blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7c7a0f6f19cbdbfc2f15745a2c4c407ced3b3d8d | [
"if self.is_classifier():\n preds = self._predict(X)\n pred_col = self._get_custom_param('predictions_col', 0)\n selector = [c for c in range(preds.ncol) if c != pred_col]\n return preds[:, selector]\nraise AttributeError(\"{} attribute 'predict_proba' is supported only for classification.\".format(self... | <|body_start_0|>
if self.is_classifier():
preds = self._predict(X)
pred_col = self._get_custom_param('predictions_col', 0)
selector = [c for c in range(preds.ncol) if c != pred_col]
return preds[:, selector]
raise AttributeError("{} attribute 'predict_prob... | H2OEstimatorPredictProbabilitiesSupport | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class H2OEstimatorPredictProbabilitiesSupport:
def predict_proba(self, X):
"""Predicts on the data. :param iterable X: data to predict on (array-like or :class:`h2o.H2OFrame`). :return: the predictions probabilities, shape=[n_samples, n_classes] (array-like or :class:`h2o.H2OFrame`)."""
... | stack_v2_sparse_classes_36k_train_017900 | 36,832 | permissive | [
{
"docstring": "Predicts on the data. :param iterable X: data to predict on (array-like or :class:`h2o.H2OFrame`). :return: the predictions probabilities, shape=[n_samples, n_classes] (array-like or :class:`h2o.H2OFrame`).",
"name": "predict_proba",
"signature": "def predict_proba(self, X)"
},
{
... | 2 | null | Implement the Python class `H2OEstimatorPredictProbabilitiesSupport` described below.
Class description:
Implement the H2OEstimatorPredictProbabilitiesSupport class.
Method signatures and docstrings:
- def predict_proba(self, X): Predicts on the data. :param iterable X: data to predict on (array-like or :class:`h2o.H... | Implement the Python class `H2OEstimatorPredictProbabilitiesSupport` described below.
Class description:
Implement the H2OEstimatorPredictProbabilitiesSupport class.
Method signatures and docstrings:
- def predict_proba(self, X): Predicts on the data. :param iterable X: data to predict on (array-like or :class:`h2o.H... | d817ab90c8c47f6787604a0b9639b66234158228 | <|skeleton|>
class H2OEstimatorPredictProbabilitiesSupport:
def predict_proba(self, X):
"""Predicts on the data. :param iterable X: data to predict on (array-like or :class:`h2o.H2OFrame`). :return: the predictions probabilities, shape=[n_samples, n_classes] (array-like or :class:`h2o.H2OFrame`)."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class H2OEstimatorPredictProbabilitiesSupport:
def predict_proba(self, X):
"""Predicts on the data. :param iterable X: data to predict on (array-like or :class:`h2o.H2OFrame`). :return: the predictions probabilities, shape=[n_samples, n_classes] (array-like or :class:`h2o.H2OFrame`)."""
if self.is_c... | the_stack_v2_python_sparse | h2o-py/h2o/sklearn/wrapper.py | h2oai/h2o-3 | train | 6,872 | |
bac021f94f2e11735c86c690c60800a8c16a2fd2 | [
"queue = self.messages.Queue(name=queue_ref.RelativeName(), retryConfig=retry_config, rateLimits=rate_limits, appEngineHttpQueue=app_engine_http_queue, stackdriverLoggingConfig=stackdriver_logging_config)\nrequest = self.messages.CloudtasksProjectsLocationsQueuesCreateRequest(parent=parent_ref.RelativeName(), queue... | <|body_start_0|>
queue = self.messages.Queue(name=queue_ref.RelativeName(), retryConfig=retry_config, rateLimits=rate_limits, appEngineHttpQueue=app_engine_http_queue, stackdriverLoggingConfig=stackdriver_logging_config)
request = self.messages.CloudtasksProjectsLocationsQueuesCreateRequest(parent=paren... | Client for queues service in the Cloud Tasks API. | BetaQueues | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BetaQueues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None):
"""Prepares and sends a Create request for creating a queue."""
<|bod... | stack_v2_sparse_classes_36k_train_017901 | 9,305 | permissive | [
{
"docstring": "Prepares and sends a Create request for creating a queue.",
"name": "Create",
"signature": "def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None)"
},
{
"docstring": "Prepares and sends a Patch req... | 2 | stack_v2_sparse_classes_30k_train_019530 | Implement the Python class `BetaQueues` described below.
Class description:
Client for queues service in the Cloud Tasks API.
Method signatures and docstrings:
- def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None): Prepares and send... | Implement the Python class `BetaQueues` described below.
Class description:
Client for queues service in the Cloud Tasks API.
Method signatures and docstrings:
- def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None): Prepares and send... | 85bb264e273568b5a0408f733b403c56373e2508 | <|skeleton|>
class BetaQueues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None):
"""Prepares and sends a Create request for creating a queue."""
<|bod... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BetaQueues:
"""Client for queues service in the Cloud Tasks API."""
def Create(self, parent_ref, queue_ref, retry_config=None, rate_limits=None, app_engine_http_queue=None, stackdriver_logging_config=None):
"""Prepares and sends a Create request for creating a queue."""
queue = self.messa... | the_stack_v2_python_sparse | google-cloud-sdk/lib/googlecloudsdk/api_lib/tasks/queues.py | bopopescu/socialliteapp | train | 0 |
146bdf8e2adb3efcd7e785903d1552757e82abba | [
"m = defaultdict(int)\nn = len(nums)\nres = 1\nfor i in range(n):\n for j in range(i):\n diff = nums[i] - nums[j]\n m[i, diff] = m[j, diff] + 1\n res = max(res, m[i, diff])\nreturn res + 1",
"n = len(nums)\ndp = [[0] * 2000 for _ in range(n)]\nres = 1\nfor i in range(n):\n for j in rang... | <|body_start_0|>
m = defaultdict(int)
n = len(nums)
res = 1
for i in range(n):
for j in range(i):
diff = nums[i] - nums[j]
m[i, diff] = m[j, diff] + 1
res = max(res, m[i, diff])
return res + 1
<|end_body_0|>
<|body_star... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestArithSeqLength(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestArithSeqLengthDP(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
m = defaultdict(int)
... | stack_v2_sparse_classes_36k_train_017902 | 2,814 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "longestArithSeqLength",
"signature": "def longestArithSeqLength(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "longestArithSeqLengthDP",
"signature": "def longestArithSeqLengthDP(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017398 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestArithSeqLength(self, nums): :type nums: List[int] :rtype: int
- def longestArithSeqLengthDP(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestArithSeqLength(self, nums): :type nums: List[int] :rtype: int
- def longestArithSeqLengthDP(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def longestArithSeqLength(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def longestArithSeqLengthDP(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestArithSeqLength(self, nums):
""":type nums: List[int] :rtype: int"""
m = defaultdict(int)
n = len(nums)
res = 1
for i in range(n):
for j in range(i):
diff = nums[i] - nums[j]
m[i, diff] = m[j, diff] + 1
... | the_stack_v2_python_sparse | L/LongestArithmeticSubsequence.py | bssrdf/pyleet | train | 2 | |
d97521b9ec229ea78a601836c046fe35cff85d0b | [
"worker = SysupdateWorker(router, firmware_config)\nworker.start()\nworker.join()",
"worker = SysupgradeWorker(router, n)\nworker.start()\nworker.join()"
] | <|body_start_0|>
worker = SysupdateWorker(router, firmware_config)
worker.start()
worker.join()
<|end_body_0|>
<|body_start_1|>
worker = SysupgradeWorker(router, n)
worker.start()
worker.join()
<|end_body_1|>
| RouterFlashFirmware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RouterFlashFirmware:
def sysupdate(router: Router, firmware_config):
"""Instantiate a NetworkCtrl and copy the firmware via SSH to the Router(/tmp/<firmware_name>.bin) :param router: :param firmware_config:"""
<|body_0|>
def sysupgrade(router: Router, n: bool):
"""In... | stack_v2_sparse_classes_36k_train_017903 | 3,026 | no_license | [
{
"docstring": "Instantiate a NetworkCtrl and copy the firmware via SSH to the Router(/tmp/<firmware_name>.bin) :param router: :param firmware_config:",
"name": "sysupdate",
"signature": "def sysupdate(router: Router, firmware_config)"
},
{
"docstring": "Instantiate a NetworkCtrl, proves if the ... | 2 | stack_v2_sparse_classes_30k_train_002437 | Implement the Python class `RouterFlashFirmware` described below.
Class description:
Implement the RouterFlashFirmware class.
Method signatures and docstrings:
- def sysupdate(router: Router, firmware_config): Instantiate a NetworkCtrl and copy the firmware via SSH to the Router(/tmp/<firmware_name>.bin) :param route... | Implement the Python class `RouterFlashFirmware` described below.
Class description:
Implement the RouterFlashFirmware class.
Method signatures and docstrings:
- def sysupdate(router: Router, firmware_config): Instantiate a NetworkCtrl and copy the firmware via SSH to the Router(/tmp/<firmware_name>.bin) :param route... | 5dbe21f47552097441601b881aa47ff66625b211 | <|skeleton|>
class RouterFlashFirmware:
def sysupdate(router: Router, firmware_config):
"""Instantiate a NetworkCtrl and copy the firmware via SSH to the Router(/tmp/<firmware_name>.bin) :param router: :param firmware_config:"""
<|body_0|>
def sysupgrade(router: Router, n: bool):
"""In... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RouterFlashFirmware:
def sysupdate(router: Router, firmware_config):
"""Instantiate a NetworkCtrl and copy the firmware via SSH to the Router(/tmp/<firmware_name>.bin) :param router: :param firmware_config:"""
worker = SysupdateWorker(router, firmware_config)
worker.start()
wor... | the_stack_v2_python_sparse | util/router_flash_firmware.py | freifunk-darmstadt/TestFramework | train | 1 | |
188405ec2c5c2996c0bdbc9c4df5fbeace808420 | [
"n = len(citations)\nll, r = (0, n - 1)\nwhile ll <= r:\n mid = (ll + r) / 2\n if citations[mid] > n - mid:\n r = mid - 1\n elif citations[mid] < n - mid:\n ll = mid + 1\n else:\n return n - mid\nreturn n - ll",
"if not citations:\n return 0\nlength = len(citations)\nleft = 0\n... | <|body_start_0|>
n = len(citations)
ll, r = (0, n - 1)
while ll <= r:
mid = (ll + r) / 2
if citations[mid] > n - mid:
r = mid - 1
elif citations[mid] < n - mid:
ll = mid + 1
else:
return n - mid
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def hIndex(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_0|>
def hIndex_2(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(citations)
ll, r ... | stack_v2_sparse_classes_36k_train_017904 | 2,466 | no_license | [
{
"docstring": ":type citations: List[int] :rtype: int",
"name": "hIndex",
"signature": "def hIndex(self, citations)"
},
{
"docstring": ":type citations: List[int] :rtype: int",
"name": "hIndex_2",
"signature": "def hIndex_2(self, citations)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hIndex(self, citations): :type citations: List[int] :rtype: int
- def hIndex_2(self, citations): :type citations: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def hIndex(self, citations): :type citations: List[int] :rtype: int
- def hIndex_2(self, citations): :type citations: List[int] :rtype: int
<|skeleton|>
class Solution:
def... | 6350568d16b0f8c49a020f055bb6d72e2705ea56 | <|skeleton|>
class Solution:
def hIndex(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_0|>
def hIndex_2(self, citations):
""":type citations: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def hIndex(self, citations):
""":type citations: List[int] :rtype: int"""
n = len(citations)
ll, r = (0, n - 1)
while ll <= r:
mid = (ll + r) / 2
if citations[mid] > n - mid:
r = mid - 1
elif citations[mid] < n - mid... | the_stack_v2_python_sparse | binary_search_tree/275_H-Index2.py | vsdrun/lc_public | train | 6 | |
f6685bed4bc88d88b0d647e9f8c34c3ac75bec7f | [
"low = high = 0\nfor c in s:\n low += 1 if c == '(' else -1\n high += 1 if c in '(*' else -1\n if high < 0:\n break\n low = max(low, 0)\nreturn low == 0",
"def go(s, stack):\n for i in range(len(s)):\n if s[i] == '(':\n stack.append(s[i])\n elif s[i] == ')':\n ... | <|body_start_0|>
low = high = 0
for c in s:
low += 1 if c == '(' else -1
high += 1 if c in '(*' else -1
if high < 0:
break
low = max(low, 0)
return low == 0
<|end_body_0|>
<|body_start_1|>
def go(s, stack):
for ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkValidString(self, s):
""":type s: str :rtype: bool 這個 greedy 的解法的想法是在 pass 整個字串的過程中 去計算當前的 `balance`, 所謂的 balance 就是把'('當成+1, 把')'當成-1, 把字串轉換成一個數字的意思 一個合法的括號方式，從 0 開始的子字串之 balance 必定大於 0 (balance 大於 0 的意思其實就是左括號比右括號多的意思) 而這題又多了一個萬能字元 - 星號，所以我們不能只計算 balance 要考慮 balance ... | stack_v2_sparse_classes_36k_train_017905 | 2,740 | no_license | [
{
"docstring": ":type s: str :rtype: bool 這個 greedy 的解法的想法是在 pass 整個字串的過程中 去計算當前的 `balance`, 所謂的 balance 就是把'('當成+1, 把')'當成-1, 把字串轉換成一個數字的意思 一個合法的括號方式，從 0 開始的子字串之 balance 必定大於 0 (balance 大於 0 的意思其實就是左括號比右括號多的意思) 而這題又多了一個萬能字元 - 星號，所以我們不能只計算 balance 要考慮 balance 可能的最大值及最小值 也就是說 '(' 會使 最大值跟最小值都 +1 ')' 會使 最大值跟最小值都 -... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkValidString(self, s): :type s: str :rtype: bool 這個 greedy 的解法的想法是在 pass 整個字串的過程中 去計算當前的 `balance`, 所謂的 balance 就是把'('當成+1, 把')'當成-1, 把字串轉換成一個數字的意思 一個合法的括號方式，從 0 開始的子字串之 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkValidString(self, s): :type s: str :rtype: bool 這個 greedy 的解法的想法是在 pass 整個字串的過程中 去計算當前的 `balance`, 所謂的 balance 就是把'('當成+1, 把')'當成-1, 把字串轉換成一個數字的意思 一個合法的括號方式，從 0 開始的子字串之 ... | ac53dd9bf2c4c9d17c9dc5f7fdda32e386658fdd | <|skeleton|>
class Solution:
def checkValidString(self, s):
""":type s: str :rtype: bool 這個 greedy 的解法的想法是在 pass 整個字串的過程中 去計算當前的 `balance`, 所謂的 balance 就是把'('當成+1, 把')'當成-1, 把字串轉換成一個數字的意思 一個合法的括號方式，從 0 開始的子字串之 balance 必定大於 0 (balance 大於 0 的意思其實就是左括號比右括號多的意思) 而這題又多了一個萬能字元 - 星號，所以我們不能只計算 balance 要考慮 balance ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkValidString(self, s):
""":type s: str :rtype: bool 這個 greedy 的解法的想法是在 pass 整個字串的過程中 去計算當前的 `balance`, 所謂的 balance 就是把'('當成+1, 把')'當成-1, 把字串轉換成一個數字的意思 一個合法的括號方式，從 0 開始的子字串之 balance 必定大於 0 (balance 大於 0 的意思其實就是左括號比右括號多的意思) 而這題又多了一個萬能字元 - 星號，所以我們不能只計算 balance 要考慮 balance 可能的最大值及最小值 也就是... | the_stack_v2_python_sparse | cs_notes/string/valid_parenthesis_string.py | hwc1824/LeetCodeSolution | train | 0 | |
5460024c542c2e0e26b846a7031d467ba27d96c4 | [
"summ = nums[0]\nfor bIndex in range(len(nums)):\n for eIndex in range(1, len(nums[bIndex:]) + 1):\n tmp = sum(nums[bIndex:bIndex + eIndex])\n if tmp > summ:\n summ = tmp\nreturn summ",
"curIndex = 0\ncurSum = maxSum = nums[0]\nfor index, num in enumerate(nums[1:]):\n if num > curSu... | <|body_start_0|>
summ = nums[0]
for bIndex in range(len(nums)):
for eIndex in range(1, len(nums[bIndex:]) + 1):
tmp = sum(nums[bIndex:bIndex + eIndex])
if tmp > summ:
summ = tmp
return summ
<|end_body_0|>
<|body_start_1|>
c... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
summ = nums[0]
for bIndex in range(l... | stack_v2_sparse_classes_36k_train_017906 | 1,045 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray1",
"signature": "def maxSubArray1(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009196 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray1(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray1(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxSubArra... | 1315727d68fc3e0c47376604b3f7d4807607e2c7 | <|skeleton|>
class Solution:
def maxSubArray1(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray1(self, nums):
""":type nums: List[int] :rtype: int"""
summ = nums[0]
for bIndex in range(len(nums)):
for eIndex in range(1, len(nums[bIndex:]) + 1):
tmp = sum(nums[bIndex:bIndex + eIndex])
if tmp > summ:
... | the_stack_v2_python_sparse | maxSubArray.py | 4ier/LeetCode | train | 4 | |
aaa47a1e25dbdad3c170a595e5c34a346d9a0d80 | [
"input_data = {}\ninput_data['name'] = kwargs.get('name', None)\ninput_data['sort_by_date'] = kwargs.get('sort_by_date', None)\ninput_data['podcast_type'] = kwargs.get('podcast_type', None)\ninput_data['duration'] = kwargs.get('duration', None)\ninput_data['published'] = kwargs.get('published', None)\ninput_data['l... | <|body_start_0|>
input_data = {}
input_data['name'] = kwargs.get('name', None)
input_data['sort_by_date'] = kwargs.get('sort_by_date', None)
input_data['podcast_type'] = kwargs.get('podcast_type', None)
input_data['duration'] = kwargs.get('duration', None)
input_data['pub... | Validations for theclient information | PodcastValidations | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PodcastValidations:
"""Validations for theclient information"""
def validate_podcast_data(self, kwargs):
"""Runs all the individual client registration data validations in one function Args: kwargs (dict): request data Returns: input_data (dict): validated data"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_017907 | 2,198 | permissive | [
{
"docstring": "Runs all the individual client registration data validations in one function Args: kwargs (dict): request data Returns: input_data (dict): validated data",
"name": "validate_podcast_data",
"signature": "def validate_podcast_data(self, kwargs)"
},
{
"docstring": "Runs all the corp... | 2 | stack_v2_sparse_classes_30k_test_000520 | Implement the Python class `PodcastValidations` described below.
Class description:
Validations for theclient information
Method signatures and docstrings:
- def validate_podcast_data(self, kwargs): Runs all the individual client registration data validations in one function Args: kwargs (dict): request data Returns:... | Implement the Python class `PodcastValidations` described below.
Class description:
Validations for theclient information
Method signatures and docstrings:
- def validate_podcast_data(self, kwargs): Runs all the individual client registration data validations in one function Args: kwargs (dict): request data Returns:... | 04ff9ebb5da482e5b2642a89654a5b5f0128eaaa | <|skeleton|>
class PodcastValidations:
"""Validations for theclient information"""
def validate_podcast_data(self, kwargs):
"""Runs all the individual client registration data validations in one function Args: kwargs (dict): request data Returns: input_data (dict): validated data"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PodcastValidations:
"""Validations for theclient information"""
def validate_podcast_data(self, kwargs):
"""Runs all the individual client registration data validations in one function Args: kwargs (dict): request data Returns: input_data (dict): validated data"""
input_data = {}
... | the_stack_v2_python_sparse | app/api/podcast/validators/validate_input.py | lunyamwis/laylinks-bend | train | 0 |
990e44e8601b8ba7e548d3a958d933dd56527ec9 | [
"odic = OrderedDict()\nodic['abc'] = 123\nodic['defg'] = 4567\nodic['xyz'] = 980\nodic['fhg'] = 456\nprint(odic)\ncollection_name = 'Hello'\nwith self.assertRaises(DuplicateKeyError):\n for n in range(2):\n time.sleep(2)\n with_mongo_collection(lambda col: col.insert_one(odic), collection_name)\nwi... | <|body_start_0|>
odic = OrderedDict()
odic['abc'] = 123
odic['defg'] = 4567
odic['xyz'] = 980
odic['fhg'] = 456
print(odic)
collection_name = 'Hello'
with self.assertRaises(DuplicateKeyError):
for n in range(2):
time.sleep(2)
... | config.py 的自动化测试案例 | MongoTest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MongoTest:
"""config.py 的自动化测试案例"""
def test_deal_with_mongo_collection(self):
"""mongodb 连续插入重复数据会报错，原因不详 :return:"""
<|body_0|>
def test_deal_with_mongo_collection(self):
"""插入mongodb中记录字段的顺序，无关，都可以被find出来 :return:"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_017908 | 8,886 | permissive | [
{
"docstring": "mongodb 连续插入重复数据会报错，原因不详 :return:",
"name": "test_deal_with_mongo_collection",
"signature": "def test_deal_with_mongo_collection(self)"
},
{
"docstring": "插入mongodb中记录字段的顺序，无关，都可以被find出来 :return:",
"name": "test_deal_with_mongo_collection",
"signature": "def test_deal_wit... | 2 | stack_v2_sparse_classes_30k_train_012438 | Implement the Python class `MongoTest` described below.
