TinyDB provides the “where” clause that you can use while searching for a particular data. The “where” clause helps by filtering the unwanted data out. With the help of the “where” clause, you can access specific data quickly.

Before using the ”where” clause, we need to first import it. The syntax of “where” clause is given below −

from tinydb import where
db.search(where(''field'') == ''value'')

Let”s understand the use of ”where” clause with the help of a couple of examples.

The Student Database

For the examples, we will use the following student database.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example 1

Let”s use the “where” clause for the subject field −

db.search(where(''subject'') == ''MySQL'')

This query will fetch all the rows where the “subject” field is “MySQL”.

[{
   ''roll_number'': 4,
   ''st_name'': ''lakan'',
   ''mark'': 200,
   ''subject'': ''MySQL'',
   ''address'': ''mumbai''
}]

Example 2

Let”s see another use of the “where” clause with the “not equal to” condition −

db.search(where(''mark'') != 275)

This query will fetch all the rows where the “mark” field is not equal to “275” −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   }
]

It is possible to extend TinyDB and modify its behaviour. There are four ways to do so −

• Custom middleware

• Custom storages

• Hooks and overrides

• Subclassing TinyDB and table

In this chapter, let”s understand each of these methods in detail.

Custom Middleware

Sometimes the user does not want to write a new storage module. In such cases, the user can modify the behaviour of an existing storage module. Let”s see an example in which we will build a custom middleware filtering out the empty items −

First, let”s see the data that will go through the custom middleware −

{
   ''_default'': {
   1: {''key1'': ''value1''},
   2: {''key2'': ''value2''},
   ……………,
   N: {''keyN'': ''valueN''}
},

Now, let”s see how we can implement the custom middleware −

class RemoveEmptyItemsMiddleware(Middleware):
def __init__(self, storage_cls):
   super(self).__init__(storage_cls)
   def read(self):
      data = self.storage.read()
      for _default in data:
         st_name = data
      for doc_id in table:
         item = st_name
         if item == {}:
            del st_name
         return data
   def close(self):
      self.storage.close()

Custom Storage

As discussed earlier, TinyDB comes with two types of storages: in-memory and JSON file storage. Along with that, TinyDB also provides an option to add our own custom storage. In the following example, let”s see how we can add a YAML storage using PyYAML −

import yaml
class YAMLStorage(Storage):
def __init__(self, db.json):
   self. db.json = db.json

To read the file −

def read(self):
   with open(self.db.json) as handle:
   try:
      info = yaml.safe_load(handle.read())
      return info

   except yaml.YAMLError:
      return None

To write the file −

def write(self, info):
   with open(self.db.json, ''w+'') as handle:
      yaml.dump(info, handle)

To close the file −

def close(self):
   pass

Hooks and Overrides

Sometimes, both custom storage and custom middleware cannot work in the way you want. In such cases, user can use predefined hooks and overrides to modify the behaviour of TinyDB. As an example, we will be configuring the name of the default table as follows −

TinyDB.default_table_name = ''student_detail''

We can also assign cache capacity as follows −

TinyDB.table_class.default_query_cache_capacity = 50

Subclassing TinyDB and Table

This is the last way we can use to modify the behaviour of TinyDB. As an example, we will be creating a subclass that can be used with hooks and overrides to override the default classes.

Class ExtendTable(Table):
   TinyDB.table_class = student_detail

Given below is a set of TinyDB extensions that can be used for various operations −

TinyDB – Introduction

What is TinyDB?

TinyDB, written in pure Python programming language, is a small and lightweight document-orineted database with no external dependencies. It provides simple APIs that makes it easy to use. We can use TinyDB database for small project applications without any configuration.

TinyDB module, available as a third-party module for Python programs, can be used to store, retereive, and modify the data in JSON format.

Features of TinyDB

TinyDB is a clean and hustle-free database to operate several formats of documents. It has the following features.

• Really tiny − TinyDB database is truly tiny in nature with only 1800 lines of code and 1600 lines tests.

• Easy to use − TinyDB is easy to use because of its simple and clean APIs.

• Document oriented − In TinyDB, we can store any document. The document will be represented as dict.

• Independent − The TinyDB database is independent of any external server and external dependencies from PyPI.

• Compatible with Python 3.6 or latest − TinyDB is tested and compatible with Python 3.6 and latest. It also works fine with PyPY3.

• Extensible − TinDB is easily extensible either by writing new storages or by modifying the behaviour of storages.

Advantages of TinyDB

TinyDB provide various benefits for students, users, and developers.

• TinyDB is open-sourced database aand it does not require any external configirations.

• It is quite easy-to-use, and the user can effortlessly handle documents.

• It automatically stores documents in the database.

• TinyDB is ideal in case of personal projects where we need to install some data.

• It is suitable for small applications that would be blown away by large databases like SQL or an external DB server.

• It uses a simple command line and query to operate data.

• There is 100% test coverage i.e., no explanation needed.

Limitatations of TinyDB

TinyDB will not be the right choice for your project if you need to −

• create indexes for tables,

• manage relationships between tables,

• use an HTTP server, or

• access from multiple processors.

Comparison with Other Databases

The following table highlights how TinyDB is different from MySQL and Oracle databases −

TinyDB – Environmental Setup

Prerequisite for TinyDB setup

To install TinyDB, you must have Python 3.6 or newer installed in your system. You can go to the link and select the latest version for your OS, i.e., Windows and Linux/Unix. We have a comprehensive tutorial on Python, which you can refer at

Installing TinyDB

You can install TinyDB in three different ways: using the Pack Manager, from its Source, or from GitHub.

Using the Package Manager

The latest release versions of TinyDB are available over both the package managers, pip and conda. Let us check how you can use them to install TinyDB −

To install TinyDB using pip, you can use the following command −

pip install tinydb

To install TinyDB via conda-forge, you can use the following command −

conda install -c conda-forge tinydb

From Source

You can also install TinyDB from source distribution. Go to link to download the files and building it from source.

From GitHub

To install TinyDB using GitHub, grab the latest development version, unpack the files, and use the following command to install it −

pip install

Setting up TinyDB

Once installed, use the following steps to set up the TinyDB database.

Step 1: Import TinyDB and its Query

First, we need to import TinyDB and its Query. Use the following command −

from tinydb import TinyDB, Query

Step 2: Create a file

TinyDB database can store data in many formats like XML, JSON, and others. We will be creating a JSON file by using the following file −

db = TinyDB(''Leekha.json'')

The above command will create an instance of TinyDB class and pass the file Leekha.Json to it. This is the file where our data will be stored. Now, the TinyDB database set up is ready, and you can work on it. We can now insert data and operate the value in the database.

