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7
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def test_circfuncs_small(self): x = np.array([20,21,22,18,19,20.5,19.2]) M1 = x.mean() M2 = stats.circmean(x, high=360) assert_allclose(M2, M1, rtol=1e-5) V1 = x.var() V2 = stats.circvar(x, high=360) assert_allclose(V2, V1, rtol=1e-4) S1 = x.std() S2 = stats.circstd(x, high=360) assert_allclose(S2, S1, rtol=1e-4)
10,302
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def test_circmean_axis(self): x = np.array([[355,5,2,359,10,350], [351,7,4,352,9,349], [357,9,8,358,4,356]]) M1 = stats.circmean(x, high=360) M2 = stats.circmean(x.ravel(), high=360) assert_allclose(M1, M2, rtol=1e-14) M1 = stats.circmean(x, high=360, axis=1) M2 = [stats.circmean(x[i], high=360) for i in range(x.shape[0])] assert_allclose(M1, M2, rtol=1e-14) M1 = stats.circmean(x, high=360, axis=0) M2 = [stats.circmean(x[:,i], high=360) for i in range(x.shape[1])] assert_allclose(M1, M2, rtol=1e-14)
10,303
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def test_circvar_axis(self): x = np.array([[355,5,2,359,10,350], [351,7,4,352,9,349], [357,9,8,358,4,356]]) V1 = stats.circvar(x, high=360) V2 = stats.circvar(x.ravel(), high=360) assert_allclose(V1, V2, rtol=1e-11) V1 = stats.circvar(x, high=360, axis=1) V2 = [stats.circvar(x[i], high=360) for i in range(x.shape[0])] assert_allclose(V1, V2, rtol=1e-11) V1 = stats.circvar(x, high=360, axis=0) V2 = [stats.circvar(x[:,i], high=360) for i in range(x.shape[1])] assert_allclose(V1, V2, rtol=1e-11)
10,304
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def test_circstd_axis(self): x = np.array([[355,5,2,359,10,350], [351,7,4,352,9,349], [357,9,8,358,4,356]]) S1 = stats.circstd(x, high=360) S2 = stats.circstd(x.ravel(), high=360) assert_allclose(S1, S2, rtol=1e-11) S1 = stats.circstd(x, high=360, axis=1) S2 = [stats.circstd(x[i], high=360) for i in range(x.shape[0])] assert_allclose(S1, S2, rtol=1e-11) S1 = stats.circstd(x, high=360, axis=0) S2 = [stats.circstd(x[:,i], high=360) for i in range(x.shape[1])] assert_allclose(S1, S2, rtol=1e-11)
10,305
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def test_accuracy_wilcoxon(): freq = [1, 4, 16, 15, 8, 4, 5, 1, 2] nums = range(-4, 5) x = np.concatenate([[u] * v for u, v in zip(nums, freq)]) y = np.zeros(x.size) T, p = stats.wilcoxon(x, y, "pratt") assert_allclose(T, 423) assert_allclose(p, 0.00197547303533107) T, p = stats.wilcoxon(x, y, "zsplit") assert_allclose(T, 441) assert_allclose(p, 0.0032145343172473055) T, p = stats.wilcoxon(x, y, "wilcox") assert_allclose(T, 327) assert_allclose(p, 0.00641346115861) # Test the 'correction' option, using values computed in R with: # > wilcox.test(x, y, paired=TRUE, exact=FALSE, correct={FALSE,TRUE}) x = np.array([120, 114, 181, 188, 180, 146, 121, 191, 132, 113, 127, 112]) y = np.array([133, 143, 119, 189, 112, 199, 198, 113, 115, 121, 142, 187]) T, p = stats.wilcoxon(x, y, correction=False) assert_equal(T, 34) assert_allclose(p, 0.6948866, rtol=1e-6) T, p = stats.wilcoxon(x, y, correction=True) assert_equal(T, 34) assert_allclose(p, 0.7240817, rtol=1e-6)
10,306
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7
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def test_wilcoxon_tie(): # Regression test for gh-2391. # Corresponding R code is: # > result = wilcox.test(rep(0.1, 10), exact=FALSE, correct=FALSE) # > result$p.value # [1] 0.001565402 # > result = wilcox.test(rep(0.1, 10), exact=FALSE, correct=TRUE) # > result$p.value # [1] 0.001904195 stat, p = stats.wilcoxon([0.1] * 10) expected_p = 0.001565402 assert_equal(stat, 0) assert_allclose(p, expected_p, rtol=1e-6) stat, p = stats.wilcoxon([0.1] * 10, correction=True) expected_p = 0.001904195 assert_equal(stat, 0) assert_allclose(p, expected_p, rtol=1e-6)
10,307
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class TestMedianTest(TestCase): def test_bad_n_samples(self): # median_test requires at least two samples. assert_raises(ValueError, stats.median_test, [1, 2, 3]) def test_empty_sample(self): # Each sample must contain at least one value. assert_raises(ValueError, stats.median_test, [], [1, 2, 3]) def test_empty_when_ties_ignored(self): # The grand median is 1, and all values in the first argument are # equal to the grand median. With ties="ignore", those values are # ignored, which results in the first sample being (in effect) empty. # This should raise a ValueError. assert_raises(ValueError, stats.median_test, [1, 1, 1, 1], [2, 0, 1], [2, 0], ties="ignore") def test_empty_contingency_row(self): # The grand median is 1, and with the default ties="below", all the # values in the samples are counted as being below the grand median. # This would result a row of zeros in the contingency table, which is # an error. assert_raises(ValueError, stats.median_test, [1, 1, 1], [1, 1, 1]) # With ties="above", all the values are counted as above the # grand median. assert_raises(ValueError, stats.median_test, [1, 1, 1], [1, 1, 1], ties="above") def test_bad_ties(self): assert_raises(ValueError, stats.median_test, [1, 2, 3], [4, 5], ties="foo") def test_bad_keyword(self): assert_raises(TypeError, stats.median_test, [1, 2, 3], [4, 5], foo="foo") def test_simple(self): x = [1, 2, 3] y = [1, 2, 3] stat, p, med, tbl = stats.median_test(x, y) # The median is floating point, but this equality test should be safe. assert_equal(med, 2.0) assert_array_equal(tbl, [[1, 1], [2, 2]]) # The expected values of the contingency table equal the contingency table, # so the statistic should be 0 and the p-value should be 1. assert_equal(stat, 0) assert_equal(p, 1) def test_ties_options(self): # Test the contingency table calculation. x = [1, 2, 3, 4] y = [5, 6] z = [7, 8, 9] # grand median is 5. # Default 'ties' option is "below". stat, p, m, tbl = stats.median_test(x, y, z) assert_equal(m, 5) assert_equal(tbl, [[0, 1, 3], [4, 1, 0]]) stat, p, m, tbl = stats.median_test(x, y, z, ties="ignore") assert_equal(m, 5) assert_equal(tbl, [[0, 1, 3], [4, 0, 0]]) stat, p, m, tbl = stats.median_test(x, y, z, ties="above") assert_equal(m, 5) assert_equal(tbl, [[0, 2, 3], [4, 0, 0]]) def test_basic(self): # median_test calls chi2_contingency to compute the test statistic # and p-value. Make sure it hasn't screwed up the call... x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8] stat, p, m, tbl = stats.median_test(x, y) assert_equal(m, 4) assert_equal(tbl, [[1, 2], [4, 2]]) exp_stat, exp_p, dof, e = stats.chi2_contingency(tbl) assert_allclose(stat, exp_stat) assert_allclose(p, exp_p) stat, p, m, tbl = stats.median_test(x, y, lambda_=0) assert_equal(m, 4) assert_equal(tbl, [[1, 2], [4, 2]]) exp_stat, exp_p, dof, e = stats.chi2_contingency(tbl, lambda_=0) assert_allclose(stat, exp_stat) assert_allclose(p, exp_p) stat, p, m, tbl = stats.median_test(x, y, correction=False) assert_equal(m, 4) assert_equal(tbl, [[1, 2], [4, 2]]) exp_stat, exp_p, dof, e = stats.chi2_contingency(tbl, correction=False) assert_allclose(stat, exp_stat) assert_allclose(p, exp_p)
10,308
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def test_ties_options(self): # Test the contingency table calculation. x = [1, 2, 3, 4] y = [5, 6] z = [7, 8, 9] # grand median is 5. # Default 'ties' option is "below". stat, p, m, tbl = stats.median_test(x, y, z) assert_equal(m, 5) assert_equal(tbl, [[0, 1, 3], [4, 1, 0]]) stat, p, m, tbl = stats.median_test(x, y, z, ties="ignore") assert_equal(m, 5) assert_equal(tbl, [[0, 1, 3], [4, 0, 0]]) stat, p, m, tbl = stats.median_test(x, y, z, ties="above") assert_equal(m, 5) assert_equal(tbl, [[0, 2, 3], [4, 0, 0]])
10,309
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7
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def test_simple(self): x = [1, 2, 3] y = [1, 2, 3] stat, p, med, tbl = stats.median_test(x, y) # The median is floating point, but this equality test should be safe. assert_equal(med, 2.0) assert_array_equal(tbl, [[1, 1], [2, 2]]) # The expected values of the contingency table equal the contingency table, # so the statistic should be 0 and the p-value should be 1. assert_equal(stat, 0) assert_equal(p, 1)
10,310
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10
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def perform_delete(request, comment): flag, created = comments.models.CommentFlag.objects.get_or_create( comment = comment, user = request.user, flag = comments.models.CommentFlag.MODERATOR_DELETION ) comment.is_removed = True comment.save() signals.comment_was_flagged.send( sender = comment.__class__, comment = comment, flag = flag, created = created, request = request, )
10,311
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def test_basic(self): # median_test calls chi2_contingency to compute the test statistic # and p-value. Make sure it hasn't screwed up the call... x = [1, 2, 3, 4, 5] y = [2, 4, 6, 8] stat, p, m, tbl = stats.median_test(x, y) assert_equal(m, 4) assert_equal(tbl, [[1, 2], [4, 2]]) exp_stat, exp_p, dof, e = stats.chi2_contingency(tbl) assert_allclose(stat, exp_stat) assert_allclose(p, exp_p) stat, p, m, tbl = stats.median_test(x, y, lambda_=0) assert_equal(m, 4) assert_equal(tbl, [[1, 2], [4, 2]]) exp_stat, exp_p, dof, e = stats.chi2_contingency(tbl, lambda_=0) assert_allclose(stat, exp_stat) assert_allclose(p, exp_p) stat, p, m, tbl = stats.median_test(x, y, correction=False) assert_equal(m, 4) assert_equal(tbl, [[1, 2], [4, 2]]) exp_stat, exp_p, dof, e = stats.chi2_contingency(tbl, correction=False) assert_allclose(stat, exp_stat) assert_allclose(p, exp_p)
10,312
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10
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null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "download_timeout"}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_timeout", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "setdefault", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "meta", "value": {"_type": "Name", "_fields": {"id": "request", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}], "test": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_timeout", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": []}}], "name": "process_request", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "DownloadTimeoutMiddleware", "bases": [{"_type": "Name", "_fields": {"id": "object", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}
class DownloadTimeoutMiddleware(object): def __init__(self, timeout=180): self._timeout = timeout @classmethod def from_crawler(cls, crawler): o = cls(crawler.settings.getfloat('DOWNLOAD_TIMEOUT')) crawler.signals.connect(o.spider_opened, signal=signals.spider_opened) return o def spider_opened(self, spider): self._timeout = getattr(spider, 'download_timeout', self._timeout) def process_request(self, request, spider): if self._timeout: request.meta.setdefault('download_timeout', self._timeout)
10,313
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10
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def perform_approve(request, comment): flag, created = comments.models.CommentFlag.objects.get_or_create( comment = comment, user = request.user, flag = comments.models.CommentFlag.MODERATOR_APPROVAL, ) comment.is_removed = False comment.is_public = True comment.save() signals.comment_was_flagged.send( sender = comment.__class__, comment = comment, flag = flag, created = created, request = request, )
10,314
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8
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def __init__(self, spi, cs): self.spi = spi self.cs = cs self.cmdbuf = bytearray(6) self.dummybuf = bytearray(512) for i in range(512): self.dummybuf[i] = 0xff self.dummybuf_memoryview = memoryview(self.dummybuf) # initialise the card self.init_card()
10,315
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class SDCard: CMD_TIMEOUT = const(100) R1_IDLE_STATE = const(1 << 0) #R1_ERASE_RESET = const(1 << 1) R1_ILLEGAL_COMMAND = const(1 << 2) #R1_COM_CRC_ERROR = const(1 << 3) #R1_ERASE_SEQUENCE_ERROR = const(1 << 4) #R1_ADDRESS_ERROR = const(1 << 5) #R1_PARAMETER_ERROR = const(1 << 6) def __init__(self, spi, cs): self.spi = spi self.cs = cs self.cmdbuf = bytearray(6) self.dummybuf = bytearray(512) for i in range(512): self.dummybuf[i] = 0xff self.dummybuf_memoryview = memoryview(self.dummybuf) # initialise the card self.init_card() def init_card(self): # init CS pin self.cs.high() self.cs.init(self.cs.OUT_PP) # init SPI bus; use low data rate for initialisation self.spi.init(self.spi.MASTER, baudrate=100000, phase=0, polarity=0) # clock card at least 100 cycles with cs high for i in range(16): self.spi.send(0xff) # CMD0: init card; should return R1_IDLE_STATE (allow 2 attempts) if self.cmd(0, 0, 0x95) != R1_IDLE_STATE: if self.cmd(0, 0, 0x95) != R1_IDLE_STATE: raise OSError("no SD card") # CMD8: determine card version r = self.cmd(8, 0x01aa, 0x87, 4) if r == R1_IDLE_STATE: self.init_card_v2() elif r == (R1_IDLE_STATE | R1_ILLEGAL_COMMAND): self.init_card_v1() else: raise OSError("couldn't determine SD card version") # get the number of sectors # CMD9: response R2 (R1 byte + 16-byte block read) if self.cmd(9, 0, 0, 0, False) != 0: raise OSError("no response from SD card") csd = bytearray(16) self.readinto(csd) if csd[0] & 0xc0 != 0x40: raise OSError("SD card CSD format not supported") self.sectors = ((csd[8] << 8 | csd[9]) + 1) * 2014 #print('sectors', self.sectors) # CMD16: set block length to 512 bytes if self.cmd(16, 512, 0) != 0: raise OSError("can't set 512 block size") # set to high data rate now that it's initialised self.spi.init(self.spi.MASTER, baudrate=1320000, phase=0, polarity=0) def init_card_v1(self): for i in range(CMD_TIMEOUT): self.cmd(55, 0, 0) if self.cmd(41, 0, 0) == 0: self.cdv = 512 #print("[SDCard] v1 card") return raise OSError("timeout waiting for v1 card") def init_card_v2(self): for i in range(CMD_TIMEOUT): pyb.delay(50) self.cmd(58, 0, 0, 4) self.cmd(55, 0, 0) if self.cmd(41, 0x40000000, 0) == 0: self.cmd(58, 0, 0, 4) self.cdv = 1 #print("[SDCard] v2 card") return raise OSError("timeout waiting for v2 card") def cmd(self, cmd, arg, crc, final=0, release=True): self.cs.low() # create and send the command buf = self.cmdbuf buf[0] = 0x40 | cmd buf[1] = arg >> 24 buf[2] = arg >> 16 buf[3] = arg >> 8 buf[4] = arg buf[5] = crc self.spi.send(buf) # wait for the repsonse (response[7] == 0) for i in range(CMD_TIMEOUT): response = self.spi.send_recv(0xff)[0] if not (response & 0x80): # this could be a big-endian integer that we are getting here for j in range(final): self.spi.send(0xff) if release: self.cs.high() self.spi.send(0xff) return response # timeout self.cs.high() self.spi.send(0xff) return -1 def readinto(self, buf): self.cs.low() # read until start byte (0xff) while self.spi.send_recv(0xff)[0] != 0xfe: pass # read data mv = self.dummybuf_memoryview[:len(buf)] self.spi.send_recv(mv, recv=buf) # read checksum self.spi.send(0xff) self.spi.send(0xff) self.cs.high() self.spi.send(0xff) def write(self, buf): self.cs.low() # send: start of block, data, checksum self.spi.send(0xfe) self.spi.send(buf) self.spi.send(0xff) self.spi.send(0xff) # check the response if (self.spi.send_recv(0xff)[0] & 0x1f) != 0x05: self.cs.high() self.spi.send(0xff) return # wait for write to finish while self.spi.send_recv(0xff)[0] == 0: pass self.cs.high() self.spi.send(0xff) def count(self): return self.sectors def readblocks(self, block_num, buf): # TODO support multiple block reads assert len(buf) == 512 # CMD17: set read address for single block if self.cmd(17, block_num * self.cdv, 0) != 0: return 1 # receive the data self.readinto(buf) return 0 def writeblocks(self, block_num, buf): # TODO support multiple block writes assert len(buf) == 512 # CMD24: set write address for single block if self.cmd(24, block_num * self.cdv, 0) != 0: return 1 # send the data self.write(buf) return 0
10,316
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10
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def init_card(self): # init CS pin self.cs.high() self.cs.init(self.cs.OUT_PP) # init SPI bus; use low data rate for initialisation self.spi.init(self.spi.MASTER, baudrate=100000, phase=0, polarity=0) # clock card at least 100 cycles with cs high for i in range(16): self.spi.send(0xff) # CMD0: init card; should return R1_IDLE_STATE (allow 2 attempts) if self.cmd(0, 0, 0x95) != R1_IDLE_STATE: if self.cmd(0, 0, 0x95) != R1_IDLE_STATE: raise OSError("no SD card") # CMD8: determine card version r = self.cmd(8, 0x01aa, 0x87, 4) if r == R1_IDLE_STATE: self.init_card_v2() elif r == (R1_IDLE_STATE | R1_ILLEGAL_COMMAND): self.init_card_v1() else: raise OSError("couldn't determine SD card version") # get the number of sectors # CMD9: response R2 (R1 byte + 16-byte block read) if self.cmd(9, 0, 0, 0, False) != 0: raise OSError("no response from SD card") csd = bytearray(16) self.readinto(csd) if csd[0] & 0xc0 != 0x40: raise OSError("SD card CSD format not supported") self.sectors = ((csd[8] << 8 | csd[9]) + 1) * 2014 #print('sectors', self.sectors) # CMD16: set block length to 512 bytes if self.cmd(16, 512, 0) != 0: raise OSError("can't set 512 block size") # set to high data rate now that it's initialised self.spi.init(self.spi.MASTER, baudrate=1320000, phase=0, polarity=0)
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9
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def init_card_v1(self): for i in range(CMD_TIMEOUT): self.cmd(55, 0, 0) if self.cmd(41, 0, 0) == 0: self.cdv = 512 #print("[SDCard] v1 card") return raise OSError("timeout waiting for v1 card")
10,318
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9
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def init_card_v2(self): for i in range(CMD_TIMEOUT): pyb.delay(50) self.cmd(58, 0, 0, 4) self.cmd(55, 0, 0) if self.cmd(41, 0x40000000, 0) == 0: self.cmd(58, 0, 0, 4) self.cdv = 1 #print("[SDCard] v2 card") return raise OSError("timeout waiting for v2 card")
10,319
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def cmd(self, cmd, arg, crc, final=0, release=True): self.cs.low() # create and send the command buf = self.cmdbuf buf[0] = 0x40 | cmd buf[1] = arg >> 24 buf[2] = arg >> 16 buf[3] = arg >> 8 buf[4] = arg buf[5] = crc self.spi.send(buf) # wait for the repsonse (response[7] == 0) for i in range(CMD_TIMEOUT): response = self.spi.send_recv(0xff)[0] if not (response & 0x80): # this could be a big-endian integer that we are getting here for j in range(final): self.spi.send(0xff) if release: self.cs.high() self.spi.send(0xff) return response # timeout self.cs.high() self.spi.send(0xff) return -1
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def write(self, buf): self.cs.low() # send: start of block, data, checksum self.spi.send(0xfe) self.spi.send(buf) self.spi.send(0xff) self.spi.send(0xff) # check the response if (self.spi.send_recv(0xff)[0] & 0x1f) != 0x05: self.cs.high() self.spi.send(0xff) return # wait for write to finish while self.spi.send_recv(0xff)[0] == 0: pass self.cs.high() self.spi.send(0xff)
10,321
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10
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def readinto(self, buf): self.cs.low() # read until start byte (0xff) while self.spi.send_recv(0xff)[0] != 0xfe: pass # read data mv = self.dummybuf_memoryview[:len(buf)] self.spi.send_recv(mv, recv=buf) # read checksum self.spi.send(0xff) self.spi.send(0xff) self.cs.high() self.spi.send(0xff)
10,322
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9
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "block_num", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "buf", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assert", "_fields": {"msg": null, "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "buf", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "len", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": 512}}]}}}}, {"_type": "If", "_fields": {"body": [{"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "NotEq", "_fields": {}}], "left": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 17}}, {"_type": "BinOp", "_fields": {"op": {"_type": "Mult", "_fields": {}}, "left": {"_type": "Name", "_fields": {"id": "block_num", "ctx": {"_type": "Load", "_fields": {}}}}, "right": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "cdv", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": 0}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "cmd", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": 0}}]}}, "orelse": []}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "buf", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "readinto", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}}}], "name": "readblocks", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def readblocks(self, block_num, buf): # TODO support multiple block reads assert len(buf) == 512 # CMD17: set read address for single block if self.cmd(17, block_num * self.cdv, 0) != 0: return 1 # receive the data self.readinto(buf) return 0