Class description:
config.py 的自动化测试案例
Method signatures and docstrings:
- def test_deal_with_mongo_collection(self): mongodb 连续插入重复数据会报错，原因不详 :return:
- def test_deal_with_mongo_collection(self): 插入mongodb中记录字段的顺序，无关，都可以被find出来 :return: | Implement the Python class `MongoTest` described below.
Class description:
config.py 的自动化测试案例
Method signatures and docstrings:
- def test_deal_with_mongo_collection(self): mongodb 连续插入重复数据会报错，原因不详 :return:
- def test_deal_with_mongo_collection(self): 插入mongodb中记录字段的顺序，无关，都可以被find出来 :return:
<|skeleton|>
class Mongo... | d6f20d926de047af6857e466cf28084d0ba69993 | <|skeleton|>
class MongoTest:
"""config.py 的自动化测试案例"""
def test_deal_with_mongo_collection(self):
"""mongodb 连续插入重复数据会报错，原因不详 :return:"""
<|body_0|>
def test_deal_with_mongo_collection(self):
"""插入mongodb中记录字段的顺序，无关，都可以被find出来 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MongoTest:
"""config.py 的自动化测试案例"""
def test_deal_with_mongo_collection(self):
"""mongodb 连续插入重复数据会报错，原因不详 :return:"""
odic = OrderedDict()
odic['abc'] = 123
odic['defg'] = 4567
odic['xyz'] = 980
odic['fhg'] = 456
print(odic)
collection_name... | the_stack_v2_python_sparse | test_case/test_config_base_utils.py | mmmaaaggg/QABAT | train | 4 |
9e6635cb59bd73a2f7b0812c705bffed39ee8d8f | [
"self.f = f\nself.gp = GP(X_init, Y_init, l, sigma_f)\naux = np.linspace(bounds[0], bounds[1], num=ac_samples)\nself.X_s = aux.reshape(-1, 1)\nself.xsi = xsi\nself.minimize = minimize",
"mu_s, sigma_s = self.gp.predict(self.X_s)\nif self.minimize is True:\n Y_s_opt = np.min(self.gp.Y)\n imp = Y_s_opt - mu_s... | <|body_start_0|>
self.f = f
self.gp = GP(X_init, Y_init, l, sigma_f)
aux = np.linspace(bounds[0], bounds[1], num=ac_samples)
self.X_s = aux.reshape(-1, 1)
self.xsi = xsi
self.minimize = minimize
<|end_body_0|>
<|body_start_1|>
mu_s, sigma_s = self.gp.predict(self... | Represents a noiseless 1D Gaussian process | BayesianOptimization | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BayesianOptimization:
"""Represents a noiseless 1D Gaussian process"""
def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True):
"""Class constructor :param f: is the black-box function to be optimized :param X_init: is a numpy.ndarray of sha... | stack_v2_sparse_classes_36k_train_017909 | 3,331 | no_license | [
{
"docstring": "Class constructor :param f: is the black-box function to be optimized :param X_init: is a numpy.ndarray of shape (t, 1) representing the inputs already sampled with the black-box function :param Y_init: is a numpy.ndarray of shape (t, 1) representing the outputs of the black-box function for eac... | 3 | stack_v2_sparse_classes_30k_train_008463 | Implement the Python class `BayesianOptimization` described below.
Class description:
Represents a noiseless 1D Gaussian process
Method signatures and docstrings:
- def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True): Class constructor :param f: is the black-box function... | Implement the Python class `BayesianOptimization` described below.
Class description:
Represents a noiseless 1D Gaussian process
Method signatures and docstrings:
- def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True): Class constructor :param f: is the black-box function... | 975f7e23906b7416e78489f6ad6331ea408c8709 | <|skeleton|>
class BayesianOptimization:
"""Represents a noiseless 1D Gaussian process"""
def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True):
"""Class constructor :param f: is the black-box function to be optimized :param X_init: is a numpy.ndarray of sha... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BayesianOptimization:
"""Represents a noiseless 1D Gaussian process"""
def __init__(self, f, X_init, Y_init, bounds, ac_samples, l=1, sigma_f=1, xsi=0.01, minimize=True):
"""Class constructor :param f: is the black-box function to be optimized :param X_init: is a numpy.ndarray of shape (t, 1) rep... | the_stack_v2_python_sparse | unsupervised_learning/0x03-hyperparameter_tuning/5-bayes_opt.py | julgachancipa/holbertonschool-machine_learning | train | 1 |
28b03e2d1e9a9e2c1d3f112d060475886d4f0ed5 | [
"def preorder(root):\n if root:\n vals.append(root.val)\n preorder(root.left)\n preorder(root.right)\nvals = []\npreorder(root)\nreturn ' '.join(map(str, vals))",
"preorder = list(map(int, data.split()))\ninorder = sorted(preorder)\n\ndef buildBST(preorder, inorder):\n if not preorder:\... | <|body_start_0|>
def preorder(root):
if root:
vals.append(root.val)
preorder(root.left)
preorder(root.right)
vals = []
preorder(root)
return ' '.join(map(str, vals))
<|end_body_0|>
<|body_start_1|>
preorder = list(map(i... | Codec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_017910 | 1,414 | permissive | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 3719f5cb059eefd66b83eb8ae990652f4b7fd124 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
def preorder(root):
if root:
vals.append(root.val)
preorder(root.left)
preorder(root.right)
vals = []
preorder... | the_stack_v2_python_sparse | Python3/0449-Serialize-and-Deserialize-BST/soln.py | wyaadarsh/LeetCode-Solutions | train | 0 | |
dd77732ee6da980ad247f90dc3b7c9cfeddda268 | [
"log.dev_info('Mask file path: {}'.format(mask_fp))\nif not os.path.isfile(mask_fp):\n log.dev_error('Path {} is not a mask file')\n return None\nmask = cio.read_image(mask_fp)\nmask.from_numpy(mask.to_numpy(), np.uint8)\nsize_x, size_y, slice_count = mask.size()\nslices = mask.to_numpy()\nrst = {}\nfor index... | <|body_start_0|>
log.dev_info('Mask file path: {}'.format(mask_fp))
if not os.path.isfile(mask_fp):
log.dev_error('Path {} is not a mask file')
return None
mask = cio.read_image(mask_fp)
mask.from_numpy(mask.to_numpy(), np.uint8)
size_x, size_y, slice_coun... | SegmentationHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SegmentationHelper:
def mask_to_contours(mask_fp):
"""Convert mask to contours :param mask_fp: Mask file path :return: Array of contours"""
<|body_0|>
def contours_to_mask(mask_fp, contours):
"""Convert contour to mask(.nii.gz) :param contours: dictionary of contours... | stack_v2_sparse_classes_36k_train_017911 | 3,104 | no_license | [
{
"docstring": "Convert mask to contours :param mask_fp: Mask file path :return: Array of contours",
"name": "mask_to_contours",
"signature": "def mask_to_contours(mask_fp)"
},
{
"docstring": "Convert contour to mask(.nii.gz) :param contours: dictionary of contours :param size: mask shape :retur... | 2 | null | Implement the Python class `SegmentationHelper` described below.
Class description:
Implement the SegmentationHelper class.
Method signatures and docstrings:
- def mask_to_contours(mask_fp): Convert mask to contours :param mask_fp: Mask file path :return: Array of contours
- def contours_to_mask(mask_fp, contours): C... | Implement the Python class `SegmentationHelper` described below.
Class description:
Implement the SegmentationHelper class.
Method signatures and docstrings:
- def mask_to_contours(mask_fp): Convert mask to contours :param mask_fp: Mask file path :return: Array of contours
- def contours_to_mask(mask_fp, contours): C... | d3206f29d37735b5cc393744faaa55295fe7d6b1 | <|skeleton|>
class SegmentationHelper:
def mask_to_contours(mask_fp):
"""Convert mask to contours :param mask_fp: Mask file path :return: Array of contours"""
<|body_0|>
def contours_to_mask(mask_fp, contours):
"""Convert contour to mask(.nii.gz) :param contours: dictionary of contours... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SegmentationHelper:
def mask_to_contours(mask_fp):
"""Convert mask to contours :param mask_fp: Mask file path :return: Array of contours"""
log.dev_info('Mask file path: {}'.format(mask_fp))
if not os.path.isfile(mask_fp):
log.dev_error('Path {} is not a mask file')
... | the_stack_v2_python_sparse | back_end/utils/segmentation_helper.py | yongweili1/portal | train | 0 | |
31bcd12cd23bee6d5051a7efec095ac49dee96eb | [
"self.agent = agent\nself.env = env\nself.replay = replay\nself.replay.shuffle = shuffle\nself._obs = None",
"rollouts = self.replay.sample()\nwith torch.no_grad():\n actions, output = self.agent.explore_on_batch(rollouts.obs_next)\n expected_values = output['value'].cpu().numpy().squeeze(-1)\nrollouts.disc... | <|body_start_0|>
self.agent = agent
self.env = env
self.replay = replay
self.replay.shuffle = shuffle
self._obs = None
<|end_body_0|>
<|body_start_1|>
rollouts = self.replay.sample()
with torch.no_grad():
actions, output = self.agent.explore_on_batch(... | ReplayRunner | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReplayRunner:
def __init__(self, agent, env, replay, shuffle=False):
"""Adapter for batch sampling from environments and replays. Args: agent (Agent): Learning agent. env (gym.Env): Environment with gym-like interface. replay (Replay): Replay for training. To disable training from replay... | stack_v2_sparse_classes_36k_train_017912 | 3,782 | permissive | [
{
"docstring": "Adapter for batch sampling from environments and replays. Args: agent (Agent): Learning agent. env (gym.Env): Environment with gym-like interface. replay (Replay): Replay for training. To disable training from replay, pass None.",
"name": "__init__",
"signature": "def __init__(self, agen... | 2 | stack_v2_sparse_classes_30k_train_001799 | Implement the Python class `ReplayRunner` described below.
Class description:
Implement the ReplayRunner class.
Method signatures and docstrings:
- def __init__(self, agent, env, replay, shuffle=False): Adapter for batch sampling from environments and replays. Args: agent (Agent): Learning agent. env (gym.Env): Envir... | Implement the Python class `ReplayRunner` described below.
Class description:
Implement the ReplayRunner class.
Method signatures and docstrings:
- def __init__(self, agent, env, replay, shuffle=False): Adapter for batch sampling from environments and replays. Args: agent (Agent): Learning agent. env (gym.Env): Envir... | b6447491250c1d41da704b989c751ff2c8a045e6 | <|skeleton|>
class ReplayRunner:
def __init__(self, agent, env, replay, shuffle=False):
"""Adapter for batch sampling from environments and replays. Args: agent (Agent): Learning agent. env (gym.Env): Environment with gym-like interface. replay (Replay): Replay for training. To disable training from replay... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReplayRunner:
def __init__(self, agent, env, replay, shuffle=False):
"""Adapter for batch sampling from environments and replays. Args: agent (Agent): Learning agent. env (gym.Env): Environment with gym-like interface. replay (Replay): Replay for training. To disable training from replay, pass None.""... | the_stack_v2_python_sparse | receptor/core/runner.py | dbobrenko/receptor | train | 0 | |
59f8929e9997f773d66b33b2a31589b184a6e062 | [
"from beartype._util.py.utilpyweakref import make_obj_weakref_and_repr\nsuper().__init__(message)\nif not isinstance(culprits, tuple):\n raise _BeartypeUtilExceptionException(f'Culprits {repr(culprits)} not tuple.')\nelif not culprits:\n raise _BeartypeUtilExceptionException('Culprits tuple empty.')\nself._cu... | <|body_start_0|>
from beartype._util.py.utilpyweakref import make_obj_weakref_and_repr
super().__init__(message)
if not isinstance(culprits, tuple):
raise _BeartypeUtilExceptionException(f'Culprits {repr(culprits)} not tuple.')
elif not culprits:
raise _BeartypeUt... | Abstract base class of all **beartype type-checking violations.** Instances of subclasses of this exception are raised by :mod:`beartype` when an object to be type-checked violates the type hint annotating that object. This includes wrapper functions generated by the :func:`beartype.beartype` decorator when either pass... | BeartypeCallHintViolation | [
"MIT",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BeartypeCallHintViolation:
"""Abstract base class of all **beartype type-checking violations.** Instances of subclasses of this exception are raised by :mod:`beartype` when an object to be type-checked violates the type hint annotating that object. This includes wrapper functions generated by the... | stack_v2_sparse_classes_36k_train_017913 | 49,857 | permissive | [
{
"docstring": "Initialize this type-checking exception. Parameters ---------- message : str Human-readable message describing this exception. culprits : Tuple[object, ...] Tuple of one or more **culprits** (i.e., user-defined objects directly responsible for this exception, typically due to violating a type hi... | 2 | null | Implement the Python class `BeartypeCallHintViolation` described below.
Class description:
Abstract base class of all **beartype type-checking violations.** Instances of subclasses of this exception are raised by :mod:`beartype` when an object to be type-checked violates the type hint annotating that object. This incl... | Implement the Python class `BeartypeCallHintViolation` described below.
Class description:
Abstract base class of all **beartype type-checking violations.** Instances of subclasses of this exception are raised by :mod:`beartype` when an object to be type-checked violates the type hint annotating that object. This incl... | 0cfd53391eb4de2f8297a4632aa5895b8d82a5b7 | <|skeleton|>
class BeartypeCallHintViolation:
"""Abstract base class of all **beartype type-checking violations.** Instances of subclasses of this exception are raised by :mod:`beartype` when an object to be type-checked violates the type hint annotating that object. This includes wrapper functions generated by the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BeartypeCallHintViolation:
"""Abstract base class of all **beartype type-checking violations.** Instances of subclasses of this exception are raised by :mod:`beartype` when an object to be type-checked violates the type hint annotating that object. This includes wrapper functions generated by the :func:`beart... | the_stack_v2_python_sparse | beartype/roar/_roarexc.py | beartype/beartype | train | 1,992 |
2201e31140c9e94ce7f3e49d1f38c0e6fdda19f3 | [
"eva = board.evaluate()\nif eva != 999 and eva != 998:\n return eva\nif board.isEnded():\n return 0\nif beta <= alpha:\n return 0\nif isMax:\n for i in range(board.sizeofX):\n for j in range(board.sizeofY):\n if board.get(i, j) == 0:\n board.move(i, j, 'X')\n ... | <|body_start_0|>
eva = board.evaluate()
if eva != 999 and eva != 998:
return eva
if board.isEnded():
return 0
if beta <= alpha:
return 0
if isMax:
for i in range(board.sizeofX):
for j in range(board.sizeofY):
... | Computer for hard difficulty | SmartestComputer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SmartestComputer:
"""Computer for hard difficulty"""
def minmax(self, board, depth, isMax, alpha, beta):
"""minmax Function that finds the best value of a move Arguments: board {Board} -- Game board depth {int} -- depth of the tree isMax {bool} -- check if is max or min alpha {int} -... | stack_v2_sparse_classes_36k_train_017914 | 3,019 | no_license | [
{
"docstring": "minmax Function that finds the best value of a move Arguments: board {Board} -- Game board depth {int} -- depth of the tree isMax {bool} -- check if is max or min alpha {int} -- value of max function beta {int} -- value of min function Returns: int -- value of moveset",
"name": "minmax",
... | 2 | stack_v2_sparse_classes_30k_train_001275 | Implement the Python class `SmartestComputer` described below.
Class description:
Computer for hard difficulty
Method signatures and docstrings:
- def minmax(self, board, depth, isMax, alpha, beta): minmax Function that finds the best value of a move Arguments: board {Board} -- Game board depth {int} -- depth of the ... | Implement the Python class `SmartestComputer` described below.
Class description:
Computer for hard difficulty
Method signatures and docstrings:
- def minmax(self, board, depth, isMax, alpha, beta): minmax Function that finds the best value of a move Arguments: board {Board} -- Game board depth {int} -- depth of the ... | 9fbbb20a63813073ca1abcb73f0c1639bd9f5a76 | <|skeleton|>
class SmartestComputer:
"""Computer for hard difficulty"""
def minmax(self, board, depth, isMax, alpha, beta):
"""minmax Function that finds the best value of a move Arguments: board {Board} -- Game board depth {int} -- depth of the tree isMax {bool} -- check if is max or min alpha {int} -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SmartestComputer:
"""Computer for hard difficulty"""
def minmax(self, board, depth, isMax, alpha, beta):
"""minmax Function that finds the best value of a move Arguments: board {Board} -- Game board depth {int} -- depth of the tree isMax {bool} -- check if is max or min alpha {int} -- value of ma... | the_stack_v2_python_sparse | Assignment 10/Computer.py | Taveeh/Fundamentals-of-Programming | train | 2 |
3b2d844358edfa8f87ccbb40f7f3b7a178157d99 | [
"a = 'AGC'\nb = 'AC'\ncomputedMatrix = [[0 for i in range(len(b) + 1)] for j in range(len(a) + 1)]\nfor i in range(1, len(a) + 1):\n computedMatrix[i][0] = computedMatrix[i - 1][0] + pah().weightFunctionDifference('', a[i - 1])\nfor i in range(1, len(b) + 1):\n computedMatrix[0][i] = computedMatrix[0][i - 1] ... | <|body_start_0|>
a = 'AGC'
b = 'AC'
computedMatrix = [[0 for i in range(len(b) + 1)] for j in range(len(a) + 1)]
for i in range(1, len(a) + 1):
computedMatrix[i][0] = computedMatrix[i - 1][0] + pah().weightFunctionDifference('', a[i - 1])
for i in range(1, len(b) + 1)... | Class to test the correctness of the computation for the class NeedlemanWunsch. | NeedlemanWunschTestClass | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NeedlemanWunschTestClass:
"""Class to test the correctness of the computation for the class NeedlemanWunsch."""
def test_computeMatrix(self):
"""Test of the computation of the matrix."""
<|body_0|>
def test_traceback(self):
"""Test of the traceback computation.""... | stack_v2_sparse_classes_36k_train_017915 | 2,597 | no_license | [
{
"docstring": "Test of the computation of the matrix.",
"name": "test_computeMatrix",
"signature": "def test_computeMatrix(self)"
},
{
"docstring": "Test of the traceback computation.",
"name": "test_traceback",
"signature": "def test_traceback(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009615 | Implement the Python class `NeedlemanWunschTestClass` described below.
Class description:
Class to test the correctness of the computation for the class NeedlemanWunsch.
Method signatures and docstrings:
- def test_computeMatrix(self): Test of the computation of the matrix.
- def test_traceback(self): Test of the tra... | Implement the Python class `NeedlemanWunschTestClass` described below.
Class description:
Class to test the correctness of the computation for the class NeedlemanWunsch.
Method signatures and docstrings:
- def test_computeMatrix(self): Test of the computation of the matrix.
- def test_traceback(self): Test of the tra... | 20d8df6172906337f81583dabb841d66b8f31857 | <|skeleton|>
class NeedlemanWunschTestClass:
"""Class to test the correctness of the computation for the class NeedlemanWunsch."""
def test_computeMatrix(self):
"""Test of the computation of the matrix."""
<|body_0|>
def test_traceback(self):
"""Test of the traceback computation.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NeedlemanWunschTestClass:
"""Class to test the correctness of the computation for the class NeedlemanWunsch."""
def test_computeMatrix(self):
"""Test of the computation of the matrix."""
a = 'AGC'
b = 'AC'
computedMatrix = [[0 for i in range(len(b) + 1)] for j in range(len... | the_stack_v2_python_sparse | new_algs/Sequence+algorithms/Needleman-Wunsch+algorithm/needlemanWunschTest.py | coolsnake/JupyterNotebook | train | 0 |
e8f7cbbde808a8878f904bf9f211dad0917ca9a6 | [
"assert isinstance(parameters, ChannelThresholderParameters)\nself.args = args = parameters\nself.channel = ChannelEncoder(input_shape, args.num_samples, args.sparsity, dtype=dtype, drange=drange, wrap=wrap)\nself.output_shape = self.channel.output_shape\nself.thresholds = np.random.normal(args.mean, args.stddev, s... | <|body_start_0|>
assert isinstance(parameters, ChannelThresholderParameters)
self.args = args = parameters
self.channel = ChannelEncoder(input_shape, args.num_samples, args.sparsity, dtype=dtype, drange=drange, wrap=wrap)
self.output_shape = self.channel.output_shape
self.thresho... | Creates a channel encoder with an additional activation threshold. A bit becomes active if and only if the underlying channel encoder activates it and its magnitude is not less than its threshold. Activation thresholds are normally distributed. | ChannelThresholder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChannelThresholder:
"""Creates a channel encoder with an additional activation threshold. A bit becomes active if and only if the underlying channel encoder activates it and its magnitude is not less than its threshold. Activation thresholds are normally distributed."""
def __init__(self, pa... | stack_v2_sparse_classes_36k_train_017916 | 38,944 | permissive | [
{
"docstring": "Argument parameters is an instance of ChannelThresholderParameters. Argument input_shape is tuple of dimensions of each input frame. Arguments dtype, drange, and wrap are passed through to the underlying channel encoder.",
"name": "__init__",
"signature": "def __init__(self, parameters, ... | 2 | stack_v2_sparse_classes_30k_train_013947 | Implement the Python class `ChannelThresholder` described below.