Uinstalling TinyDB

If in case you need to uninstall TinyDB, you can use the following command −

pip uninstall tinydb

TinyDB – Insert Data

We have created the instance of the TinyDB and passed a JSON file to it where our data will be stored. It is now time to insert the items in our database. The data should be in the form of a Python dictionary.

Syntax

To insert an item, you can use insert() method whose syntax is given below −

db.insert({''type1'': ''value1'', ''type2'': ''value2'', ''typeN'': ''valueN''})

We can also create a dictionary first and then use the insert() method to insert the data into our database.

data_item = {''type1'': ''value1'', ''type2'': ''value2'', ''typeN'': ''valueN'' } db.insert(data_item)

After running the above command, the insert() method will return the ID of the newly created object. And, our JSON file will look like the one shown below −

{"_default": {"1": {"type1": "value1", "type2": "value2", "typeN": "valueN"}}}

Look at the above table entries: ”default” is the name of the table, ”1” is the ID of the newly created object, and the values are the data we have just inserted.

Example: Inserting a Single Item

Let”s understand the above concept with the help of examples. Suppose we have a database having student information showing roll numbers, names, marks, subjects, and addresses. Following is the information stored in the database −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   }
]

In the above database, if you want to insert a new student record (i.e., a single item), use the following command −

db.insert({
   ''roll_number'': 6,
   ''st_name'':''jim'',
   ''mark'':300,
   ''subject'':''sql'',
   ''address'':''pune''
})

It will return the ID of the newly created object −

6

Let”s enter one more record−

db.insert({
   ''roll_number'': 7,
   ''st_name'':''karan'',
   ''mark'':290,
   ''subject'':''NoSQL'',
   ''address'':''chennai''
})

It will return the ID of the newly created object −

7

If you want to check the stored items in the database, use the all() method as follows −

db.all()

It will produce the following output −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   },
   {
      "roll_number":6,
      "st_name":"jim",
      "mark":300,
      "subject":"sql",
      "address":"pune"
   },
   {
      "roll_number":7,
      "st_name":"karan",
      "mark":290,
      "subject":"NoSQL",
      "address":"chennai"
   }
]

You can observe that it added two new data items in the JSON file.

Example: Inserting Multiple items at a Time

You can also insert multiple items at a time in a TinyDB database. For this, you need to use the insert_multiple() method. Let” see an example −

items = [
   {''roll_number'': 8, ''st_name'': ''petter'', ''address'': ''mumbai''},
   {''roll_number'': 9, ''st_name'': ''sadhana'', ''subject'': ''SQL''}
]
db.insert_multiple(items)

Now, check the stored items in database, using the all() method as follows −

db.all()

It will produce the following output −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   },
   {
      "roll_number":6,
      "st_name":"jim",
      "mark":300,
      "subject":"sql",
      "address":"pune"
   },
   {
      "roll_number":7,
      "st_name":"karan",
      "mark":290,
      "subject":"NoSQL",
      "address":"chennai"
   },
   {
      "roll_number":8,
      "st_name":"petter",
      "address":"mumbai"
   },
   {
      "roll_number":9,
      "st_name":"sadhana",
      "subject":"SQL"
   }
]

You can observe that it added two new data items in the JSON file. You can also skip some key values from the dataitems (as we have done) while adding the last two items. We have skipped ”mark” and ”address”.

TinyDB – Retrieve Data

There are numerous ways with the help of which you can retrieve data from a TinyDB database. But to use those ways, you first need to create an instance of the Query class as follows −

from tinydb import Query
Student = Query()

Here, Student is the name of the database.

Let”s check the various ways to retrieve the information from a TinyDB database.

Data Retrieval Using the Search() Method

The search() method, as its name implies, returns the list of items that mathches the query we provided, otherwise it will return an empty list.

For this and other examples, we will be using the following student database data −

[
   {
      "roll_number": 1,
      "st_name": "elen",
      "mark": 250,
      "subject": "TinyDB",
      "address": "delhi"
   },
   {
      "roll_number": 2,
      "st_name": "Ram",
      "mark": [
         250,
         280
      ],
      "subject": [
         "TinyDB",
         "MySQL"
      ],
      "address": "delhi"
   },
   {
      "roll_number": 3,
      "st_name": "kevin",
      "mark": [
         180,
         200
      ],
      "subject": [
         "oracle",
         "sql"
      ],
      "address": "keral"
   },
   {
      "roll_number": 4,
      "st_name": "lakan",
      "mark": 200,
      "subject": "MySQL",
      "address": "mumbai"
   },
   {
      "roll_number": 5,
      "st_name": "karan",
      "mark": 275,
      "subject": "TinyDB",
      "address": "benglore"
   }
]

Let”s take an example to understand the search() method −

from tinydb import TinyDB, Query
db = TinyDB("leekha.json")
student = Query()
db.search(student.subject == ''TinyDB'' )

The above query will retrieve the the following output from the student database −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Data Retrieval Using the get() Method

As opposed to the search() method, the get() method returns only one matching document. It will return None, otherwise. For example, let”s take the following code −

from tinydb import TinyDB, Query
student = Query()
db.get(student.subject == ''TinyDB'' )

The above query will retrieve the following data from the student database.

[{''roll_number'': 1, ''st_name'': ''elen'', ''mark'': 250, ''subject'': ''TinyDB'', ''address'': ''delhi''}]

Data Retrieval using the all() Method

The all() method returns all the documents in the database. For example,

db.all()

It will retrieve the entire data from the student database.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Data Retrieval Using the for Loop

The for loop also returns all the documents in the database. For example,

for info in db:
   print(info)

Just like the all() method, it will retrieve all the rows from the student database.

TinyDB – Update Data

TinyDB can store data in many formats and we can easily reterive the stored data using various methods. But sometimes, we need to update the data, for which we can use the update() method.

For updating the database, we first need to create an instance of the Query class. You can use the following command for this purpose −

from tinydb import Query
Student = Query()

Here, Student is the name of our database.

The update() Method

Here is the syntax for the update() method −

db.update({ updated field: updated information… }, stable field: information)

Let”s take an example to understand how the update() method works. For this example, we will be using the following student database −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

As per the given data, the name of the student with the roll_number “1” is “elen”. The following query will update the student name to “Adam” −

from tinydb import TinyDB, Query
student = Query()
db.update({''st_name'' : ''Adam''}, student.roll_number == 1 )

It will return the id of the updated object −

[1]

Now, you can use the all() method to see the updated database −

db.all()

It will display the updated data −

[
   {
      "roll_number":1,
      "st_name":"Adam",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Sometimes, we need to update one or more fields of all the documents in a database. For this, we can use the update() mehod directly and don”t need to write the query argument. The following query will change the address of all the students to ”College_Hostel”−

db.update({''address'': ''College_Hostel''})

It will return the ids of the updated object −

[1,2,3,4,5]

Again, you can use the all() method to see the updated database.

db.all()

It will show the updated data −

[
   {
      "roll_number":1,
      "st_name":"Adam",
      "mark":250,
      "subject":"TinyDB",
      "address":"College_Hostel"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":" College_Hostel "
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":" College_Hostel "
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":" College_Hostel "
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":" College_Hostel "
   }
]

Observe that the address fields of all the rows have the same data, i.e., ”College_Hostel”.

