GramDB 1.1.0

Unlimited Capacity Database For Programming Using Telegram as Database.

GramDB

Data Structure:

• GramDB Class:

• CACHE_TABLE: Dictionary containing table names as keys and a list of record IDs as values.

{"test_table": [123, 456]}

• CACHE_DATA: Dictionary containing all records with their record ID key (_m_id) as keys and the record data as values.

{"123": {"_m_id": "123", "_id": 696969696969, "name": "John", "age": 30}}

• db: Instance of EfficientDictQuery class which holds the actual in-memory data structure for efficient querying.

• EfficientDictQuery Class:

• data: Dictionary containing tables as keys and dictionaries of records as values. Each record dictionary has its primary key (_id) as a key and the record data as the value. (Similar to CACHE_DATA but potentially more organized)

{"696969696969": {"_id": "696969696969", "_m_id": "123", "name": "John", "age": 30}}

• indexes: Dictionary where each key represents a field name in the records, and the value is another dictionary. This inner dictionary maps each unique value of that field to a list of (table_name, record_id) tuples referencing records containing that value.
• schemas: Dictionary containing table names as keys and tuples of field names (schema) as values.

Functionalities:

• GramDB Class:

• initialize(): Initializes the connection with the Telegram database by fetching authentication details and building the internal data structures.

• create(table_name, schema): Creates a new table with the specified schema (list of field names).

• fetch(table_name, query): Fetches records from a table based on a query dictionary (key-value pairs matching record fields).

• fetch_all(): Fetches all records from all tables.

• insert(table_name, record): Inserts a new record into a table. The record must contain a _id field.

• delete(table_name, query): Deletes records from a table based on a query dictionary.

• update(table_name, query, update_query): Updates records in a table based on a query dictionary and updates the specified fields with the values provided in the update_query dictionary.

• delete_table(table_name): Deletes a table entirely.

• close(): Closes the asynchronous session.

• EfficientDictQuery Class:

• Provides methods for querying, inserting, updating, and deleting data efficiently using the internal data structures (data, indexes, and schemas). Maintains indexes to enable faster searches based on field values.

Data format:

• CACHE_TABLE

{
    "_id": 6939393728, # primary key
    "_m_id": "54", # data id
    "name": "akabane",
    ... so on in json format
}

• PRIMARY KEY

  • Primary key is a mandatory key which will exist in all records.
  • "_id" key represents the primary key
  • If no primary key provided while inserting record, random unique primary key will be generated and will get inserted with the record
  • It is unique for every record

• DATA KEY

  • Data id represents the location of data
  • "_m_id" key represents the data id
  • It's a reserved key which gets generated automatically
  • It is unique for every record

create

await db.create("table_name", ("name", "rollno", "section"))

• table_name: name of the table that you want to create
• schema: set of fields

fetch_all

result = await db.fetch_all()

• returns all records in list

fetch

result = await db.fetch("table_name", {"name": "akabane"})

• table_name: name of the table
• query: your search query
• returns specific records matching the query

insert

data = {
    "name": "akabane",
    "class": 3,
    "rollno": 24
}

await db.insert("table_name", data)

• table_name: name of the table
• record: your data in JSON/dict form

delete

await db.delete("table_name", {"name": "akabane"})

• table_name: name of the table
• query: query for deleting matching data

delete_table

await db.delete_table("table_name)

• table_name: name of the table

update

query = {
    "name": "akabane"
}

update_query = {
    "class": 7
}

await db.update("table_name", query, update_query)

• table_name: name of the table
• query: query for deleting matching data
• update_query: data for inserting new data