Class description:
Creates a channel encoder with an additional activation threshold. A bit becomes active if and only if the underlying channel encoder activates it and its magnitude is not less than its threshold. Activation thresholds are normally dis... | Implement the Python class `ChannelThresholder` described below.
Class description:
Creates a channel encoder with an additional activation threshold. A bit becomes active if and only if the underlying channel encoder activates it and its magnitude is not less than its threshold. Activation thresholds are normally dis... | 367f8701ec18226029d7ef070e70e9a8248a1374 | <|skeleton|>
class ChannelThresholder:
"""Creates a channel encoder with an additional activation threshold. A bit becomes active if and only if the underlying channel encoder activates it and its magnitude is not less than its threshold. Activation thresholds are normally distributed."""
def __init__(self, pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChannelThresholder:
"""Creates a channel encoder with an additional activation threshold. A bit becomes active if and only if the underlying channel encoder activates it and its magnitude is not less than its threshold. Activation thresholds are normally distributed."""
def __init__(self, parameters, inp... | the_stack_v2_python_sparse | encoders.py | ctrl-z-9000-times/HTM_experiments | train | 15 |
ca64c8db1f0e15754a752cf24a18a6c36f63885d | [
"candidate = 0\nfor i in xrange(n):\n if knows(candidate, i):\n candidate = i\nfor i in xrange(candidate):\n if knows(candidate, i):\n return -1\nfor i in xrange(candidate + 1, n):\n if not knows(i, candidate):\n return -1\nreturn candidate",
"candidates = [True] * n\ncount = 0\nfor ... | <|body_start_0|>
candidate = 0
for i in xrange(n):
if knows(candidate, i):
candidate = i
for i in xrange(candidate):
if knows(candidate, i):
return -1
for i in xrange(candidate + 1, n):
if not knows(i, candidate):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findCelebrity(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def findCelebrity_slow(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
candidate = 0
for i in xrange(n):
if kno... | stack_v2_sparse_classes_36k_train_017917 | 1,145 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "findCelebrity",
"signature": "def findCelebrity(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "findCelebrity_slow",
"signature": "def findCelebrity_slow(self, n)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017599 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findCelebrity(self, n): :type n: int :rtype: int
- def findCelebrity_slow(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findCelebrity(self, n): :type n: int :rtype: int
- def findCelebrity_slow(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def findCelebrity(self, n):
... | ed15eb27936b39980d4cb5fb61cd937ec7ddcb6a | <|skeleton|>
class Solution:
def findCelebrity(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def findCelebrity_slow(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findCelebrity(self, n):
""":type n: int :rtype: int"""
candidate = 0
for i in xrange(n):
if knows(candidate, i):
candidate = i
for i in xrange(candidate):
if knows(candidate, i):
return -1
for i in xr... | the_stack_v2_python_sparse | alice/LC277.py | AliceTTXu/LeetCode | train | 0 | |
e3f1e91a022165a526299378047d7249c65a6eaa | [
"username = request.GET.get('username', None)\nif username is not None:\n pm = get_object_or_404(PM, user__username=username)\n serializer = CMSerializer(pm)\n return JsonResponse({'pms': [serializer.data]}, safe=False)\nelse:\n pms = PM.objects.all()\n serializer = PMSerializer(pms, many=True)\n ... | <|body_start_0|>
username = request.GET.get('username', None)
if username is not None:
pm = get_object_or_404(PM, user__username=username)
serializer = CMSerializer(pm)
return JsonResponse({'pms': [serializer.data]}, safe=False)
else:
pms = PM.obje... | 专业负责人view | PMs | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PMs:
"""专业负责人view"""
def get(self, request):
"""查询专业负责人"""
<|body_0|>
def post(self, request):
"""增加专业负责人"""
<|body_1|>
def delete(self, request):
"""删除导员"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
username = request.GE... | stack_v2_sparse_classes_36k_train_017918 | 16,053 | permissive | [
{
"docstring": "查询专业负责人",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "增加专业负责人",
"name": "post",
"signature": "def post(self, request)"
},
{
"docstring": "删除导员",
"name": "delete",
"signature": "def delete(self, request)"
}
] | 3 | stack_v2_sparse_classes_30k_train_010225 | Implement the Python class `PMs` described below.
Class description:
专业负责人view
Method signatures and docstrings:
- def get(self, request): 查询专业负责人
- def post(self, request): 增加专业负责人
- def delete(self, request): 删除导员 | Implement the Python class `PMs` described below.
Class description:
专业负责人view
Method signatures and docstrings:
- def get(self, request): 查询专业负责人
- def post(self, request): 增加专业负责人
- def delete(self, request): 删除导员
<|skeleton|>
class PMs:
"""专业负责人view"""
def get(self, request):
"""查询专业负责人"""
... | 7aaa1be773718de1beb3ce0080edca7c4114b7ad | <|skeleton|>
class PMs:
"""专业负责人view"""
def get(self, request):
"""查询专业负责人"""
<|body_0|>
def post(self, request):
"""增加专业负责人"""
<|body_1|>
def delete(self, request):
"""删除导员"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PMs:
"""专业负责人view"""
def get(self, request):
"""查询专业负责人"""
username = request.GET.get('username', None)
if username is not None:
pm = get_object_or_404(PM, user__username=username)
serializer = CMSerializer(pm)
return JsonResponse({'pms': [seria... | the_stack_v2_python_sparse | user/views.py | MIXISAMA/MIS-backend | train | 0 |
1738ed8d4580f1107dfbee9373698fe766ade0ac | [
"ENFORCER.enforce_call(action='identity:check_grant', build_target=functools.partial(self._build_enforcement_target_attr, role_id=role_id, project_id=project_id, group_id=group_id))\ninherited = self._check_if_inherited()\nPROVIDERS.assignment_api.get_grant(role_id=role_id, group_id=group_id, project_id=project_id,... | <|body_start_0|>
ENFORCER.enforce_call(action='identity:check_grant', build_target=functools.partial(self._build_enforcement_target_attr, role_id=role_id, project_id=project_id, group_id=group_id))
inherited = self._check_if_inherited()
PROVIDERS.assignment_api.get_grant(role_id=role_id, group_i... | ProjectGroupGrantResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectGroupGrantResource:
def get(self, project_id, group_id, role_id):
"""Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}"""
<|body_0|>
def put(self, project_id, group_id, role_id):
"""Grant role for group o... | stack_v2_sparse_classes_36k_train_017919 | 22,149 | permissive | [
{
"docstring": "Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}",
"name": "get",
"signature": "def get(self, project_id, group_id, role_id)"
},
{
"docstring": "Grant role for group on project. PUT /v3/projects/{project_id}/groups/{group_i... | 3 | stack_v2_sparse_classes_30k_train_008062 | Implement the Python class `ProjectGroupGrantResource` described below.
Class description:
Implement the ProjectGroupGrantResource class.
Method signatures and docstrings:
- def get(self, project_id, group_id, role_id): Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{r... | Implement the Python class `ProjectGroupGrantResource` described below.
Class description:
Implement the ProjectGroupGrantResource class.
Method signatures and docstrings:
- def get(self, project_id, group_id, role_id): Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{r... | 03a0a8146a78682ede9eca12a5a7fdacde2035c8 | <|skeleton|>
class ProjectGroupGrantResource:
def get(self, project_id, group_id, role_id):
"""Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}"""
<|body_0|>
def put(self, project_id, group_id, role_id):
"""Grant role for group o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectGroupGrantResource:
def get(self, project_id, group_id, role_id):
"""Check grant for project, group, role. GET/HEAD /v3/projects/{project_id/groups/{group_id}/roles/{role_id}"""
ENFORCER.enforce_call(action='identity:check_grant', build_target=functools.partial(self._build_enforcement_t... | the_stack_v2_python_sparse | keystone/api/projects.py | sapcc/keystone | train | 0 | |
89a1c295989ea29028690fe55dcfb797285e968f | [
"self._config = config\nself._log = log\nlog.info('Pulsar Search Interface Initialisation')",
"self._log.info('Starting Pulsar Search Interface')\nauthorizer = DummyAuthorizer()\nauthorizer.add_user(self._config['login']['user'], self._config['login']['psswd'], '.', perm=self._config['login']['perm'])\nauthorizer... | <|body_start_0|>
self._config = config
self._log = log
log.info('Pulsar Search Interface Initialisation')
<|end_body_0|>
<|body_start_1|>
self._log.info('Starting Pulsar Search Interface')
authorizer = DummyAuthorizer()
authorizer.add_user(self._config['login']['user'], ... | Add docstring! | PulsarStart | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PulsarStart:
"""Add docstring!"""
def __init__(self, config, log):
"""Constructor. The supplied configuration dictionary must contain all parameters needed to define new user See pulsar_receiver_config.json for an example. Args: config (dict): Dictionary containing JSON configuration... | stack_v2_sparse_classes_36k_train_017920 | 5,054 | permissive | [
{
"docstring": "Constructor. The supplied configuration dictionary must contain all parameters needed to define new user See pulsar_receiver_config.json for an example. Args: config (dict): Dictionary containing JSON configuration file. log: Logger.",
"name": "__init__",
"signature": "def __init__(self,... | 2 | stack_v2_sparse_classes_30k_train_010389 | Implement the Python class `PulsarStart` described below.
Class description:
Add docstring!
Method signatures and docstrings:
- def __init__(self, config, log): Constructor. The supplied configuration dictionary must contain all parameters needed to define new user See pulsar_receiver_config.json for an example. Args... | Implement the Python class `PulsarStart` described below.
Class description:
Add docstring!
Method signatures and docstrings:
- def __init__(self, config, log): Constructor. The supplied configuration dictionary must contain all parameters needed to define new user See pulsar_receiver_config.json for an example. Args... | 5875dc0489f707232534ce75daf3707f909bcd15 | <|skeleton|>
class PulsarStart:
"""Add docstring!"""
def __init__(self, config, log):
"""Constructor. The supplied configuration dictionary must contain all parameters needed to define new user See pulsar_receiver_config.json for an example. Args: config (dict): Dictionary containing JSON configuration... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PulsarStart:
"""Add docstring!"""
def __init__(self, config, log):
"""Constructor. The supplied configuration dictionary must contain all parameters needed to define new user See pulsar_receiver_config.json for an example. Args: config (dict): Dictionary containing JSON configuration file. log: L... | the_stack_v2_python_sparse | sip/science_pipeline_workflows/receive_pss/pulsar_search.py | SKA-ScienceDataProcessor/integration-prototype | train | 3 |
9edda2526ddac0aef5e4df6e38d8d83f70b775ed | [
"self.img_size = img_size\nself.conf_thres = conf_thres\nself.nms_thres = nms_thres\nsuper(Yolov3Detector, self).__init__(model=get_yolov3(img_size=img_size), device=device, batch_size=batch_size)",
"imgs = super().preprocessing(imgs)\nimgs = [self.__yolov3_img_pre(img) for img in imgs]\nimgs = [torch.unsqueeze(i... | <|body_start_0|>
self.img_size = img_size
self.conf_thres = conf_thres
self.nms_thres = nms_thres
super(Yolov3Detector, self).__init__(model=get_yolov3(img_size=img_size), device=device, batch_size=batch_size)
<|end_body_0|>
<|body_start_1|>
imgs = super().preprocessing(imgs)
... | Yolov3Detector | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Yolov3Detector:
def __init__(self, device, conf_thres=0.8, nms_thres=0.4, img_size=416, batch_size=1):
"""Yolov3目标探测网络 Args: device (torch.device): 模型运行硬件 cuda or cpu conf_thres (float, optional): 目标置信度阈值. Defaults to 0.8. nms_thres (float, optional): 非极大值抑制阈值. Defaults to 0.4. img_size ... | stack_v2_sparse_classes_36k_train_017921 | 16,869 | no_license | [
{
"docstring": "Yolov3目标探测网络 Args: device (torch.device): 模型运行硬件 cuda or cpu conf_thres (float, optional): 目标置信度阈值. Defaults to 0.8. nms_thres (float, optional): 非极大值抑制阈值. Defaults to 0.4. img_size (int, optional): 网络输入大小. Defaults to 416. batch_size (int, optional): 批处理大小. Defaults to 1.",
"name": "__init_... | 5 | null | Implement the Python class `Yolov3Detector` described below.
Class description:
Implement the Yolov3Detector class.
Method signatures and docstrings:
- def __init__(self, device, conf_thres=0.8, nms_thres=0.4, img_size=416, batch_size=1): Yolov3目标探测网络 Args: device (torch.device): 模型运行硬件 cuda or cpu conf_thres (float,... | Implement the Python class `Yolov3Detector` described below.
Class description:
Implement the Yolov3Detector class.
Method signatures and docstrings:
- def __init__(self, device, conf_thres=0.8, nms_thres=0.4, img_size=416, batch_size=1): Yolov3目标探测网络 Args: device (torch.device): 模型运行硬件 cuda or cpu conf_thres (float,... | 3a0a7faab7049199312604e47f820b189973717e | <|skeleton|>
class Yolov3Detector:
def __init__(self, device, conf_thres=0.8, nms_thres=0.4, img_size=416, batch_size=1):
"""Yolov3目标探测网络 Args: device (torch.device): 模型运行硬件 cuda or cpu conf_thres (float, optional): 目标置信度阈值. Defaults to 0.8. nms_thres (float, optional): 非极大值抑制阈值. Defaults to 0.4. img_size ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Yolov3Detector:
def __init__(self, device, conf_thres=0.8, nms_thres=0.4, img_size=416, batch_size=1):
"""Yolov3目标探测网络 Args: device (torch.device): 模型运行硬件 cuda or cpu conf_thres (float, optional): 目标置信度阈值. Defaults to 0.8. nms_thres (float, optional): 非极大值抑制阈值. Defaults to 0.4. img_size (int, optional... | the_stack_v2_python_sparse | components/detector/objectdetector.py | SDGLBL/ITrafficSceneApplication | train | 3 | |
8cd089e5fe8ac3149330de8c17073ee2b4a187c4 | [
"super(BinaryComposition, self).__init__(operator, left, right)\nself.operator = operator\nself.left = left\nself.right = right\nself.validate()",
"_validate_operator_name(self.operator, BinaryComposition.SUPPORTED_OPERATORS)\nif not isinstance(self.left, Expression):\n raise TypeError(u'Expected Expression le... | <|body_start_0|>
super(BinaryComposition, self).__init__(operator, left, right)
self.operator = operator
self.left = left
self.right = right
self.validate()
<|end_body_0|>
<|body_start_1|>
_validate_operator_name(self.operator, BinaryComposition.SUPPORTED_OPERATORS)
... | An expression created by composing two expressions together. | BinaryComposition | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinaryComposition:
"""An expression created by composing two expressions together."""
def __init__(self, operator, left, right):
"""Construct an expression that connects two expressions with an operator. Args: operator: unicode, specifying where the field was declared left: Expressio... | stack_v2_sparse_classes_36k_train_017922 | 41,432 | permissive | [
{
"docstring": "Construct an expression that connects two expressions with an operator. Args: operator: unicode, specifying where the field was declared left: Expression on the left side of the binary operator right: Expression on the right side of the binary operator Returns: new BinaryComposition object",
... | 5 | stack_v2_sparse_classes_30k_train_003924 | Implement the Python class `BinaryComposition` described below.
Class description:
An expression created by composing two expressions together.
Method signatures and docstrings:
- def __init__(self, operator, left, right): Construct an expression that connects two expressions with an operator. Args: operator: unicode... | Implement the Python class `BinaryComposition` described below.
Class description:
An expression created by composing two expressions together.
Method signatures and docstrings:
- def __init__(self, operator, left, right): Construct an expression that connects two expressions with an operator. Args: operator: unicode... | 4511793281698bd55e63fd7a3f25f9cb094084d4 | <|skeleton|>
class BinaryComposition:
"""An expression created by composing two expressions together."""
def __init__(self, operator, left, right):
"""Construct an expression that connects two expressions with an operator. Args: operator: unicode, specifying where the field was declared left: Expressio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinaryComposition:
"""An expression created by composing two expressions together."""
def __init__(self, operator, left, right):
"""Construct an expression that connects two expressions with an operator. Args: operator: unicode, specifying where the field was declared left: Expression on the left... | the_stack_v2_python_sparse | graphql_compiler/compiler/expressions.py | jb-kensho/graphql-compiler | train | 0 |
985c1981365a5c9e7c886a5077741b078bd2fca3 | [
"self.var = var\nself.con = con\nself.var_descr = var_descr\nself.con_descr = con_descr",
"r = 'L-System Variables:\\n'\nfor i in range(0, len(self.var)):\n r += '{}: {}\\n'.format(self.var[i], self.var_descr[i])\nr += 'L-System Constants:\\n'\nfor i in range(0, len(self.con)):\n r += '{}: {}\\n'.format(sel... | <|body_start_0|>
self.var = var
self.con = con
self.var_descr = var_descr
self.con_descr = con_descr
<|end_body_0|>
<|body_start_1|>
r = 'L-System Variables:\n'
for i in range(0, len(self.var)):
r += '{}: {}\n'.format(self.var[i], self.var_descr[i])
r... | The L-system vocabulary | vocabulary | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class vocabulary:
"""The L-system vocabulary"""
def __init__(self, var: list, con: list, var_descr: list, con_descr: list) -> None:
"""Vocabulary parameters Parameters ---------- vocab : list The vocabulary members descr : list The description of the vocabulary members"""
<|body_0|... | stack_v2_sparse_classes_36k_train_017923 | 18,172 | permissive | [
{
"docstring": "Vocabulary parameters Parameters ---------- vocab : list The vocabulary members descr : list The description of the vocabulary members",
"name": "__init__",
"signature": "def __init__(self, var: list, con: list, var_descr: list, con_descr: list) -> None"
},
{
"docstring": "Format... | 2 | stack_v2_sparse_classes_30k_test_000323 | Implement the Python class `vocabulary` described below.
Class description:
The L-system vocabulary
Method signatures and docstrings:
- def __init__(self, var: list, con: list, var_descr: list, con_descr: list) -> None: Vocabulary parameters Parameters ---------- vocab : list The vocabulary members descr : list The d... | Implement the Python class `vocabulary` described below.
Class description:
The L-system vocabulary
Method signatures and docstrings:
- def __init__(self, var: list, con: list, var_descr: list, con_descr: list) -> None: Vocabulary parameters Parameters ---------- vocab : list The vocabulary members descr : list The d... | b47e951cc465f1d2d6ca4384b2bce05c6e96e2a0 | <|skeleton|>
class vocabulary:
"""The L-system vocabulary"""
def __init__(self, var: list, con: list, var_descr: list, con_descr: list) -> None:
"""Vocabulary parameters Parameters ---------- vocab : list The vocabulary members descr : list The description of the vocabulary members"""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class vocabulary:
"""The L-system vocabulary"""
def __init__(self, var: list, con: list, var_descr: list, con_descr: list) -> None:
"""Vocabulary parameters Parameters ---------- vocab : list The vocabulary members descr : list The description of the vocabulary members"""
self.var = var
... | the_stack_v2_python_sparse | Models/MarcMentat/evolve_soft_2d/evolve/lsystems.py | martinventer/Naude_Masters-Project | train | 0 |
c652428851eb81eab8ea3fa740d3fb1f52b51bfc | [
"K = len(probs)\nself.q = torch.zeros(K).cuda()\nself.J = torch.LongTensor([0] * K).cuda()\nsmaller = []\nlarger = []\nfor kk, prob in enumerate(probs):\n self.q[kk] = K * prob\n if self.q[kk] < 1.0:\n smaller.append(kk)\n else:\n larger.append(kk)\nwhile len(smaller) > 0 and len(larger) > 0:... | <|body_start_0|>
K = len(probs)
self.q = torch.zeros(K).cuda()
self.J = torch.LongTensor([0] * K).cuda()
smaller = []
larger = []
for kk, prob in enumerate(probs):
self.q[kk] = K * prob
if self.q[kk] < 1.0:
smaller.append(kk)
... | Fast sampling from a multinomial distribution. https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/ | AliasMultinomial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AliasMultinomial:
"""Fast sampling from a multinomial distribution. https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/"""
def __init__(self, probs):
"""probs: a float tensor with shape [K]. It represents probabilities of dif... | stack_v2_sparse_classes_36k_train_017924 | 29,814 | no_license | [
{
"docstring": "probs: a float tensor with shape [K]. It represents probabilities of different outcomes. There are K outcomes. Probabilities sum to one.",
"name": "__init__",
"signature": "def __init__(self, probs)"
},
{
"docstring": "Draw N samples from the distribution.",
"name": "draw",
... | 2 | stack_v2_sparse_classes_30k_train_016198 | Implement the Python class `AliasMultinomial` described below.
Class description:
Fast sampling from a multinomial distribution. https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
Method signatures and docstrings:
- def __init__(self, probs): probs: a float ... | Implement the Python class `AliasMultinomial` described below.
