将数据追加到现有的 pytables 表

Question

我是 PyTables 的新手，我实现了一些在 Pytables 中从表中插入和检索数据的基本技术。但是，我不确定如何在现有的 PyTables 表中插入数据，因为我在 tutorial 中读取/获取的所有内容都是创建一个新表（使用 h5file.createTable() 方法）。以下是教程中关于将数据插入从头开始创建的 PytTables 表的基本代码：

h5file = openFile("tutorial1.h5", mode = "w", title = "Test file")
group = h5file.createGroup("/", 'detector', 'Detector information')
table = h5file.createTable(group, 'readout', Particle, "Readout example")

for i in xrange(10):
    particle['name']  = 'Particle: %6d' % (i)
    particle['TDCcount'] = i % 256
    particle['ADCcount'] = (i * 256) % (1 << 16)
    particle['grid_i'] = i
    particle['grid_j'] = 10 - i
    particle['pressure'] = float(i*i)
    particle['energy'] = float(particle['pressure'] ** 4)
    particle['idnumber'] = i * (2 ** 34)
    # Insert a new particle record
    particle.append()

    table.flush()

附：本教程中有一个place 讨论将数据附加到现有表，但使用的是从头开始创建的表，基本上不知道选择预先存在的表来附加数据。请帮忙。谢谢。

Answer 1

您需要以附加模式"a" 打开您的文件。也不要再次创建组和表。这又追加了 10 行：

import tables


class Particle(tables.IsDescription):
    name      = tables.StringCol(16)   # 16-character String
    idnumber  = tables.Int64Col()      # Signed 64-bit integer
    ADCcount  = tables.UInt16Col()     # Unsigned short integer
    TDCcount  = tables.UInt8Col()      # unsigned byte
    grid_i    = tables.Int32Col()      # 32-bit integer
    grid_j    = tables.Int32Col()      # 32-bit integer
    pressure  = tables.Float32Col()    # float  (single-precision)
    energy    = tables.Float64Col()    # double (double-precision)

h5file = tables.openFile("tutorial1.h5", mode = "a")
table = h5file.root.detector.readout

particle = table.row

for i in range(10, 20):
    particle['name']  = 'Particle: %6d' % (i)
    particle['TDCcount'] = i % 256
    particle['ADCcount'] = (i * 256) % (1 << 16)
    particle['grid_i'] = i
    particle['grid_j'] = 10 - i
    particle['pressure'] = float(i*i)
    particle['energy'] = float(particle['pressure'] ** 4)
    particle['idnumber'] = i * (2 ** 34)
    # Insert a new particle record
    particle.append()

h5file.close()