TinyDB – Delete Data

In case you need to delete a particular set of data permanently from a TinyDB database, you can do so by using the remove() method. Like for reteriving and updating the data, you first need to create an instance of the Query class for deleting the data. You can use the following command for this purpose −

from tinydb import Query
Student = Query()

Here, Student is the name of our database.

The remove() Method

Here is the syntax for the remove() method −

db.remove( Query() field regex )

The remove() method accepts both an optional condition as well as an optional list of documents IDs.

The student Database

We will use the following student database, for the examples in this chapter.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example: Deleting a Single Row of Data

Let”s take an example to understand the remove() method.

from tinydb import TinyDB, Query
student = Query()
db.remove(student.roll_number == 5)

The above query will delete the data where the student”s roll number is 5. It will return the ID of the removed object −

[5]

Now, we can use the all() method to see the updated database.

db.all()

It will display the data from the updated database −

[
   {
      "roll_number":1,
      "st_name":"Adam",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   }
]

Example: Deleting Multiple Rows of Data

If you want to remove more than one row at a time, you can use the remove() method as follows −

from tinydb import TinyDB, Query
student = Query()
db.remove(student.roll_number > 2)

It will return the IDs of the removed object:

[3,4]

Use the all() method to see the updated database.

db.all()

It will display the data from the updated database −

[
   {
      "roll_number":1,
      "st_name":"Adam",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   }
]

Example: Deleting the Entire Data

If you want to remove all the data from a database, you can use the truncate() method as follows −

db.truncate()

Next, use the all() method to see the updated database.

db.all()

It will show an empty database as the output −

[]

TinyDB – Querying

TinyDB has a rich set of queries. We have ways to construct queries: the first way resembles the syntax of ORM tools and the second is the traditional way of using the ”Where” clause.

In this chapter, let”s understand these two ways of constructing a query in a TinyDB database.

The First Method: Importing a Query

The first method resembles the syntax of ORM tools in which first we need to import the query in the command prompt. After importing, we can use the query object to operate the TinyDB database. The syntax is given below −

from tinydb import Query
student = Query()

Here, ”student” is the name of our database. For the examples, we will be using the following student database.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example

Following is the query to retereive the data from the student database where the roll_no of the students are less than 3 −

>>> db.search(Query().roll_number < 3)

Or,

>>> student = Query()
>>> db.search(student.roll_number < 3)

The above search query will produce the following result −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   }
]

Sometimes the file name is not a valid Python identifier. In that case, we would not be able to access that field. For such cases, we need to switch to dict access notation as follows −

student = Query();

# Invalid Python syntax
db.search(student.security-code == ''ABCD'')

# Use the following dict access notation
db.search(student[''security-code''] == ''ABCD'')

The Second Method: Using the “where” Clause

The second way is the traditional way of constructing queries that uses the “where” clause. The syntax is given below −

from tinydb import where
db.search(where(''field'') == ''value'')

Example

TinyDB “where” clause for the subject field −

db.search(where(''subject'') == ''MySQL'')

The above query will produce the following output −

[{
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
}]

TinyDB – Searching

TinyDB provides the search() method to help you search any data from a document. Along with the query() object, the search() method can be used to find the data in a JSON file. We have various ways in which we can use the search() method on a TinyDB database.

Method 1: TinyDB search() with Existence of a Field

We can search the data from a database based on the existence of a field. Let”s understand it with an example. For this and other examples, we will be using the following student database.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example

The search query based on the existence of a field is as follows −

from tinydb import Query
student = Query()
db.search(student.address.exists())

The above query will retrieve the following data from the student file −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Method 2: TinyDB search() with Regular Expression

We can search for a particular data from a database using regular expression (Regex). Let”s understand how it works with a couple of examples.

Example 1

Full item search matching the Regular Expression −

from tinydb import Query
student = Query()
db.search(student.st_name.matches(''[aZ]*''))

This query will produce the following output −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example-2

Case-sensitive search with Regular Expression −

from tinydb import Query
import re
student = Query()
db.search(student.st_name.matches(''lakan'', flags=re.IGNORECASE))

It wil produce the following output −

[{
   ''roll_number'': 4,
   ''st_name'': ''lakan'',
   ''mark'': 200,
   ''subject'': ''MySQL'',
   ''address'': ''mumbai''
}]

Example-3

Any part of the item matching with Regular Expression −

from tinydb import Query
student = Query()
db.search(student.st_name.search(''r+''))

This query will produce the following output −

[{
   ''roll_number'': 5,
   ''st_name'': ''karan'',
   ''mark'': 275,
   ''subject'': ''TinyDB'',
   ''address'': ''benglore''
}]

Method 3: TinyDB search() using a Substring

We can also use a substring while searching for a particular data from a TinyDB database. Let”s understand how it works with a couple of examples −

Example-1

Take a look at this query; it will fetch the all the rows where the “address” field is “delhi”.

from tinydb import Query
student = Query()
db.search(student[''address''] == ''delhi'')

It will produce the following output −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   }
]

Example-2

In this query, we have used a slightly different syntax for the search() method.

from tinydb import Query
student = Query()
db.search(student.address.search(''mumbai''))

It will fetch all the rows where the “address” field is “mumbai”.

[{
   ''roll_number'': 4,
   ''st_name'': ''lakan'',
   ''mark'': 200,
   ''subject'': ''MySQL'',
   ''address'': ''mumbai''
}]

TinyDB – The where Clause

TinyDB provides the “where” clause that you can use while searching for a particular data. The “where” clause helps by filtering the unwanted data out. With the help of the “where” clause, you can access specific data quickly.

Before using the ”where” clause, we need to first import it. The syntax of “where” clause is given below −

from tinydb import where
db.search(where(''field'') == ''value'')

Let”s understand the use of ”where” clause with the help of a couple of examples.

The Student Database

For the examples, we will use the following student database.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example 1

Let”s use the “where” clause for the subject field −

db.search(where(''subject'') == ''MySQL'')

This query will fetch all the rows where the “subject” field is “MySQL”.

[{
   ''roll_number'': 4,
   ''st_name'': ''lakan'',
   ''mark'': 200,
   ''subject'': ''MySQL'',
   ''address'': ''mumbai''
}]

Example 2

Let”s see another use of the “where” clause with the “not equal to” condition −

db.search(where(''mark'') != 275)

This query will fetch all the rows where the “mark” field is not equal to “275” −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   }
]

TinyDB – The exists() Query

TinyDB provides an advanced query called exists() that checks the existence of data in a JSON file. The exists() query actually tests the availability of a subfield data from a JSON file. The exists() query works on the basis of a Boolean condition. If the subfield exists (i.e., BOOLEAN TRUE), it will fetch the data accordingly from the JSON file, otherwise it will return a blank value.