Class description:
Fast sampling from a multinomial distribution. https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/
Method signatures and docstrings:
- def __init__(self, probs): probs: a float ... | 82d3e9808073f2145b039ccf464c526cb85274e3 | <|skeleton|>
class AliasMultinomial:
"""Fast sampling from a multinomial distribution. https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/"""
def __init__(self, probs):
"""probs: a float tensor with shape [K]. It represents probabilities of dif... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AliasMultinomial:
"""Fast sampling from a multinomial distribution. https://hips.seas.harvard.edu/blog/2013/03/03/the-alias-method-efficient-sampling-with-many-discrete-outcomes/"""
def __init__(self, probs):
"""probs: a float tensor with shape [K]. It represents probabilities of different outcom... | the_stack_v2_python_sparse | business/p201908/3507_750/lda2vec_model.py | Alvin2580du/alvin_py | train | 12 |
488191c352f647b27d8df2026e5f4fbc6622f390 | [
"username = 'admin'\npassword = 'szx0982'\ncls.db = cls.connect_db(username, password)\nlogging.info('DBManager init success')",
"client = MongoClient(cls.HOST, cls.PORT)\ndbAuth = client.szx_admin\ndbAuth.authenticate(username, password)\nreturn client.szx_admin"
] | <|body_start_0|>
username = 'admin'
password = 'szx0982'
cls.db = cls.connect_db(username, password)
logging.info('DBManager init success')
<|end_body_0|>
<|body_start_1|>
client = MongoClient(cls.HOST, cls.PORT)
dbAuth = client.szx_admin
dbAuth.authenticate(user... | 数据库管理 | DBManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DBManager:
"""数据库管理"""
def init(cls):
"""数据库初始化"""
<|body_0|>
def connect_db(cls, username, password):
"""连接数据库"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
username = 'admin'
password = 'szx0982'
cls.db = cls.connect_db(usern... | stack_v2_sparse_classes_36k_train_017925 | 906 | no_license | [
{
"docstring": "数据库初始化",
"name": "init",
"signature": "def init(cls)"
},
{
"docstring": "连接数据库",
"name": "connect_db",
"signature": "def connect_db(cls, username, password)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000356 | Implement the Python class `DBManager` described below.
Class description:
数据库管理
Method signatures and docstrings:
- def init(cls): 数据库初始化
- def connect_db(cls, username, password): 连接数据库 | Implement the Python class `DBManager` described below.
Class description:
数据库管理
Method signatures and docstrings:
- def init(cls): 数据库初始化
- def connect_db(cls, username, password): 连接数据库
<|skeleton|>
class DBManager:
"""数据库管理"""
def init(cls):
"""数据库初始化"""
<|body_0|>
def connect_db(cls... | 5feaf8b466c125e93fd08f31cc0eed99c9b4d164 | <|skeleton|>
class DBManager:
"""数据库管理"""
def init(cls):
"""数据库初始化"""
<|body_0|>
def connect_db(cls, username, password):
"""连接数据库"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DBManager:
"""数据库管理"""
def init(cls):
"""数据库初始化"""
username = 'admin'
password = 'szx0982'
cls.db = cls.connect_db(username, password)
logging.info('DBManager init success')
def connect_db(cls, username, password):
"""连接数据库"""
client = MongoCli... | the_stack_v2_python_sparse | base/db/DBManger.py | goodcan/financial-system-backend | train | 1 |
cdff1d96ff767a993a1b3b35bb86b417dad60690 | [
"if n == 1:\n return True\nelif n == 0:\n return False\nelse:\n c = 0\n for i in bin(n):\n if c < 3:\n c += 1\n continue\n elif i == '1':\n return False\n return True",
"if n > 0 and n & n - 1 == 0:\n return True\nelse:\n return False",
"if n <... | <|body_start_0|>
if n == 1:
return True
elif n == 0:
return False
else:
c = 0
for i in bin(n):
if c < 3:
c += 1
continue
elif i == '1':
return False
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isPowerOfTwo_0(self, n: int) -> bool:
"""笨办法.遍历二进制码. 如果整数是2的幂次方,则其二进制数除了最高位是1,其余为都为0 :param n: :return:"""
<|body_0|>
def isPowerOfTwo_1(self, n: int) -> bool:
"""如果n是2的幂次方,则 n&n-1=0 举例: 8=>100 7=>111 8&7=0 :param n: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_017926 | 1,578 | permissive | [
{
"docstring": "笨办法.遍历二进制码. 如果整数是2的幂次方,则其二进制数除了最高位是1,其余为都为0 :param n: :return:",
"name": "isPowerOfTwo_0",
"signature": "def isPowerOfTwo_0(self, n: int) -> bool"
},
{
"docstring": "如果n是2的幂次方,则 n&n-1=0 举例: 8=>100 7=>111 8&7=0 :param n: :return:",
"name": "isPowerOfTwo_1",
"signature": "d... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo_0(self, n: int) -> bool: 笨办法.遍历二进制码. 如果整数是2的幂次方,则其二进制数除了最高位是1,其余为都为0 :param n: :return:
- def isPowerOfTwo_1(self, n: int) -> bool: 如果n是2的幂次方,则 n&n-1=0 举例: 8=>10... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isPowerOfTwo_0(self, n: int) -> bool: 笨办法.遍历二进制码. 如果整数是2的幂次方,则其二进制数除了最高位是1,其余为都为0 :param n: :return:
- def isPowerOfTwo_1(self, n: int) -> bool: 如果n是2的幂次方,则 n&n-1=0 举例: 8=>10... | 60e9ef1051a1d0441ab1c5484a51ab77a306bf5b | <|skeleton|>
class Solution:
def isPowerOfTwo_0(self, n: int) -> bool:
"""笨办法.遍历二进制码. 如果整数是2的幂次方,则其二进制数除了最高位是1,其余为都为0 :param n: :return:"""
<|body_0|>
def isPowerOfTwo_1(self, n: int) -> bool:
"""如果n是2的幂次方,则 n&n-1=0 举例: 8=>100 7=>111 8&7=0 :param n: :return:"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isPowerOfTwo_0(self, n: int) -> bool:
"""笨办法.遍历二进制码. 如果整数是2的幂次方,则其二进制数除了最高位是1,其余为都为0 :param n: :return:"""
if n == 1:
return True
elif n == 0:
return False
else:
c = 0
for i in bin(n):
if c < 3:
... | the_stack_v2_python_sparse | Week 7/id_710/LeetCode_231_710.py | chenlei65368/algorithm004-05 | train | 1 | |
4565c7b8b4dbc2832519dd865eb1f6c386495adb | [
"if applyTransform:\n boundPts = [obj.matrix_world * Vector(corner) for corner in obj.bound_box]\nelse:\n boundPts = obj.bound_box\nxmin = min([pt[0] for pt in boundPts])\nxmax = max([pt[0] for pt in boundPts])\nymin = min([pt[1] for pt in boundPts])\nymax = max([pt[1] for pt in boundPts])\nzmin = min([pt[2] ... | <|body_start_0|>
if applyTransform:
boundPts = [obj.matrix_world * Vector(corner) for corner in obj.bound_box]
else:
boundPts = obj.bound_box
xmin = min([pt[0] for pt in boundPts])
xmax = max([pt[0] for pt in boundPts])
ymin = min([pt[1] for pt in boundPts... | Utilities to build BBOX object from various Blender context | getBBOX | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class getBBOX:
"""Utilities to build BBOX object from various Blender context"""
def fromObj(obj, applyTransform=True):
"""Create a 3D BBOX from Blender object"""
<|body_0|>
def fromScn(cls, scn):
"""Create a 3D BBOX from Blender Scene union of bounding box of all obje... | stack_v2_sparse_classes_36k_train_017927 | 7,516 | no_license | [
{
"docstring": "Create a 3D BBOX from Blender object",
"name": "fromObj",
"signature": "def fromObj(obj, applyTransform=True)"
},
{
"docstring": "Create a 3D BBOX from Blender Scene union of bounding box of all objects containing in the scene",
"name": "fromScn",
"signature": "def fromSc... | 4 | stack_v2_sparse_classes_30k_train_003817 | Implement the Python class `getBBOX` described below.
Class description:
Utilities to build BBOX object from various Blender context
Method signatures and docstrings:
- def fromObj(obj, applyTransform=True): Create a 3D BBOX from Blender object
- def fromScn(cls, scn): Create a 3D BBOX from Blender Scene union of bou... | Implement the Python class `getBBOX` described below.
Class description:
Utilities to build BBOX object from various Blender context
Method signatures and docstrings:
- def fromObj(obj, applyTransform=True): Create a 3D BBOX from Blender object
- def fromScn(cls, scn): Create a 3D BBOX from Blender Scene union of bou... | c3469272f0775ca8c9ad98e74465e16610ef0983 | <|skeleton|>
class getBBOX:
"""Utilities to build BBOX object from various Blender context"""
def fromObj(obj, applyTransform=True):
"""Create a 3D BBOX from Blender object"""
<|body_0|>
def fromScn(cls, scn):
"""Create a 3D BBOX from Blender Scene union of bounding box of all obje... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class getBBOX:
"""Utilities to build BBOX object from various Blender context"""
def fromObj(obj, applyTransform=True):
"""Create a 3D BBOX from Blender object"""
if applyTransform:
boundPts = [obj.matrix_world * Vector(corner) for corner in obj.bound_box]
else:
... | the_stack_v2_python_sparse | operators/utils/bgis_utils.py | blendergis/BlenderGIS | train | 3 |
33139806453009cc9cadda8583218f6cc7d28f13 | [
"errors = []\nif not HAS_XMLTODICT:\n errors.append(missing_required_lib('xmltodict'))\nreturn errors",
"errors = self._check_reqs()\nif errors:\n return {'errors': errors}\ncli_output = self._task_args.get('text')\nnetwork_os = self._task_args.get('parser').get('os') or self._task_vars.get('ansible_network... | <|body_start_0|>
errors = []
if not HAS_XMLTODICT:
errors.append(missing_required_lib('xmltodict'))
return errors
<|end_body_0|>
<|body_start_1|>
errors = self._check_reqs()
if errors:
return {'errors': errors}
cli_output = self._task_args.get('te... | The xml parser class Convert an xml string to structured data using xmltodict | CliParser | [
"MIT",
"GPL-3.0-or-later",
"GPL-3.0-only",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CliParser:
"""The xml parser class Convert an xml string to structured data using xmltodict"""
def _check_reqs():
"""Check the prerequisites for the xml parser"""
<|body_0|>
def parse(self, *_args, **_kwargs):
"""Std entry point for a cli_parse parse execution :r... | stack_v2_sparse_classes_36k_train_017928 | 2,153 | permissive | [
{
"docstring": "Check the prerequisites for the xml parser",
"name": "_check_reqs",
"signature": "def _check_reqs()"
},
{
"docstring": "Std entry point for a cli_parse parse execution :return: Errors or parsed text as structured data :rtype: dict :example: The parse function of a parser should r... | 2 | stack_v2_sparse_classes_30k_test_000552 | Implement the Python class `CliParser` described below.
Class description:
The xml parser class Convert an xml string to structured data using xmltodict
Method signatures and docstrings:
- def _check_reqs(): Check the prerequisites for the xml parser
- def parse(self, *_args, **_kwargs): Std entry point for a cli_par... | Implement the Python class `CliParser` described below.
Class description:
The xml parser class Convert an xml string to structured data using xmltodict
Method signatures and docstrings:
- def _check_reqs(): Check the prerequisites for the xml parser
- def parse(self, *_args, **_kwargs): Std entry point for a cli_par... | 2ea7d4f00212f502bc684ac257371ada73da1ca9 | <|skeleton|>
class CliParser:
"""The xml parser class Convert an xml string to structured data using xmltodict"""
def _check_reqs():
"""Check the prerequisites for the xml parser"""
<|body_0|>
def parse(self, *_args, **_kwargs):
"""Std entry point for a cli_parse parse execution :r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CliParser:
"""The xml parser class Convert an xml string to structured data using xmltodict"""
def _check_reqs():
"""Check the prerequisites for the xml parser"""
errors = []
if not HAS_XMLTODICT:
errors.append(missing_required_lib('xmltodict'))
return errors
... | the_stack_v2_python_sparse | intro-ansible/venv3/lib/python3.8/site-packages/ansible_collections/ansible/netcommon/plugins/cli_parsers/xml_parser.py | SimonFangCisco/dne-dna-code | train | 0 |
6163f0a1adb85a9fe56b50b3065461837c654ae9 | [
"if device in cls.warned_devices:\n return\ncls.warned_devices.add(device)\nif fstype is None:\n logger.warning(f'Failed to determine filesystem type for {path} (device id: {device}). Using soft file locks to avoid potential data corruption.')\n return\nlogger.warning(f'The lock file {path} is on a filesys... | <|body_start_0|>
if device in cls.warned_devices:
return
cls.warned_devices.add(device)
if fstype is None:
logger.warning(f'Failed to determine filesystem type for {path} (device id: {device}). Using soft file locks to avoid potential data corruption.')
return... | This class is used to inspect the file system state and determine if the file being created can use `fcntl` / `flock` or should use soft file locks. This can be achieved by finding the device owning the parent directory and mapping it to the partition and finally checking the filesystem type. We prefer using soft file ... | FileSystemInspector | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileSystemInspector:
"""This class is used to inspect the file system state and determine if the file being created can use `fcntl` / `flock` or should use soft file locks. This can be achieved by finding the device owning the parent directory and mapping it to the partition and finally checking ... | stack_v2_sparse_classes_36k_train_017929 | 7,858 | permissive | [
{
"docstring": "Warn only once per device. This is used to avoid spamming the logs with the same message.",
"name": "_warn_only_once",
"signature": "def _warn_only_once(cls, path: str, device: int, fstype: Optional[str]) -> None"
},
{
"docstring": "Returns a mapping of device numbers to filesyst... | 4 | null | Implement the Python class `FileSystemInspector` described below.
Class description:
This class is used to inspect the file system state and determine if the file being created can use `fcntl` / `flock` or should use soft file locks. This can be achieved by finding the device owning the parent directory and mapping it... | Implement the Python class `FileSystemInspector` described below.
Class description:
This class is used to inspect the file system state and determine if the file being created can use `fcntl` / `flock` or should use soft file locks. This can be achieved by finding the device owning the parent directory and mapping it... | 34e5c2c29abe9b26699760074adcadfe8fd4cfe0 | <|skeleton|>
class FileSystemInspector:
"""This class is used to inspect the file system state and determine if the file being created can use `fcntl` / `flock` or should use soft file locks. This can be achieved by finding the device owning the parent directory and mapping it to the partition and finally checking ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileSystemInspector:
"""This class is used to inspect the file system state and determine if the file being created can use `fcntl` / `flock` or should use soft file locks. This can be achieved by finding the device owning the parent directory and mapping it to the partition and finally checking the filesyste... | the_stack_v2_python_sparse | src/python/aim/_core/storage/locking.py | aimhubio/aim | train | 4,091 |
4e9098d394baadbf5e1be6f80dfe0384f89b8690 | [
"super(CreateCuttlefishActionTest, self).setUp()\nself.build_client = mock.MagicMock()\nself.Patch(android_build_client, 'AndroidBuildClient', return_value=self.build_client)\nself.compute_client = mock.MagicMock()\nself.Patch(cvd_compute_client, 'CvdComputeClient', return_value=self.compute_client)\nself.Patch(cvd... | <|body_start_0|>
super(CreateCuttlefishActionTest, self).setUp()
self.build_client = mock.MagicMock()
self.Patch(android_build_client, 'AndroidBuildClient', return_value=self.build_client)
self.compute_client = mock.MagicMock()
self.Patch(cvd_compute_client, 'CvdComputeClient', r... | Test create_cuttlefish_action. | CreateCuttlefishActionTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateCuttlefishActionTest:
"""Test create_cuttlefish_action."""
def setUp(self):
"""Set up the test."""
<|body_0|>
def _CreateCfg(self):
"""A helper method that creates a mock configuration object."""
<|body_1|>
def testCreateDevices(self):
... | stack_v2_sparse_classes_36k_train_017930 | 7,513 | permissive | [
{
"docstring": "Set up the test.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "A helper method that creates a mock configuration object.",
"name": "_CreateCfg",
"signature": "def _CreateCfg(self)"
},
{
"docstring": "Test CreateDevices.",
"name": "testCr... | 3 | null | Implement the Python class `CreateCuttlefishActionTest` described below.
Class description:
Test create_cuttlefish_action.
Method signatures and docstrings:
- def setUp(self): Set up the test.
- def _CreateCfg(self): A helper method that creates a mock configuration object.
- def testCreateDevices(self): Test CreateD... | Implement the Python class `CreateCuttlefishActionTest` described below.
Class description:
Test create_cuttlefish_action.
Method signatures and docstrings:
- def setUp(self): Set up the test.
- def _CreateCfg(self): A helper method that creates a mock configuration object.
- def testCreateDevices(self): Test CreateD... | 78a61ca023cbf1a0cecfef8b97df2b274ac3a988 | <|skeleton|>
class CreateCuttlefishActionTest:
"""Test create_cuttlefish_action."""
def setUp(self):
"""Set up the test."""
<|body_0|>
def _CreateCfg(self):
"""A helper method that creates a mock configuration object."""
<|body_1|>
def testCreateDevices(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CreateCuttlefishActionTest:
"""Test create_cuttlefish_action."""
def setUp(self):
"""Set up the test."""
super(CreateCuttlefishActionTest, self).setUp()
self.build_client = mock.MagicMock()
self.Patch(android_build_client, 'AndroidBuildClient', return_value=self.build_clie... | the_stack_v2_python_sparse | tools/acloud/public/actions/create_cuttlefish_action_test.py | ZYHGOD-1/Aosp11 | train | 0 |
9796b6b007d6c0cfe68ac39cb8d29628b4836f51 | [
"self.csv_features = {}\nself.meta_features = []\nself.logger = fmeobjects.FMELogFile()\nself.session = FME_utils.create_session()",
"order = feature.getAttribute(ORDER)\nif order == 1:\n default_key = feature.getAttribute('default_key')\n default_value = feature.getAttribute('default_value')\n self.csv_... | <|body_start_0|>
self.csv_features = {}
self.meta_features = []
self.logger = fmeobjects.FMELogFile()
self.session = FME_utils.create_session()
<|end_body_0|>
<|body_start_1|>
order = feature.getAttribute(ORDER)
if order == 1:
default_key = feature.getAttribu... | This class implement the design pattern: *Processing Composite Data* | FeatureProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureProcessor:
"""This class implement the design pattern: *Processing Composite Data*"""
def __init__(self):
"""This constructor method created a dictionary and a list to store the features."""
<|body_0|>
def input(self, feature):
"""Load the incoming feature... | stack_v2_sparse_classes_36k_train_017931 | 6,105 | permissive | [
{
"docstring": "This constructor method created a dictionary and a list to store the features.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Load the incoming features. The features from the CSV (_order=1) are stored in a dictionary according to the unique format nam... | 4 | null | Implement the Python class `FeatureProcessor` described below.
Class description:
This class implement the design pattern: *Processing Composite Data*
Method signatures and docstrings:
- def __init__(self): This constructor method created a dictionary and a list to store the features.
- def input(self, feature): Load... | Implement the Python class `FeatureProcessor` described below.
Class description:
This class implement the design pattern: *Processing Composite Data*
Method signatures and docstrings:
- def __init__(self): This constructor method created a dictionary and a list to store the features.
- def input(self, feature): Load... | 82368614a2658260c0f09a1b5d341918310626e5 | <|skeleton|>
class FeatureProcessor:
"""This class implement the design pattern: *Processing Composite Data*"""
def __init__(self):
"""This constructor method created a dictionary and a list to store the features."""
<|body_0|>
def input(self, feature):
"""Load the incoming feature... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureProcessor:
"""This class implement the design pattern: *Processing Composite Data*"""
def __init__(self):
"""This constructor method created a dictionary and a list to store the features."""
self.csv_features = {}
self.meta_features = []
self.logger = fmeobjects.FME... | the_stack_v2_python_sparse | FME_files/FME_Custom_Transformers/Python/GEOPORTAL_WEBLINK_ADDER_NG.py | federal-geospatial-platform/fgp-metadata-proxy | train | 10 |
396fd021d2a349856c3822a0a3d6b26428400bf7 | [
"url = await SourceCollector._api_url(self)\ncomponent = self._parameter('component')\nbranch = self._parameter('branch')\nreturn URL(f'{url}/project/issues?id={component}&branch={branch}')",
"url = await SourceCollector._api_url(self)\ncomponent = self._parameter('component')\nbranch = self._parameter('branch')\... | <|body_start_0|>
url = await SourceCollector._api_url(self)
component = self._parameter('component')
branch = self._parameter('branch')
return URL(f'{url}/project/issues?id={component}&branch={branch}')
<|end_body_0|>
<|body_start_1|>
url = await SourceCollector._api_url(self)
... | SonarQube suppressed violations collector. | SonarQubeSuppressedViolations | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SonarQubeSuppressedViolations:
"""SonarQube suppressed violations collector."""
async def _landing_url(self, responses: SourceResponses) -> URL:
"""Override to not include the rules parameter in the landing URL. This collector uses two SonarQube endpoints to get the suppressed violat... | stack_v2_sparse_classes_36k_train_017932 | 2,824 | permissive | [
{
"docstring": "Override to not include the rules parameter in the landing URL. This collector uses two SonarQube endpoints to get the suppressed violations. As we can't include both URLs in the landing URL, we use the overview of all issues as landing page.",
"name": "_landing_url",
"signature": "async... | 4 | null | Implement the Python class `SonarQubeSuppressedViolations` described below.