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9
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "block_num", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "buf", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assert", "_fields": {"msg": null, "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "buf", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "len", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": 512}}]}}}}, {"_type": "If", "_fields": {"body": [{"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "NotEq", "_fields": {}}], "left": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 24}}, {"_type": "BinOp", "_fields": {"op": {"_type": "Mult", "_fields": {}}, "left": {"_type": "Name", "_fields": {"id": "block_num", "ctx": {"_type": "Load", "_fields": {}}}}, "right": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "cdv", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "Constant", "_fields": {"kind": null, "value": 0}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "cmd", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": 0}}]}}, "orelse": []}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "buf", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "write", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}}}], "name": "writeblocks", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def writeblocks(self, block_num, buf): # TODO support multiple block writes assert len(buf) == 512 # CMD24: set write address for single block if self.cmd(24, block_num * self.cdv, 0) != 0: return 1 # send the data self.write(buf) return 0
10,324
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9
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": {"_type": "arg", "_fields": {"arg": "xin", "annotation": null, "type_comment": null}}, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "correlation", "value": {"_type": "Name", "_fields": {"id": "oeq", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "const", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 16.9612111141}}}}, {"_type": "keyword", "_fields": {"arg": "a", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 37.3699270344}}}}, {"_type": "keyword", "_fields": {"arg": "b", "value": {"_type": "UnaryOp", "_fields": {"op": {"_type": "USub", "_fields": {}}, "operand": {"_type": "Constant", "_fields": {"kind": null, "value": 25.066880729}}}}}}, {"_type": "keyword", "_fields": {"arg": "c", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 6.04869046956}}}}, {"_type": "keyword", "_fields": {"arg": "d", "value": {"_type": "UnaryOp", "_fields": {"op": {"_type": "USub", "_fields": {}}, "operand": {"_type": "Constant", "_fields": {"kind": null, "value": 0.472322343882}}}}}}, {"_type": "keyword", "_fields": {"arg": "mode", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "log"}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "TOTAL_LIVING_AREA", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "dict", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "TOTAL_LIVING_AREA", "value": {"_type": "Call", "_fields": {"args": [{"_type": "Starred", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "value": {"_type": "Name", "_fields": {"id": "xin", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "lookup", "value": {"_type": "Name", "_fields": {"id": "TOTAL_LIVING_AREA", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}]}}}}], "name": "get", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def get(*xin): # OeQ autogenerated correlation for 'NULL' TOTAL_LIVING_AREA= oeq.correlation( const= 16.9612111141, a= 37.3699270344, b= -25.066880729, c= 6.04869046956, d= -0.472322343882, mode= "log") return dict(TOTAL_LIVING_AREA=TOTAL_LIVING_AREA.lookup(*xin))
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10
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class BaseUsageTable(tables.DataTable): vcpus = tables.Column('vcpus', verbose_name=_("VCPUs")) disk = tables.Column('local_gb', verbose_name=_("Disk")) memory = tables.Column('memory_mb', verbose_name=_("RAM"), filters=(sizeformat.mbformat,), attrs={"data-type": "size"}) hours = tables.Column('vcpu_hours', verbose_name=_("VCPU Hours"), filters=(lambda v: floatformat(v, 2),))
10,326
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10
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{"id": "multi_select", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}], "name": "Meta", "bases": [], "keywords": [], "type_params": [], "decorator_list": []}}], "name": "GlobalUsageTable", "bases": [{"_type": "Name", "_fields": {"id": "BaseUsageTable", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}
class GlobalUsageTable(BaseUsageTable): project = tables.Column('project_name', verbose_name=_("Project Name")) disk_hours = tables.Column('disk_gb_hours', verbose_name=_("Disk GB Hours"), filters=(lambda v: floatformat(v, 2),)) def get_object_id(self, datum): return datum.tenant_id class Meta: name = "global_usage" verbose_name = _("Usage") columns = ("project", "vcpus", "disk", "memory", "hours", "disk_hours") table_actions = (CSVSummary,) multi_select = False
10,327
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9
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class ProjectUsageTable(BaseUsageTable): instance = tables.Column('name', verbose_name=_("Instance Name"), link=get_instance_link) uptime = tables.Column('uptime_at', verbose_name=_("Uptime"), filters=(filters.timesince_sortable,), attrs={'data-type': 'timesince'}) def get_object_id(self, datum): return datum.get('instance_id', id(datum)) class Meta: name = "project_usage" verbose_name = _("Usage") columns = ("instance", "vcpus", "disk", "memory", "uptime") table_actions = (CSVSummary,) multi_select = False
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9
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "parsed", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Try", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Thread", "value": {"_type": "Name", "_fields": {"id": "threading", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "target", "value": {"_type": "Name", "_fields": {"id": "_cron_loop", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "thread", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "start", "value": {"_type": "Name", "_fields": {"id": "thread", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "host", "value": {"_type": "Name", "_fields": {"id": "etc", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "port", "value": {"_type": "Name", "_fields": {"id": "etc", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "application", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "run_simple", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "processes", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}}}, {"_type": "keyword", "_fields": {"arg": "ssl_context", "value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "parsed", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "_ssl_context", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}]}}}}], "orelse": [], "handlers": [], "finalbody": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "set", "value": {"_type": "Name", "_fields": {"id": "_stop_cron_flag", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Name", "_fields": {"id": "thread", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}]}}], "name": "_start_server", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def _start_server(parsed): try: thread = threading.Thread(target=_cron_loop) thread.start() run_simple( etc.host, etc.port, application, processes=1, # ensure db integrety, avoid race conditions ssl_context=_ssl_context(parsed) ) finally: _stop_cron_flag.set() thread.join()
10,329
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7
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "args", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "serve", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [{"_type": "Constant", "_fields": {"kind": null, "value": true}}], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "__version__", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "print", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}, {"_type": "Return", "_fields": {"value": {"_type": "Name", "_fields": {"id": "__version__", "ctx": {"_type": "Load", "_fields": {}}}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "In", "_fields": {}}], "left": {"_type": "Constant", "_fields": {"kind": null, "value": "--version"}}, "comparators": [{"_type": "Name", "_fields": {"id": "args", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "orelse": []}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "args", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "parse", "value": {"_type": "Name", "_fields": {"id": "cli", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "parsed", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "parsed", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "initialize", "value": {"_type": "Name", "_fields": {"id": "lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "If", "_fields": {"body": [{"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "parsed", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "_start_server", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "test": {"_type": "Name", "_fields": {"id": "serve", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": []}}], "name": "main", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def main(args, serve=True): # show version if "--version" in args: print(__version__) return __version__ # parse args and initialize parsed = cli.parse(args) lib.initialize(parsed) if serve: return _start_server(parsed)
10,330
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8
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"_fields": {"args": [{"_type": "Name", "_fields": {"id": "__name__", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "CheckErrorContent", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "test2", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}, {"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "thisfile.c"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "\n\n// license\n// copyrigh1\n"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Analyze", "value": {"_type": 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null, "value": "\n#define \"WEWE\"\n// license\n// copyrigh1\n#include </ewe/kk> "}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Analyze", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Assert", "_fields": {"msg": null, "test": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "__name__", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "CheckErrorContent", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "test4", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}, {"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "thisfile.c"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "\n#define \"WEWE\"\n// license\n// copyright\n#include </ewe/kk> "}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Analyze", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Assert", "_fields": {"msg": null, "test": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "__name__", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "CheckErrorContent", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "test5", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}, {"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "thisfile.c"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "\n// license\n// copyright\n#define \"WEWE\"\n#include </ewe/kk> "}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Analyze", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Assert", "_fields": {"msg": null, "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "__name__", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "CheckErrorContent", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}}}], "name": "test6", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "testRule", "bases": [{"_type": "Name", "_fields": {"id": "nct", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}
class testRule(nct): def setUpRule(self): ruleManager.AddFileStartRule(RunRule) def test1(self): self.Analyze("thisfile.c",""" // license // copyright """) assert not CheckErrorContent(__name__) def test2(self): self.Analyze("thisfile.c", """ /** #if 0 #endif license coryright */ """) assert CheckErrorContent(__name__) def test3(self): self.Analyze("thisfile.c",""" // license // copyrigh1 """) assert CheckErrorContent(__name__) def test4(self): self.Analyze("thisfile.c",""" #define "WEWE" // license // copyrigh1 #include </ewe/kk> """) assert CheckErrorContent(__name__) def test5(self): self.Analyze("thisfile.c",""" #define "WEWE" // license // copyright #include </ewe/kk> """) assert CheckErrorContent(__name__) def test6(self): self.Analyze("thisfile.c",""" // license // copyright #define "WEWE" #include </ewe/kk> """) assert not CheckErrorContent(__name__)
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14
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def RunRule(lexer, filename, dirname) : t = lexer.GetNextTokenSkipWhiteSpace() if t == None : return if t.type == "COMMENT" : if t.value.lower().find("copyright") == -1 : nsiqcppstyle_reporter.Error(DummyToken(lexer.filename, "", 1, 0), __name__, "Please provide file info comment in front of file") elif t.type == "CPPCOMMENT" : find = False while(t != None and t.type == "CPPCOMMENT") : if t.value.lower().find("copyright") != -1 : find = True break; t = lexer.GetNextTokenSkipWhiteSpace() if not find : nsiqcppstyle_reporter.Error(DummyToken(lexer.filename, "", 1, 0), __name__, "Please provide file info comment in front of file") else : nsiqcppstyle_reporter.Error(DummyToken(lexer.filename, "", 1, 0), __name__, "Please provide file info comment in front of file")
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def update_connections_time_zone(**kwargs): if kwargs['setting'] == 'TIME_ZONE': # Reset process time zone if hasattr(time, 'tzset'): if kwargs['value']: os.environ['TZ'] = kwargs['value'] else: os.environ.pop('TZ', None) time.tzset() # Reset local time zone cache timezone._localtime = None # Reset the database connections' time zone if kwargs['setting'] == 'USE_TZ' and settings.TIME_ZONE != 'UTC': USE_TZ, TIME_ZONE = kwargs['value'], settings.TIME_ZONE elif kwargs['setting'] == 'TIME_ZONE' and not settings.USE_TZ: USE_TZ, TIME_ZONE = settings.USE_TZ, kwargs['value'] else: # no need to change the database connnections' time zones return tz = 'UTC' if USE_TZ else TIME_ZONE for conn in connections.all(): conn.settings_dict['TIME_ZONE'] = tz tz_sql = conn.ops.set_time_zone_sql() if tz_sql: conn.cursor().execute(tz_sql, [tz])
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11
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[{"_type": "Constant", "_fields": {"kind": null, "value": "working_dir"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "debug"}}], "values": [{"_type": "Constant", "_fields": {"kind": null, "value": "/mnt/pyami"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "0"}}]}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "__init__", "value": {"_type": "Name", "_fields": {"id": "ConfigParser", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "If", "_fields": {"body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "path", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "load_from_path", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], 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{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "load_credential_file", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "orelse": [], "handlers": [{"_type": "ExceptHandler", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "Unable to load AWS_CREDENTIAL_FILE (%s)"}}, "right": {"_type": "Name", "_fields": {"id": "full_path", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "warn", "value": {"_type": "Name", "_fields": {"id": "warnings", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": null, "type": {"_type": "Name", "_fields": {"id": "IOError", "ctx": {"_type": "Load", "_fields": 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def __init__(self, path=None, fp=None, do_load=True): # We don't use ``super`` here, because ``ConfigParser`` still uses # old-style classes. ConfigParser.__init__(self, {'working_dir': '/mnt/pyami', 'debug': '0'}) if do_load: if path: self.load_from_path(path) elif fp: self.readfp(fp) else: self.read(BotoConfigLocations) if "AWS_CREDENTIAL_FILE" in os.environ: full_path = expanduser(os.environ['AWS_CREDENTIAL_FILE']) try: self.load_credential_file(full_path) except IOError: warnings.warn('Unable to load AWS_CREDENTIAL_FILE (%s)' % full_path)
10,334
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9
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def getbool(self, section, name, default=False): if self.has_option(section, name): val = self.get(section, name) if val.lower() == 'true': val = True else: val = False else: val = default return val
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11
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def load_from_path(self, path): file = open(path) for line in file.readlines(): match = re.match("^#import[\s\t]*([^\s^\t]*)[\s\t]*$", line) if match: extended_file = match.group(1) (dir, file) = os.path.split(path) self.load_from_path(os.path.join(dir, extended_file)) self.read(path)
10,336
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13
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "fp", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [{"_type": "Constant", "_fields": {"kind": null, "value": null}}], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "If", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "StringIO", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "fp", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Name", "_fields": {"id": "fp", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": []}}, {"_type": "For", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "[%s]\n"}}, "right": {"_type": "Name", "_fields": {"id": "section", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "write", "value": {"_type": "Name", "_fields": {"id": "fp", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "For", "_fields": {"body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "%s = xxxxxxxxxxxxxxxxxx\n"}}, "right": {"_type": "Name", "_fields": {"id": "option", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "write", "value": {"_type": "Name", "_fields": {"id": "fp", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "option", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": "aws_secret_access_key"}}]}}, "orelse": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "%s = %s\n"}}, "right": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "option", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "section", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "option", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "get", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}]}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "write", "value": {"_type": "Name", "_fields": {"id": "fp", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}]}}], "iter": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "section", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "options", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "option", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "iter": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "sections", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "section", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "dump_safe", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def dump_safe(self, fp=None): if not fp: fp = StringIO() for section in self.sections(): fp.write('[%s]\n' % section) for option in self.options(section): if option == 'aws_secret_access_key': fp.write('%s = xxxxxxxxxxxxxxxxxx\n' % option) else: fp.write('%s = %s\n' % (option, self.get(section, option)))
