我正在遍历一棵树并形成一个(key:value) lmdb数据库。我正在努力使树返回迭代lmdb。
。

用于创建lmdb数据库的代码:
import lmdb
import pickle
class node:
def __init__(self, info, level = 0):
self._info = info
self.level = level
# A:1
# / \
# B:2 C:3
# / \
# D:4 G:7
# / \
# E:5 F:6
# "A" : serialized node-A
# "A.B" : serialized node-B
# "A.C" : serialized node-c
# "A.B.D" : serialized node - D
# "A.C.G" : serialized node - G
# "A.B.D.E" : serialized node - E
# "A.B.D.F" : serialized node - F
#Form the lmdb from Tree
env = lmdb.open("test.lmdb")
txn = env.begin(write=True)
new_node = node({"A":1})
txn.put(pickle.dumps("A"), pickle.dumps(new_node))
new_node = node({"B":2}, 1)
txn.put(pickle.dumps("A.B"), pickle.dumps(new_node))
new_node = node({"C":3}, 1)
txn.put(pickle.dumps("A.C"), pickle.dumps(new_node))
new_node = node({"D":4}, 2)
txn.put(pickle.dumps("A.B.D"), pickle.dumps(new_node))
new_node = node({"G":7}, 2)
txn.put(pickle.dumps("A.C.G"), pickle.dumps(new_node))
new_node = node({"E":5}, 3)
txn.put(pickle.dumps("A.B.D.E"), pickle.dumps(new_node))
new_node = node({"F":6}, 3)
txn.put(pickle.dumps("A.B.D.F"), pickle.dumps(new_node))迭代数据库代码:
env = lmdb.open("test.lmdb")
txn = env.begin()
cursor = txn.cursor()
for idx, value in enumerate(cursor):
a,b = pickle.loads(value[0]), pickle.loads(value[1])
print(a,b)发布于 2021-08-25 19:07:31
我终于想出了如何形成这棵树。
#form Tree from lmdb
cursor = txn.cursor()
root = Node()
for idx, value in enumerate(cursor):
a,b = pickle.loads(value[0]), pickle.loads(value[1]) # a: string b: obj
print(a,b)
tree_node = root #always start with root
_xl = a.split(".") #list of paths
if len(_xl) == 1:
setattr(root,a,b)
else:
_il = _xl[:len(_xl) - 1] # all path except child
_child_name = _xl[-1]
#discover parent
parent = root
for item in _il:
parent = getattr(parent,item)
setattr(parent, _child_name, b)https://stackoverflow.com/questions/68914545
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