Class description:
SonarQube suppressed violations collector.
Method signatures and docstrings:
- async def _landing_url(self, responses: SourceResponses) -> URL: Override to not include the rules parameter in the landing URL. This collector ... | Implement the Python class `SonarQubeSuppressedViolations` described below.
Class description:
SonarQube suppressed violations collector.
Method signatures and docstrings:
- async def _landing_url(self, responses: SourceResponses) -> URL: Override to not include the rules parameter in the landing URL. This collector ... | 5d9952bf0bd47895824fa78428d3e4f4d6b5d9b3 | <|skeleton|>
class SonarQubeSuppressedViolations:
"""SonarQube suppressed violations collector."""
async def _landing_url(self, responses: SourceResponses) -> URL:
"""Override to not include the rules parameter in the landing URL. This collector uses two SonarQube endpoints to get the suppressed violat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SonarQubeSuppressedViolations:
"""SonarQube suppressed violations collector."""
async def _landing_url(self, responses: SourceResponses) -> URL:
"""Override to not include the rules parameter in the landing URL. This collector uses two SonarQube endpoints to get the suppressed violations. As we c... | the_stack_v2_python_sparse | components/collector/src/source_collectors/sonarqube/suppressed_violations.py | ICTU/quality-time | train | 43 |
142bc8a0fe3973592e486549f618261f42c5f9dc | [
"self.project = project\nself.date = date\nself.dest = dest",
"pattern = 'cat /home/logs/vm-lnx-idpdm*/httpd/{project}.ncep.noaa.gov/access.{year}{month:02d}{day:02}'\nif self.date != dt.date.today():\n pattern += '.gz'\nkwargs = {'project': self.project, 'year': self.date.year, 'month': self.date.month, 'day'... | <|body_start_0|>
self.project = project
self.date = date
self.dest = dest
<|end_body_0|>
<|body_start_1|>
pattern = 'cat /home/logs/vm-lnx-idpdm*/httpd/{project}.ncep.noaa.gov/access.{year}{month:02d}{day:02}'
if self.date != dt.date.today():
pattern += '.gz'
... | Download and count log file hits for a single day. Attributes ---------- project : str Specifies the project to process. date : datetime.date Defines year and month for log file merging. logfiles : list List of log files for the given month. | DailyApacheLogCount | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DailyApacheLogCount:
"""Download and count log file hits for a single day. Attributes ---------- project : str Specifies the project to process. date : datetime.date Defines year and month for log file merging. logfiles : list List of log files for the given month."""
def __init__(self, proj... | stack_v2_sparse_classes_36k_train_017933 | 2,546 | no_license | [
{
"docstring": "Parameters ---------- date : datetime.date Defines date for daily log file hits counting. dest : str CSV file",
"name": "__init__",
"signature": "def __init__(self, project, date, dest)"
},
{
"docstring": "Count the number of items in the files",
"name": "run",
"signature... | 2 | stack_v2_sparse_classes_30k_test_000994 | Implement the Python class `DailyApacheLogCount` described below.
Class description:
Download and count log file hits for a single day. Attributes ---------- project : str Specifies the project to process. date : datetime.date Defines year and month for log file merging. logfiles : list List of log files for the given... | Implement the Python class `DailyApacheLogCount` described below.
Class description:
Download and count log file hits for a single day. Attributes ---------- project : str Specifies the project to process. date : datetime.date Defines year and month for log file merging. logfiles : list List of log files for the given... | 8002cd4822a61075b365b3823d574f3c0ecc3b45 | <|skeleton|>
class DailyApacheLogCount:
"""Download and count log file hits for a single day. Attributes ---------- project : str Specifies the project to process. date : datetime.date Defines year and month for log file merging. logfiles : list List of log files for the given month."""
def __init__(self, proj... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DailyApacheLogCount:
"""Download and count log file hits for a single day. Attributes ---------- project : str Specifies the project to process. date : datetime.date Defines year and month for log file merging. logfiles : list List of log files for the given month."""
def __init__(self, project, date, de... | the_stack_v2_python_sparse | abusive-user-detection/gis_utilities/daily_log_merge.py | quintusdias/gis-monitoring | train | 0 |
612dc6af577ba900d27d448d62eb286d4a04b347 | [
"format_file = 'csv'\nkwargs = locals()\nkwargs['schema'] = _check_schema(kwargs['schema'])\ntmp = _apply_datareader(format_file, kwargs)\nreturn tmp",
"format_file = 'json'\nkwargs = locals()\nkwargs['schema'] = _check_schema(kwargs['schema'])\ntmp = _apply_datareader(format_file, kwargs)\nreturn tmp",
"format... | <|body_start_0|>
format_file = 'csv'
kwargs = locals()
kwargs['schema'] = _check_schema(kwargs['schema'])
tmp = _apply_datareader(format_file, kwargs)
return tmp
<|end_body_0|>
<|body_start_1|>
format_file = 'json'
kwargs = locals()
kwargs['schema'] = _ch... | DataReader | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataReader:
def csv(filepath, num_of_parts='*', schema='str', sep=',', header=True, delimiter=None, na_filter=True, usecols=None, prefix=None, engine=None, converters=None, true_values=None, false_values=None, skipinitialspace=False, na_values=None, keep_default_na=True, skip_blank_lines=True, p... | stack_v2_sparse_classes_36k_train_017934 | 7,699 | permissive | [
{
"docstring": "Reads a csv file. :param filepath: :param num_of_parts: :param schema: :param sep: :param header: :param delimiter: :param na_filter: :param usecols: :param prefix: :param engine: :param converters: :param true_values: :param false_values: :param skipinitialspace: :param na_values: :param keep_d... | 4 | stack_v2_sparse_classes_30k_train_018123 | Implement the Python class `DataReader` described below.
Class description:
Implement the DataReader class.
Method signatures and docstrings:
- def csv(filepath, num_of_parts='*', schema='str', sep=',', header=True, delimiter=None, na_filter=True, usecols=None, prefix=None, engine=None, converters=None, true_values=N... | Implement the Python class `DataReader` described below.
Class description:
Implement the DataReader class.
Method signatures and docstrings:
- def csv(filepath, num_of_parts='*', schema='str', sep=',', header=True, delimiter=None, na_filter=True, usecols=None, prefix=None, engine=None, converters=None, true_values=N... | 09ab7c474c8badc9932de3e1148f62ffba16b0b2 | <|skeleton|>
class DataReader:
def csv(filepath, num_of_parts='*', schema='str', sep=',', header=True, delimiter=None, na_filter=True, usecols=None, prefix=None, engine=None, converters=None, true_values=None, false_values=None, skipinitialspace=False, na_values=None, keep_default_na=True, skip_blank_lines=True, p... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataReader:
def csv(filepath, num_of_parts='*', schema='str', sep=',', header=True, delimiter=None, na_filter=True, usecols=None, prefix=None, engine=None, converters=None, true_values=None, false_values=None, skipinitialspace=False, na_values=None, keep_default_na=True, skip_blank_lines=True, parse_dates=Fal... | the_stack_v2_python_sparse | ddf_library/bases/data_reader.py | eubr-bigsea/Compss-Python | train | 3 | |
2f3a397abb79415922ead343d429dc1111c7d23a | [
"self._sensors = sensors\nself._const = const\nself.firmware = {}\nself.requested = {}\nself.started = {}\nself.unstarted = {}",
"fw_type = None\nfw_ver = None\nif not isinstance(updates, tuple):\n updates = (updates,)\nfor store in updates:\n fw_id = store.pop(msg.node_id, None)\n if fw_id is not None:\... | <|body_start_0|>
self._sensors = sensors
self._const = const
self.firmware = {}
self.requested = {}
self.started = {}
self.unstarted = {}
<|end_body_0|>
<|body_start_1|>
fw_type = None
fw_ver = None
if not isinstance(updates, tuple):
u... | Organize OTAFirmware updates. | OTAFirmware | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OTAFirmware:
"""Organize OTAFirmware updates."""
def __init__(self, sensors, const):
"""Set up OTA firmware instance."""
<|body_0|>
def _get_fw(self, msg, updates, req_fw_type=None, req_fw_ver=None):
"""Get firmware type, version and a dict holding binary data.""... | stack_v2_sparse_classes_36k_train_017935 | 6,845 | permissive | [
{
"docstring": "Set up OTA firmware instance.",
"name": "__init__",
"signature": "def __init__(self, sensors, const)"
},
{
"docstring": "Get firmware type, version and a dict holding binary data.",
"name": "_get_fw",
"signature": "def _get_fw(self, msg, updates, req_fw_type=None, req_fw_... | 5 | stack_v2_sparse_classes_30k_train_013616 | Implement the Python class `OTAFirmware` described below.
Class description:
Organize OTAFirmware updates.
Method signatures and docstrings:
- def __init__(self, sensors, const): Set up OTA firmware instance.
- def _get_fw(self, msg, updates, req_fw_type=None, req_fw_ver=None): Get firmware type, version and a dict h... | Implement the Python class `OTAFirmware` described below.
Class description:
Organize OTAFirmware updates.
Method signatures and docstrings:
- def __init__(self, sensors, const): Set up OTA firmware instance.
- def _get_fw(self, msg, updates, req_fw_type=None, req_fw_ver=None): Get firmware type, version and a dict h... | f7264321986a66193192a10f3261fe268eeb7601 | <|skeleton|>
class OTAFirmware:
"""Organize OTAFirmware updates."""
def __init__(self, sensors, const):
"""Set up OTA firmware instance."""
<|body_0|>
def _get_fw(self, msg, updates, req_fw_type=None, req_fw_ver=None):
"""Get firmware type, version and a dict holding binary data.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OTAFirmware:
"""Organize OTAFirmware updates."""
def __init__(self, sensors, const):
"""Set up OTA firmware instance."""
self._sensors = sensors
self._const = const
self.firmware = {}
self.requested = {}
self.started = {}
self.unstarted = {}
de... | the_stack_v2_python_sparse | mysensors/ota.py | theolind/pymysensors | train | 68 |
656256fb8189a363ae884d547f42ee47acf4f06b | [
"matrix = copy.deepcopy(grid)\nxLength = len(grid)\nyLength = xLength and len(grid[0])\nfor i in range(1, xLength):\n matrix[i][0] += matrix[i - 1][0]\nfor i in range(1, yLength):\n matrix[0][i] += matrix[0][i - 1]\nfor i in range(1, xLength):\n for j in range(1, yLength):\n matrix[i][j] += min(matr... | <|body_start_0|>
matrix = copy.deepcopy(grid)
xLength = len(grid)
yLength = xLength and len(grid[0])
for i in range(1, xLength):
matrix[i][0] += matrix[i - 1][0]
for i in range(1, yLength):
matrix[0][i] += matrix[0][i - 1]
for i in range(1, xLength... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum2(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
matrix = copy.deepcopy(grid)
... | stack_v2_sparse_classes_36k_train_017936 | 1,207 | permissive | [
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minPathSum",
"signature": "def minPathSum(self, grid)"
},
{
"docstring": ":type grid: List[List[int]] :rtype: int",
"name": "minPathSum2",
"signature": "def minPathSum2(self, grid)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum2(self, grid): :type grid: List[List[int]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minPathSum(self, grid): :type grid: List[List[int]] :rtype: int
- def minPathSum2(self, grid): :type grid: List[List[int]] :rtype: int
<|skeleton|>
class Solution:
def ... | c8bf33af30569177c5276ffcd72a8d93ba4c402a | <|skeleton|>
class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_0|>
def minPathSum2(self, grid):
""":type grid: List[List[int]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minPathSum(self, grid):
""":type grid: List[List[int]] :rtype: int"""
matrix = copy.deepcopy(grid)
xLength = len(grid)
yLength = xLength and len(grid[0])
for i in range(1, xLength):
matrix[i][0] += matrix[i - 1][0]
for i in range(1, yLe... | the_stack_v2_python_sparse | 1-100/61-70/64-minimumPathSum/minimumPathSum.py | xuychen/Leetcode | train | 0 | |
100bf4227863d859549157f6294da31fa184ab24 | [
"self.parameters = parameters\nself._tree = None\nself._paths = None\nreturn",
"if self._tree is None:\n parameters = self.parameters[:]\n leaves = parameters.pop()\n parameters.reverse()\n tree = [TreeNode(Parameters(leaves.name, leaf)) for leaf in leaves.parameters]\n for level in parameters:\n ... | <|body_start_0|>
self.parameters = parameters
self._tree = None
self._paths = None
return
<|end_body_0|>
<|body_start_1|>
if self._tree is None:
parameters = self.parameters[:]
leaves = parameters.pop()
parameters.reverse()
tree = ... | A class to build a tree from iterative parameters The main product is the `paths` attribute which can be iterated over to get the parameters for a test. | ParameterTree | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParameterTree:
"""A class to build a tree from iterative parameters The main product is the `paths` attribute which can be iterated over to get the parameters for a test."""
def __init__(self, parameters):
""":param: - `parameters`: list of parameter objects with a `name` property"""... | stack_v2_sparse_classes_36k_train_017937 | 3,506 | permissive | [
{
"docstring": ":param: - `parameters`: list of parameter objects with a `name` property",
"name": "__init__",
"signature": "def __init__(self, parameters)"
},
{
"docstring": "builds the tree bottoms-up from the parameters :return: list of trees (highest nodes are parameters[0], leaves are param... | 4 | stack_v2_sparse_classes_30k_train_012207 | Implement the Python class `ParameterTree` described below.
Class description:
A class to build a tree from iterative parameters The main product is the `paths` attribute which can be iterated over to get the parameters for a test.
Method signatures and docstrings:
- def __init__(self, parameters): :param: - `paramet... | Implement the Python class `ParameterTree` described below.
Class description:
A class to build a tree from iterative parameters The main product is the `paths` attribute which can be iterated over to get the parameters for a test.
Method signatures and docstrings:
- def __init__(self, parameters): :param: - `paramet... | b4d1c77e1d611fe2b30768b42bdc7493afb0ea95 | <|skeleton|>
class ParameterTree:
"""A class to build a tree from iterative parameters The main product is the `paths` attribute which can be iterated over to get the parameters for a test."""
def __init__(self, parameters):
""":param: - `parameters`: list of parameter objects with a `name` property"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParameterTree:
"""A class to build a tree from iterative parameters The main product is the `paths` attribute which can be iterated over to get the parameters for a test."""
def __init__(self, parameters):
""":param: - `parameters`: list of parameter objects with a `name` property"""
self... | the_stack_v2_python_sparse | apetools/lexicographers/parametertree.py | russell-n/oldape | train | 0 |
75064ee9a463a109fc0d4c9876edce92211b627d | [
"user = request.user\nway = Way.get_by_id(way_id)\nif not way:\n return RESPONSE_400_OBJECT_NOT_FOUND\nif not user == way.user:\n return RESPONSE_403_ACCESS_DENIED\nif not notification_id:\n data = [notification.to_dict() for notification in way.notifications.all().order_by('week_day')]\n return JsonRes... | <|body_start_0|>
user = request.user
way = Way.get_by_id(way_id)
if not way:
return RESPONSE_400_OBJECT_NOT_FOUND
if not user == way.user:
return RESPONSE_403_ACCESS_DENIED
if not notification_id:
data = [notification.to_dict() for notification... | Notification view that handles GET, POST, PUT, DELETE requests and provides appropriate operations with notification model. | NotificationView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NotificationView:
"""Notification view that handles GET, POST, PUT, DELETE requests and provides appropriate operations with notification model."""
def get(self, request, way_id, notification_id=None):
"""Method that handles GET request."""
<|body_0|>
def put(self, reque... | stack_v2_sparse_classes_36k_train_017938 | 4,575 | no_license | [
{
"docstring": "Method that handles GET request.",
"name": "get",
"signature": "def get(self, request, way_id, notification_id=None)"
},
{
"docstring": "Method that handles PUT request.",
"name": "put",
"signature": "def put(self, request, way_id, notification_id=None)"
},
{
"doc... | 4 | stack_v2_sparse_classes_30k_train_000561 | Implement the Python class `NotificationView` described below.
Class description:
Notification view that handles GET, POST, PUT, DELETE requests and provides appropriate operations with notification model.
Method signatures and docstrings:
- def get(self, request, way_id, notification_id=None): Method that handles GE... | Implement the Python class `NotificationView` described below.
Class description:
Notification view that handles GET, POST, PUT, DELETE requests and provides appropriate operations with notification model.
Method signatures and docstrings:
- def get(self, request, way_id, notification_id=None): Method that handles GE... | c5f533bd049f6939037b14045e2aa2550aaac36a | <|skeleton|>
class NotificationView:
"""Notification view that handles GET, POST, PUT, DELETE requests and provides appropriate operations with notification model."""
def get(self, request, way_id, notification_id=None):
"""Method that handles GET request."""
<|body_0|>
def put(self, reque... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NotificationView:
"""Notification view that handles GET, POST, PUT, DELETE requests and provides appropriate operations with notification model."""
def get(self, request, way_id, notification_id=None):
"""Method that handles GET request."""
user = request.user
way = Way.get_by_id(... | the_stack_v2_python_sparse | way_to_home/notification/views.py | Lv-365python/wayToHome | train | 1 |
34b3ec9886ea5db9563fc67b1d7d9ae3031b15a5 | [
"node_list = response.xpath(\"//tr[@class='even'] | //tr[@class='odd']\")\nfor node in node_list:\n item = TencentItem()\n item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()\n item['position_link'] = 'https://hr.tencent.com/' + node.xpath('./td[1]/a/@href').extract_first()\n item['po... | <|body_start_0|>
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
for node in node_list:
item = TencentItem()
item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()
item['position_link'] = 'https://hr.tencent.com/' + node.xpath('.... | TencentCrawlSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TencentCrawlSpider:
def parse_page(self, response):
"""默认列表页的解析方法"""
<|body_0|>
def parse_detail(self, response):
"""解析详情页的响应内容"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
... | stack_v2_sparse_classes_36k_train_017939 | 2,542 | no_license | [
{
"docstring": "默认列表页的解析方法",
"name": "parse_page",
"signature": "def parse_page(self, response)"
},
{
"docstring": "解析详情页的响应内容",
"name": "parse_detail",
"signature": "def parse_detail(self, response)"
}
] | 2 | null | Implement the Python class `TencentCrawlSpider` described below.
Class description:
Implement the TencentCrawlSpider class.
Method signatures and docstrings:
- def parse_page(self, response): 默认列表页的解析方法
- def parse_detail(self, response): 解析详情页的响应内容 | Implement the Python class `TencentCrawlSpider` described below.
Class description:
Implement the TencentCrawlSpider class.
Method signatures and docstrings:
- def parse_page(self, response): 默认列表页的解析方法
- def parse_detail(self, response): 解析详情页的响应内容
<|skeleton|>
class TencentCrawlSpider:
def parse_page(self, re... | a51e31acff41292e568ac22b0e213e6cb48218fa | <|skeleton|>
class TencentCrawlSpider:
def parse_page(self, response):
"""默认列表页的解析方法"""
<|body_0|>
def parse_detail(self, response):
"""解析详情页的响应内容"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TencentCrawlSpider:
def parse_page(self, response):
"""默认列表页的解析方法"""
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
for node in node_list:
item = TencentItem()
item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()
... | the_stack_v2_python_sparse | 爬虫项目/code10/2.Spider类多级页面数据采集/Tencent2/Tencent2/spiders/tencent_crawl.py | byst4nder/his_spider | train | 1 | |
de16b5d3e4695e00c3c38680f1151f0318ba91a5 | [
"if not nums:\n return 0\nif val not in nums:\n return len(nums)\npos = 0\nwhile True:\n if pos == len(nums) or not len(nums):\n break\n if nums[pos] == val:\n del nums[pos]\n else:\n pos += 1\nreturn len(nums)",
"if not nums:\n return 0\ni = 0\nwhile i < len(nums):\n if ... | <|body_start_0|>
if not nums:
return 0
if val not in nums:
return len(nums)
pos = 0
while True:
if pos == len(nums) or not len(nums):
break
if nums[pos] == val:
del nums[pos]
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeElement_old(self, nums: List[int], val: int) -> int:
"""老方法 48 ms 13.9 MB Python3"""
<|body_0|>
def removeElement(self, nums: List[int], val: int) -> int:
"""20191021 40 ms 13.6 MB Python3"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_017940 | 1,167 | no_license | [
{
"docstring": "老方法 48 ms 13.9 MB Python3",
"name": "removeElement_old",
"signature": "def removeElement_old(self, nums: List[int], val: int) -> int"
},
{
"docstring": "20191021 40 ms 13.6 MB Python3",
"name": "removeElement",
"signature": "def removeElement(self, nums: List[int], val: i... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement_old(self, nums: List[int], val: int) -> int: 老方法 48 ms 13.9 MB Python3
- def removeElement(self, nums: List[int], val: int) -> int: 20191021 40 ms 13.6 MB Pytho... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeElement_old(self, nums: List[int], val: int) -> int: 老方法 48 ms 13.9 MB Python3
- def removeElement(self, nums: List[int], val: int) -> int: 20191021 40 ms 13.6 MB Pytho... | 99a3abf1774933af73a8405f9b59e5e64906bca4 | <|skeleton|>
class Solution:
def removeElement_old(self, nums: List[int], val: int) -> int:
"""老方法 48 ms 13.9 MB Python3"""
<|body_0|>
def removeElement(self, nums: List[int], val: int) -> int:
"""20191021 40 ms 13.6 MB Python3"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeElement_old(self, nums: List[int], val: int) -> int:
"""老方法 48 ms 13.9 MB Python3"""
if not nums:
return 0
if val not in nums:
return len(nums)
pos = 0
while True:
if pos == len(nums) or not len(nums):
... | the_stack_v2_python_sparse | leetcode/27.remove_element.py | iamkissg/leetcode | train | 0 | |
907b81588ab02d14608e7dddba7c100b9aaf33a7 | [
"super().__init__(entry, controller, poolObject, **kwargs)\nself._attr_device_class = device_class\nself._rounding_factor = rounding_factor\nself._attr_state_class = SensorStateClass.MEASUREMENT",
"value = str(self._poolObject[self._attribute_key])\nif self._rounding_factor:\n value = str(int(round(int(value) ... | <|body_start_0|>
super().__init__(entry, controller, poolObject, **kwargs)
self._attr_device_class = device_class
self._rounding_factor = rounding_factor
self._attr_state_class = SensorStateClass.MEASUREMENT
<|end_body_0|>
<|body_start_1|>
value = str(self._poolObject[self._attr... | Representation of an Pentair sensor. | PoolSensor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PoolSensor:
"""Representation of an Pentair sensor."""
def __init__(self, entry: ConfigEntry, controller: ModelController, poolObject: PoolObject, device_class: Optional[SensorDeviceClass], rounding_factor: int=0, **kwargs):
"""Initialize."""