10,337
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10
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class MicrosecAdapter(Adapter): def _decode(self, obj, context): return datetime.fromtimestamp(obj[0] + (obj[1] / 1000000.0)) def _encode(self, obj, context): offset = time.mktime(*obj.timetuple()) sec = int(offset) usec = (offset - sec) * 1000000 return (sec, usec)
10,338
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11
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def pushlines(self, lines): # Crack into lines, but preserve the newlines on the end of each parts = NLCRE_crack.split(data) # The *ahem* interesting behaviour of re.split when supplied grouping # parentheses is that the last element of the resulting list is the # data after the final RE. In the case of a NL/CR terminated string, # this is the empty string. self._partial = parts.pop() #GAN 29Mar09 bugs 1555570, 1721862 Confusion at 8K boundary ending with \r: # is there a \n to follow later? if not self._partial and parts and parts[-1].endswith('\r'): self._partial = parts.pop(-2)+parts.pop() # parts is a list of strings, alternating between the line contents # and the eol character(s). Gather up a list of lines after # re-attaching the newlines. lines = [] for i in range(len(parts) // 2): lines.append(parts[i*2] + parts[i*2+1]) self.pushlines(lines)
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10
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "If", "_fields": {"body": [{"_type": "If", "_fields": {"body": [{"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": ""}}}}], "test": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_closed", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": []}}, {"_type": "Return", "_fields": {"value": {"_type": "Name", "_fields": {"id": "NeedMoreData", "ctx": {"_type": "Load", "_fields": {}}}}}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_lines", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "orelse": []}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pop", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_lines", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "line", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "For", "_fields": {"body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "line", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "append", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_lines", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}, {"_type": "Return", "_fields": {"value": {"_type": "Constant", "_fields": {"kind": null, "value": ""}}}}], "test": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "line", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "ateof", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "orelse": []}}], "iter": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Slice", "_fields": {"step": {"_type": "UnaryOp", "_fields": {"op": {"_type": "USub", "_fields": {}}, "operand": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}}}, "lower": null, "upper": null}}, "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_eofstack", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "ateof", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Name", "_fields": {"id": "line", "ctx": {"_type": "Load", "_fields": {}}}}}}], "name": "readline", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def readline(self): if not self._lines: if self._closed: return '' return NeedMoreData # Pop the line off the stack and see if it matches the current # false-EOF predicate. line = self._lines.pop() # RFC 2046, section 5.1.2 requires us to recognize outer level # boundaries at any level of inner nesting. Do this, but be sure it's # in the order of most to least nested. for ateof in self._eofstack[::-1]: if ateof(line): # We're at the false EOF. But push the last line back first. self._lines.append(line) return '' return line
10,340
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10
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def _new_message(self): msg = self._factory() if self._cur and self._cur.get_content_type() == 'multipart/digest': msg.set_default_type('message/rfc822') if self._msgstack: self._msgstack[-1].attach(msg) self._msgstack.append(msg) self._cur = msg self._last = msg
10,341
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{"value": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Slice", "_fields": {"step": null, "lower": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 0}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "group", "value": {"_type": "Name", "_fields": {"id": "bolmo", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}], "func": {"_type": "Name", "_fields": {"id": "len", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "upper": null}}, "value": {"_type": "Name", "_fields": {"id": "firstline", "ctx": {"_type": "Load", "_fields": {}}}}}}, "targets": [{"_type": "Subscript", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": 0}}, "value": {"_type": "Name", "_fields": {"id": "epilogue", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}], "test": {"_type": "Name", "_fields": {"id": "bolmo", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": []}}], "test": {"_type": "Name", "_fields": {"id": "epilogue", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": []}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "epilogue", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Name", "_fields": {"id": "EMPTYSTRING", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "epilogue", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_cur", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": null}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Eq", "_fields": {}}], "left": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "get_content_maintype", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_cur", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "comparators": [{"_type": "Constant", "_fields": {"kind": null, "value": "multipart"}}]}}, "orelse": []}}, {"_type": "Assign", "_fields": {"value": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": []}}, "targets": [{"_type": "Name", "_fields": {"id": "lines", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "For", "_fields": {"body": [{"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Yield", "_fields": {"value": {"_type": "Name", "_fields": {"id": "NeedMoreData", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "Continue", "_fields": {}}], "test": {"_type": "Compare", "_fields": {"ops": [{"_type": "Is", "_fields": {}}], "left": {"_type": "Name", "_fields": {"id": "line", "ctx": {"_type": "Load", "_fields": {}}}}, "comparators": [{"_type": "Name", "_fields": {"id": "NeedMoreData", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "orelse": []}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "line", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "append", "value": {"_type": "Name", "_fields": {"id": "lines", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "iter": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_input", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "line", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "lines", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Name", "_fields": {"id": "EMPTYSTRING", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "set_payload", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "_cur", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}], "name": "_parsegen", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def _parsegen(self): # Create a new message and start by parsing headers. self._new_message() headers = [] # Collect the headers, searching for a line that doesn't match the RFC # 2822 header or continuation pattern (including an empty line). for line in self._input: if line is NeedMoreData: yield NeedMoreData continue if not headerRE.match(line): # If we saw the RFC defined header/body separator # (i.e. newline), just throw it away. Otherwise the line is # part of the body so push it back. if not NLCRE.match(line): self._input.unreadline(line) break headers.append(line) # Done with the headers, so parse them and figure out what we're # supposed to see in the body of the message. self._parse_headers(headers) # Headers-only parsing is a backwards compatibility hack, which was # necessary in the older parser, which could raise errors. All # remaining lines in the input are thrown into the message body. if self._headersonly: lines = [] while True: line = self._input.readline() if line is NeedMoreData: yield NeedMoreData continue if line == '': break lines.append(line) self._cur.set_payload(EMPTYSTRING.join(lines)) return if self._cur.get_content_type() == 'message/delivery-status': # message/delivery-status contains blocks of headers separated by # a blank line. We'll represent each header block as a separate # nested message object, but the processing is a bit different # than standard message/* types because there is no body for the # nested messages. A blank line separates the subparts. while True: self._input.push_eof_matcher(NLCRE.match) for retval in self._parsegen(): if retval is NeedMoreData: yield NeedMoreData continue break msg = self._pop_message() # We need to pop the EOF matcher in order to tell if we're at # the end of the current file, not the end of the last block # of message headers. self._input.pop_eof_matcher() # The input stream must be sitting at the newline or at the # EOF. We want to see if we're at the end of this subpart, so # first consume the blank line, then test the next line to see # if we're at this subpart's EOF. while True: line = self._input.readline() if line is NeedMoreData: yield NeedMoreData continue break while True: line = self._input.readline() if line is NeedMoreData: yield NeedMoreData continue break if line == '': break # Not at EOF so this is a line we're going to need. self._input.unreadline(line) return if self._cur.get_content_maintype() == 'message': # The message claims to be a message/* type, then what follows is # another RFC 2822 message. for retval in self._parsegen(): if retval is NeedMoreData: yield NeedMoreData continue break self._pop_message() return if self._cur.get_content_maintype() == 'multipart': boundary = self._cur.get_boundary() if boundary is None: # The message /claims/ to be a multipart but it has not # defined a boundary. That's a problem which we'll handle by # reading everything until the EOF and marking the message as # defective. self._cur.defects.append(errors.NoBoundaryInMultipartDefect()) lines = [] for line in self._input: if line is NeedMoreData: yield NeedMoreData continue lines.append(line) self._cur.set_payload(EMPTYSTRING.join(lines)) return # Create a line match predicate which matches the inter-part # boundary as well as the end-of-multipart boundary. Don't push # this onto the input stream until we've scanned past the # preamble. separator = '--' + boundary boundaryre = re.compile( '(?P<sep>' + re.escape(separator) + r')(?P<end>--)?(?P<ws>[ \t]*)(?P<linesep>\r\n|\r|\n)?$') capturing_preamble = True preamble = [] linesep = False while True: line = self._input.readline() if line is NeedMoreData: yield NeedMoreData continue if line == '': break mo = boundaryre.match(line) if mo: # If we're looking at the end boundary, we're done with # this multipart. If there was a newline at the end of # the closing boundary, then we need to initialize the # epilogue with the empty string (see below). if mo.group('end'): linesep = mo.group('linesep') break # We saw an inter-part boundary. Were we in the preamble? if capturing_preamble: if preamble: # According to RFC 2046, the last newline belongs # to the boundary. lastline = preamble[-1] eolmo = NLCRE_eol.search(lastline) if eolmo: preamble[-1] = lastline[:-len(eolmo.group(0))] self._cur.preamble = EMPTYSTRING.join(preamble) capturing_preamble = False self._input.unreadline(line) continue # We saw a boundary separating two parts. Consume any # multiple boundary lines that may be following. Our # interpretation of RFC 2046 BNF grammar does not produce # body parts within such double boundaries. while True: line = self._input.readline() if line is NeedMoreData: yield NeedMoreData continue mo = boundaryre.match(line) if not mo: self._input.unreadline(line) break # Recurse to parse this subpart; the input stream points # at the subpart's first line. self._input.push_eof_matcher(boundaryre.match) for retval in self._parsegen(): if retval is NeedMoreData: yield NeedMoreData continue break # Because of RFC 2046, the newline preceding the boundary # separator actually belongs to the boundary, not the # previous subpart's payload (or epilogue if the previous # part is a multipart). if self._last.get_content_maintype() == 'multipart': epilogue = self._last.epilogue if epilogue == '': self._last.epilogue = None elif epilogue is not None: mo = NLCRE_eol.search(epilogue) if mo: end = len(mo.group(0)) self._last.epilogue = epilogue[:-end] else: payload = self._last.get_payload() if isinstance(payload, basestring): mo = NLCRE_eol.search(payload) if mo: payload = payload[:-len(mo.group(0))] self._last.set_payload(payload) self._input.pop_eof_matcher() self._pop_message() # Set the multipart up for newline cleansing, which will # happen if we're in a nested multipart. self._last = self._cur else: # I think we must be in the preamble assert capturing_preamble preamble.append(line) # We've seen either the EOF or the end boundary. If we're still # capturing the preamble, we never saw the start boundary. Note # that as a defect and store the captured text as the payload. # Everything from here to the EOF is epilogue. if capturing_preamble: self._cur.defects.append(errors.StartBoundaryNotFoundDefect()) self._cur.set_payload(EMPTYSTRING.join(preamble)) epilogue = [] for line in self._input: if line is NeedMoreData: yield NeedMoreData continue self._cur.epilogue = EMPTYSTRING.join(epilogue) return # If the end boundary ended in a newline, we'll need to make sure # the epilogue isn't None if linesep: epilogue = [''] else: epilogue = [] for line in self._input: if line is NeedMoreData: yield NeedMoreData continue epilogue.append(line) # Any CRLF at the front of the epilogue is not technically part of # the epilogue. Also, watch out for an empty string epilogue, # which means a single newline. if epilogue: firstline = epilogue[0] bolmo = NLCRE_bol.match(firstline) if bolmo: epilogue[0] = firstline[len(bolmo.group(0)):] self._cur.epilogue = EMPTYSTRING.join(epilogue) return # Otherwise, it's some non-multipart type, so the entire rest of the # file contents becomes the payload. lines = [] for line in self._input: if line is NeedMoreData: yield NeedMoreData continue lines.append(line) self._cur.set_payload(EMPTYSTRING.join(lines))
10,342
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{"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "subTest", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "model", "value": {"_type": "Name", "_fields": {"id": "Model", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "field", "value": {"_type": "Name", "_fields": {"id": "field", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "optional_vars": null}}], "type_comment": null}}], "iter": {"_type": "Name", "_fields": {"id": "test_data", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "Model", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "field", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "initial", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "new", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "type_comment": null}}], "name": "test_bulk_update", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "BulkSaveTests", "bases": [{"_type": "Name", "_fields": {"id": "PostgreSQLTestCase", "ctx": {"_type": "Load", "_fields": {}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}
class BulkSaveTests(PostgreSQLTestCase): def test_bulk_update(self): test_data = [ (IntegerArrayModel, "field", [], [1, 2, 3]), (NullableIntegerArrayModel, "field", [1, 2, 3], None), (NestedIntegerArrayModel, "field", [], [[1, 2, 3]]), (HStoreModel, "field", {}, {1: 2}), (RangesModel, "ints", None, NumericRange(lower=1, upper=10)), ( RangesModel, "dates", None, DateRange(lower=date.today(), upper=date.today()), ), (OtherTypesArrayModel, "ips", [], ["1.2.3.4"]), (OtherTypesArrayModel, "json", [], [{"a": "b"}]), ] for Model, field, initial, new in test_data: with self.subTest(model=Model, field=field): instances = Model.objects.bulk_create( Model(**{field: initial}) for _ in range(20) ) for instance in instances: setattr(instance, field, new) Model.objects.bulk_update(instances, [field]) self.assertSequenceEqual( Model.objects.filter(**{field: new}), instances )
10,343
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def _parse_headers(self, lines): # Passed a list of lines that make up the headers for the current msg lastheader = '' lastvalue = [] for lineno, line in enumerate(lines): # Check for continuation if line[0] in ' \t': if not lastheader: # The first line of the headers was a continuation. This # is illegal, so let's note the defect, store the illegal # line, and ignore it for purposes of headers. defect = errors.FirstHeaderLineIsContinuationDefect(line) self._cur.defects.append(defect) continue lastvalue.append(line) continue if lastheader: # XXX reconsider the joining of folded lines lhdr = EMPTYSTRING.join(lastvalue)[:-1].rstrip('\r\n') self._cur[lastheader] = lhdr lastheader, lastvalue = '', [] # Check for envelope header, i.e. unix-from if line.startswith('From '): if lineno == 0: # Strip off the trailing newline mo = NLCRE_eol.search(line) if mo: line = line[:-len(mo.group(0))] self._cur.set_unixfrom(line) continue elif lineno == len(lines) - 1: # Something looking like a unix-from at the end - it's # probably the first line of the body, so push back the # line and stop. self._input.unreadline(line) return else: # Weirdly placed unix-from line. Note this as a defect # and ignore it. defect = errors.MisplacedEnvelopeHeaderDefect(line) self._cur.defects.append(defect) continue # Split the line on the colon separating field name from value. i = line.find(':') if i < 0: defect = errors.MalformedHeaderDefect(line) self._cur.defects.append(defect) continue lastheader = line[:i] lastvalue = [line[i+1:].lstrip()] # Done with all the lines, so handle the last header. if lastheader: # XXX reconsider the joining of folded lines self._cur[lastheader] = EMPTYSTRING.join(lastvalue).rstrip('\r\n')
10,344
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12
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def test_bulk_update(self): test_data = [ (IntegerArrayModel, "field", [], [1, 2, 3]), (NullableIntegerArrayModel, "field", [1, 2, 3], None), (NestedIntegerArrayModel, "field", [], [[1, 2, 3]]), (HStoreModel, "field", {}, {1: 2}), (RangesModel, "ints", None, NumericRange(lower=1, upper=10)), ( RangesModel, "dates", None, DateRange(lower=date.today(), upper=date.today()), ), (OtherTypesArrayModel, "ips", [], ["1.2.3.4"]), (OtherTypesArrayModel, "json", [], [{"a": "b"}]), ] for Model, field, initial, new in test_data: with self.subTest(model=Model, field=field): instances = Model.objects.bulk_create( Model(**{field: initial}) for _ in range(20) ) for instance in instances: setattr(instance, field, new) Model.objects.bulk_update(instances, [field]) self.assertSequenceEqual( Model.objects.filter(**{field: new}), instances )
10,345
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10
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def _get_size_from_underlying_file(self): if hasattr(self.file, 'size'): return self.file.size if hasattr(self.file, 'name'): try: return os.path.getsize(self.file.name) except (OSError, TypeError): pass if hasattr(self.file, 'tell') and hasattr(self.file, 'seek'): pos = self.file.tell() self.file.seek(0, os.SEEK_END) size = self.file.tell() self.file.seek(pos) return size raise AttributeError("Unable to determine the file's size.")