Syntax

The syntax of TinyDB exists() is as follows −

db.search(Query().field.exists())

Here, field represents the part of data that we want to access. Query() is the object created from the JSON table student.

We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s use the TinyDB exists() query for the field named ”subject” −

db.search(student.subject.exists())

This query will fetch all the rows because all the rows have the “subject” field −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":" TinyDB ",
      "address":"benglore"
   }
]

Example 2

Now let”s use the exists() query for the ”address” field −

db.search(student.address.exists())

It will fetch the following rows −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":" TinyDB ",
      "address":"benglore"
   }
]

Example 3

Now, let”s try the exists() query for a field that is not available −

db.search(student.city.exists())

Since none of the rows in the given table has a field called “city”, the above exists() query will return a blank value −

[]

TinyDB – The matches() Query

The matches() query matches the data from a JSON file with a given condition (in the form of a regular expression) and returns the results accordingly. It will return a blank value if the condition does not match with the data in the file.

Syntax

The syntax of TinyDB matches() is as follows −

db.search(Query().field.matches(regular expression))

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student.

Let”s understand how it works with the help of a couple of examples. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can use matches() for full item search.

from tinydb import Query
student = Query()
db.search(student.st_name.matches(''[aZ]*''))

This query will fetch all the rows −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example 2

Let”s see how we can use matches() for case-sensitive search.

from tinydb import Query
import re
student = Query()
db.search(student.st_name.matches(''ram'', flags=re.IGNORECASE))

This query will fetch the rows where the student name matches the string “ram”. Observe that we have used a flag to ignore the case while matching the strings.

[{
   ''roll_number'': 2,
   ''st_name'': ''Ram'',
   ''mark'': [250, 280],
   ''subject'': [''TinyDB'', ''MySQL''],
   ''address'': ''delhi''
}]

Example 3

Let”s see how we can use matches() for a particular item.

student = Query()
db.search(student.address.matches(''keral''))

This query will fetch the rows where the address matches the string “keral”.

[{''roll_number'': 3, ''st_name'': ''kevin'', ''mark'': [180, 200], ''subject'':
[''oracle'', ''sql''], ''address'': ''keral''}]

Example 4

Let”s see what matches() would return when it does not find a particular item −

student = Query()
db.search(student.address.matches(''Ratlam''))

There are no rows where the “address” field matches the string “Ratlam”, hence it will return a blank value −

[]

TinyDB – The test() Query

The test() query will test if the given arguments match with the data in a table. If it matches with the data, it will return the matched data, otherwise it will return blank. First of all, we need to define a test function and its arguments and then it will search the item in a given database.

Syntax

The syntax of TinyDB test() is as follows −

db.search(Query().field.test(function or condition, *arguments))

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student.

We can create a custom test function as follows −

object = lambda t: t == ''value''

Here the lamba keyword is important to create the custom test function.

Let”s understand how it works with the help of a couple of examples. We will use the same student database that we have used in all the previous chapters.

Example 1

We will first create a test function and then use it in our student table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
objects = lambda t: t == [250, 280]
db.search(Query().mark.test(objects))

It will fetch the rows where the “mark” field has the values [250, 280] −

[{''roll_number'': 2, ''st_name'': ''Ram'', ''mark'': [250, 280], ''subject'':
[''TinyDB'', ''MySQL''], ''address'': ''delhi''}]

Example 2

In this example, we will use the “subject” field in the test function −

student = Query()
db = TinyDB(''student.json'')
objects = lambda t: t == ''TinyDB''
db.search(student.subject.test(objects))

This query will fetch all the rows where the “subject” field has the value “TinyDB” −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

TinyDB – The any() Query

For searching the fields containing a list, TinyDB provides a method called any(). This method matches at least one given value from the database. It finds either an entire list or a minimum one value as per the query provided.

Syntax

The syntax of TinyDB any() is as follows −

db.search(Query().field.any(query|list)

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student.

• If we will provide query as the argument of any() method, it will match all the documents where at least one document in the list field match the given query.

• On the other hand, if we will provide list as the argument of any() method, it will match all the documents where at least one document in the list field is present in the given list.

Let”s understand how it works with the help of a couple of examples. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can find the fields from our student table where subject is either TinyDB, or MySQL, or SQL or combination of any two or three −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(Query().subject.any([''TinyDB'', ''MySQL'', ''oracle'']))

The above query will fetch all the rows where the “subject” field contains any of the following values: “TinyDB”, “MySQL”, or “oracle” −

[
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   }
]

Example 2

Let”s see how the any() method reacts when it doesn”t match anything from the given list −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(Query().subject.any([''Oracle'']))

This query will return a blank value because there are no rows with its “subject” as “Oracle”.

[]

Example 3

Observe that it is case-sensitive. The “subject” field does not have “Oracle“, but it does have “oracle“. Try the following query −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(Query().subject.any([''oracle'']))

It will fetch the following row −

[{
   ''roll_number'': 3,
   ''st_name'': ''kevin'',
   ''mark'': [180, 200],
   ''subject'': [''oracle'', ''sql''],
   ''address'': ''keral''
}]

As it is case-sensitive, it returned a blank value in the previous example because there are no rows with its “subject” as “Oracle”.

TinyDB – The all() Query

TinyDB provides a method called all() that finds an entire list of values as per the query provided. Let”s take an example and find out how it works.

Syntax

The syntax of TinyDB all() is as follows −

db.search(Query().field.all(query|list)

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student.

• If we will provide a query as the argument of all() method, it will match all the documents where all documents in the list field match the given query.

• On the other hand, if we will provide a list as the argument of all() method, it will match all the documents where all documents in the list field are present in the given list.

Let”s understand how it works with the help of a couple of examples. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can find the fields from our student table where the subjects are both TinyDB, and MySQL −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(Query().subject.all([''TinyDB'', ''MySQL'']))

This query will fetch the following row −

[{
   ''roll_number'': 2,
   ''st_name'': ''Ram'',
   ''mark'': [250, 280],
   ''subject'': [''TinyDB'', ''MySQL''],
   ''address'': ''delhi''
}]

Example 2

Let”s see how we can use all() to get the entire data from our database −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.all()

It will fetch all the rows from the linked database −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

TinyDB – The one_of() Query

For matching the subfield data, TinyDB provides a method called one_of(). This method searches a single category and gets at least one similar value. It will match if the field is contained in the provided list.

Syntax

The syntax of TinyDB one_of() is as follows −

db.search(Query().field.one_of(list)

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student. It will fetch either single or multiple values of one category.