<|body_0|>
def state(self) -... | stack_v2_sparse_classes_36k_train_017941 | 7,986 | no_license | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, entry: ConfigEntry, controller: ModelController, poolObject: PoolObject, device_class: Optional[SensorDeviceClass], rounding_factor: int=0, **kwargs)"
},
{
"docstring": "Return the state of the sensor.",
"name... | 3 | stack_v2_sparse_classes_30k_train_006163 | Implement the Python class `PoolSensor` described below.
Class description:
Representation of an Pentair sensor.
Method signatures and docstrings:
- def __init__(self, entry: ConfigEntry, controller: ModelController, poolObject: PoolObject, device_class: Optional[SensorDeviceClass], rounding_factor: int=0, **kwargs):... | Implement the Python class `PoolSensor` described below.
Class description:
Representation of an Pentair sensor.
Method signatures and docstrings:
- def __init__(self, entry: ConfigEntry, controller: ModelController, poolObject: PoolObject, device_class: Optional[SensorDeviceClass], rounding_factor: int=0, **kwargs):... | 625290c164c60611f501ee773583c06a85281300 | <|skeleton|>
class PoolSensor:
"""Representation of an Pentair sensor."""
def __init__(self, entry: ConfigEntry, controller: ModelController, poolObject: PoolObject, device_class: Optional[SensorDeviceClass], rounding_factor: int=0, **kwargs):
"""Initialize."""
<|body_0|>
def state(self) -... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PoolSensor:
"""Representation of an Pentair sensor."""
def __init__(self, entry: ConfigEntry, controller: ModelController, poolObject: PoolObject, device_class: Optional[SensorDeviceClass], rounding_factor: int=0, **kwargs):
"""Initialize."""
super().__init__(entry, controller, poolObject... | the_stack_v2_python_sparse | custom_components/intellicenter/sensor.py | ntalekt/homeassistant | train | 213 |
91c9e47fe12440e5c5c9e766820f87cf132199b3 | [
"abort_if_product_doesnt_exist(product_id)\nproduct = ProductModel.query.get(product_id)\nreturn product.serialize",
"abort_if_product_doesnt_exist(product_id)\nproduct = ProductModel.query.get(product_id)\ndb.session.delete(product)\ndb.session.commit()\nreturn ('', 204)",
"args = parser.parse_args()\nproduct ... | <|body_start_0|>
abort_if_product_doesnt_exist(product_id)
product = ProductModel.query.get(product_id)
return product.serialize
<|end_body_0|>
<|body_start_1|>
abort_if_product_doesnt_exist(product_id)
product = ProductModel.query.get(product_id)
db.session.delete(produ... | Flask-Restful Implementation of API for Product. | Product | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Product:
"""Flask-Restful Implementation of API for Product."""
def get(self, product_id):
"""Checks to see if Product record with id={product_id} exist, and if so serialize and return it. Args: product_id(int): Id of product to retrieve. Returns: Serialized dict/json data containing... | stack_v2_sparse_classes_36k_train_017942 | 4,455 | no_license | [
{
"docstring": "Checks to see if Product record with id={product_id} exist, and if so serialize and return it. Args: product_id(int): Id of product to retrieve. Returns: Serialized dict/json data containing the information for one product and a status code of 200.",
"name": "get",
"signature": "def get(... | 3 | stack_v2_sparse_classes_30k_train_014840 | Implement the Python class `Product` described below.
Class description:
Flask-Restful Implementation of API for Product.
Method signatures and docstrings:
- def get(self, product_id): Checks to see if Product record with id={product_id} exist, and if so serialize and return it. Args: product_id(int): Id of product t... | Implement the Python class `Product` described below.
Class description:
Flask-Restful Implementation of API for Product.
Method signatures and docstrings:
- def get(self, product_id): Checks to see if Product record with id={product_id} exist, and if so serialize and return it. Args: product_id(int): Id of product t... | 15c675b997da64d3b2c6d7fcae147edcdd55858d | <|skeleton|>
class Product:
"""Flask-Restful Implementation of API for Product."""
def get(self, product_id):
"""Checks to see if Product record with id={product_id} exist, and if so serialize and return it. Args: product_id(int): Id of product to retrieve. Returns: Serialized dict/json data containing... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Product:
"""Flask-Restful Implementation of API for Product."""
def get(self, product_id):
"""Checks to see if Product record with id={product_id} exist, and if so serialize and return it. Args: product_id(int): Id of product to retrieve. Returns: Serialized dict/json data containing the informat... | the_stack_v2_python_sparse | DiamondCaseWeb/api/product.py | engineering-diamondcasehair/diamonds | train | 0 |
5b13fffd940cacac656b8504e7f9c5c0d540b991 | [
"available_cars = []\nall_cars = self.get_full_content()\nfor car in all_cars:\n if not car.is_booked():\n available_cars.append(car)\nreturn available_cars",
"booked_cars = []\nall_cars = self.get_full_content()\nfor car in all_cars:\n if car.is_booked():\n booked_cars.append(car)\nreturn boo... | <|body_start_0|>
available_cars = []
all_cars = self.get_full_content()
for car in all_cars:
if not car.is_booked():
available_cars.append(car)
return available_cars
<|end_body_0|>
<|body_start_1|>
booked_cars = []
all_cars = self.get_full_con... | CarService | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CarService:
def get_available_cars(self):
"""Saekir alla bila sem eru ekki i leigu og skilar theim"""
<|body_0|>
def get_booked_cars(self):
"""Saekir alla bila sem eru i leigu og skilar theim"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
available... | stack_v2_sparse_classes_36k_train_017943 | 836 | no_license | [
{
"docstring": "Saekir alla bila sem eru ekki i leigu og skilar theim",
"name": "get_available_cars",
"signature": "def get_available_cars(self)"
},
{
"docstring": "Saekir alla bila sem eru i leigu og skilar theim",
"name": "get_booked_cars",
"signature": "def get_booked_cars(self)"
}
... | 2 | stack_v2_sparse_classes_30k_train_001192 | Implement the Python class `CarService` described below.
Class description:
Implement the CarService class.
Method signatures and docstrings:
- def get_available_cars(self): Saekir alla bila sem eru ekki i leigu og skilar theim
- def get_booked_cars(self): Saekir alla bila sem eru i leigu og skilar theim | Implement the Python class `CarService` described below.
Class description:
Implement the CarService class.
Method signatures and docstrings:
- def get_available_cars(self): Saekir alla bila sem eru ekki i leigu og skilar theim
- def get_booked_cars(self): Saekir alla bila sem eru i leigu og skilar theim
<|skeleton|... | c9533d91081ab5ac34467e367d10efc1c1c75746 | <|skeleton|>
class CarService:
def get_available_cars(self):
"""Saekir alla bila sem eru ekki i leigu og skilar theim"""
<|body_0|>
def get_booked_cars(self):
"""Saekir alla bila sem eru i leigu og skilar theim"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CarService:
def get_available_cars(self):
"""Saekir alla bila sem eru ekki i leigu og skilar theim"""
available_cars = []
all_cars = self.get_full_content()
for car in all_cars:
if not car.is_booked():
available_cars.append(car)
return availa... | the_stack_v2_python_sparse | services/CarService.py | superhetja/verkefni1 | train | 0 | |
bb9b51346698c76cb60c28b9861b494958c59a6e | [
"self.app = createApp(TestConfig)\nself.appContext = self.app.app_context()\nself.appContext.push()\nself.testApp = self.app.test_client()\nself._savepointContext = transactionContext(self)\nself._savepointContext.__enter__()",
"self._savepointContext.__exit__(None, None, None)\nself.appContext.pop()\nself.appCon... | <|body_start_0|>
self.app = createApp(TestConfig)
self.appContext = self.app.app_context()
self.appContext.push()
self.testApp = self.app.test_client()
self._savepointContext = transactionContext(self)
self._savepointContext.__enter__()
<|end_body_0|>
<|body_start_1|>
... | Basic class for testcase | TestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCase:
"""Basic class for testcase"""
def setUp(self):
"""Set up application for the tests"""
<|body_0|>
def tearDown(self):
"""Close application for the tests"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.app = createApp(TestConfig)
... | stack_v2_sparse_classes_36k_train_017944 | 1,330 | no_license | [
{
"docstring": "Set up application for the tests",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Close application for the tests",
"name": "tearDown",
"signature": "def tearDown(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019071 | Implement the Python class `TestCase` described below.
Class description:
Basic class for testcase
Method signatures and docstrings:
- def setUp(self): Set up application for the tests
- def tearDown(self): Close application for the tests | Implement the Python class `TestCase` described below.
Class description:
Basic class for testcase
Method signatures and docstrings:
- def setUp(self): Set up application for the tests
- def tearDown(self): Close application for the tests
<|skeleton|>
class TestCase:
"""Basic class for testcase"""
def setUp... | 3afb4012b515e471f29dc5c0e0aae1501aea7ce7 | <|skeleton|>
class TestCase:
"""Basic class for testcase"""
def setUp(self):
"""Set up application for the tests"""
<|body_0|>
def tearDown(self):
"""Close application for the tests"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCase:
"""Basic class for testcase"""
def setUp(self):
"""Set up application for the tests"""
self.app = createApp(TestConfig)
self.appContext = self.app.app_context()
self.appContext.push()
self.testApp = self.app.test_client()
self._savepointContext = ... | the_stack_v2_python_sparse | backend/tests1/testCase.py | YuyaoZhong/4156-team-project | train | 2 |
0d905c70ba5f2281bdd791133b5f2758b3a9279d | [
"if not matrix or not matrix[0]:\n return 0\nrow = len(matrix)\ncol = len(matrix[0])\ncur = [0 for _ in xrange(row + 1)]\nmaxw = pre = 0\nfor j in xrange(1, col + 1):\n for i in xrange(1, row + 1):\n tmp = cur[i]\n if matrix[i - 1][j - 1] == '1':\n cur[i] = min(cur[i - 1], cur[i], pre... | <|body_start_0|>
if not matrix or not matrix[0]:
return 0
row = len(matrix)
col = len(matrix[0])
cur = [0 for _ in xrange(row + 1)]
maxw = pre = 0
for j in xrange(1, col + 1):
for i in xrange(1, row + 1):
tmp = cur[i]
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maximalSquareON(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_0|>
def maximalSquare(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not matrix or no... | stack_v2_sparse_classes_36k_train_017945 | 1,941 | permissive | [
{
"docstring": ":type matrix: List[List[str]] :rtype: int",
"name": "maximalSquareON",
"signature": "def maximalSquareON(self, matrix)"
},
{
"docstring": ":type matrix: List[List[str]] :rtype: int",
"name": "maximalSquare",
"signature": "def maximalSquare(self, matrix)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquareON(self, matrix): :type matrix: List[List[str]] :rtype: int
- def maximalSquare(self, matrix): :type matrix: List[List[str]] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maximalSquareON(self, matrix): :type matrix: List[List[str]] :rtype: int
- def maximalSquare(self, matrix): :type matrix: List[List[str]] :rtype: int
<|skeleton|>
class Solu... | 86f1cb98de801f58c39d9a48ce9de12df7303d20 | <|skeleton|>
class Solution:
def maximalSquareON(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_0|>
def maximalSquare(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maximalSquareON(self, matrix):
""":type matrix: List[List[str]] :rtype: int"""
if not matrix or not matrix[0]:
return 0
row = len(matrix)
col = len(matrix[0])
cur = [0 for _ in xrange(row + 1)]
maxw = pre = 0
for j in xrange(1, ... | the_stack_v2_python_sparse | 221-Maximal-Square/solution.py | Tanych/CodeTracking | train | 0 | |
348918ea500e26ca921123b5bec04b70873037cd | [
"for draggable in self.excess_draggables:\n if self.excess_draggables[draggable]:\n return False\nfor index, draggable_ids in enumerate(self.correct_groups):\n current_rule = list(self.correct_positions[index].keys())[0]\n if 'number' in current_rule:\n rule_values = self.correct_positions[in... | <|body_start_0|>
for draggable in self.excess_draggables:
if self.excess_draggables[draggable]:
return False
for index, draggable_ids in enumerate(self.correct_groups):
current_rule = list(self.correct_positions[index].keys())[0]
if 'number' in current... | Grader class for drag and drop inputtype. | DragAndDrop | [
"MIT",
"AGPL-3.0-only",
"AGPL-3.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DragAndDrop:
"""Grader class for drag and drop inputtype."""
def grade(self):
"""Grader user answer. Checks if every draggable isplaced on proper target or on proper coordinates within radius of forgiveness (default is 10). Returns: bool."""
<|body_0|>
def compare_positi... | stack_v2_sparse_classes_36k_train_017946 | 15,253 | permissive | [
{
"docstring": "Grader user answer. Checks if every draggable isplaced on proper target or on proper coordinates within radius of forgiveness (default is 10). Returns: bool.",
"name": "grade",
"signature": "def grade(self)"
},
{
"docstring": "Compares two lists of positions with flag rules. Orde... | 3 | null | Implement the Python class `DragAndDrop` described below.
Class description:
Grader class for drag and drop inputtype.
Method signatures and docstrings:
- def grade(self): Grader user answer. Checks if every draggable isplaced on proper target or on proper coordinates within radius of forgiveness (default is 10). Ret... | Implement the Python class `DragAndDrop` described below.
Class description:
Grader class for drag and drop inputtype.
Method signatures and docstrings:
- def grade(self): Grader user answer. Checks if every draggable isplaced on proper target or on proper coordinates within radius of forgiveness (default is 10). Ret... | 5809eaca7079a15ee56b0b7fcfea425337046c97 | <|skeleton|>
class DragAndDrop:
"""Grader class for drag and drop inputtype."""
def grade(self):
"""Grader user answer. Checks if every draggable isplaced on proper target or on proper coordinates within radius of forgiveness (default is 10). Returns: bool."""
<|body_0|>
def compare_positi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DragAndDrop:
"""Grader class for drag and drop inputtype."""
def grade(self):
"""Grader user answer. Checks if every draggable isplaced on proper target or on proper coordinates within radius of forgiveness (default is 10). Returns: bool."""
for draggable in self.excess_draggables:
... | the_stack_v2_python_sparse | Part-03-Understanding-Software-Crafting-Your-Own-Tools/models/edx-platform/common/lib/sandbox-packages/verifiers/draganddrop.py | luque/better-ways-of-thinking-about-software | train | 3 |
330c746b8fc75b8d698c83bbbbae41a9a077c913 | [
"if type(self) != type(other):\n return False\nreturn True",
"shape = x.shape\nparties = x.parties\nnr_parties = len(parties)\nkwargs = {'seed_id_locations': secrets.randbits(64)}\ndecomposed_shares = [share.bit_decomposition(share, ring_size, False, **kwargs) for share in x.child]\nres_shares: List[MPCTensor]... | <|body_start_0|>
if type(self) != type(other):
return False
return True
<|end_body_0|>
<|body_start_1|>
shape = x.shape
parties = x.parties
nr_parties = len(parties)
kwargs = {'seed_id_locations': secrets.randbits(64)}
decomposed_shares = [share.bit_d... | ABY3 Protocol Implementation. | ABY3 | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ABY3:
"""ABY3 Protocol Implementation."""
def __eq__(self, other: Any) -> bool:
"""Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not."""
<|body_0|>
def bit_inj... | stack_v2_sparse_classes_36k_train_017947 | 4,866 | permissive | [
{
"docstring": "Check if \"self\" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not.",
"name": "__eq__",
"signature": "def __eq__(self, other: Any) -> bool"
},
{
"docstring": "Perform ABY3 bit injecti... | 4 | stack_v2_sparse_classes_30k_train_010558 | Implement the Python class `ABY3` described below.
Class description:
ABY3 Protocol Implementation.
Method signatures and docstrings:
- def __eq__(self, other: Any) -> bool: Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if e... | Implement the Python class `ABY3` described below.
Class description:
ABY3 Protocol Implementation.
Method signatures and docstrings:
- def __eq__(self, other: Any) -> bool: Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if e... | 1d2c6928b95a2f8164167a8c53f350b188e4533c | <|skeleton|>
class ABY3:
"""ABY3 Protocol Implementation."""
def __eq__(self, other: Any) -> bool:
"""Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not."""
<|body_0|>
def bit_inj... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ABY3:
"""ABY3 Protocol Implementation."""
def __eq__(self, other: Any) -> bool:
"""Check if "self" is equal with another object given a set of attributes to compare. Args: other (Any): Object to compare Returns: bool: True if equal False if not."""
if type(self) != type(other):
... | the_stack_v2_python_sparse | packages/syft/src/syft/core/smpc/protocol/aby3/aby3.py | aanurraj/PySyft | train | 0 |
6e956b186c71c9e6b26a60596aa9c3942ca5494b | [
"self.info_for_layers_dict = info_for_layers_dict\nself.gpmap_type = gpmap_type\nself.gpmap_kwargs = gpmap_kwargs\nself.alphabet = validate_alphabet(alphabet)\nself.C = len(self.alphabet)\nself.theta_regularization = theta_regularization\nself.eta_regularization = eta_regularization\nself.ohe_batch_size = ohe_batch... | <|body_start_0|>
self.info_for_layers_dict = info_for_layers_dict
self.gpmap_type = gpmap_type
self.gpmap_kwargs = gpmap_kwargs
self.alphabet = validate_alphabet(alphabet)
self.C = len(self.alphabet)
self.theta_regularization = theta_regularization
self.eta_regula... | Represents a measurement process agnostic model. Parameters ---------- sequence_length: (int) Integer specifying the length of a single training sequence. number_of_bins: (int) Integer specifying the number of bins. (Only used for MPA regression). alphabet: (str) Specifies the type of input sequences. Three possible ch... | MeasurementProcessAgnosticModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MeasurementProcessAgnosticModel:
"""Represents a measurement process agnostic model. Parameters ---------- sequence_length: (int) Integer specifying the length of a single training sequence. number_of_bins: (int) Integer specifying the number of bins. (Only used for MPA regression). alphabet: (st... | stack_v2_sparse_classes_36k_train_017948 | 21,053 | permissive | [
{
"docstring": "Construct class instance.",
"name": "__init__",
"signature": "def __init__(self, info_for_layers_dict, sequence_length, number_of_bins, gpmap_type, gpmap_kwargs, alphabet, theta_regularization, eta_regularization, ohe_batch_size, custom_gpmap, initial_weights)"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_train_012690 | Implement the Python class `MeasurementProcessAgnosticModel` described below.
Class description:
Represents a measurement process agnostic model. Parameters ---------- sequence_length: (int) Integer specifying the length of a single training sequence. number_of_bins: (int) Integer specifying the number of bins. (Only ... | Implement the Python class `MeasurementProcessAgnosticModel` described below.