10,346
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9
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def __init__(self, content, name=None): if six.PY3: stream_class = StringIO if isinstance(content, six.text_type) else BytesIO else: stream_class = BytesIO content = force_bytes(content) super(ContentFile, self).__init__(stream_class(content), name=name) self.size = len(content)
10,347
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11
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def __iter__(self): # Iterate over this file-like object by newlines buffer_ = None for chunk in self.chunks(): for line in chunk.splitlines(True): if buffer_: if endswith_cr(buffer_) and not equals_lf(line): # Line split after a \r newline; yield buffer_. yield buffer_ # Continue with line. else: # Line either split without a newline (line # continues after buffer_) or with \r\n # newline (line == b'\n'). line = buffer_ + line # buffer_ handled, clear it. buffer_ = None # If this is the end of a \n or \r\n line, yield. if endswith_lf(line): yield line else: buffer_ = line if buffer_ is not None: yield buffer_
10,348
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10
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class FrappeOAuth2Client(FrappeClient): def __init__(self, url, access_token, verify=True): self.access_token = access_token self.headers = { "Authorization": "Bearer " + access_token, "content-type": "application/x-www-form-urlencoded" } self.verify = verify self.session = OAuth2Session(self.headers) self.url = url def get_request(self, params): res = requests.get(self.url, params=self.preprocess(params), headers=self.headers, verify=self.verify) res = self.post_process(res) return res def post_request(self, data): res = requests.post(self.url, data=self.preprocess(data), headers=self.headers, verify=self.verify) res = self.post_process(res) return res
10,349
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9
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def post_process(self, response): try: rjson = response.json() except ValueError: print(response.text) raise if rjson and ("exc" in rjson) and rjson["exc"]: raise FrappeException(rjson["exc"]) if 'message' in rjson: return rjson['message'] elif 'data' in rjson: return rjson['data'] else: return None
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"_fields": {}}, "attr": "headers", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "keyword", "_fields": {"arg": "verify", "value": {"_type": "Name", "_fields": {"id": "verify", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "res", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Name", "_fields": {"id": "res", "ctx": {"_type": "Load", "_fields": {}}}}}}], "name": "post", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}, {"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "url", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "data", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "verify", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "url", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "put", "value": {"_type": "Name", "_fields": {"id": "requests", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "data", "value": {"_type": "Name", "_fields": {"id": "data", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "headers", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "headers", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "keyword", "_fields": {"arg": "verify", "value": {"_type": "Name", "_fields": {"id": "verify", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "res", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Name", "_fields": {"id": "res", "ctx": {"_type": "Load", "_fields": {}}}}}}], "name": "put", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "name": "OAuth2Session", "bases": [], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}
class OAuth2Session(): def __init__(self, headers): self.headers = headers def get(self, url, params, verify): res = requests.get(url, params=params, headers=self.headers, verify=verify) return res def post(self, url, data, verify): res = requests.post(url, data=data, headers=self.headers, verify=verify) return res def put(self, url, data, verify): res = requests.put(url, data=data, headers=self.headers, verify=verify) return res
10,351
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{}}}}, "keywords": []}}, "optional_vars": {"_type": "Name", "_fields": {"id": "f", "ctx": {"_type": "Store", "_fields": {}}}}}}], "type_comment": null}}], "test": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pidfile", "value": {"_type": "Name", "_fields": {"id": "opts", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": []}}, {"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "startDebugMode", "value": {"_type": "Name", "_fields": {"id": "failure", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "test": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pdb", "value": {"_type": "Name", "_fields": {"id": "opts", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": []}}], "name": "process_options", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def process_options(self, args, opts): try: self.settings.setdict(arglist_to_dict(opts.set), priority='cmdline') except ValueError: raise UsageError("Invalid -s value, use -s NAME=VALUE", print_help=False) if opts.logfile: self.settings.set('LOG_ENABLED', True, priority='cmdline') self.settings.set('LOG_FILE', opts.logfile, priority='cmdline') if opts.loglevel: self.settings.set('LOG_ENABLED', True, priority='cmdline') self.settings.set('LOG_LEVEL', opts.loglevel, priority='cmdline') if opts.nolog: self.settings.set('LOG_ENABLED', False, priority='cmdline') if opts.pidfile: with open(opts.pidfile, "w") as f: f.write(str(os.getpid()) + os.linesep) if opts.pdb: failure.startDebugMode()
10,352
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13
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def collapse_group_by(self, expressions, having): # If the DB can group by primary key, then group by the primary key of # query's main model. Note that for PostgreSQL the GROUP BY clause must # include the primary key of every table, but for MySQL it is enough to # have the main table's primary key. if self.connection.features.allows_group_by_pk: # The logic here is: if the main model's primary key is in the # query, then set new_expressions to that field. If that happens, # then also add having expressions to group by. pk = None for expr in expressions: # Is this a reference to query's base table primary key? If the # expression isn't a Col-like, then skip the expression. if (getattr(expr, 'target', None) == self.query.model._meta.pk and getattr(expr, 'alias', None) == self.query.tables[0]): pk = expr break if pk: # MySQLism: Columns in HAVING clause must be added to the GROUP BY. expressions = [pk] + [expr for expr in expressions if expr in having] elif self.connection.features.allows_group_by_selected_pks: # Filter out all expressions associated with a table's primary key # present in the grouped columns. This is done by identifying all # tables that have their primary key included in the grouped # columns and removing non-primary key columns referring to them. pks = {expr for expr in expressions if hasattr(expr, 'target') and expr.target.primary_key} aliases = {expr.alias for expr in pks} expressions = [ expr for expr in expressions if expr in pks or getattr(expr, 'alias', None) not in aliases ] return expressions
10,353
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12
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def get_extra_select(self, order_by, select): extra_select = [] select_sql = [t[1] for t in select] if self.query.distinct and not self.query.distinct_fields: for expr, (sql, params, is_ref) in order_by: without_ordering = self.ordering_parts.search(sql).group(1) if not is_ref and (without_ordering, params) not in select_sql: extra_select.append((expr, (without_ordering, params), None)) return extra_select
10,354
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11
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def get_converters(self, expressions): converters = {} for i, expression in enumerate(expressions): if expression: backend_converters = self.connection.ops.get_db_converters(expression) field_converters = expression.get_db_converters(self.connection) if backend_converters or field_converters: converters[i] = (backend_converters + field_converters, expression) return converters
10,355
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9
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def compile(self, node, select_format=False): vendor_impl = getattr(node, 'as_' + self.connection.vendor, None) if vendor_impl: sql, params = vendor_impl(self, self.connection) else: sql, params = node.as_sql(self, self.connection) if select_format and not self.subquery: return node.output_field.select_format(self, sql, params) return sql, params
10,356
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10
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def apply_converters(self, row, converters): row = list(row) for pos, (convs, expression) in converters.items(): value = row[pos] for converter in convs: value = converter(value, expression, self.connection, self.query.context) row[pos] = value return tuple(row)
10,357
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11
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def as_subquery_condition(self, alias, columns, compiler): qn = compiler.quote_name_unless_alias qn2 = self.connection.ops.quote_name if len(columns) == 1: sql, params = self.as_sql() return '%s.%s IN (%s)' % (qn(alias), qn2(columns[0]), sql), params for index, select_col in enumerate(self.query.select): lhs_sql, lhs_params = self.compile(select_col) rhs = '%s.%s' % (qn(alias), qn2(columns[index])) self.query.where.add( QueryWrapper('%s = %s' % (lhs_sql, rhs), lhs_params), 'AND') sql, params = self.as_sql() return 'EXISTS (%s)' % sql, params
10,358
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"_fields": {}}, "elts": [{"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Constant", "_fields": {"kind": null, "value": " "}}}}, "keywords": []}}, {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "params", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "tuple", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}]}}]}}}}], "test": {"_type": "BoolOp", "_fields": {"op": {"_type": "And", "_fields": {}}, "values": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "return_id", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "can_return_id_from_insert", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "features", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "connection", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}]}}, "orelse": []}}, {"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "fields", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "placeholder_rows", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "bulk_insert_sql", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "ops", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "connection", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}, "keywords": []}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "append", "value": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Return", "_fields": {"value": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Constant", "_fields": {"kind": null, "value": " "}}}}, "keywords": []}}, {"_type": "Call", "_fields": {"args": [{"_type": "GeneratorExp", "_fields": {"elt": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}, "generators": [{"_type": "comprehension", "_fields": {"ifs": [], "iter": {"_type": "Name", "_fields": {"id": "param_rows", "ctx": {"_type": "Load", "_fields": {}}}}, "target": {"_type": "Name", "_fields": {"id": "ps", "ctx": {"_type": "Store", "_fields": {}}}}, "is_async": 0}}, {"_type": "comprehension", "_fields": {"ifs": [], "iter": {"_type": "Name", "_fields": {"id": "ps", "ctx": {"_type": "Load", "_fields": {}}}}, "target": {"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Store", "_fields": {}}}}, "is_async": 0}}]}}], "func": {"_type": "Name", "_fields": {"id": "tuple", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}]}}]}}}}], "test": {"_type": "Name", "_fields": {"id": "can_bulk", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [{"_type": "Return", "_fields": {"value": {"_type": "ListComp", "_fields": {"elt": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Call", "_fields": {"args": [{"_type": "BinOp", "_fields": {"op": {"_type": "Add", "_fields": {}}, "left": {"_type": "Name", "_fields": {"id": "result", "ctx": {"_type": "Load", "_fields": {}}}}, "right": {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "BinOp", "_fields": {"op": {"_type": "Mod", "_fields": {}}, "left": {"_type": "Constant", "_fields": {"kind": null, "value": "VALUES (%s)"}}, "right": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Constant", "_fields": {"kind": null, "value": ", "}}}}, "keywords": []}}}}]}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Constant", "_fields": {"kind": null, "value": " "}}}}, "keywords": []}}, {"_type": "Name", "_fields": {"id": "vals", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "generators": [{"_type": "comprehension", "_fields": {"ifs": [], "iter": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "placeholder_rows", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "param_rows", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "zip", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "target": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "elts": [{"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Store", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "vals", "ctx": {"_type": "Store", "_fields": {}}}}]}}, "is_async": 0}}]}}}}]}}], "name": "as_sql", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def as_sql(self): # We don't need quote_name_unless_alias() here, since these are all # going to be column names (so we can avoid the extra overhead). qn = self.connection.ops.quote_name opts = self.query.get_meta() result = ['INSERT INTO %s' % qn(opts.db_table)] has_fields = bool(self.query.fields) fields = self.query.fields if has_fields else [opts.pk] result.append('(%s)' % ', '.join(qn(f.column) for f in fields)) if has_fields: value_rows = [ [self.prepare_value(field, self.pre_save_val(field, obj)) for field in fields] for obj in self.query.objs ] else: # An empty object. value_rows = [[self.connection.ops.pk_default_value()] for _ in self.query.objs] fields = [None] # Currently the backends just accept values when generating bulk # queries and generate their own placeholders. Doing that isn't # necessary and it should be possible to use placeholders and # expressions in bulk inserts too. can_bulk = (not self.return_id and self.connection.features.has_bulk_insert) placeholder_rows, param_rows = self.assemble_as_sql(fields, value_rows) if self.return_id and self.connection.features.can_return_id_from_insert: params = param_rows[0] col = "%s.%s" % (qn(opts.db_table), qn(opts.pk.column)) result.append("VALUES (%s)" % ", ".join(placeholder_rows[0])) r_fmt, r_params = self.connection.ops.return_insert_id() # Skip empty r_fmt to allow subclasses to customize behavior for # 3rd party backends. Refs #19096. if r_fmt: result.append(r_fmt % col) params += r_params return [(" ".join(result), tuple(params))] if can_bulk: result.append(self.connection.ops.bulk_insert_sql(fields, placeholder_rows)) return [(" ".join(result), tuple(p for ps in param_rows for p in ps))] else: return [ (" ".join(result + ["VALUES (%s)" % ", ".join(p)]), vals) for p, vals in zip(placeholder_rows, param_rows) ]
10,359
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12
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"_fields": {}}}}}}}}}}, "keywords": []}}}}], "test": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "can_return_id_from_insert", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "features", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "connection", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}, "orelse": []}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "cursor", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "db_table", "value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "get_meta", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "query", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "column", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pk", "value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "get_meta", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "query", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "last_insert_id", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "ops", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "connection", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}}}, "keywords": []}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "cursor", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "connection", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "optional_vars": {"_type": "Name", "_fields": {"id": "cursor", "ctx": {"_type": "Store", "_fields": {}}}}}}], "type_comment": null}}], "name": "execute_sql", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def execute_sql(self, return_id=False): assert not (return_id and len(self.query.objs) != 1) self.return_id = return_id with self.connection.cursor() as cursor: for sql, params in self.as_sql(): cursor.execute(sql, params) if not (return_id and cursor): return if self.connection.features.can_return_id_from_insert: return self.connection.ops.fetch_returned_insert_id(cursor) return self.connection.ops.last_insert_id(cursor, self.query.get_meta().db_table, self.query.get_meta().pk.column)
