Analysis of Ethereum Blockchairs into Sqlite Databases: Effective Approach
The analysis of blockchairs, the analysis of blockchairs. In this article,
Why sqlite3?
Sqlite3 is an excellent choice for this task as a result:
- Relational database capacity : easy to query, create, update and delete in the database.
2.
- Support for multiple databases : more databases can handle at the same time.
- Easy and fast
: sqlite3 is optimized for performance.
Ethereum Blockchain Data Structure
Before we get into the implementation details, understand how Ethereum blockchairs are structured:
1.
- Each Block Contains:
* Time Stamp
* The Previous Block Hashja (yes partenthash)
* Number of Transactions in the Block (NumtransectionCount)
* List of Transactions Within The Block (Transactions')
Blockchain Analyst Execution
We use Python as our program language, together with sqlite3 for database operations. The Eth-Bocks directory is also used to retrieve the Ethereum blockchain data.
Python
Import Sqlite3
From Datetime Import Datetime
Class Blockparser:
Def __init __ (self):
Self.conn = sqlite3.connect (': memory:')
Self.cursor = self.conn.cursor ()
Def parse_blockchain (self, blockchain_url):
Roll First Block from Blockchain URL
Block = eth_blocks.get (blockchain_url)
If the Block is Not:
restore
Create a table for the database
Self.create_table ()
Insert data into the database
Self.inSert_Data (block.timestamp, block.hash, block.parenthash, block.numtransectioncount, block.transections)
Return
DEF CREATE_TABLE (SELF):
"" "Create a table with the columns you need." "
sql = "" "
Creating a table if there is no blockchain_data (
ID Integer Primary Key Auto Installation,
The time stamp text is not zero,
Parent_hash text is not zero,
Num_transections Whole Number is Not Zero,
TEXT TRANSACTIONS
);
"" "
Self.curssor.execute (sql)
Self.conn.commit ()
Def Insert_Data (Self, Timestamp, Hash, Bracket, Numtransctions, Transactions):
"" "Insert data into the blockchain table." "
sql = "" "
Insert Blockchain_data (Time Stamp, Parent_hash, Num_transctions, Transactions)
Values (?,? ,,? ,,?);
"" "
Self.curssor.execute (sql, (timestamp, hash, numtransctions, transactions))
Self.conn.commit ()
An example of use
Analyst = blockparser ()
Url = '
If the analysis.parse_blockchain (URL):
Print ("Blockchain Successfully Analyzed!")
Other:
Print ("Error Analysis of the Blockchain.")
To Optimize Efficiency
The special implementation is effective for most uses, there are some optimizations that can be done to further improved performance:
.
- Using a more effective database scheme
:
3.