Class description:
Represents a measurement process agnostic model. Parameters ---------- sequence_length: (int) Integer specifying the length of a single training sequence. number_of_bins: (int) Integer specifying the number of bins. (Only ... | f83f6e94d3d6ceeb7f19401d369da1908cfac31d | <|skeleton|>
class MeasurementProcessAgnosticModel:
"""Represents a measurement process agnostic model. Parameters ---------- sequence_length: (int) Integer specifying the length of a single training sequence. number_of_bins: (int) Integer specifying the number of bins. (Only used for MPA regression). alphabet: (st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MeasurementProcessAgnosticModel:
"""Represents a measurement process agnostic model. Parameters ---------- sequence_length: (int) Integer specifying the length of a single training sequence. number_of_bins: (int) Integer specifying the number of bins. (Only used for MPA regression). alphabet: (str) Specifies ... | the_stack_v2_python_sparse | mavenn/src/regression_types.py | jbkinney/mavenn | train | 21 |
9152fa8a73a1f448bb6a9b67bf3a535b3188f67b | [
"self.methods = [method() for method in args]\nself.method_arguments = arguments\nif list(self.method_arguments.keys()) != [method._designation for method in self.methods]:\n print(list(self.method_arguments.keys()))\n print([method._designation for method in self.methods])\n raise ValueError('The keys of ... | <|body_start_0|>
self.methods = [method() for method in args]
self.method_arguments = arguments
if list(self.method_arguments.keys()) != [method._designation for method in self.methods]:
print(list(self.method_arguments.keys()))
print([method._designation for method in se... | Workflow class that aggregates all the steps of the analysis and the corresponding functions. | Workflow | [
"GPL-2.0-only",
"GPL-1.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Workflow:
"""Workflow class that aggregates all the steps of the analysis and the corresponding functions."""
def __init__(self, *args, arguments: dict) -> None:
"""Initialize the Workflow args: list of functions that will be executed in the order they are passed kwargs: dict of argu... | stack_v2_sparse_classes_36k_train_017949 | 2,859 | permissive | [
{
"docstring": "Initialize the Workflow args: list of functions that will be executed in the order they are passed kwargs: dict of arguments that will be passed to the functions, the keys must match the function names, the values must be list of len 2 [*args, **kwargs] ARGUMENTS OR KEYWORD ARGUMENTS ARE \"METHO... | 2 | null | Implement the Python class `Workflow` described below.
Class description:
Workflow class that aggregates all the steps of the analysis and the corresponding functions.
Method signatures and docstrings:
- def __init__(self, *args, arguments: dict) -> None: Initialize the Workflow args: list of functions that will be e... | Implement the Python class `Workflow` described below.
Class description:
Workflow class that aggregates all the steps of the analysis and the corresponding functions.
Method signatures and docstrings:
- def __init__(self, *args, arguments: dict) -> None: Initialize the Workflow args: list of functions that will be e... | 3139e5d45e1433a56481dcd00a3031c658089b73 | <|skeleton|>
class Workflow:
"""Workflow class that aggregates all the steps of the analysis and the corresponding functions."""
def __init__(self, *args, arguments: dict) -> None:
"""Initialize the Workflow args: list of functions that will be executed in the order they are passed kwargs: dict of argu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Workflow:
"""Workflow class that aggregates all the steps of the analysis and the corresponding functions."""
def __init__(self, *args, arguments: dict) -> None:
"""Initialize the Workflow args: list of functions that will be executed in the order they are passed kwargs: dict of arguments that wi... | the_stack_v2_python_sparse | src/nanopyx/methods/old_workflow.py | HenriquesLab/NanoPyx | train | 33 |
9b427360d67190f16d7c4d34fef9e8ec80624fb8 | [
"self.active_user = User.objects.create_user(username='active_user', email='activeuser@gmail.com', password='p@55words')\nself.inactive_user = User.objects.create_user(username='inactive_user', email='inactiveuser@gmail.com', password='p@55words')\nself.inactive_user.is_active = False\nself.inactive_user.save()\nse... | <|body_start_0|>
self.active_user = User.objects.create_user(username='active_user', email='activeuser@gmail.com', password='p@55words')
self.inactive_user = User.objects.create_user(username='inactive_user', email='inactiveuser@gmail.com', password='p@55words')
self.inactive_user.is_active = Fa... | A class containing generic tests that are utilised throughout the different view tests. | ViewsTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewsTestCase:
"""A class containing generic tests that are utilised throughout the different view tests."""
def setUp(self):
"""Set up users to be used throughout testing."""
<|body_0|>
def only_active_user_access_test(self, view_url, template_name):
"""Tests th... | stack_v2_sparse_classes_36k_train_017950 | 2,779 | permissive | [
{
"docstring": "Set up users to be used throughout testing.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tests that only active users have access to this view. :param view_url: The url of the view being tested. :param template_name: The name of the template for the view b... | 3 | stack_v2_sparse_classes_30k_train_016199 | Implement the Python class `ViewsTestCase` described below.
Class description:
A class containing generic tests that are utilised throughout the different view tests.
Method signatures and docstrings:
- def setUp(self): Set up users to be used throughout testing.
- def only_active_user_access_test(self, view_url, tem... | Implement the Python class `ViewsTestCase` described below.
Class description:
A class containing generic tests that are utilised throughout the different view tests.
Method signatures and docstrings:
- def setUp(self): Set up users to be used throughout testing.
- def only_active_user_access_test(self, view_url, tem... | 85b450d7f6d0313c5e5ef53a262a850b7e93c3d6 | <|skeleton|>
class ViewsTestCase:
"""A class containing generic tests that are utilised throughout the different view tests."""
def setUp(self):
"""Set up users to be used throughout testing."""
<|body_0|>
def only_active_user_access_test(self, view_url, template_name):
"""Tests th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViewsTestCase:
"""A class containing generic tests that are utilised throughout the different view tests."""
def setUp(self):
"""Set up users to be used throughout testing."""
self.active_user = User.objects.create_user(username='active_user', email='activeuser@gmail.com', password='p@55w... | the_stack_v2_python_sparse | communique/utils/utils_tests.py | michael-xander/communique-webapp | train | 0 |
b3e87335321a0c174c1b4b4df70db2fb0f231d1b | [
"if not prices:\n return 0\nnum_i0 = 0\nnum_i1 = -prices[0]\nfor price in prices:\n tmp = num_i0\n num_i0 = max(num_i0, num_i1 + price)\n num_i1 = max(num_i1, tmp - price)\nreturn num_i0",
"if not prices:\n return 0\nn = len(prices)\nif k > n // 2:\n return self.maxProfit_inf(prices)\ndp = [[[0 ... | <|body_start_0|>
if not prices:
return 0
num_i0 = 0
num_i1 = -prices[0]
for price in prices:
tmp = num_i0
num_i0 = max(num_i0, num_i1 + price)
num_i1 = max(num_i1, tmp - price)
return num_i0
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit_inf(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, k, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not prices:
return ... | stack_v2_sparse_classes_36k_train_017951 | 4,994 | no_license | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit_inf",
"signature": "def maxProfit_inf(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, k, prices)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_inf(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, k, prices): :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit_inf(self, prices): :type prices: List[int] :rtype: int
- def maxProfit(self, k, prices): :type prices: List[int] :rtype: int
<|skeleton|>
class Solution:
def ... | 013f6f222c6c2a617787b258f8a37003a9f51526 | <|skeleton|>
class Solution:
def maxProfit_inf(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit(self, k, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit_inf(self, prices):
""":type prices: List[int] :rtype: int"""
if not prices:
return 0
num_i0 = 0
num_i1 = -prices[0]
for price in prices:
tmp = num_i0
num_i0 = max(num_i0, num_i1 + price)
num_i1 = ma... | the_stack_v2_python_sparse | sub_seq.py | terrifyzhao/leetcode | train | 0 | |
cc34c81e7d6790392b7ada67954ba0ab86307af1 | [
"dp = [0, 1, 2, 3]\nif n < 2:\n return -1\nelif n == 2:\n return 1\nelif n == 3:\n return 2\nfor i in range(4, n + 1):\n temp = 0\n for j in range(1, i // 2 + 1):\n temp = max(temp, dp[j] * dp[i - j])\n dp.append(temp)\nreturn dp[n]",
"if n < 2:\n return -1\nelif n == 2:\n return 1\... | <|body_start_0|>
dp = [0, 1, 2, 3]
if n < 2:
return -1
elif n == 2:
return 1
elif n == 3:
return 2
for i in range(4, n + 1):
temp = 0
for j in range(1, i // 2 + 1):
temp = max(temp, dp[j] * dp[i - j])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def integerBreak(self, n: int) -> int:
"""dp[i] 代表整数i的最大积拆分 dp[i] = max(dp[i-j] * dp[j]) j=1_最短回文串.py,...,i-1_最短回文串.py. dp[0-3] = 0, 1_最短回文串.py, 2, 3 res = dp[-1_最短回文串.py]"""
<|body_0|>
def integerBreak(self, n: int) -> int:
"""贪心： 多分3 尾为1分2，2"""
<|... | stack_v2_sparse_classes_36k_train_017952 | 1,039 | no_license | [
{
"docstring": "dp[i] 代表整数i的最大积拆分 dp[i] = max(dp[i-j] * dp[j]) j=1_最短回文串.py,...,i-1_最短回文串.py. dp[0-3] = 0, 1_最短回文串.py, 2, 3 res = dp[-1_最短回文串.py]",
"name": "integerBreak",
"signature": "def integerBreak(self, n: int) -> int"
},
{
"docstring": "贪心： 多分3 尾为1分2，2",
"name": "integerBreak",
"s... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerBreak(self, n: int) -> int: dp[i] 代表整数i的最大积拆分 dp[i] = max(dp[i-j] * dp[j]) j=1_最短回文串.py,...,i-1_最短回文串.py. dp[0-3] = 0, 1_最短回文串.py, 2, 3 res = dp[-1_最短回文串.py]
- def int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def integerBreak(self, n: int) -> int: dp[i] 代表整数i的最大积拆分 dp[i] = max(dp[i-j] * dp[j]) j=1_最短回文串.py,...,i-1_最短回文串.py. dp[0-3] = 0, 1_最短回文串.py, 2, 3 res = dp[-1_最短回文串.py]
- def int... | 57f303aa6e76f7c5292fa60bffdfddcb4ff9ddfb | <|skeleton|>
class Solution:
def integerBreak(self, n: int) -> int:
"""dp[i] 代表整数i的最大积拆分 dp[i] = max(dp[i-j] * dp[j]) j=1_最短回文串.py,...,i-1_最短回文串.py. dp[0-3] = 0, 1_最短回文串.py, 2, 3 res = dp[-1_最短回文串.py]"""
<|body_0|>
def integerBreak(self, n: int) -> int:
"""贪心： 多分3 尾为1分2，2"""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def integerBreak(self, n: int) -> int:
"""dp[i] 代表整数i的最大积拆分 dp[i] = max(dp[i-j] * dp[j]) j=1_最短回文串.py,...,i-1_最短回文串.py. dp[0-3] = 0, 1_最短回文串.py, 2, 3 res = dp[-1_最短回文串.py]"""
dp = [0, 1, 2, 3]
if n < 2:
return -1
elif n == 2:
return 1
e... | the_stack_v2_python_sparse | 4_LEETCODE/9_Greedy/343_整数拆分.py | fzingithub/SwordRefers2Offer | train | 1 | |
9f992bb06b34efc444921a3d7780eca52dfc8c41 | [
"self.words_dict = defaultdict(list)\nfor w_index, word in enumerate(words):\n self.words_dict[word].append(w_index)",
"distance_candidate = None\nlen_s = len(self.words_dict[word1])\nlen_b = len(self.words_dict[word2])\nj_init = 0\nfor i in range(0, len_s):\n for j in range(j_init, len_b):\n distanc... | <|body_start_0|>
self.words_dict = defaultdict(list)
for w_index, word in enumerate(words):
self.words_dict[word].append(w_index)
<|end_body_0|>
<|body_start_1|>
distance_candidate = None
len_s = len(self.words_dict[word1])
len_b = len(self.words_dict[word2])
... | WordDistance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.words_dict = defaultdict(list)
... | stack_v2_sparse_classes_36k_train_017953 | 2,062 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortest(self, word1, word2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015840 | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int
<|skeleton|>
class WordDistance:
... | 9387c1cbf1cac2db1aebf5ad196230705ab0fcc7 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
self.words_dict = defaultdict(list)
for w_index, word in enumerate(words):
self.words_dict[word].append(w_index)
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype:... | the_stack_v2_python_sparse | shortest_world_distance_II.py | lightening0907/algorithm | train | 0 | |
d93627371e20c333b86cfa8532f8c8a80e175a71 | [
"try:\n data_conf_frm().put_step_source(nnid, ver, node, request.data)\n return Response(json.dumps(request.data))\nexcept Exception as e:\n return_data = {'status': '404', 'result': str(e)}\n return Response(json.dumps(return_data))",
"try:\n return_data = data_conf_frm().get_data_conf(nnid, ver, ... | <|body_start_0|>
try:
data_conf_frm().put_step_source(nnid, ver, node, request.data)
return Response(json.dumps(request.data))
except Exception as e:
return_data = {'status': '404', 'result': str(e)}
return Response(json.dumps(return_data))
<|end_body_0|>
... | WorkFlowDataConfFrame | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkFlowDataConfFrame:
def post(self, request, nnid, ver, node):
"""- desc : insert cnn configuration data completed"""
<|body_0|>
def get(self, request, nnid, ver, node):
"""- desc : get cnn configuration data"""
<|body_1|>
def put(self, request, nnid, ... | stack_v2_sparse_classes_36k_train_017954 | 2,412 | permissive | [
{
"docstring": "- desc : insert cnn configuration data completed",
"name": "post",
"signature": "def post(self, request, nnid, ver, node)"
},
{
"docstring": "- desc : get cnn configuration data",
"name": "get",
"signature": "def get(self, request, nnid, ver, node)"
},
{
"docstrin... | 4 | stack_v2_sparse_classes_30k_test_000317 | Implement the Python class `WorkFlowDataConfFrame` described below.
Class description:
Implement the WorkFlowDataConfFrame class.
Method signatures and docstrings:
- def post(self, request, nnid, ver, node): - desc : insert cnn configuration data completed
- def get(self, request, nnid, ver, node): - desc : get cnn c... | Implement the Python class `WorkFlowDataConfFrame` described below.
Class description:
Implement the WorkFlowDataConfFrame class.
Method signatures and docstrings:
- def post(self, request, nnid, ver, node): - desc : insert cnn configuration data completed
- def get(self, request, nnid, ver, node): - desc : get cnn c... | 6ad2fbc7384e4dbe7e3e63bdb44c8ce0387f4b7f | <|skeleton|>
class WorkFlowDataConfFrame:
def post(self, request, nnid, ver, node):
"""- desc : insert cnn configuration data completed"""
<|body_0|>
def get(self, request, nnid, ver, node):
"""- desc : get cnn configuration data"""
<|body_1|>
def put(self, request, nnid, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WorkFlowDataConfFrame:
def post(self, request, nnid, ver, node):
"""- desc : insert cnn configuration data completed"""
try:
data_conf_frm().put_step_source(nnid, ver, node, request.data)
return Response(json.dumps(request.data))
except Exception as e:
... | the_stack_v2_python_sparse | api/views/workflow_dataconf_frame.py | yurimkoo/tensormsa | train | 1 | |
30040e46f6612422c1fc0ef6f18b770859b94e18 | [
"super().__init__(flatten_flag=flatten_flag, n_pca_components=n_pca_components, extract_hog_flag=extract_hog_flag, type_cnn=type_cnn)\nself.segment_lungs_flag = segment_lungs_flag\nself.u_net_model_path = u_net_model_path\nself.u_net_weights_path = u_net_weights_path\nself.segment_lungs_method = segment_lungs_metho... | <|body_start_0|>
super().__init__(flatten_flag=flatten_flag, n_pca_components=n_pca_components, extract_hog_flag=extract_hog_flag, type_cnn=type_cnn)
self.segment_lungs_flag = segment_lungs_flag
self.u_net_model_path = u_net_model_path
self.u_net_weights_path = u_net_weights_path
... | Children Class of ImagePreProcessor. Used to transform 2D X-Ray Images only of the chest cavity. | ChestXRayPreProcessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChestXRayPreProcessor:
"""Children Class of ImagePreProcessor. Used to transform 2D X-Ray Images only of the chest cavity."""
def __init__(self, flatten_flag=False, n_pca_components=0, extract_hog_flag=False, type_cnn='', segment_lungs_flag=False, segment_lungs_method='', u_net_model_path=''... | stack_v2_sparse_classes_36k_train_017955 | 17,079 | no_license | [
{
"docstring": "Constructor of the class. :param flatten_flag: (bool) whether to express the numpy array of data with shape [n_samples, n_features] :param n_pca_components: (int) number of principal components that will be computed from the data \"x\". Must be an integer between 2 and 3. :param extract_hog_flag... | 3 | stack_v2_sparse_classes_30k_train_005489 | Implement the Python class `ChestXRayPreProcessor` described below.
Class description:
Children Class of ImagePreProcessor. Used to transform 2D X-Ray Images only of the chest cavity.
Method signatures and docstrings:
- def __init__(self, flatten_flag=False, n_pca_components=0, extract_hog_flag=False, type_cnn='', se... | Implement the Python class `ChestXRayPreProcessor` described below.
Class description:
Children Class of ImagePreProcessor. Used to transform 2D X-Ray Images only of the chest cavity.
Method signatures and docstrings:
- def __init__(self, flatten_flag=False, n_pca_components=0, extract_hog_flag=False, type_cnn='', se... | c46f4b2ba7762420186cb710d2932adf00829d6f | <|skeleton|>
class ChestXRayPreProcessor:
"""Children Class of ImagePreProcessor. Used to transform 2D X-Ray Images only of the chest cavity."""
def __init__(self, flatten_flag=False, n_pca_components=0, extract_hog_flag=False, type_cnn='', segment_lungs_flag=False, segment_lungs_method='', u_net_model_path=''... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ChestXRayPreProcessor:
"""Children Class of ImagePreProcessor. Used to transform 2D X-Ray Images only of the chest cavity."""
def __init__(self, flatten_flag=False, n_pca_components=0, extract_hog_flag=False, type_cnn='', segment_lungs_flag=False, segment_lungs_method='', u_net_model_path='', u_net_weigh... | the_stack_v2_python_sparse | pre_processors.py | jonathand94/ML-Classifiers-Library | train | 0 |
dba1f422578fff268508c6c25e5ac10c38b5696d | [
"self.modelPath = inputPath\nif os.path.exists('/'.join([self.modelPath, 'checkpoints'])):\n self.modelPath = '/'.join([self.modelPath, 'checkpoints'])\nconfigFile = self.modelPath + '/net_config.json'\nif not os.path.exists(configFile):\n sys.exit('could not find config file {}, cannot load DNN'.format(confi... | <|body_start_0|>
self.modelPath = inputPath
if os.path.exists('/'.join([self.modelPath, 'checkpoints'])):
self.modelPath = '/'.join([self.modelPath, 'checkpoints'])
configFile = self.modelPath + '/net_config.json'
if not os.path.exists(configFile):
sys.exit('could... | Model | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Model:
def __init__(self, inputPath):
"""load dnn model with Keras"""
<|body_0|>
def setVariables(self):
"""read list of variables used for DNN evaluation read norm table with mean and std.dev values for all of theses variables"""
<|body_1|>
def findBest... | stack_v2_sparse_classes_36k_train_017956 | 3,217 | no_license | [
{
"docstring": "load dnn model with Keras",
"name": "__init__",
"signature": "def __init__(self, inputPath)"
},
{
"docstring": "read list of variables used for DNN evaluation read norm table with mean and std.dev values for all of theses variables",
"name": "setVariables",
"signature": "... | 4 | null | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- def __init__(self, inputPath): load dnn model with Keras
- def setVariables(self): read list of variables used for DNN evaluation read norm table with mean and std.dev values for all o... | Implement the Python class `Model` described below.
Class description:
Implement the Model class.
Method signatures and docstrings:
- def __init__(self, inputPath): load dnn model with Keras
- def setVariables(self): read list of variables used for DNN evaluation read norm table with mean and std.dev values for all o... | 79f4b883eec1ea335edba28ddb1444fb2e693ea6 | <|skeleton|>
class Model:
def __init__(self, inputPath):
"""load dnn model with Keras"""
<|body_0|>
def setVariables(self):
"""read list of variables used for DNN evaluation read norm table with mean and std.dev values for all of theses variables"""
<|body_1|>
def findBest... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Model:
def __init__(self, inputPath):
"""load dnn model with Keras"""
self.modelPath = inputPath
if os.path.exists('/'.join([self.modelPath, 'checkpoints'])):
self.modelPath = '/'.join([self.modelPath, 'checkpoints'])
configFile = self.modelPath + '/net_config.json'... | the_stack_v2_python_sparse | karim/load/model.py | kit-cn-cms/karim | train | 0 | |
31f2f7b2fc882c821de580c8f5ed3c977501cec6 | [
"self.ParticleInstanceIn = ParticleInstanceIn\nself.bar_angle = bar_angle\nself.data = dict()\nif self.bar_angle == None:\n self.bar_angle = -1.0 * BarTransform.bar_fourier_compute(self, self.ParticleInstanceIn.data['x'], self.ParticleInstanceIn.data['y'], maxr=maxr)\nself.bar_angle += rel_bar_angle\nself.calcul... | <|body_start_0|>
self.ParticleInstanceIn = ParticleInstanceIn
self.bar_angle = bar_angle
self.data = dict()
if self.bar_angle == None:
self.bar_angle = -1.0 * BarTransform.bar_fourier_compute(self, self.ParticleInstanceIn.data['x'], self.ParticleInstanceIn.data['y'], maxr=max... | BarTransform : class to do the work to calculate the bar position and transform particles on it's own, BarTransform will reset the particles to be in the bar frame (planar transformation) inputs ----------------------- ParticleInstanceIn : the input PSP instance bar_angle : (default=None) the known bar angle rel_bar_an... | BarTransform | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BarTransform:
"""BarTransform : class to do the work to calculate the bar position and transform particles on it's own, BarTransform will reset the particles to be in the bar frame (planar transformation) inputs ----------------------- ParticleInstanceIn : the input PSP instance bar_angle : (defa... | stack_v2_sparse_classes_36k_train_017957 | 20,224 | permissive | [
{
"docstring": "see documentation above",
"name": "__init__",
"signature": "def __init__(self, ParticleInstanceIn, bar_angle=None, rel_bar_angle=0.0, minr=0.0, maxr=1.0)"
},
{
"docstring": "calculate_transform_and_return do the modification of the input PSP instance to be in the bar frame. input... | 3 | stack_v2_sparse_classes_30k_train_013187 | Implement the Python class `BarTransform` described below.