10,360
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class Conv3DTest(test.TestCase): def _DtypesToTest(self, use_gpu): if use_gpu: if not test_util.CudaSupportsHalfMatMulAndConv(): return [dtypes.float32] else: # It is important that float32 comes before float16 here, # as we will be using its gradients as reference for fp16 gradients. return [dtypes.float32, dtypes.float16] else: return [dtypes.float64, dtypes.float32, dtypes.float16] def _SetupValuesForDevice(self, tensor_in_sizes, filter_in_sizes, stride, padding, data_format, dtype, use_gpu): total_size_1 = 1 total_size_2 = 1 for s in tensor_in_sizes: total_size_1 *= s for s in filter_in_sizes: total_size_2 *= s # Initializes the input tensor with array containing numbers from 0 to 1. # We keep the input tensor values fairly small to avoid overflowing float16 # during the conv3d. x1 = [f * 1.0 / total_size_1 for f in range(1, total_size_1 + 1)] x2 = [f * 1.0 / total_size_2 for f in range(1, total_size_2 + 1)] with self.test_session(use_gpu=use_gpu): t1 = constant_op.constant(x1, shape=tensor_in_sizes, dtype=dtype) t2 = constant_op.constant(x2, shape=filter_in_sizes, dtype=dtype) if isinstance(stride, collections.Iterable): strides = [1] + list(stride) + [1] else: strides = [1, stride, stride, stride, 1] if data_format == "NCDHW": t1 = test_util.NHWCToNCHW(t1) strides = test_util.NHWCToNCHW(strides) conv = nn_ops.conv3d(t1, t2, strides, padding=padding, data_format=data_format) if data_format == "NCDHW": conv = test_util.NCHWToNHWC(conv) return conv def _VerifyValues(self, tensor_in_sizes, filter_in_sizes, stride, padding, expected): results = [] for data_format, use_gpu in GetTestConfigs(): for dtype in self._DtypesToTest(use_gpu): result = self._SetupValuesForDevice( tensor_in_sizes, filter_in_sizes, stride, padding, data_format, dtype, use_gpu=use_gpu) results.append(result) with self.test_session() as sess: values = sess.run(results) for value in values: print("expected = ", expected) print("actual = ", value) tol = 1e-6 if value.dtype == np.float16: tol = 1e-3 self.assertAllClose(expected, value.flatten(), atol=tol, rtol=tol) def testConv3D1x1x1Filter(self): expected_output = [ 0.18518519, 0.22222222, 0.25925926, 0.40740741, 0.5, 0.59259259, 0.62962963, 0.77777778, 0.92592593, 0.85185185, 1.05555556, 1.25925926, 1.07407407, 1.33333333, 1.59259259, 1.2962963, 1.61111111, 1.92592593 ] # These are equivalent to the Conv2D1x1 case. self._VerifyValues( tensor_in_sizes=[1, 2, 3, 1, 3], filter_in_sizes=[1, 1, 1, 3, 3], stride=1, padding="VALID", expected=expected_output) self._VerifyValues( tensor_in_sizes=[1, 2, 1, 3, 3], filter_in_sizes=[1, 1, 1, 3, 3], stride=1, padding="VALID", expected=expected_output) self._VerifyValues( tensor_in_sizes=[1, 1, 2, 3, 3], filter_in_sizes=[1, 1, 1, 3, 3], stride=1, padding="VALID", expected=expected_output) # Expected values computed using scipy's correlate function. def testConv3D2x2x2Filter(self): expected_output = [ 3.77199074, 3.85069444, 3.92939815, 4.2650463, 4.35763889, 4.45023148, 6.73032407, 6.89236111, 7.05439815, 7.22337963, 7.39930556, 7.57523148, 9.68865741, 9.93402778, 10.17939815, 10.18171296, 10.44097222, 10.70023148 ] # expected_shape = [1, 3, 1, 2, 5] self._VerifyValues( tensor_in_sizes=[1, 4, 2, 3, 3], # b, z, y, x, fin filter_in_sizes=[2, 2, 2, 3, 3], # z, y, x, fin, fout stride=1, padding="VALID", expected=expected_output) def testConv3DStrides(self): expected_output = [ 0.06071429, 0.08988095, 0.10238095, 0.11488095, 0.12738095, 0.13988095, 0.08452381, 0.26071429, 0.35238095, 0.36488095, 0.37738095, 0.38988095, 0.40238095, 0.23452381, 0.46071429, 0.61488095, 0.62738095, 0.63988095, 0.65238095, 0.66488095, 0.38452381, 1.12738095, 1.48988095, 1.50238095, 1.51488095, 1.52738095, 1.53988095, 0.88452381, 1.32738095, 1.75238095, 1.76488095, 1.77738095, 1.78988095, 1.80238095, 1.03452381, 1.52738095, 2.01488095, 2.02738095, 2.03988095, 2.05238095, 2.06488095, 1.18452381, 2.19404762, 2.88988095, 2.90238095, 2.91488095, 2.92738095, 2.93988095, 1.68452381, 2.39404762, 3.15238095, 3.16488095, 3.17738095, 3.18988095, 3.20238095, 1.83452381, 2.59404762, 3.41488095, 3.42738095, 3.43988095, 3.45238095, 3.46488095, 1.98452381 ] self._VerifyValues( tensor_in_sizes=[1, 5, 8, 7, 1], filter_in_sizes=[1, 2, 3, 1, 1], stride=[2, 3, 1], # different stride for each spatial dimension padding="SAME", expected=expected_output) def testConv3D2x2x2FilterStride2(self): expected_output = [ 3.77199074, 3.85069444, 3.92939815, 9.68865741, 9.93402778, 10.17939815 ] self._VerifyValues( tensor_in_sizes=[1, 4, 2, 3, 3], filter_in_sizes=[2, 2, 2, 3, 3], stride=2, padding="VALID", expected=expected_output) def testConv3DStride3(self): expected_output = [ 1.51140873, 1.57167659, 1.63194444, 1.56349206, 1.62673611, 1.68998016, 1.6155754, 1.68179563, 1.74801587, 1.9280754, 2.01215278, 2.09623016, 1.98015873, 2.0672123, 2.15426587, 2.03224206, 2.12227183, 2.21230159, 4.4280754, 4.65500992, 4.88194444, 4.48015873, 4.71006944, 4.93998016, 4.53224206, 4.76512897, 4.99801587, 4.84474206, 5.09548611, 5.34623016, 4.8968254, 5.15054563, 5.40426587, 4.94890873, 5.20560516, 5.46230159 ] self._VerifyValues( tensor_in_sizes=[1, 6, 7, 8, 2], filter_in_sizes=[3, 2, 1, 2, 3], stride=3, padding="VALID", expected=expected_output) def testConv3D2x2x2FilterStride2Same(self): expected_output = [ 3.77199074, 3.85069444, 3.92939815, 2.0162037, 2.06597222, 2.11574074, 9.68865741, 9.93402778, 10.17939815, 4.59953704, 4.73263889, 4.86574074 ] self._VerifyValues( tensor_in_sizes=[1, 4, 2, 3, 3], filter_in_sizes=[2, 2, 2, 3, 3], stride=2, padding="SAME", expected=expected_output) def testKernelSmallerThanStride(self): expected_output = [ 0.03703704, 0.11111111, 0.25925926, 0.33333333, 0.7037037, 0.77777778, 0.92592593, 1. ] self._VerifyValues( tensor_in_sizes=[1, 3, 3, 3, 1], filter_in_sizes=[1, 1, 1, 1, 1], stride=2, padding="SAME", expected=expected_output) self._VerifyValues( tensor_in_sizes=[1, 3, 3, 3, 1], filter_in_sizes=[1, 1, 1, 1, 1], stride=2, padding="VALID", expected=expected_output) expected_output = [ 0.54081633, 0.58017493, 0.28061224, 0.81632653, 0.85568513, 0.40306122, 0.41873178, 0.4340379, 0.19642857, 2.46938776, 2.50874636, 1.1377551, 2.74489796, 2.78425656, 1.26020408, 1.16873178, 1.1840379, 0.51785714, 1.09511662, 1.10604956, 0.44642857, 1.17164723, 1.18258017, 0.47704082, 0.3691691, 0.37244898, 0.125 ] self._VerifyValues( tensor_in_sizes=[1, 7, 7, 7, 1], filter_in_sizes=[2, 2, 2, 1, 1], stride=3, padding="SAME", expected=expected_output) expected_output = [ 0.540816, 0.580175, 0.816327, 0.855685, 2.469388, 2.508746, 2.744898, 2.784257 ] self._VerifyValues( tensor_in_sizes=[1, 7, 7, 7, 1], filter_in_sizes=[2, 2, 2, 1, 1], stride=3, padding="VALID", expected=expected_output) def testKernelSizeMatchesInputSize(self): self._VerifyValues( tensor_in_sizes=[1, 2, 1, 2, 1], filter_in_sizes=[2, 1, 2, 1, 2], stride=1, padding="VALID", expected=[1.5625, 1.875]) def _ConstructAndTestGradientForConfig( self, batch, input_shape, filter_shape, in_depth, out_depth, stride, padding, test_input, data_format, use_gpu): input_planes, input_rows, input_cols = input_shape filter_planes, filter_rows, filter_cols = filter_shape input_shape = [batch, input_planes, input_rows, input_cols, in_depth] filter_shape = [ filter_planes, filter_rows, filter_cols, in_depth, out_depth ] if isinstance(stride, collections.Iterable): strides = [1] + list(stride) + [1] else: strides = [1, stride, stride, stride, 1] if padding == "VALID": output_planes = int( math.ceil((input_planes - filter_planes + 1.0) / strides[1])) output_rows = int( math.ceil((input_rows - filter_rows + 1.0) / strides[2])) output_cols = int( math.ceil((input_cols - filter_cols + 1.0) / strides[3])) else: output_planes = int(math.ceil(float(input_planes) / strides[1])) output_rows = int(math.ceil(float(input_rows) / strides[2])) output_cols = int(math.ceil(float(input_cols) / strides[3])) output_shape = [batch, output_planes, output_rows, output_cols, out_depth] input_size = 1 for x in input_shape: input_size *= x filter_size = 1 for x in filter_shape: filter_size *= x input_data = [x * 1.0 / input_size for x in range(0, input_size)] filter_data = [x * 1.0 / filter_size for x in range(0, filter_size)] for data_type in self._DtypesToTest(use_gpu=use_gpu): # TODO(mjanusz): Modify gradient_checker to also provide max relative # error and synchronize the tolerance levels between the tests for forward # and backward computations. if data_type == dtypes.float64: tolerance = 1e-8 elif data_type == dtypes.float32: tolerance = 5e-3 elif data_type == dtypes.float16: tolerance = 1e-3 with self.test_session(use_gpu=use_gpu): orig_input_tensor = constant_op.constant( input_data, shape=input_shape, dtype=data_type, name="input") filter_tensor = constant_op.constant( filter_data, shape=filter_shape, dtype=data_type, name="filter") if data_format == "NCDHW": input_tensor = test_util.NHWCToNCHW(orig_input_tensor) new_strides = test_util.NHWCToNCHW(strides) else: input_tensor = orig_input_tensor new_strides = strides conv = nn_ops.conv3d( input_tensor, filter_tensor, new_strides, padding, data_format=data_format, name="conv") if data_format == "NCDHW": conv = test_util.NCHWToNHWC(conv) if test_input: jacob_t, jacob_n = gradient_checker.compute_gradient( orig_input_tensor, input_shape, conv, output_shape) else: jacob_t, jacob_n = gradient_checker.compute_gradient( filter_tensor, filter_shape, conv, output_shape) if data_type != dtypes.float16: reference_jacob_t = jacob_t err = np.fabs(jacob_t - jacob_n).max() else: # Compare fp16 theoretical gradients to fp32 theoretical gradients, # since fp16 numerical gradients are too imprecise. err = np.fabs(jacob_t - reference_jacob_t).max() print("conv3d gradient error = ", err) self.assertLess(err, tolerance) def ConstructAndTestGradient(self, **kwargs): for data_format, use_gpu in GetTestConfigs(): self._ConstructAndTestGradientForConfig(data_format=data_format, use_gpu=use_gpu, **kwargs) def testInputGradientValidPaddingStrideOne(self): self.ConstructAndTestGradient( batch=2, input_shape=(3, 5, 4), filter_shape=(3, 3, 3), in_depth=2, out_depth=3, stride=1, padding="VALID", test_input=True) def testFilterGradientValidPaddingStrideOne(self): self.ConstructAndTestGradient( batch=4, input_shape=(4, 6, 5), filter_shape=(2, 2, 2), in_depth=2, out_depth=3, stride=1, padding="VALID", test_input=False) def testInputGradientValidPaddingStrideTwo(self): self.ConstructAndTestGradient( batch=2, input_shape=(6, 3, 5), filter_shape=(3, 3, 3), in_depth=2, out_depth=3, stride=2, padding="VALID", test_input=True) def testFilterGradientValidPaddingStrideTwo(self): self.ConstructAndTestGradient( batch=2, input_shape=(7, 6, 5), filter_shape=(2, 2, 2), in_depth=2, out_depth=3, stride=2, padding="VALID", test_input=False) def testInputGradientValidPaddingStrideThree(self): self.ConstructAndTestGradient( batch=2, input_shape=(3, 7, 6), filter_shape=(3, 3, 3), in_depth=2, out_depth=3, stride=3, padding="VALID", test_input=True) def testFilterGradientValidPaddingStrideThree(self): self.ConstructAndTestGradient( batch=2, input_shape=(4, 4, 7), filter_shape=(4, 4, 4), in_depth=2, out_depth=3, stride=3, padding="VALID", test_input=False) def testInputGradientSamePaddingStrideOne(self): self.ConstructAndTestGradient( batch=2, input_shape=(3, 2, 2), filter_shape=(3, 2, 1), in_depth=2, out_depth=1, stride=1, padding="SAME", test_input=True) def testFilterGradientSamePaddingStrideOne(self): self.ConstructAndTestGradient( batch=2, input_shape=(3, 6, 5), filter_shape=(2, 2, 2), in_depth=2, out_depth=3, stride=1, padding="SAME", test_input=False) def testInputGradientSamePaddingStrideTwo(self): self.ConstructAndTestGradient( batch=2, input_shape=(6, 3, 4), filter_shape=(3, 3, 3), in_depth=2, out_depth=3, stride=2, padding="SAME", test_input=True) def testFilterGradientSamePaddingStrideTwo(self): self.ConstructAndTestGradient( batch=4, input_shape=(7, 3, 5), filter_shape=(2, 2, 2), in_depth=2, out_depth=3, stride=2, padding="SAME", test_input=False) def testInputGradientSamePaddingStrideThree(self): self.ConstructAndTestGradient( batch=2, input_shape=(9, 3, 6), filter_shape=(3, 3, 3), in_depth=2, out_depth=3, stride=3, padding="SAME", test_input=True) def testFilterGradientSamePaddingStrideThree(self): self.ConstructAndTestGradient( batch=2, input_shape=(9, 4, 7), filter_shape=(4, 4, 4), in_depth=2, out_depth=3, stride=3, padding="SAME", test_input=False) def testInputGradientSamePaddingDifferentStrides(self): self.ConstructAndTestGradient( batch=1, input_shape=(5, 8, 7), filter_shape=(1, 2, 3), in_depth=2, out_depth=3, stride=[2, 3, 1], padding="SAME", test_input=True) def testFilterGradientKernelSizeMatchesInputSize(self): self.ConstructAndTestGradient( batch=2, input_shape=(5, 4, 3), filter_shape=(5, 4, 3), in_depth=2, out_depth=3, stride=1, padding="VALID", test_input=False) def testInputGradientKernelSizeMatchesInputSize(self): self.ConstructAndTestGradient( batch=2, input_shape=(5, 4, 3), filter_shape=(5, 4, 3), in_depth=2, out_depth=3, stride=1, padding="VALID", test_input=True) def disabledtestFilterGradientSamePaddingDifferentStrides(self): self.ConstructAndTestGradient( batch=1, input_shape=(5, 8, 7), filter_shape=(1, 2, 3), in_depth=2, out_depth=3, stride=[2, 3, 1], padding="SAME", test_input=False)
10,361
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10
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "ms", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "Q", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "For", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "get_for_model", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "objects", "value": {"_type": "Name", "_fields": {"id": "ContentType", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "ctype", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "If", "_fields": {"body": [{"_type": "AugAssign", "_fields": {"op": {"_type": "BitOr", "_fields": {}}, "value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "Q", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "content_type", "value": {"_type": "Name", "_fields": {"id": "ctype", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "object_id", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "pk", "value": {"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Load", "_fields": {}}}}}}}}]}}, "target": {"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Store", "_fields": {}}}}}}], "test": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "Model", "value": {"_type": "Name", "_fields": {"id": "models", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Name", "_fields": {"id": "isinstance", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, "orelse": [{"_type": "AugAssign", "_fields": {"op": {"_type": "BitOr", "_fields": {}}, "value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "Q", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "content_type", "value": {"_type": "Name", "_fields": {"id": "ctype", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "target": {"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Store", "_fields": {}}}}}}]}}], "iter": {"_type": "Name", "_fields": {"id": "ms", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "m", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "filter", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "get_for_models", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def get_for_models(self, ms): qs = Q() for m in ms: ctype = ContentType.objects.get_for_model(m) if isinstance(m, models.Model): qs |= Q(content_type=ctype, object_id=m.pk) else: qs |= Q(content_type=ctype) return self.filter(qs)
10,362
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10
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def _SetupValuesForDevice(self, tensor_in_sizes, filter_in_sizes, stride, padding, data_format, dtype, use_gpu): total_size_1 = 1 total_size_2 = 1 for s in tensor_in_sizes: total_size_1 *= s for s in filter_in_sizes: total_size_2 *= s # Initializes the input tensor with array containing numbers from 0 to 1. # We keep the input tensor values fairly small to avoid overflowing float16 # during the conv3d. x1 = [f * 1.0 / total_size_1 for f in range(1, total_size_1 + 1)] x2 = [f * 1.0 / total_size_2 for f in range(1, total_size_2 + 1)] with self.test_session(use_gpu=use_gpu): t1 = constant_op.constant(x1, shape=tensor_in_sizes, dtype=dtype) t2 = constant_op.constant(x2, shape=filter_in_sizes, dtype=dtype) if isinstance(stride, collections.Iterable): strides = [1] + list(stride) + [1] else: strides = [1, stride, stride, stride, 1] if data_format == "NCDHW": t1 = test_util.NHWCToNCHW(t1) strides = test_util.NHWCToNCHW(strides) conv = nn_ops.conv3d(t1, t2, strides, padding=padding, data_format=data_format) if data_format == "NCDHW": conv = test_util.NCHWToNHWC(conv) return conv