Let”s understand how it works with the help of a couple examples. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can find the fields from our student table where address is either “delhi” or “pune” −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(Query().address.one_of([''delhi'', ''pune'']))

It will fetch all the rows where the “address” field contains either “delhi” or “pune”.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   }
]

Example 2

Let”s see another example with ”subject” field −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(Query().subject.one_of([''TinyDB'', ''MySQL'']))

It will fetch all the rows where the “subject” field contains either “TinyDB” or “MySQL”.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":4,
      "st_name":"lakhan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

TinyDB – Logical Negate

Logical Negate works as an inverse logical gate. It will match the documents that don”t match the given query. In simple words, it will display the opposite meaning of the given command.

Syntax

The syntax of TinyDB Logical Negate is as follows −

db.search(~(Query().field)

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student. It will fetch the data that represents the opposite meaning of the given command.

Let”s take a couple of examples and see how it works. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can find the fields from our student table where the student name is not ”elen” −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(~(Query().st_name == ''elen''))

The above query will fetch all the rows where the student name is not “elen”.

[
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example 2

Let”s see how we can avoid a particular address using logical negate −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search(~(student.address.one_of([''keral'', ''delhi''])))

This query will fetch all the rows where the “address” field does not have either “keral” or “delhi”.

[
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

TinyDB – Logical AND

The “Logical AND” operator combines multiple conditions and evaluates to True if all the conditions are met. TinyDB Logical AND operates on two queries of a database. If both the queries are True, TinyDB will fetch the required data. On the other hand, if any one of the queries is False, it will return a blank.

Syntax

The syntax of TinyDB Logical AND is as follows −

db.search((Query().(query1) & (Query().(query2)

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student. It will fetch the data if both the conditions met, otherwise it will return a blank.

Let”s take a couple examples and see how Logial AND works. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see what our TinyDB Student database returns when we apply Logical AND on “st_name=lakhan” and “subject=MYSQL” field −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search ((Query().st_name == ''lakhan'') & (Query().subject == ''MySQL''))

This query will fetch only those rows where the student name is “lakhan” and the “subject” is “MySQL”.

[{
   ''roll_number'': 4,
   ''st_name'': ''lakhan'',
   ''mark'': 200,
   ''subject'': ''MySQL'',
   ''address'': ''mumbai''
}]

Example 2

In this example, let”s apply Logical AND on the “subject” and “roll_number” fields −

from tinydb import TinyDB, Query
student = Query()
db = TinyDB(''student.json'')
db.search((student.subject.search(''M'')) & (student.roll_number < 5))

This query will fetch all the rows where the roll_number is less than “4” and “subject” starts with the letter “M”.

[{
   ''roll_number'': 4,
   ''st_name'': ''lakhan'',
   ''mark'': 200,
   ''subject'': ''MySQL'',
   ''address'': ''mumbai''
}]

TinyDB – Logical OR

The “Logical OR” operator combines multiple conditions and evaluates to True only if either of the condition is met. TinyDB Logical OR operates on two queries of a database. If any one of the queries is True, TinyDB will fetch the required data. On the other hand, if both the queries are False, it will return a blank.

Syntax

The syntax of TinyDB Logical OR is as follows −

db.search((Query().(query1) | (Query().(query2)

Here, field represents the part of data that we want to access. Query() is the object created of our JSON table named student. It will fetch the data if any one of the conditions is met, otherwise it will return a blank.

Let”s take a couple of examples and see how it works. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see what our TinyDB Student database returns when we apply Logical OR on the “st_name” and “subject” fields and check the following conditions: “st_name=lakhan” and “subject=TinyDB” −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search ((Query().st_name == ''lakan'') | (Query().subject == ''TinyDB''))

This query will fetch the following rows −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":4,
      "st_name":"lakhan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   }
]

Example 2

In this example, let”s apply Logical OR on the “subject” and “roll_number” fields −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.search((student.subject.search(''M'')) | (student.roll_number < 5))

This query will fetch all the rows where the “subject” field starts with the letter “M” or the “roll_number” is less than “5”.

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakhan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   }
]

TinyDB – Handling Data Query

TinyDB – Storing Multiple Data

We have already discussed how you can use the ”insert” query to store data in a database. On a similar note, you can use the ”insert_multiple” query to store multiple data items simultaneously. Here is the syntax of ”insert_multiple” query in TinyDB:

db.insert_multiple ([
   { key1 : value1, key2 : value2, ..., keyN : valueN},
   { key1 : value1, key2 : value2, ..., keyN : valueN }
])

Let”s take a couple of examples to demonstrate how the “insert_multiple” query works. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can insert two records of students in our ”student” table using the insert_multiple query −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.insert_multiple([
   {
      "roll_number":6,
      "st_name":"Siya",
      "mark":240,
      "subject":"NoSQL",
      "address":"pune"
   },
   {
      "roll_number":7,
      "st_name":"Adam",
      "mark":210,
      "subject":"oracle",
      "address":"Keral"
   }
])

It will display the document IDs of the newly saved records −

[6, 7]

Let”s check whether the new records are saved in the database or not? Use the all() method, as shown below −

db.all()

It will show all the records stored in the given table −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   },
   {
      "roll_number":6,
      "st_name":"Siya",
      "mark":240,
      "subject":"NoSQL",
      "address":"pune"
   },
   {
      "roll_number":7,
      "st_name":"Adam",
      "mark":210,
      "subject":"oracle",
      "address":"Keral"
   }
]

You can see the two new records of students have been saved in the database.

Example 2

Let”s see how we can use insert_multiple with a for loop to insert multiple values simultaneously in a table. Use the following code −

db.insert_multiple({''roll_number'': 10, ''numbers'': r} for r in range(3))

It will return the document IDs of the newly saved records −

[8, 9, 10]

Again, use the all() method to verify whether the new records have been saved in the database or not?

db.all()

It will fetch all the records stored in the given student table −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"TinyDB",
      "address":"benglore"
   },
   {
      "roll_number":6,
      "st_name":"Siya",
      "mark":240,
      "subject":"NoSQL",
      "address":"pune"
   },
   {
      "roll_number":7,
      "st_name":"Adam",
      "mark":210,
      "subject":"oracle",
      "address":"Keral"
   },
   {
      "roll_number":10,
      "numbers":0
   },
   {
      "roll_number":10,
      "numbers":1
   },
   {
      "roll_number":10,
      "numbers":2
   }
]

Notice the last three rows. We have used the insert_multiple method with a for loop to insert three new entries.

TinyDB – Modifying the Data

We have already discussed the update query with the help of which we can modify the values as well as handle the data in our database. But the update query such as db.update(fields, query) allows us to update a document by adding or overwriting its values.

