pip install git+https://github.com/tidesdb/tidesdb-python.git

import tidesdb
print(tidesdb.__version__)

 from tidesdb import TidesDB, TidesDBCompressionAlgo, TidesDBMemtableDS
# Open a TidesDB database
db = TidesDB.open('my_db')
# Create a column family
db.create_column_family(
 "my_column_family", 
 1024*1024*64, # Flush threshold (64MB)
 12, # Max level skip list, if using hash table is irrelevant
 0.24, # Probability skip list, if using hash table is irrelevant
 True, # Enable compression, is slower
 TidesDBCompressionAlgo.COMPRESS_SNAPPY, # Compression algorithm can be NO_COMPRESSION, COMPRESS_SNAPPY, COMPRESS_LZ4, COMPRESS_ZSTD
 True, # Enable bloom filter
 TidesDBMemtableDS.SKIP_LIST # Use skip list for memtable
)
# Put key-value pair into the database
db.put("my_column_family", b"key1", b"value1", ttl=3600) # ttl=-1 for no ttl
# Get the value for the key
value = db.get("my_column_family", b"key1")
print(f"Key: key1, Value: {value}")
# Delete the key-value pair
db.delete("my_column_family", b"key1")
# Try to get the deleted key (should raise an exception or return None)
try:
 value = db.get("my_column_family", b"key1")
except Exception as e:
 print(f"Error: {e}")
# Close the database
db.close()

from tidesdb import TidesDB, Transaction, TidesDBCompressionAlgo, TidesDBMemtableDS
# Open the database
db = TidesDB.open('my_db')
# Create a column family
db.create_column_family(
 "my_column_family", 
 1024*1024*64, # Flush threshold (64MB)
 12, # Max level skip list, if using hash table is irrelevant
 0.24, # Probability skip list, if using hash table is irrelevant
 True, # Enable compression
 TidesDBCompressionAlgo.COMPRESS_SNAPPY, # Compression algorithm can be NO_COMPRESSION, COMPRESS_SNAPPY, COMPRESS_LZ4, COMPRESS_ZSTD
 True, # Enable bloom filter
 TidesDBMemtableDS.SKIP_LIST # Use skip list for memtable
)
# Begin a transaction on the column family
txn = Transaction.begin(db, "my_column_family")
# Put multiple key-value pairs in the transaction
txn.put(b"key2", b"value2", ttl=-1)
txn.put(b"key3", b"value3", ttl=-1)
# Commit the transaction
txn.commit()
# Verify the values
value2 = db.get("my_column_family", b"key2")
value3 = db.get("my_column_family", b"key3")
print(f"Key: key2, Value: {value2}")
print(f"Key: key3, Value: {value3}")
# Close the database
db.close()

from tidesdb import TidesDB, Cursor, TidesDBCompressionAlgo, TidesDBMemtableDS
# Open the database
db = TidesDB.open('my_db')
# Create a column family
db.create_column_family(
 "my_column_family", 
 1024*1024*64, # Flush threshold (64MB)
 12, # Max level skip list, if using hash table is irrelevant
 0.24, # Probability skip list, if using hash table is irrelevan
 True, # Enable compression
 TidesDBCompressionAlgo.COMPRESS_SNAPPY, # Compression algorithm can be NO_COMPRESSION, COMPRESS_SNAPPY, COMPRESS_LZ4, COMPRESS_ZSTD
 True, # Enable bloom filter
 TidesDBMemtableDS.SKIP_LIST # Use skip list for memtable or HASH_TABLE
)
# Insert some key-value pairs
db.put("my_column_family", b"key1", b"value1", ttl=3600)
db.put("my_column_family", b"key2", b"value2", ttl=3600)
db.put("my_column_family", b"key3", b"value3", ttl=3600)
# Initialize the cursor to iterate over the column family
cursor = Cursor.init(db, "my_column_family")
# Loop to fetch and print all key-value pairs
try:
 while True:
 key, value = cursor.get()
 print(f"Key: {key}, Value: {value}")
 cursor.next() # Move to the next element
except Exception as e:
 # Exception is raised when there are no more elements to iterate
 print("End of column family reached.")
try:
 while True:
 key, value = cursor.get()
 print(f"Key: {key}, Value: {value}")
 cursor.prev() # Move to the previous element
except Exception as e:
 # Exception is raised when there are no more elements to iterate
 print("Start of column family reached.")
# Free the cursor resources
cursor.free()
# Close the database
db.close()

from tidesdb import TidesDB
# Open the database
db = TidesDB.open('my_db')
# List all column families in the database
column_families = db.list_column_families()
print(f"Column families: \n{column_families}")
# Close the database
db.close()

from tidesdb import TidesDB
# Open the database
db = TidesDB.open('my_db')
# Drop the specified column family
db.drop_column_family("my_column_family")
# Close the database
db.close()

db.compact_sstables("my_column_family", max_threads=4) # max threads is refering to amount of threads used for compaction process
# 4 threads means 2 sstables being paired per thread which is faster than a lone thread say.