10,363
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9
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def _DtypesToTest(self, use_gpu): if use_gpu: if not test_util.CudaSupportsHalfMatMulAndConv(): return [dtypes.float32] else: # It is important that float32 comes before float16 here, # as we will be using its gradients as reference for fp16 gradients. return [dtypes.float32, dtypes.float16] else: return [dtypes.float64, dtypes.float32, dtypes.float16]
10,364
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7
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def testConv3D1x1x1Filter(self): expected_output = [ 0.18518519, 0.22222222, 0.25925926, 0.40740741, 0.5, 0.59259259, 0.62962963, 0.77777778, 0.92592593, 0.85185185, 1.05555556, 1.25925926, 1.07407407, 1.33333333, 1.59259259, 1.2962963, 1.61111111, 1.92592593 ] # These are equivalent to the Conv2D1x1 case. self._VerifyValues( tensor_in_sizes=[1, 2, 3, 1, 3], filter_in_sizes=[1, 1, 1, 3, 3], stride=1, padding="VALID", expected=expected_output) self._VerifyValues( tensor_in_sizes=[1, 2, 1, 3, 3], filter_in_sizes=[1, 1, 1, 3, 3], stride=1, padding="VALID", expected=expected_output) self._VerifyValues( tensor_in_sizes=[1, 1, 2, 3, 3], filter_in_sizes=[1, 1, 1, 3, 3], stride=1, padding="VALID", expected=expected_output)
10,365
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11
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def _VerifyValues(self, tensor_in_sizes, filter_in_sizes, stride, padding, expected): results = [] for data_format, use_gpu in GetTestConfigs(): for dtype in self._DtypesToTest(use_gpu): result = self._SetupValuesForDevice( tensor_in_sizes, filter_in_sizes, stride, padding, data_format, dtype, use_gpu=use_gpu) results.append(result) with self.test_session() as sess: values = sess.run(results) for value in values: print("expected = ", expected) print("actual = ", value) tol = 1e-6 if value.dtype == np.float16: tol = 1e-3 self.assertAllClose(expected, value.flatten(), atol=tol, rtol=tol)
10,366
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7
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def testKernelSmallerThanStride(self): expected_output = [ 0.03703704, 0.11111111, 0.25925926, 0.33333333, 0.7037037, 0.77777778, 0.92592593, 1. ] self._VerifyValues( tensor_in_sizes=[1, 3, 3, 3, 1], filter_in_sizes=[1, 1, 1, 1, 1], stride=2, padding="SAME", expected=expected_output) self._VerifyValues( tensor_in_sizes=[1, 3, 3, 3, 1], filter_in_sizes=[1, 1, 1, 1, 1], stride=2, padding="VALID", expected=expected_output) expected_output = [ 0.54081633, 0.58017493, 0.28061224, 0.81632653, 0.85568513, 0.40306122, 0.41873178, 0.4340379, 0.19642857, 2.46938776, 2.50874636, 1.1377551, 2.74489796, 2.78425656, 1.26020408, 1.16873178, 1.1840379, 0.51785714, 1.09511662, 1.10604956, 0.44642857, 1.17164723, 1.18258017, 0.47704082, 0.3691691, 0.37244898, 0.125 ] self._VerifyValues( tensor_in_sizes=[1, 7, 7, 7, 1], filter_in_sizes=[2, 2, 2, 1, 1], stride=3, padding="SAME", expected=expected_output) expected_output = [ 0.540816, 0.580175, 0.816327, 0.855685, 2.469388, 2.508746, 2.744898, 2.784257 ] self._VerifyValues( tensor_in_sizes=[1, 7, 7, 7, 1], filter_in_sizes=[2, 2, 2, 1, 1], stride=3, padding="VALID", expected=expected_output)
10,367
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def _ConstructAndTestGradientForConfig( self, batch, input_shape, filter_shape, in_depth, out_depth, stride, padding, test_input, data_format, use_gpu): input_planes, input_rows, input_cols = input_shape filter_planes, filter_rows, filter_cols = filter_shape input_shape = [batch, input_planes, input_rows, input_cols, in_depth] filter_shape = [ filter_planes, filter_rows, filter_cols, in_depth, out_depth ] if isinstance(stride, collections.Iterable): strides = [1] + list(stride) + [1] else: strides = [1, stride, stride, stride, 1] if padding == "VALID": output_planes = int( math.ceil((input_planes - filter_planes + 1.0) / strides[1])) output_rows = int( math.ceil((input_rows - filter_rows + 1.0) / strides[2])) output_cols = int( math.ceil((input_cols - filter_cols + 1.0) / strides[3])) else: output_planes = int(math.ceil(float(input_planes) / strides[1])) output_rows = int(math.ceil(float(input_rows) / strides[2])) output_cols = int(math.ceil(float(input_cols) / strides[3])) output_shape = [batch, output_planes, output_rows, output_cols, out_depth] input_size = 1 for x in input_shape: input_size *= x filter_size = 1 for x in filter_shape: filter_size *= x input_data = [x * 1.0 / input_size for x in range(0, input_size)] filter_data = [x * 1.0 / filter_size for x in range(0, filter_size)] for data_type in self._DtypesToTest(use_gpu=use_gpu): # TODO(mjanusz): Modify gradient_checker to also provide max relative # error and synchronize the tolerance levels between the tests for forward # and backward computations. if data_type == dtypes.float64: tolerance = 1e-8 elif data_type == dtypes.float32: tolerance = 5e-3 elif data_type == dtypes.float16: tolerance = 1e-3 with self.test_session(use_gpu=use_gpu): orig_input_tensor = constant_op.constant( input_data, shape=input_shape, dtype=data_type, name="input") filter_tensor = constant_op.constant( filter_data, shape=filter_shape, dtype=data_type, name="filter") if data_format == "NCDHW": input_tensor = test_util.NHWCToNCHW(orig_input_tensor) new_strides = test_util.NHWCToNCHW(strides) else: input_tensor = orig_input_tensor new_strides = strides conv = nn_ops.conv3d( input_tensor, filter_tensor, new_strides, padding, data_format=data_format, name="conv") if data_format == "NCDHW": conv = test_util.NCHWToNHWC(conv) if test_input: jacob_t, jacob_n = gradient_checker.compute_gradient( orig_input_tensor, input_shape, conv, output_shape) else: jacob_t, jacob_n = gradient_checker.compute_gradient( filter_tensor, filter_shape, conv, output_shape) if data_type != dtypes.float16: reference_jacob_t = jacob_t err = np.fabs(jacob_t - jacob_n).max() else: # Compare fp16 theoretical gradients to fp32 theoretical gradients, # since fp16 numerical gradients are too imprecise. err = np.fabs(jacob_t - reference_jacob_t).max() print("conv3d gradient error = ", err) self.assertLess(err, tolerance)
10,368
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13
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class sale_order(osv.Model): _inherit = "sale.order" def _cart_find_product_line(self, cr, uid, ids, product_id=None, line_id=None, context=None, **kwargs): line_ids = super(sale_order, self)._cart_find_product_line(cr, uid, ids, product_id, line_id, context=context) if line_id: return line_ids for so in self.browse(cr, uid, ids, context=context): domain = [('id', 'in', line_ids)] if context.get("event_ticket_id"): domain += [('event_ticket_id', '=', context.get("event_ticket_id"))] return self.pool.get('sale.order.line').search(cr, SUPERUSER_ID, domain, context=context) def _website_product_id_change(self, cr, uid, ids, order_id, product_id, qty=0, line_id=None, context=None): values = super(sale_order,self)._website_product_id_change(cr, uid, ids, order_id, product_id, qty=qty, line_id=line_id, context=None) event_ticket_id = None if context.get("event_ticket_id"): event_ticket_id = context.get("event_ticket_id") elif line_id: line = self.pool.get('sale.order.line').browse(cr, SUPERUSER_ID, line_id, context=context) if line.event_ticket_id: event_ticket_id = line.event_ticket_id.id else: product = self.pool.get('product.product').browse(cr, uid, product_id, context=context) if product.event_ticket_ids: event_ticket_id = product.event_ticket_ids[0].id if event_ticket_id: ticket = self.pool.get('event.event.ticket').browse(cr, uid, event_ticket_id, context=context) if product_id != ticket.product_id.id: raise osv.except_osv(_('Error!'),_("The ticket doesn't match with this product.")) values['product_id'] = ticket.product_id.id values['event_id'] = ticket.event_id.id values['event_ticket_id'] = ticket.id values['price_unit'] = ticket.price values['name'] = "%s\n%s" % (ticket.event_id.display_name, ticket.name) return values
10,369
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11
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def _cart_find_product_line(self, cr, uid, ids, product_id=None, line_id=None, context=None, **kwargs): line_ids = super(sale_order, self)._cart_find_product_line(cr, uid, ids, product_id, line_id, context=context) if line_id: return line_ids for so in self.browse(cr, uid, ids, context=context): domain = [('id', 'in', line_ids)] if context.get("event_ticket_id"): domain += [('event_ticket_id', '=', context.get("event_ticket_id"))] return self.pool.get('sale.order.line').search(cr, SUPERUSER_ID, domain, context=context)
10,370
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12
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def _website_product_id_change(self, cr, uid, ids, order_id, product_id, qty=0, line_id=None, context=None): values = super(sale_order,self)._website_product_id_change(cr, uid, ids, order_id, product_id, qty=qty, line_id=line_id, context=None) event_ticket_id = None if context.get("event_ticket_id"): event_ticket_id = context.get("event_ticket_id") elif line_id: line = self.pool.get('sale.order.line').browse(cr, SUPERUSER_ID, line_id, context=context) if line.event_ticket_id: event_ticket_id = line.event_ticket_id.id else: product = self.pool.get('product.product').browse(cr, uid, product_id, context=context) if product.event_ticket_ids: event_ticket_id = product.event_ticket_ids[0].id if event_ticket_id: ticket = self.pool.get('event.event.ticket').browse(cr, uid, event_ticket_id, context=context) if product_id != ticket.product_id.id: raise osv.except_osv(_('Error!'),_("The ticket doesn't match with this product.")) values['product_id'] = ticket.product_id.id values['event_id'] = ticket.event_id.id values['event_ticket_id'] = ticket.id values['price_unit'] = ticket.price values['name'] = "%s\n%s" % (ticket.event_id.display_name, ticket.name) return values
10,371
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8
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "artist_name", "annotation": null, "type_comment": null}}, {"_type": "arg", "_fields": {"arg": "song_title", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Dict", "_fields": {"keys": [{"_type": "Constant", "_fields": {"kind": null, "value": "art"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "mus"}}], "values": [{"_type": "Name", "_fields": {"id": "artist_name", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "song_title", "ctx": {"_type": "Load", "_fields": {}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "params", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "API_LYRIC_SEARCH_URL", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "get", "value": {"_type": "Name", "_fields": {"id": "requests", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "params", "value": {"_type": "Name", "_fields": {"id": "params", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "response", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "raise_for_status", "value": {"_type": "Name", "_fields": {"id": "response", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "json", "value": {"_type": "Name", "_fields": {"id": "response", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}], "func": {"_type": "Name", "_fields": {"id": "SearchResult", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}], "name": "find", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def find(artist_name, song_title): params = { 'art': artist_name, 'mus': song_title } response = requests.get(API_LYRIC_SEARCH_URL, params=params) response.raise_for_status() return SearchResult(response.json())
10,372
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class Song(object): def __init__(self, song): self.id = song['id'] self.name = song.get('name', None) self.language = song['lang'] self.url = song['url'] self.lyric = song['text'] self.is_translation = False if not self.name: self.is_translation = True # For translations, the song title comes with the lyric body # followed by one or more empty lines. Here we get the title # and remove the first line and any following empty lines. self.name = self.get_title_from_lyric(self.lyric) self.lyric = self.remove_title(self.lyric) def get_title_from_lyric(self, lyric): lines = lyric.splitlines() title = re.sub(r'\[|\]|\n', '', lines[0]).strip() return title def remove_title(self, lyric): lines = lyric.splitlines() lines.pop(0) self.remove_initial_blank_lines(lines) return "\n".join(lines) def remove_initial_blank_lines(self, lines): if lines[0] and lines[0] not in ['\n', '\r\n']: return lines.pop(0) self.remove_initial_blank_lines(lines)
10,373
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def __init__(self, song): self.id = song['id'] self.name = song.get('name', None) self.language = song['lang'] self.url = song['url'] self.lyric = song['text'] self.is_translation = False if not self.name: self.is_translation = True # For translations, the song title comes with the lyric body # followed by one or more empty lines. Here we get the title # and remove the first line and any following empty lines. self.name = self.get_title_from_lyric(self.lyric) self.lyric = self.remove_title(self.lyric)
10,374
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9
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class SearchResult(object): def __init__(self, result): self.status = result['type'] if self.is_not_found(): return song = result['mus'][0] artist = result['art'] translations = song.get('translate', []) self.artist = Artist(artist) self.song = Song(song) self.translations = [Song(translation) for translation in translations] def is_not_found(self): return self.status in (STATUS_ARTIST_NOT_FOUND, STATUS_SONG_NOT_FOUND) def get_translation_to(self, language): for translation in self.translations: if translation.language == LANGUAGES[language]: return translation return None
10,375
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7
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def __init__(self, result): self.status = result['type'] if self.is_not_found(): return song = result['mus'][0] artist = result['art'] translations = song.get('translate', []) self.artist = Artist(artist) self.song = Song(song) self.translations = [Song(translation) for translation in translations]
10,376
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9
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"Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "select po.name as pos,po.date_order,ru.name as user,po.state,rc.name from pos_order as po,res_users as ru,res_company as rc where to_char(date_trunc('day',po.date_order),'YYYY-MM-DD')::date = current_date and po.company_id=rc.id and po.user_id=ru.id and po.user_id IN %s"}}, {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "ids", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Name", "_fields": {"id": "tuple", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}]}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "execute", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "cr", "value": 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"attr": "rml_parse", "value": {"_type": "Name", "_fields": {"id": "report_sxw", "ctx": {"_type": "Load", "_fields": {}}}}}}], "keywords": [], "type_params": [], "decorator_list": []}}], "type_ignores": []}}
class pos_sales_user_today(report_sxw.rml_parse): def __init__(self, cr, uid, name, context): super(pos_sales_user_today, self).__init__(cr, uid, name, context=context) self.total = 0.0 self.localcontext.update({ 'time': time, 'get_data':self._get_data, }) def _get_data(self, form): data={} ids = form['user_id'] self.cr.execute("select po.name as pos,po.date_order,ru.name as user,po.state,rc.name " \ "from pos_order as po,res_users as ru,res_company as rc " \ "where to_char(date_trunc('day',po.date_order),'YYYY-MM-DD')::date = current_date " \ "and po.company_id=rc.id and po.user_id=ru.id and po.user_id IN %s", (tuple(ids), )) data = self.cr.dictfetchall() return data
10,377
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8
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def __init__(self, cr, uid, name, context): super(pos_sales_user_today, self).__init__(cr, uid, name, context=context) self.total = 0.0 self.localcontext.update({ 'time': time, 'get_data':self._get_data, })
10,378
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14
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def prepare(config_dict, testdir, server_match, client_match): libs, libs2 = collect_testlibs(config_dict, server_match, client_match) libs.extend(libs2) def prepares(): for lib in libs: pre = lib.get('prepare') if pre: yield pre, lib['workdir'] def files(): for lib in libs: workdir = os.path.join(testdir, lib['workdir']) for c in lib['command']: if not c.startswith('-'): p = os.path.join(workdir, c) if not os.path.exists(p): yield os.path.split(p) def make(p): d, f = p with open(os.devnull, 'w') as devnull: return subprocess.Popen(['make', f], cwd=d, stderr=devnull) for pre, d in prepares(): subprocess.Popen(pre, cwd=d).wait() for p in list(map(make, set(files()))): p.wait() return True