But sometimes, we would like to remove one field or need to increment its value. In such cases, we can pass a function instead of fields. We can use the following operations with the update query −

The Increment Query

The increment query, as its name implies, is used to increment the value of a key in the database. The syntax of increment query is as follows −

from tinydb.operations import increment
db.update(increment(''key''))

The Add Query

The add query is used to add value to the value of a key. It works for the strings as well. The syntax of add query is as follows −

from tinydb.operations import add
db.update(add(key, value))

The Set Query

This query is used to set the key to the value of the data. The syntax of set query is as follows −

from tinydb.operations import set
db.update(set(key, value))

The Decrement Query

The decrement query is used to decrement the value of a key. The syntax of decrement query is as follows −

from tinydb.operations import decrement
db.update(decrement(key))

The Subtract Query

The subtarct query is used to subtract value from the value of a key. The syntax of subtract query is as follows −

from tinydb.operations import subtract
db.update(subtract(key, value))

The Delete Query

The delete query is used to delete a key from a document. The syntax of delete query is as follows −

from tinydb.operations import delete
db.update(delete(key))

Let”s take a couple of examples to demonstrate how you can use these operations along with the update query. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can increment the marks of a student in our student table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
from tinydb.operations import increment
db.update(increment(''mark''), Query().mark == 275)

It will produce the following output −

[5]

The above output shows that it has updated the record whose document ID is 5.

Example 2

Let”s see how we can add 5 marks to the marks of a student in our student table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
from tinydb.operations import add
db.update(add(''mark'', 5), Query().mark == 200)

It will produce the following output −

[4]

The above output shows that it has updated the record whose document ID is 4.

Example 3

Let”s see how we can set the marks to 259 where the marks of a student are 250 in our student table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
from tinydb.operations import add
db.update(add(''mark'', 259), Query().mark == 250)

It will produce the following output −

[1]

The above output shows that it has updated the record whose document ID is 1.

Example 4

Let”s see how we can decrement the marks of a student in our student table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
from tinydb.operations import decrement
db.update(decrement(''mark''), Query().mark == 205)

It will produce the following output −

[4]

The above output shows that it has updated the record whose document ID is 4.

Example 5

Let”s see how we can subtract 5 marks to the marks of a student in our student table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
from tinydb.operations import add
db.update(add(''mark'', 5), Query().mark == 204)

It will produce the following output −

[4]

The above output shows that it has updated the record whose document ID is 4.

Example 6

Let”s see how we can subtract 5 marks to the marks of a student in our student table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
from tinydb.operations import delete
db.update(delete(''mark''), Query().mark == 209)

It will produce the following output −

[4]

The above output shows that it has updated the record whose document ID is 4. It will delete the mark field from the database where the value is 209.

Example 7

Let”s see how we can update multiple values in a table with a single query −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
from tinydb import where
db.update_multiple([
   ({''st_name'':''Eliana''}, where (''roll_number'')==1),
   ({''mark'':20}, where (''roll_number'') ==2)
])

It will produce the following output −

[1,2]

The above output shows that it has updated two records whose document IDs are 1 and 2.

TinyDB – Upserting Data

We discussed the update and insert queries, but sometimes, we a need a mix of both update and insert. In such cases, TinyDB provides a unique upsert query. This query helps us to insert and update data at a time as per the condition. It works in two ways −

• If data is available, then it chooses the update operation.

• If data is not available, then it chooses the insert operation.

Syntax

The syntax of upsert query is as follows −

db.upsert({ ''key'' : ''value'', ''logged - in'' : True}, regular expression)

Let”s take a couple of examples to demonstrate how you can use this upsert query in TinyDB. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can use the upsert query to change the address of a student to “surat”, whose roll numbe is 2. In this case, we we have a matching user, hence it will update with the address to have logged-in set to True −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.upsert({''address'':''Surat''}, Query().roll_number==2)

It will produce the following output, which means record number “2” got updated.

[2]

Use the following code to verify whether record number “2” got updated or not −

db.get(doc_id=2)

It will show the updated data −

{
   ''roll_number'': 2,
   ''st_name'': ''Ram'',
   ''mark'': [250, 280],
   ''subject'': [''TinyDB'', ''MySQL''],
   ''address'': ''Surat''
}

Example 2

Let”s see how we can use the upsert query for unavailable data in our table −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.upsert({''E-mail'':''ram@gmail.com'',''logged-in'': True},
Query().roll_number==2)

It will show the following output, which means the document with the ID “2” got updated.

[2]

Use the following code to verify the updated values −

db.get(doc_id=2)

It will produce the following output −

{
   "roll_number":2,
   "st_name":"Ram",
   "mark":[
      250,
      280
   ],
   "subject":[
      "TinyDB",
      "MySQL"
   ],
   "address":"Surat",
   "logged-in":true,
   "E-mail":"ram@gmail.com"
}

Notice that we used the upsert query to create a new key (E-mail) which was non-existent and supplied it with the value “ram@gmail.com“.

TinyDB – Retrieving Data

After creating a database, we need to frequently retrieve the data from that database. Following are the ways by which we can reterive the data from a database −

The len() Query

With the help of this query, we can get the number of documents in a database. Its syntax is as follows −

len(db)

The get Query

The get query is used to reterive specific documents matching a query. Its syntax is as follows −

db.get(query)

The contains Query

The contains query is used to check whether the database contains a matching value or not. Its syntax is as follows −

db.contains(query)

The count Query

The count query is used to retrieve the number of matching documents from a database. Its syntax is as follows −

db.count(query)

Let”s take a few examples to understand how these queries work in TinyDB. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can use the len() query to get the number of documents in our database −

from tinydb import TinyDB
db = TinyDB(''student.json'')
print ("Number of documents in student db: ", len(db))

It will show the number of documents present in the specified database −

Number of documents in student db: 5

Example 2

Let”s see how we can use the get() query to get a specific document from our database −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.get(Query().address == ''delhi'')

This query will fetch the row where the “address” field has the value “delhi”.

{
   ''roll_number'': 1,
   ''st_name'': ''elen'',
   ''mark'': 250,
   ''subject'': ''TinyDB'',
   ''address'': ''delhi''
}

Example 3

Let”s see how we can use the contains() query to verify if our database contains a specific value −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
db.contains(Query().address == ''delhi'')

The contains() query returns a Boolean value, based on the existence of the specified value in the given database. In this case, it will return “True” because our database does have a “address” key with the value “delhi”.

True

Example 4

Let”s see how we can use the count() query to get the number of documents for which a given condition is True −

from tinydb import TinyDB, Query
db = TinyDB(''student.json'')
print (db.count(Query().subject == ''NoSQL''))

It will return the following output −

3

It means there are 3 documents in the database where the “subject” key has the value “NoSQL”.

TinyDB – Document ID

TinyDB uses document ID, represented by doc_id, to access as well as modify the value of documents in a database. Here we will see how we can use this document_id for various operations.

