Array Indexing NumPy Array Slicing NumPy Data Types NumPy Copy vs View NumPy Array Shape NumPy Array Reshape NumPy Array Iterating NumPy Array Join NumPy Array Split NumPy Array Search NumPy Array Sort NumPy Array Filter NumPy Random
Random Intro Data Distribution Random Permutation Seaborn Module Normal Distribution Binomial Distribution Poisson Distribution Uniform Distribution Logistic Distribution Multinomial Distribution Exponential Distribution Chi Square Distribution Rayleigh Distribution Pareto Distribution Zipf Distribution
NumPy ufunc
ufunc Intro ufunc Create Function ufunc Simple Arithmetic ufunc Rounding Decimals ufunc Logs ufunc Summations ufunc Products ufunc Differences ufunc Finding LCM ufunc Finding GCD ufunc Trigonometric ufunc Hyperbolic ufunc Set Operations

Machine Learning

Getting Started Mean Median Mode Standard Deviation Percentile Data Distribution Normal Data Distribution Scatter Plot Linear Regression Polynomial Regression Multiple Regression Scale Train/Test Decision Tree

Python MySQL

MySQL Get Started MySQL Create Database MySQL Create Table MySQL Insert MySQL Select MySQL Where MySQL Order By MySQL Delete MySQL Drop Table MySQL Update MySQL Limit MySQL Join

Python MongoDB

MongoDB Get Started MongoDB Create Database MongoDB Create Collection MongoDB Insert MongoDB Find MongoDB Query MongoDB Sort MongoDB Delete MongoDB Drop Collection MongoDB Update MongoDB Limit

Python Reference

Python Overview Python Built-in Functions Python String Methods Python List Methods Python Dictionary Methods Python Tuple Methods Python Set Methods Python File Methods Python Keywords Python Exceptions Python Glossary

Module Reference

Random Module Requests Module Math Module cMath Module

Python How To

Remove List Duplicates Reverse a String Add Two Numbers

Python Examples

Python Examples Python Exercises Python Quiz Python Certificate

Python MongoDB

❮ Previous Next ❯

Python can be used in database applications.

One of the most popular NoSQL database is MongoDB.

MongoDB

MongoDB stores data in JSON-like documents, which makes the database very flexible and scalable.

To be able to experiment with the code examples in this tutorial, you will need access to a MongoDB database.

You can download a free MongoDB database at https://www.mongodb.com.

PyMongo

Python needs a MongoDB driver to access the MongoDB database.

In this tutorial we will use the MongoDB driver "PyMongo".

We recommend that you use PIP to install "PyMongo".

PIP is most likely already installed in your Python environment.

Navigate your command line to the location of PIP, and type the following:

Download and install "PyMongo":

C:\Users\Your Name\AppData\Local\Programs\Python\Python36-32\Scripts>python -m pip install pymongo

Now you have downloaded and installed a mongoDB driver.

Test PyMongo

To test if the installation was successful, or if you already have "pymongo" installed, create a Python page with the following content:

demo_mongodb_test.py:

import pymongo
Run example »

If the above code was executed with no errors, "pymongo" is installed and ready to be used.

❮ Previous Next ❯