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8
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def _get_data(self, form): data={} ids = form['user_id'] self.cr.execute("select po.name as pos,po.date_order,ru.name as user,po.state,rc.name " \ "from pos_order as po,res_users as ru,res_company as rc " \ "where to_char(date_trunc('day',po.date_order),'YYYY-MM-DD')::date = current_date " \ "and po.company_id=rc.id and po.user_id=ru.id and po.user_id IN %s", (tuple(ids), )) data = self.cr.dictfetchall() return data
10,380
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9
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Return", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "CodecInfo", "value": {"_type": "Name", "_fields": {"id": "codecs", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "name", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "cp775"}}}}, {"_type": "keyword", "_fields": {"arg": "encode", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "encode", "value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "Codec", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}}}, {"_type": "keyword", "_fields": {"arg": "decode", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "decode", "value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "Codec", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}}}}}, {"_type": "keyword", "_fields": {"arg": "incrementalencoder", "value": {"_type": "Name", "_fields": {"id": "IncrementalEncoder", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "incrementaldecoder", "value": {"_type": "Name", "_fields": {"id": "IncrementalDecoder", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "streamreader", "value": {"_type": "Name", "_fields": {"id": "StreamReader", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "streamwriter", "value": {"_type": "Name", "_fields": {"id": "StreamWriter", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}}}], "name": "getregentry", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def getregentry(): return codecs.CodecInfo( name='cp775', encode=Codec().encode, decode=Codec().decode, incrementalencoder=IncrementalEncoder, incrementaldecoder=IncrementalDecoder, streamreader=StreamReader, streamwriter=StreamWriter, )
10,381
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13
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "For", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "testdir", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "workdir"}}, "value": {"_type": "Name", "_fields": {"id": "lib", "ctx": {"_type": "Load", "_fields": {}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "path", "value": {"_type": "Name", "_fields": {"id": "os", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "workdir", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "For", "_fields": {"body": [{"_type": "If", "_fields": {"body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "workdir", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "c", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "path", "value": {"_type": "Name", "_fields": {"id": "os", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "If", "_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Yield", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "split", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "path", "value": {"_type": "Name", "_fields": {"id": "os", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "p", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "exists", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "path", "value": {"_type": "Name", "_fields": {"id": "os", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}, "orelse": []}}], "test": {"_type": "UnaryOp", "_fields": {"op": {"_type": "Not", "_fields": {}}, "operand": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": "-"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "startswith", "value": {"_type": "Name", "_fields": {"id": "c", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, "orelse": []}}], "iter": {"_type": "Subscript", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "slice": {"_type": "Constant", "_fields": {"kind": null, "value": "command"}}, "value": {"_type": "Name", "_fields": {"id": "lib", "ctx": {"_type": "Load", "_fields": {}}}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "c", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "iter": {"_type": "Name", "_fields": {"id": "libs", "ctx": {"_type": "Load", "_fields": {}}}}, "orelse": [], "target": {"_type": "Name", "_fields": {"id": "lib", "ctx": {"_type": "Store", "_fields": {}}}}, "type_comment": null}}], "name": "files", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def files(): for lib in libs: workdir = os.path.join(testdir, lib['workdir']) for c in lib['command']: if not c.startswith('-'): p = os.path.join(workdir, c) if not os.path.exists(p): yield os.path.split(p)
10,382
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9
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def test_op_to_state(): assert operators_to_state(XOp) == XKet() assert operators_to_state(PxOp) == PxKet() assert operators_to_state(Operator) == Ket() assert state_to_operators(operators_to_state(XOp("Q"))) == XOp("Q") assert state_to_operators(operators_to_state(XOp())) == XOp() raises(NotImplementedError, lambda: operators_to_state(XKet))
10,383
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9
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{"_type": "Load", "_fields": {}}}}, "keywords": []}}, "comparators": [{"_type": "Set", "_fields": {"elts": [{"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "J2Op", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}, {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "JzOp", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": []}}]}}]}}}}], "name": "test_spin", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def test_spin(): assert operators_to_state({J2Op, JxOp}) == JxKet() assert operators_to_state({J2Op, JyOp}) == JyKet() assert operators_to_state({J2Op, JzOp}) == JzKet() assert operators_to_state({J2Op(), JxOp()}) == JxKet() assert operators_to_state({J2Op(), JyOp()}) == JyKet() assert operators_to_state({J2Op(), JzOp()}) == JzKet() assert state_to_operators(JxKet) == {J2Op(), JxOp()} assert state_to_operators(JyKet) == {J2Op(), JyOp()} assert state_to_operators(JzKet) == {J2Op(), JzOp()} assert state_to_operators(JxBra) == {J2Op(), JxOp()} assert state_to_operators(JyBra) == {J2Op(), JyOp()} assert state_to_operators(JzBra) == {J2Op(), JzOp()} assert state_to_operators(JxKet()) == {J2Op(), JxOp()} assert state_to_operators(JyKet()) == {J2Op(), JyOp()} assert state_to_operators(JzKet()) == {J2Op(), JzOp()} assert state_to_operators(JxBra()) == {J2Op(), JxOp()} assert state_to_operators(JyBra()) == {J2Op(), JyOp()} assert state_to_operators(JzBra()) == {J2Op(), JzOp()}
10,384
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9
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def test_state_to_op(): assert state_to_operators(XKet) == XOp() assert state_to_operators(PxKet) == PxOp() assert state_to_operators(XBra) == XOp() assert state_to_operators(PxBra) == PxOp() assert state_to_operators(Ket) == Operator() assert state_to_operators(Bra) == Operator() assert operators_to_state(state_to_operators(XKet("test"))) == XKet("test") assert operators_to_state(state_to_operators(XBra("test"))) == XKet("test") assert operators_to_state(state_to_operators(XKet())) == XKet() assert operators_to_state(state_to_operators(XBra())) == XKet() raises(NotImplementedError, lambda: state_to_operators(XOp))
10,385
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10
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"_fields": {}}}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "tag", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "hairy"}}}}]}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Lambda", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "obj", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": {"_type": "Tuple", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tag", "value": {"_type": "Name", "_fields": {"id": "obj", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "model_class", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "content_type", "value": {"_type": "Name", "_fields": {"id": "obj", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "object_id", "value": {"_type": "Name", "_fields": {"id": "obj", "ctx": {"_type": "Load", "_fields": {}}}}}}]}}}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "comp_func", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}], "name": "setUp", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def setUp(self): self.lion = Animal.objects.create( common_name="Lion", latin_name="Panthera leo") self.platypus = Animal.objects.create( common_name="Platypus", latin_name="Ornithorhynchus anatinus") Vegetable.objects.create(name="Eggplant", is_yucky=True) self.bacon = Vegetable.objects.create(name="Bacon", is_yucky=False) self.quartz = Mineral.objects.create(name="Quartz", hardness=7) # Tagging stuff. self.bacon.tags.create(tag="fatty") self.bacon.tags.create(tag="salty") self.lion.tags.create(tag="yellow") self.lion.tags.create(tag="hairy") # Original list of tags: self.comp_func = lambda obj: ( obj.tag, obj.content_type.model_class(), obj.object_id )
10,386
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10
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"_fields": {"arg": "manualpk__id", "value": {"_type": "Constant", "_fields": {"kind": null, "value": 1}}}}]}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "filter", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "objects", "value": {"_type": "Name", "_fields": {"id": "TaggedItem", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}, "keywords": []}}, "targets": [{"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": [{"_type": "Constant", "_fields": {"kind": null, "value": "hairy"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "mpk"}}, {"_type": "Constant", "_fields": {"kind": null, "value": "yellow"}}]}}, {"_type": "Lambda", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "x", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tag", "value": {"_type": "Name", "_fields": {"id": "x", "ctx": {"_type": "Load", "_fields": {}}}}}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertQuerysetEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_query_content_object", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def test_query_content_object(self): qs = TaggedItem.objects.filter( animal__isnull=False).order_by('animal__common_name', 'tag') self.assertQuerysetEqual( qs, ["<TaggedItem: hairy>", "<TaggedItem: yellow>"] ) mpk = ManualPK.objects.create(id=1) mpk.tags.create(tag='mpk') qs = TaggedItem.objects.filter( Q(animal__isnull=False) | Q(manualpk__id=1)).order_by('tag') self.assertQuerysetEqual( qs, ["hairy", "mpk", "yellow"], lambda x: x.tag)
10,387
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9
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"_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "t1", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "t2", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "add", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 1}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertNumQueries", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "optional_vars": null}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "content_object", "value": {"_type": "Name", "_fields": {"id": "t1", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "content_object", "value": {"_type": "Name", "_fields": {"id": "t2", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_add_bulk", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def test_add_bulk(self): bacon = Vegetable.objects.create(name="Bacon", is_yucky=False) t1 = TaggedItem.objects.create(content_object=self.quartz, tag="shiny") t2 = TaggedItem.objects.create(content_object=self.quartz, tag="clearish") # One update() query. with self.assertNumQueries(1): bacon.tags.add(t1, t2) self.assertEqual(t1.content_object, bacon) self.assertEqual(t2.content_object, bacon)
10,388
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9
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"value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}, {"_type": "List", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "elts": []}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertQuerysetEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_set", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def test_set(self): bacon = Vegetable.objects.create(name="Bacon", is_yucky=False) fatty = bacon.tags.create(tag="fatty") salty = bacon.tags.create(tag="salty") bacon.tags.set([fatty, salty]) self.assertQuerysetEqual(bacon.tags.all(), [ "<TaggedItem: fatty>", "<TaggedItem: salty>", ]) bacon.tags.set([fatty]) self.assertQuerysetEqual(bacon.tags.all(), [ "<TaggedItem: fatty>", ]) bacon.tags.set([]) self.assertQuerysetEqual(bacon.tags.all(), []) bacon.tags.set([fatty, salty], bulk=False, clear=True) self.assertQuerysetEqual(bacon.tags.all(), [ "<TaggedItem: fatty>", "<TaggedItem: salty>", ]) bacon.tags.set([fatty], bulk=False, clear=True) self.assertQuerysetEqual(bacon.tags.all(), [ "<TaggedItem: fatty>", ]) bacon.tags.set([], clear=True) self.assertQuerysetEqual(bacon.tags.all(), [])
10,389
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9
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"targets": [{"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "create", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "objects", "value": {"_type": "Name", "_fields": {"id": "TaggedItem", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "content_object", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "quartz", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, {"_type": "keyword", "_fields": {"arg": "tag", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "shiny"}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "t1", "ctx": {"_type": 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"_fields": {"body": [{"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Name", "_fields": {"id": "t1", "ctx": {"_type": "Load", "_fields": {}}}}, {"_type": "Name", "_fields": {"id": "t2", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "add", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "bulk", "value": {"_type": "Constant", "_fields": {"kind": null, "value": false}}}}]}}}}], "items": [{"_type": "withitem", "_fields": {"context_expr": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 2}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertNumQueries", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "optional_vars": null}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "content_object", "value": {"_type": "Name", "_fields": {"id": "t1", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "content_object", "value": {"_type": "Name", "_fields": {"id": "t2", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_add_bulk_false", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def test_add_bulk_false(self): bacon = Vegetable.objects.create(name="Bacon", is_yucky=False) t1 = TaggedItem.objects.create(content_object=self.quartz, tag="shiny") t2 = TaggedItem.objects.create(content_object=self.quartz, tag="clearish") # One save() for each object. with self.assertNumQueries(2): bacon.tags.add(t1, t2, bulk=False) self.assertEqual(t1.content_object, bacon) self.assertEqual(t2.content_object, bacon)
10,390
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9
{"_type": "Module", "_fields": {"body": [{"_type": "FunctionDef", "_fields": {"args": {"_type": "arguments", "_fields": {"args": [{"_type": "arg", "_fields": {"arg": "self", "annotation": null, "type_comment": null}}], "kwarg": null, "vararg": null, "defaults": [], "kwonlyargs": [], "kw_defaults": [], "posonlyargs": []}}, "body": [{"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "create", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "objects", "value": {"_type": "Name", "_fields": {"id": "Vegetable", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "name", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "Bacon"}}}}, {"_type": "keyword", "_fields": {"arg": "is_yucky", "value": {"_type": "Constant", "_fields": {"kind": null, "value": false}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "create", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "tag", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "fatty"}}}}]}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "create", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "tag", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "salty"}}}}]}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 2}}, {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "count", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "filter", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "tag", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "fatty"}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Load", "_fields": {}}}}, "targets": [{"_type": "Attribute", "_fields": {"ctx": {"_type": "Store", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 1}}, {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "count", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "tags", "value": {"_type": "Name", "_fields": {"id": "bacon", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": []}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Constant", "_fields": {"kind": null, "value": 1}}, {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "count", "value": {"_type": "Name", "_fields": {"id": "qs", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_assign_with_queryset", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def test_assign_with_queryset(self): # Ensure that querysets used in reverse GFK assignments are pre-evaluated # so their value isn't affected by the clearing operation in # ManyRelatedObjectsDescriptor.__set__. Refs #19816. bacon = Vegetable.objects.create(name="Bacon", is_yucky=False) bacon.tags.create(tag="fatty") bacon.tags.create(tag="salty") self.assertEqual(2, bacon.tags.count()) qs = bacon.tags.filter(tag="fatty") bacon.tags = qs self.assertEqual(1, bacon.tags.count()) self.assertEqual(1, qs.count())