Display Data using Document ID

We can use doc_id in get() method to display the data from a database. Its syntax is as follows −

db.get(doc_id = value)

Check for a Document in a Database

We can use doc_id in contains() method to check if a document is present in a database or not. Its syntax is given below −

db.contains(doc_id = value)

Update All Documents

We can use doc_id in update() method to update all the documents in a database with the given document IDs. Here is its syntax −

db.update({key : value}, doc_ids = […])

Remove a Document

We can use doc_id in remove() method to remove a specific document or all the documents in a database with the given document IDs. Its syntax is given below −

db.remove(doc_ids = […])

Let”s take a few examples to demonstrate how you can use doc_id in TinyDB with these methods. We will use the same student database that we have used in all the previous chapters.

Example 1

Let”s see how we can use doc_id to get the data of a specific document from a database −

from tinydb import TinyDB
db = TinyDB(''student.json'')
db.get(doc_id = 5)

It will fetch the data from the document with the doc_id “5”.

{
   ''roll_number'': 5,
   ''st_name'': ''karan'',
   ''mark'': 275,
   ''subject'': ''oracle'',
   ''address'': ''benglore''
}

Example 2

Let”s see how we can use doc_id to check if the database contains a document with a specific ID −

from tinydb import TinyDB
db = TinyDB(''student.json'')
db.contains(doc_id = 15)

Based on the availability of the document, it will return either True or False. In this case, our database does not have a document with the doc_id “15”. Hence, it returns False.

False

Example 3

Let”s see how we can use doc_id to update the documents of our database −

from tinydb import TinyDB
db = TinyDB(''student.json'')
db.update({''mark'':''280''}, doc_ids = [4])

Here, we updated the “marks” field of the document with the doc_id “4”. To check the updated data, use the following query −

print(db.get(doc_id=4))

It will display the updated data of the document with the doc_id “4” −

{
   ''roll_number'': 4,
   ''st_name'': ''lakan'',
   ''mark'': ''280'',
   ''subject'': ''MySQL'',
   ''address'': ''mumbai''
}

Example 4

Let”s see how we can use doc_id to remove specific documents from our database −

from tinydb import TinyDB
db = TinyDB(''student.json'')
db.remove(doc_ids = [3,4])

Here, we removed two documents with doc_ids “3” and “4”. To verify, use the following get() queries −

db.get(doc_id=3)
db.get(doc_id=4)

It will show the following output −

None
None

It means that we have successfully removed the documents with doc_ids “3” and “4”.

TinyDB – Tables

In TinyDB, we can work with multiple tables. These tables have the same properties as the TinyDB class. Let”s see how we can create tables in TinyDB and apply various operations on them −

Creating Tables

It’s very easy to create a table in TinyDB. Here”s its syntax −

table_object = db.table(''table name'')

Inserting Values in a Table

To insert data in a specific table, use the following syntax −

table_object.insert({ ''key'' : value })

Retreiving Values from a Table

To retrieve values from a table, use the following query −

table_object.all()

Deleting a Table from a Database

To delete a table from a database, use the drop_table() query. Here is its syntax −

db.drop_table(''table name'')

Delete Multiple Tables from a Database

To delete multiple tables from a database, use the following query −

db.drop_tables()

Let”s understand how to use these queries with the help of a few examples. We will use the same student database that we have used in all the previous chapters.

Example 1

Use the following code to create a new table called Student_Detail −

from tinydb import TinyDB, Query
db = TinyDB("student.json")
table_object = db.table(''Student_Detail'')

Example 2

Next, let”s insert values in this new table Student_Detail −

from tinydb import TinyDB, Query
db = TinyDB("student.json")
table_object = db.table(''Student_Detail'')
table_object.insert({
   ''roll_number'': 1,
   ''st_name'': ''elen'',
   ''mark'': 250,
   ''subject'': ''TinyDB'',
   ''address'': ''delhi''
})

It will return the doc_id of the record inserted in the table.

[1]

To verify, use the following code −

from tinydb import TinyDB, Query
db = TinyDB("student.json")
table_object = db.table(''Student_Detail'')
table_object.all()

It will show data contained in the Student_Detail table −

{''roll_number'': 1, ''st_name'': ''elen'', ''mark'': 250, ''subject'': ''TinyDB'', ''address'': ''delhi''}

Example 3

To see all the tables present in the database, use the following query −

from tinydb import TinyDB, Query
db = TinyDB("student.json")
print(db.tables())

There are two tables inside “student.json”. It will show the names of these two tables −

{''Student_Detail'', ''_default''}

Example 4

Let”s see how we can reterive all the values from a table −

from tinydb import TinyDB, Query
db = TinyDB("student.json")
table_object = db.table("Student_Detail")
print(table_object.all())

It will show the following output −

[{
   ''roll_number'': 1,
   ''st_name'': ''elen'',
   ''mark'': 250,
   ''subject'': ''TinyDB'',
   ''address'': ''delhi''
}]

Example 5

Let”s see how we can remove a table from a database −

from tinydb import TinyDB, Query
db = TinyDB("student.json")
db.drop_table(''Student_Detail'')

It will remove the “Student_Detail” table from the database. To remove all the tables from a database, use the “drop_tables()” query −

db.drop_tables()

It will remove all the tables from the database.

TinyDB – Default Table

TinyDB provides a default table in which it automatically saves and modifies the data. We can also set a table as the default table. The basic queries, methods, and operations will work on that default table. In this chapter, let”s see how we can see the tables in a database and how we can set a table of our choice as the default table −

Showing the Tables in a Database

To get the list of all the tables in a database, use the following code −

from tinydb import TinyDB, Query
db = TinyDB("student.json")
db.tables()

It will produce the following output: We have two tables inside “student.json”, hence it will show the names of these two tables −

{''Student_Detail'', ''_default''}

The output shows that we have two tables in our database, one is “Student_Detail” and the other “_default”.

Displaying the Values of the Default Table

If you use the all() query, it will show the contents of the default table −

from tinydb import TinyDB
db = TinyDB("student.json")
db.all()

To show the contents of the “Student_Detail” table, use the following query −

from tinydb import TinyDB
db = TinyDB("student.json")
print(db.table("Student_Detail").all())

It will show the contents of the “Student_Detail” table −

[{
   ''roll_number'': 1,
   ''st_name'': ''elen'',
   ''mark'': 250,
   ''subject'': ''TinyDB'',
   ''address'': ''delhi''
}]

Setting a Default Table

You can set a table of your choice as the default table. For that, you need to use the following code −

from tinydb import TinyDB
db = TinyDB("student.json")
db.default_table_name = "Student_Detail"

It will set the “Student_Detail” table as the default table for our database.

