source: trunk/src/allmydata/test/mutable/test_interoperability.py

"""
Ported to Python 3.
"""

import os, base64
from ..common import AsyncTestCase
from testtools.matchers import HasLength
from allmydata import uri
from allmydata.storage.common import storage_index_to_dir
from allmydata.util import fileutil
from .. import common_util as testutil
from ..no_network import GridTestMixin

class Interoperability(GridTestMixin, AsyncTestCase, testutil.ShouldFailMixin):
    sdmf_old_shares = {}
    sdmf_old_shares[0] = b"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"
    sdmf_old_shares[1] = b"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"
    sdmf_old_shares[2] = b"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"
    sdmf_old_shares[3] = b"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"
    sdmf_old_shares[4] = b"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"
    sdmf_old_shares[5] = b"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"
    sdmf_old_shares[6] = b"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"
    sdmf_old_shares[7] = b"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"
    sdmf_old_shares[8] = b"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"
    sdmf_old_shares[9] = b"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"
    sdmf_old_cap = b"URI:SSK:gmjgofw6gan57gwpsow6gtrz3e:5adm6fayxmu3e4lkmfvt6lkkfix34ai2wop2ioqr4bgvvhiol3kq"
    sdmf_old_contents = b"This is a test file.\n"
    def copy_sdmf_shares(self):
        # We'll basically be short-circuiting the upload process.
        servernums = list(self.g.servers_by_number.keys())
        assert len(servernums) == 10

        assignments = list(zip(self.sdmf_old_shares.keys(), servernums))
        # Get the storage index.
        cap = uri.from_string(self.sdmf_old_cap)
        si = cap.get_storage_index()

        # Now execute each assignment by writing the storage.
        for (share, servernum) in assignments:
            sharedata = base64.b64decode(self.sdmf_old_shares[share])
            storedir = self.get_serverdir(servernum)
            storage_path = os.path.join(storedir, "shares",
                                        storage_index_to_dir(si))
            fileutil.make_dirs(storage_path)
            fileutil.write(os.path.join(storage_path, "%d" % share),
                           sharedata)
        # ...and verify that the shares are there.
        shares = self.find_uri_shares(self.sdmf_old_cap)
        self.assertThat(shares, HasLength(10))

    def test_new_downloader_can_read_old_shares(self):
        self.basedir = "mutable/Interoperability/new_downloader_can_read_old_shares"
        self.set_up_grid()
        self.copy_sdmf_shares()
        nm = self.g.clients[0].nodemaker
        n = nm.create_from_cap(self.sdmf_old_cap)
        d = n.download_best_version()
        d.addCallback(self.assertEqual, self.sdmf_old_contents)
        return d