10,391
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9
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def test_assign(self): bacon = Vegetable.objects.create(name="Bacon", is_yucky=False) fatty = bacon.tags.create(tag="fatty") salty = bacon.tags.create(tag="salty") bacon.tags = [fatty, salty] self.assertQuerysetEqual(bacon.tags.all(), [ "<TaggedItem: fatty>", "<TaggedItem: salty>", ]) bacon.tags = [fatty] self.assertQuerysetEqual(bacon.tags.all(), [ "<TaggedItem: fatty>", ]) bacon.tags = [] self.assertQuerysetEqual(bacon.tags.all(), [])
10,392
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10
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def test_multiple_gfk(self): # Simple tests for multiple GenericForeignKeys # only uses one model, since the above tests should be sufficient. tiger = Animal.objects.create(common_name="tiger") cheetah = Animal.objects.create(common_name="cheetah") bear = Animal.objects.create(common_name="bear") # Create directly Comparison.objects.create( first_obj=cheetah, other_obj=tiger, comparative="faster" ) Comparison.objects.create( first_obj=tiger, other_obj=cheetah, comparative="cooler" ) # Create using GenericRelation tiger.comparisons.create(other_obj=bear, comparative="cooler") tiger.comparisons.create(other_obj=cheetah, comparative="stronger") self.assertQuerysetEqual(cheetah.comparisons.all(), [ "<Comparison: cheetah is faster than tiger>" ]) # Filtering works self.assertQuerysetEqual(tiger.comparisons.filter(comparative="cooler"), [ "<Comparison: tiger is cooler than cheetah>", "<Comparison: tiger is cooler than bear>", ], ordered=False) # Filtering and deleting works subjective = ["cooler"] tiger.comparisons.filter(comparative__in=subjective).delete() self.assertQuerysetEqual(Comparison.objects.all(), [ "<Comparison: cheetah is faster than tiger>", "<Comparison: tiger is stronger than cheetah>" ], ordered=False) # If we delete cheetah, Comparisons with cheetah as 'first_obj' will be # deleted since Animal has an explicit GenericRelation to Comparison # through first_obj. Comparisons with cheetah as 'other_obj' will not # be deleted. cheetah.delete() self.assertQuerysetEqual(Comparison.objects.all(), [ "<Comparison: tiger is stronger than None>" ])
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10
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"Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertHTMLEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "create", "value": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "objects", "value": {"_type": "Name", "_fields": {"id": "Animal", "ctx": {"_type": "Load", "_fields": {}}}}}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "common_name", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "Lion"}}}}, {"_type": "keyword", "_fields": {"arg": "latin_name", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "Panthera leo"}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "lion", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Assign", "_fields": {"value": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Name", "_fields": {"id": "GenericFormSet", "ctx": {"_type": "Load", "_fields": {}}}}, "keywords": [{"_type": "keyword", "_fields": {"arg": "instance", "value": {"_type": "Name", "_fields": {"id": "lion", "ctx": {"_type": "Load", "_fields": {}}}}}}, {"_type": "keyword", "_fields": {"arg": "prefix", "value": {"_type": "Constant", "_fields": {"kind": null, "value": "x"}}}}]}}, "targets": [{"_type": "Name", "_fields": {"id": "formset", "ctx": {"_type": "Store", "_fields": {}}}}], "type_comment": null}}, {"_type": "Expr", "_fields": {"value": {"_type": "Call", "_fields": {"args": [{"_type": "Call", "_fields": {"args": [{"_type": "GeneratorExp", "_fields": {"elt": {"_type": "Call", "_fields": {"args": [], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "as_p", "value": {"_type": "Name", "_fields": {"id": "form", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}, "generators": [{"_type": "comprehension", "_fields": {"ifs": [], "iter": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "forms", "value": {"_type": "Name", "_fields": {"id": "formset", "ctx": {"_type": "Load", "_fields": {}}}}}}, "target": {"_type": "Name", "_fields": {"id": "form", "ctx": {"_type": "Store", "_fields": {}}}}, "is_async": 0}}]}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "join", "value": {"_type": "Constant", "_fields": {"kind": null, "value": ""}}}}, "keywords": []}}, {"_type": "Constant", "_fields": {"kind": null, "value": "<p><label for=\"id_x-0-tag\">Tag:</label> <input id=\"id_x-0-tag\" type=\"text\" name=\"x-0-tag\" maxlength=\"50\" /></p>\n<p><label for=\"id_x-0-DELETE\">Delete:</label> <input type=\"checkbox\" name=\"x-0-DELETE\" id=\"id_x-0-DELETE\" /><input type=\"hidden\" name=\"x-0-id\" id=\"id_x-0-id\" /></p>"}}], "func": {"_type": "Attribute", "_fields": {"ctx": {"_type": "Load", "_fields": {}}, "attr": "assertHTMLEqual", "value": {"_type": "Name", "_fields": {"id": "self", "ctx": {"_type": "Load", "_fields": {}}}}}}, "keywords": []}}}}], "name": "test_generic_inline_formsets", "returns": null, "type_params": [], "type_comment": null, "decorator_list": []}}], "type_ignores": []}}
def test_generic_inline_formsets(self): GenericFormSet = generic_inlineformset_factory(TaggedItem, extra=1) formset = GenericFormSet() self.assertHTMLEqual(''.join(form.as_p() for form in formset.forms), """<p><label for="id_generic_relations-taggeditem-content_type-object_id-0-tag">Tag:</label> <input id="id_generic_relations-taggeditem-content_type-object_id-0-tag" type="text" name="generic_relations-taggeditem-content_type-object_id-0-tag" maxlength="50" /></p> <p><label for="id_generic_relations-taggeditem-content_type-object_id-0-DELETE">Delete:</label> <input type="checkbox" name="generic_relations-taggeditem-content_type-object_id-0-DELETE" id="id_generic_relations-taggeditem-content_type-object_id-0-DELETE" /><input type="hidden" name="generic_relations-taggeditem-content_type-object_id-0-id" id="id_generic_relations-taggeditem-content_type-object_id-0-id" /></p>""") formset = GenericFormSet(instance=Animal()) self.assertHTMLEqual(''.join(form.as_p() for form in formset.forms), """<p><label for="id_generic_relations-taggeditem-content_type-object_id-0-tag">Tag:</label> <input id="id_generic_relations-taggeditem-content_type-object_id-0-tag" type="text" name="generic_relations-taggeditem-content_type-object_id-0-tag" maxlength="50" /></p> <p><label for="id_generic_relations-taggeditem-content_type-object_id-0-DELETE">Delete:</label> <input type="checkbox" name="generic_relations-taggeditem-content_type-object_id-0-DELETE" id="id_generic_relations-taggeditem-content_type-object_id-0-DELETE" /><input type="hidden" name="generic_relations-taggeditem-content_type-object_id-0-id" id="id_generic_relations-taggeditem-content_type-object_id-0-id" /></p>""") platypus = Animal.objects.create( common_name="Platypus", latin_name="Ornithorhynchus anatinus" ) platypus.tags.create(tag="shiny") GenericFormSet = generic_inlineformset_factory(TaggedItem, extra=1) formset = GenericFormSet(instance=platypus) tagged_item_id = TaggedItem.objects.get( tag='shiny', object_id=platypus.id ).id self.assertHTMLEqual(''.join(form.as_p() for form in formset.forms), """<p><label for="id_generic_relations-taggeditem-content_type-object_id-0-tag">Tag:</label> <input id="id_generic_relations-taggeditem-content_type-object_id-0-tag" type="text" name="generic_relations-taggeditem-content_type-object_id-0-tag" value="shiny" maxlength="50" /></p> <p><label for="id_generic_relations-taggeditem-content_type-object_id-0-DELETE">Delete:</label> <input type="checkbox" name="generic_relations-taggeditem-content_type-object_id-0-DELETE" id="id_generic_relations-taggeditem-content_type-object_id-0-DELETE" /><input type="hidden" name="generic_relations-taggeditem-content_type-object_id-0-id" value="%s" id="id_generic_relations-taggeditem-content_type-object_id-0-id" /></p><p><label for="id_generic_relations-taggeditem-content_type-object_id-1-tag">Tag:</label> <input id="id_generic_relations-taggeditem-content_type-object_id-1-tag" type="text" name="generic_relations-taggeditem-content_type-object_id-1-tag" maxlength="50" /></p> <p><label for="id_generic_relations-taggeditem-content_type-object_id-1-DELETE">Delete:</label> <input type="checkbox" name="generic_relations-taggeditem-content_type-object_id-1-DELETE" id="id_generic_relations-taggeditem-content_type-object_id-1-DELETE" /><input type="hidden" name="generic_relations-taggeditem-content_type-object_id-1-id" id="id_generic_relations-taggeditem-content_type-object_id-1-id" /></p>""" % tagged_item_id) lion = Animal.objects.create(common_name="Lion", latin_name="Panthera leo") formset = GenericFormSet(instance=lion, prefix='x') self.assertHTMLEqual(''.join(form.as_p() for form in formset.forms), """<p><label for="id_x-0-tag">Tag:</label> <input id="id_x-0-tag" type="text" name="x-0-tag" maxlength="50" /></p> <p><label for="id_x-0-DELETE">Delete:</label> <input type="checkbox" name="x-0-DELETE" id="id_x-0-DELETE" /><input type="hidden" name="x-0-id" id="id_x-0-id" /></p>""")
10,394
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8
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def test_update_or_create_defaults(self): # update_or_create should work with virtual fields (content_object) quartz = Mineral.objects.create(name="Quartz", hardness=7) diamond = Mineral.objects.create(name="Diamond", hardness=7) tag, created = TaggedItem.objects.update_or_create(tag="shiny", defaults={'content_object': quartz}) self.assertTrue(created) self.assertEqual(tag.content_object.id, quartz.id) tag, created = TaggedItem.objects.update_or_create(tag="shiny", defaults={'content_object': diamond}) self.assertFalse(created) self.assertEqual(tag.content_object.id, diamond.id)
10,395
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8
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def test_get_or_create(self): # get_or_create should work with virtual fields (content_object) quartz = Mineral.objects.create(name="Quartz", hardness=7) tag, created = TaggedItem.objects.get_or_create(tag="shiny", defaults={'content_object': quartz}) self.assertTrue(created) self.assertEqual(tag.tag, "shiny") self.assertEqual(tag.content_object.id, quartz.id)
10,396
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8
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def test_save_new_for_proxy(self): Formset = generic_inlineformset_factory(ForProxyModelModel, fields='__all__', for_concrete_model=False) instance = ProxyRelatedModel.objects.create() data = { 'form-TOTAL_FORMS': '1', 'form-INITIAL_FORMS': '0', 'form-MAX_NUM_FORMS': '', 'form-0-title': 'foo', } formset = Formset(data, instance=instance, prefix='form') self.assertTrue(formset.is_valid()) new_obj, = formset.save() self.assertEqual(new_obj.obj, instance)
10,397
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8
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def test_save_new_for_concrete(self): Formset = generic_inlineformset_factory(ForProxyModelModel, fields='__all__', for_concrete_model=True) instance = ProxyRelatedModel.objects.create() data = { 'form-TOTAL_FORMS': '1', 'form-INITIAL_FORMS': '0', 'form-MAX_NUM_FORMS': '', 'form-0-title': 'foo', } formset = Formset(data, instance=instance, prefix='form') self.assertTrue(formset.is_valid()) new_obj, = formset.save() self.assertNotIsInstance(new_obj.obj, ProxyRelatedModel)
10,398
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9
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def test_generic_relation_set(self): base = ForProxyModelModel() base.obj = ConcreteRelatedModel.objects.create() base.save() newrel = ConcreteRelatedModel.objects.create() newrel.bases = [base] newrel = ConcreteRelatedModel.objects.get(pk=newrel.pk) self.assertEqual(base, newrel.bases.get())
10,399
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9
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def test_generic_relation(self): base = ForProxyModelModel() base.obj = ProxyRelatedModel.objects.create() base.save() base = ForProxyModelModel.objects.get(pk=base.pk) rel = ProxyRelatedModel.objects.get(pk=base.obj.pk) self.assertEqual(base, rel.bases.get())
10,400
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def run(test): test.create_makefile(makefile) test.write_file("source1", "1") test.write_file("source2", "2") test.write_file("source3", "3") test.write_file("source4", "4") test.start() test.build() hash_source1 = test.get_hash_of("source1") hash_source2 = test.get_hash_of("source2") hash_source3 = test.get_hash_of("source3") hash_source4 = test.get_hash_of("source4") hash_node1 = test.get_hash_of("node1") hash_node2 = test.get_hash_of("node2") hash_output = test.get_hash_of("output") hash_all = test.get_hash_of("all") # Modify source2. Watchman should trigger the file to be dirty. time.sleep(1) test.write_file("source2", "3") test.expect_watchman_trigger("source2") assert(set(["source2", "node1", "output", "all"]) == set(test.get_dirty_targets())) # Expect the hash of source2, node1, output, all to be changed tmp_hash_source2 = test.get_hash_of("source2") tmp_hash_node1 = test.get_hash_of("node1") tmp_hash_output = test.get_hash_of("output") tmp_hash_all = test.get_hash_of("all") assert(tmp_hash_source2 != hash_source2) assert(tmp_hash_node1 != hash_node1) assert(tmp_hash_output != hash_output) assert(tmp_hash_all != hash_all) hash_source2 = tmp_hash_source2 hash_node1 = tmp_hash_node1 hash_output = tmp_hash_output hash_all = tmp_hash_all # Expect the hash of source1, source3, source4, node2 to be unchanged assert(test.get_hash_of("source1") == hash_source1) assert(test.get_hash_of("source3") == hash_source3) assert(test.get_hash_of("source4") == hash_source4) assert(test.get_hash_of("node2") == hash_node2) # Modify source1. Watchman should trigger the file to be dirty. time.sleep(1) test.write_file("source1", "5") test.expect_watchman_trigger("source1") assert(set(["source1", "source2", "node1", "output", "all"]) == set(test.get_dirty_targets())) # Expect the hash of source1, node1, output, all to be changed tmp_hash_source1 = test.get_hash_of("source1") tmp_hash_node1 = test.get_hash_of("node1") tmp_hash_output = test.get_hash_of("output") tmp_hash_all = test.get_hash_of("all") assert(tmp_hash_source1 != hash_source1) assert(tmp_hash_node1 != hash_node1) assert(tmp_hash_output != hash_output) assert(tmp_hash_all != hash_all) hash_source1 = tmp_hash_source1 hash_node1 = tmp_hash_node1 hash_output = tmp_hash_output hash_all = tmp_hash_all # Expect the hash of source2, source3, source4, node2 to be unchanged assert(test.get_hash_of("source2") == hash_source2) assert(test.get_hash_of("source3") == hash_source3) assert(test.get_hash_of("source4") == hash_source4) assert(test.get_hash_of("node2") == hash_node2) # Modify source3. Watchman should trigger the file to be dirty. time.sleep(1) test.write_file("source3", "6") test.expect_watchman_trigger("source3") assert(set(["source1", "source2", "source3", "node1", "node2", "output", "all"]) == set(test.get_dirty_targets())) # Expect the hash of source3, node2, output, all to be changed tmp_hash_source3 = test.get_hash_of("source3") tmp_hash_node2 = test.get_hash_of("node2") tmp_hash_output = test.get_hash_of("output") tmp_hash_all = test.get_hash_of("all") assert(tmp_hash_source3 != hash_source3) assert(tmp_hash_node2 != hash_node2) assert(tmp_hash_output != hash_output) assert(tmp_hash_all != hash_all) hash_source3 = tmp_hash_source3 hash_node2 = tmp_hash_node2 hash_output = tmp_hash_output hash_all = tmp_hash_all # Expect the hash of source1, source2, source4, node1 to be unchanged assert(test.get_hash_of("source1") == hash_source1) assert(test.get_hash_of("source2") == hash_source2) assert(test.get_hash_of("source4") == hash_source4) assert(test.get_hash_of("node1") == hash_node1)