TinyDB – Caching Query

Catching query is an advanced feature of TinyDB with the help of which it caches the query result for performance optimization. In this way, when we run the same query again, TinyDB doesn”t need to read the data from the storage. We can pass the cache_size to the table function to optimize the query cache size.

Syntax

The syntax of TinyDB query caching is shown below −

table = db.table(''table_name'', cache_size=value)

Example

TinyDB creates cache size memory in given table.

from tinydb import TinyDB
db = TinyDB(''student.json'')
objects = db.table(''Student_Detail'', cache_size = 50)
objects.all()

It will produce the following output. Observe that cache size does not affect the table values.

[{
   ''roll_number'': 1,
   ''st_name'': ''elen'',
   ''mark'': 250,
   ''subject'': ''TinyDB'',
   ''address'': ''delhi''
}]

We can set unlimited cache size by putting “cache_size = None”.

objects = db.table(''Student_Detail'', cache_size = None)

We can also disable the cache size by putting “cache_size = 0”.

objects = db.table(''Student_Detail'', cache_size = 0)

To clear the cache size, use the following query −

db.clear_cache()

TinyDB – Storage Types

TinyDB has two types of storage: JSON and in-memory. TinyDB, by default, stores the data in JSON files. While creating a database, you need to specify the path where to store the JSON file on your computer.

Storing Data in a JSON File

First, let”s see how we can use a JSON file to store the data −

from tinydb import TinyDB, where
db = TinyDB(''path/to/file_name.json'')

Example 1

In this example, we are showing how you can insert multiple documents into a JSON file −

from tinydb import TinyDB
db = TinyDB(''storage.json'')
db.insert_multiple([
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakhan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   }
])

Here, we inserted 5 documents inside “storage.json”. To verify the records, use the following query −

db.all()

It will show the contents of “storage.json” file −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakhan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   }
]

Using in-memory to Store Data

Now, let”s see how we can use “in-memory” to store the data −

from tinydb import TinyDB
from tinydb.storages import MemoryStorage
object = TinyDB(storage = MemoryStorage)
TinyDB.DEFAULT_STORAGE = MemoryStorage

Example 2

The following example shows how you can insert multiple documents in default storage memory −

from tinydb import TinyDB
from tinydb.storages import MemoryStorage
object = TinyDB(storage = MemoryStorage)
TinyDB.DEFAULT_STORAGE = MemoryStorage
object.insert_multiple([
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   }
])

To verify whether the documents have been inserted or not, use the following query −

object.all()

The following output shows the inserted data −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   }
]

TinyDB – Middleware

TinyDB middleware helps us to customize database storage behavior by wrapping around the existing storage. This middleware improves the performance of the database.

Caching Middleware

This middleware, as its name implies, improves the speed of a database by reducing the disk I/O. The working of CachingMiddleware is as follows −

• First, it catches all the read operations.

• Then it writes the data to the disk after a configured number of write operations.

Syntax

The syntax to use CachingMiddleware is as follows −

from tinydb.storages import JSONStorage
from tinydb.middlewares import CachingMiddleware
db = TinyDB(''middleware.json'', storage = CachingMiddleware(JSONStorage))
db.close()

Example

The following example shows how you can perform a basic middleware procedure in a database.

from tinydb import TinyDB
from tinydb.storages import JSONStorage
from tinydb.middlewares import CachingMiddleware
object = TinyDB(''storage.json'', storage=CachingMiddleware(JSONStorage))
object.all()

Output

It will produce the following output −

[
   {
      "roll_number":1,
      "st_name":"elen",
      "mark":250,
      "subject":"TinyDB",
      "address":"delhi"
   },
   {
      "roll_number":2,
      "st_name":"Ram",
      "mark":[
         250,
         280
      ],
      "subject":[
         "TinyDB",
         "MySQL"
      ],
      "address":"delhi"
   },
   {
      "roll_number":3,
      "st_name":"kevin",
      "mark":[
         180,
         200
      ],
      "subject":[
         "oracle",
         "sql"
      ],
      "address":"keral"
   },
   {
      "roll_number":4,
      "st_name":"lakan",
      "mark":200,
      "subject":"MySQL",
      "address":"mumbai"
   },
   {
      "roll_number":5,
      "st_name":"karan",
      "mark":275,
      "subject":"oracle",
      "address":"benglore"
   }
]

Close the database to make sure that all the data is safely written.

db.close()

TinyDB – Extend TinyDB

It is possible to extend TinyDB and modify its behaviour. There are four ways to do so −

• Custom middleware

• Custom storages

• Hooks and overrides

• Subclassing TinyDB and table

In this chapter, let”s understand each of these methods in detail.

Custom Middleware

Sometimes the user does not want to write a new storage module. In such cases, the user can modify the behaviour of an existing storage module. Let”s see an example in which we will build a custom middleware filtering out the empty items −

First, let”s see the data that will go through the custom middleware −

{
   ''_default'': {
   1: {''key1'': ''value1''},
   2: {''key2'': ''value2''},
   ……………,
   N: {''keyN'': ''valueN''}
},

Now, let”s see how we can implement the custom middleware −

class RemoveEmptyItemsMiddleware(Middleware):
def __init__(self, storage_cls):
   super(self).__init__(storage_cls)
   def read(self):
      data = self.storage.read()
      for _default in data:
         st_name = data
      for doc_id in table:
         item = st_name
         if item == {}:
            del st_name
         return data
   def close(self):
      self.storage.close()

Custom Storage

As discussed earlier, TinyDB comes with two types of storages: in-memory and JSON file storage. Along with that, TinyDB also provides an option to add our own custom storage. In the following example, let”s see how we can add a YAML storage using PyYAML −

import yaml
class YAMLStorage(Storage):
def __init__(self, db.json):
   self. db.json = db.json

To read the file −

def read(self):
   with open(self.db.json) as handle:
   try:
      info = yaml.safe_load(handle.read())
      return info

   except yaml.YAMLError:
      return None

To write the file −

def write(self, info):
   with open(self.db.json, ''w+'') as handle:
      yaml.dump(info, handle)

To close the file −

def close(self):
   pass

Hooks and Overrides

Sometimes, both custom storage and custom middleware cannot work in the way you want. In such cases, user can use predefined hooks and overrides to modify the behaviour of TinyDB. As an example, we will be configuring the name of the default table as follows −

TinyDB.default_table_name = ''student_detail''

We can also assign cache capacity as follows −

TinyDB.table_class.default_query_cache_capacity = 50

Subclassing TinyDB and Table

This is the last way we can use to modify the behaviour of TinyDB. As an example, we will be creating a subclass that can be used with hooks and overrides to override the default classes.

Class ExtendTable(Table):
   TinyDB.table_class = student_detail

TinyDB – Extensions

Given below is a set of TinyDB extensions that can be used for various operations −

The following resources contain additional information on TinyDB. Please use them to get more in-depth knowledge on this.