Class description:
BarTransform : class to do the work to calculate the bar position and transform particles on it's own, BarTransform will reset the particles to be in the bar frame (planar transformation) inputs ----------------------- ParticleInstanceIn : t... | Implement the Python class `BarTransform` described below.
Class description:
BarTransform : class to do the work to calculate the bar position and transform particles on it's own, BarTransform will reset the particles to be in the bar frame (planar transformation) inputs ----------------------- ParticleInstanceIn : t... | 189ed0b94b08309badde5da9b31f233cc2ec1765 | <|skeleton|>
class BarTransform:
"""BarTransform : class to do the work to calculate the bar position and transform particles on it's own, BarTransform will reset the particles to be in the bar frame (planar transformation) inputs ----------------------- ParticleInstanceIn : the input PSP instance bar_angle : (defa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BarTransform:
"""BarTransform : class to do the work to calculate the bar position and transform particles on it's own, BarTransform will reset the particles to be in the bar frame (planar transformation) inputs ----------------------- ParticleInstanceIn : the input PSP instance bar_angle : (default=None) the... | the_stack_v2_python_sparse | exptool/analysis/pattern.py | michael-petersen/exptool | train | 5 |
e195f16ebd106c69a875618646cbfb476c7f46d2 | [
"self.root = Path(__file__).parent.absolute()\nif not args:\n return\nself.build = Path(args.build_dir).resolve()\nif args.install_prefix:\n self.installed = Path(args.install_prefix).resolve()\nelse:\n self.installed = self.build.parent / (self.build.stem + '-install')\nif sys.platform == 'win32' and sys.... | <|body_start_0|>
self.root = Path(__file__).parent.absolute()
if not args:
return
self.build = Path(args.build_dir).resolve()
if args.install_prefix:
self.installed = Path(args.install_prefix).resolve()
else:
self.installed = self.build.parent ... | root: Directory where scr, build config and tools are located (and this file) build: Directory where build output files (i.e. *.o) are saved install: Directory where .so from build and .py from src are put together. site: Directory where the built SciPy version was installed. This is a custom prefix, followed by a rela... | Dirs | [
"BSL-1.0",
"BSD-2-Clause",
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Qhull",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dirs:
"""root: Directory where scr, build config and tools are located (and this file) build: Directory where build output files (i.e. *.o) are saved install: Directory where .so from build and .py from src are put together. site: Directory where the built SciPy version was installed. This is a c... | stack_v2_sparse_classes_36k_train_017958 | 49,632 | permissive | [
{
"docstring": ":params args: object like Context(build_dir, install_prefix)",
"name": "__init__",
"signature": "def __init__(self, args=None)"
},
{
"docstring": "Add site dir to sys.path / PYTHONPATH",
"name": "add_sys_path",
"signature": "def add_sys_path(self)"
},
{
"docstring... | 3 | stack_v2_sparse_classes_30k_train_016790 | Implement the Python class `Dirs` described below.
Class description:
root: Directory where scr, build config and tools are located (and this file) build: Directory where build output files (i.e. *.o) are saved install: Directory where .so from build and .py from src are put together. site: Directory where the built S... | Implement the Python class `Dirs` described below.
Class description:
root: Directory where scr, build config and tools are located (and this file) build: Directory where build output files (i.e. *.o) are saved install: Directory where .so from build and .py from src are put together. site: Directory where the built S... | bae3476b8a245866f5f7f1b824a0a7919f3880a9 | <|skeleton|>
class Dirs:
"""root: Directory where scr, build config and tools are located (and this file) build: Directory where build output files (i.e. *.o) are saved install: Directory where .so from build and .py from src are put together. site: Directory where the built SciPy version was installed. This is a c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dirs:
"""root: Directory where scr, build config and tools are located (and this file) build: Directory where build output files (i.e. *.o) are saved install: Directory where .so from build and .py from src are put together. site: Directory where the built SciPy version was installed. This is a custom prefix,... | the_stack_v2_python_sparse | dev.py | rgommers/scipy | train | 17 |
67f067459fe6c6af550ee61aa817dd18e4a0e3bf | [
"plt.rcParams['figure.figsize'] = figsize\nself.fig = plt.figure()\nframe_axes = self.fig.add_subplot(111, frameon=False, xticklabels=(), yticklabels=())\nframe_axes.set_title(title)\nself.shape = shape\nself.num_subplots = 0",
"self.num_subplots += 1\nself.fig.add_subplot(self.shape[0], self.shape[1], self.num_s... | <|body_start_0|>
plt.rcParams['figure.figsize'] = figsize
self.fig = plt.figure()
frame_axes = self.fig.add_subplot(111, frameon=False, xticklabels=(), yticklabels=())
frame_axes.set_title(title)
self.shape = shape
self.num_subplots = 0
<|end_body_0|>
<|body_start_1|>
... | Class to manage subplotting of histograms. | HistArray | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HistArray:
"""Class to manage subplotting of histograms."""
def __init__(self, title='', figsize=(12, 12), shape=(4, 3)):
"""Parameters ---------- title: str [''] Overall title of the figure. figsize: tuple [(12, 12)] Figure dimensions in x, y inches shape: tuple [(4, 3)] Number of s... | stack_v2_sparse_classes_36k_train_017959 | 6,100 | permissive | [
{
"docstring": "Parameters ---------- title: str [''] Overall title of the figure. figsize: tuple [(12, 12)] Figure dimensions in x, y inches shape: tuple [(4, 3)] Number of subplots in the y and x dimensions, respectively.",
"name": "__init__",
"signature": "def __init__(self, title='', figsize=(12, 12... | 2 | null | Implement the Python class `HistArray` described below.
Class description:
Class to manage subplotting of histograms.
Method signatures and docstrings:
- def __init__(self, title='', figsize=(12, 12), shape=(4, 3)): Parameters ---------- title: str [''] Overall title of the figure. figsize: tuple [(12, 12)] Figure di... | Implement the Python class `HistArray` described below.
Class description:
Class to manage subplotting of histograms.
Method signatures and docstrings:
- def __init__(self, title='', figsize=(12, 12), shape=(4, 3)): Parameters ---------- title: str [''] Overall title of the figure. figsize: tuple [(12, 12)] Figure di... | 320ddc07432bcaa05723944738a6e02b6841b69e | <|skeleton|>
class HistArray:
"""Class to manage subplotting of histograms."""
def __init__(self, title='', figsize=(12, 12), shape=(4, 3)):
"""Parameters ---------- title: str [''] Overall title of the figure. figsize: tuple [(12, 12)] Figure dimensions in x, y inches shape: tuple [(4, 3)] Number of s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HistArray:
"""Class to manage subplotting of histograms."""
def __init__(self, title='', figsize=(12, 12), shape=(4, 3)):
"""Parameters ---------- title: str [''] Overall title of the figure. figsize: tuple [(12, 12)] Figure dimensions in x, y inches shape: tuple [(4, 3)] Number of subplots in th... | the_stack_v2_python_sparse | bin.src/plot_instcat_dists.py | LSSTDESC/sims_GCRCatSimInterface | train | 1 |
65a76d43a704f9997a10fd449e81db4a18dc6ff4 | [
"order = get_object_or_404(Order, id=id)\nform = OrderForm(instance=order)\nreturn render(request, 'order/add-order.html', {'form': form, 'func': 'Update', 'order': order})",
"order = get_object_or_404(Order, id=id)\nclient = get_object_or_404(Client, id=order.client.id)\nform = OrderForm(request.POST, instance=o... | <|body_start_0|>
order = get_object_or_404(Order, id=id)
form = OrderForm(instance=order)
return render(request, 'order/add-order.html', {'form': form, 'func': 'Update', 'order': order})
<|end_body_0|>
<|body_start_1|>
order = get_object_or_404(Order, id=id)
client = get_object_... | Class based view for updating new order. | OrderUpdateView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrderUpdateView:
"""Class based view for updating new order."""
def get(self, request, id):
"""Return add new order form."""
<|body_0|>
def post(self, request, id):
"""Save order and redirect to order list."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_017960 | 3,127 | no_license | [
{
"docstring": "Return add new order form.",
"name": "get",
"signature": "def get(self, request, id)"
},
{
"docstring": "Save order and redirect to order list.",
"name": "post",
"signature": "def post(self, request, id)"
}
] | 2 | null | Implement the Python class `OrderUpdateView` described below.
Class description:
Class based view for updating new order.
Method signatures and docstrings:
- def get(self, request, id): Return add new order form.
- def post(self, request, id): Save order and redirect to order list. | Implement the Python class `OrderUpdateView` described below.
Class description:
Class based view for updating new order.
Method signatures and docstrings:
- def get(self, request, id): Return add new order form.
- def post(self, request, id): Save order and redirect to order list.
<|skeleton|>
class OrderUpdateView... | 93c3106ab90fb9aed85658f93f51686ba4734091 | <|skeleton|>
class OrderUpdateView:
"""Class based view for updating new order."""
def get(self, request, id):
"""Return add new order form."""
<|body_0|>
def post(self, request, id):
"""Save order and redirect to order list."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrderUpdateView:
"""Class based view for updating new order."""
def get(self, request, id):
"""Return add new order form."""
order = get_object_or_404(Order, id=id)
form = OrderForm(instance=order)
return render(request, 'order/add-order.html', {'form': form, 'func': 'Upda... | the_stack_v2_python_sparse | order/views/order_views.py | saadali5997/tms | train | 0 |
887cf4cde1ba4f7cc89f78b6ee44b0603b867ddf | [
"self.sensors = sensors\nself.last_state = None\nself.wrapper = wrapper\nself.attribute = attribute\nself.block = block\nself.description = description\nself._unit = self.description.unit\nif block is not None:\n if callable(self._unit):\n self._unit = self._unit(block.info(attribute))\n self._unique_i... | <|body_start_0|>
self.sensors = sensors
self.last_state = None
self.wrapper = wrapper
self.attribute = attribute
self.block = block
self.description = description
self._unit = self.description.unit
if block is not None:
if callable(self._unit):... | Represent a shelly sleeping block attribute entity. | ShellySleepingBlockAttributeEntity | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShellySleepingBlockAttributeEntity:
"""Represent a shelly sleeping block attribute entity."""
def __init__(self, wrapper: ShellyDeviceWrapper, block: aioshelly.Block, attribute: str, description: BlockAttributeDescription, entry: entity_registry.RegistryEntry | None=None, sensors: set | None... | stack_v2_sparse_classes_36k_train_017961 | 13,987 | permissive | [
{
"docstring": "Initialize the sleeping sensor.",
"name": "__init__",
"signature": "def __init__(self, wrapper: ShellyDeviceWrapper, block: aioshelly.Block, attribute: str, description: BlockAttributeDescription, entry: entity_registry.RegistryEntry | None=None, sensors: set | None=None) -> None"
},
... | 3 | stack_v2_sparse_classes_30k_train_012755 | Implement the Python class `ShellySleepingBlockAttributeEntity` described below.
Class description:
Represent a shelly sleeping block attribute entity.
Method signatures and docstrings:
- def __init__(self, wrapper: ShellyDeviceWrapper, block: aioshelly.Block, attribute: str, description: BlockAttributeDescription, e... | Implement the Python class `ShellySleepingBlockAttributeEntity` described below.
Class description:
Represent a shelly sleeping block attribute entity.
Method signatures and docstrings:
- def __init__(self, wrapper: ShellyDeviceWrapper, block: aioshelly.Block, attribute: str, description: BlockAttributeDescription, e... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class ShellySleepingBlockAttributeEntity:
"""Represent a shelly sleeping block attribute entity."""
def __init__(self, wrapper: ShellyDeviceWrapper, block: aioshelly.Block, attribute: str, description: BlockAttributeDescription, entry: entity_registry.RegistryEntry | None=None, sensors: set | None... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShellySleepingBlockAttributeEntity:
"""Represent a shelly sleeping block attribute entity."""
def __init__(self, wrapper: ShellyDeviceWrapper, block: aioshelly.Block, attribute: str, description: BlockAttributeDescription, entry: entity_registry.RegistryEntry | None=None, sensors: set | None=None) -> Non... | the_stack_v2_python_sparse | homeassistant/components/shelly/entity.py | BenWoodford/home-assistant | train | 11 |
abd3c58f36126962cba2e37147fd986969b8c24e | [
"g1 = GeoIP()\npath = settings.GEOIP_PATH\ng2 = GeoIP(path, 0)\ng3 = GeoIP.open(path, 0)\nfor g in (g1, g2, g3):\n self.assertEqual(True, bool(g._country))\n self.assertEqual(True, bool(g._city))\ncity = os.path.join(path, 'GeoLiteCity.dat')\ncntry = os.path.join(path, 'GeoIP.dat')\ng4 = GeoIP(city, country='... | <|body_start_0|>
g1 = GeoIP()
path = settings.GEOIP_PATH
g2 = GeoIP(path, 0)
g3 = GeoIP.open(path, 0)
for g in (g1, g2, g3):
self.assertEqual(True, bool(g._country))
self.assertEqual(True, bool(g._city))
city = os.path.join(path, 'GeoLiteCity.dat')... | GeoIPTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeoIPTest:
def test01_init(self):
"""Testing GeoIP initialization."""
<|body_0|>
def test02_bad_query(self):
"""Testing GeoIP query parameter checking."""
<|body_1|>
def test03_country(self):
"""Testing GeoIP country querying methods."""
... | stack_v2_sparse_classes_36k_train_017962 | 4,706 | permissive | [
{
"docstring": "Testing GeoIP initialization.",
"name": "test01_init",
"signature": "def test01_init(self)"
},
{
"docstring": "Testing GeoIP query parameter checking.",
"name": "test02_bad_query",
"signature": "def test02_bad_query(self)"
},
{
"docstring": "Testing GeoIP country ... | 6 | stack_v2_sparse_classes_30k_train_011147 | Implement the Python class `GeoIPTest` described below.
Class description:
Implement the GeoIPTest class.
Method signatures and docstrings:
- def test01_init(self): Testing GeoIP initialization.
- def test02_bad_query(self): Testing GeoIP query parameter checking.
- def test03_country(self): Testing GeoIP country que... | Implement the Python class `GeoIPTest` described below.
Class description:
Implement the GeoIPTest class.
Method signatures and docstrings:
- def test01_init(self): Testing GeoIP initialization.
- def test02_bad_query(self): Testing GeoIP query parameter checking.
- def test03_country(self): Testing GeoIP country que... | fa182e8ae82f33764d5e1f70bcd45899e1bf17e6 | <|skeleton|>
class GeoIPTest:
def test01_init(self):
"""Testing GeoIP initialization."""
<|body_0|>
def test02_bad_query(self):
"""Testing GeoIP query parameter checking."""
<|body_1|>
def test03_country(self):
"""Testing GeoIP country querying methods."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeoIPTest:
def test01_init(self):
"""Testing GeoIP initialization."""
g1 = GeoIP()
path = settings.GEOIP_PATH
g2 = GeoIP(path, 0)
g3 = GeoIP.open(path, 0)
for g in (g1, g2, g3):
self.assertEqual(True, bool(g._country))
self.assertEqual(Tr... | the_stack_v2_python_sparse | django/contrib/gis/geoip/tests.py | gregmuellegger/django | train | 22 | |
6e7feb7a628fd0bd9f46fae49b7ad23e21bf9aff | [
"c = []\nself.dfs(c, '', digits)\nreturn c",
"if not r:\n return cmbs.append(s) if s else None\nfor ch in self.d[r[0]]:\n self.dfs(cmbs, s + ch, r[1:])",
"if not digits:\n return []\nif len(digits) == 1:\n return [x for x in self.d[digits[0]]]\nreturn [x + y for x in self.d[digits[0]] for y in self.... | <|body_start_0|>
c = []
self.dfs(c, '', digits)
return c
<|end_body_0|>
<|body_start_1|>
if not r:
return cmbs.append(s) if s else None
for ch in self.d[r[0]]:
self.dfs(cmbs, s + ch, r[1:])
<|end_body_1|>
<|body_start_2|>
if not digits:
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def letterCombinations(self, digits):
""":type digits: str :rtype: List[str]"""
<|body_0|>
def dfs(self, cmbs, s, r):
""":type cmbs: List[str] :type s: str :type r: str"""
<|body_1|>
def letterCombinations_pre1(self, digits):
""":type d... | stack_v2_sparse_classes_36k_train_017963 | 1,029 | permissive | [
{
"docstring": ":type digits: str :rtype: List[str]",
"name": "letterCombinations",
"signature": "def letterCombinations(self, digits)"
},
{
"docstring": ":type cmbs: List[str] :type s: str :type r: str",
"name": "dfs",
"signature": "def dfs(self, cmbs, s, r)"
},
{
"docstring": "... | 3 | stack_v2_sparse_classes_30k_train_000976 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def letterCombinations(self, digits): :type digits: str :rtype: List[str]
- def dfs(self, cmbs, s, r): :type cmbs: List[str] :type s: str :type r: str
- def letterCombinations_pr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def letterCombinations(self, digits): :type digits: str :rtype: List[str]
- def dfs(self, cmbs, s, r): :type cmbs: List[str] :type s: str :type r: str
- def letterCombinations_pr... | cb70ca87aa4604d1aec83d4224b3489eacebba75 | <|skeleton|>
class Solution:
def letterCombinations(self, digits):
""":type digits: str :rtype: List[str]"""
<|body_0|>
def dfs(self, cmbs, s, r):
""":type cmbs: List[str] :type s: str :type r: str"""
<|body_1|>
def letterCombinations_pre1(self, digits):
""":type d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def letterCombinations(self, digits):
""":type digits: str :rtype: List[str]"""
c = []
self.dfs(c, '', digits)
return c
def dfs(self, cmbs, s, r):
""":type cmbs: List[str] :type s: str :type r: str"""
if not r:
return cmbs.append(s) if... | the_stack_v2_python_sparse | LeetCode/Python3/0017._Letter_Combinations_of_a_Phone_Number.py | icgw/practice | train | 1 | |
1bb69a91efb77ee151f70f2ba35860b4a4cbaaea | [
"dirpath_test_tree = os.path.join(dirpath_testdata, 'dir_with_folders_for_filtering')\ndetect_nothing_exp = '^$'\nactual_output = tuple(da.lwc.search._dirname_filtered_os_walk_gen(root=dirpath_test_tree, direxcl=[detect_nothing_exp]))\nexpected_output = ((os.path.join(dirpath_test_tree), ['dir_to_be_filtered', 'dir... | <|body_start_0|>
dirpath_test_tree = os.path.join(dirpath_testdata, 'dir_with_folders_for_filtering')
detect_nothing_exp = '^$'
actual_output = tuple(da.lwc.search._dirname_filtered_os_walk_gen(root=dirpath_test_tree, direxcl=[detect_nothing_exp]))
expected_output = ((os.path.join(dirpat... | Specify the da.lwc.search._dirname_filtered_os_walk_gen() function. | Specify_DirnameFilteredOsWalkGen | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Specify_DirnameFilteredOsWalkGen:
"""Specify the da.lwc.search._dirname_filtered_os_walk_gen() function."""
def it_filtering_nothing_at_all(self, dirpath_testdata):
"""Test the use of an expression that matches nothing to exclude."""
<|body_0|>
def it_filter_something_by... | stack_v2_sparse_classes_36k_train_017964 | 29,518 | permissive | [
{
"docstring": "Test the use of an expression that matches nothing to exclude.",
"name": "it_filtering_nothing_at_all",
"signature": "def it_filtering_nothing_at_all(self, dirpath_testdata)"
},
{
"docstring": "Test that we may filter items using its' full name.",
"name": "it_filter_something... | 2 | null | Implement the Python class `Specify_DirnameFilteredOsWalkGen` described below.
Class description:
Specify the da.lwc.search._dirname_filtered_os_walk_gen() function.
Method signatures and docstrings:
- def it_filtering_nothing_at_all(self, dirpath_testdata): Test the use of an expression that matches nothing to exclu... | Implement the Python class `Specify_DirnameFilteredOsWalkGen` described below.
Class description:
Specify the da.lwc.search._dirname_filtered_os_walk_gen() function.
Method signatures and docstrings:
- def it_filtering_nothing_at_all(self, dirpath_testdata): Test the use of an expression that matches nothing to exclu... | 04a13be2792323e3f9fdb83fd236a8e9cfe6aa2d | <|skeleton|>
class Specify_DirnameFilteredOsWalkGen:
"""Specify the da.lwc.search._dirname_filtered_os_walk_gen() function."""
def it_filtering_nothing_at_all(self, dirpath_testdata):
"""Test the use of an expression that matches nothing to exclude."""
<|body_0|>
def it_filter_something_by... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Specify_DirnameFilteredOsWalkGen:
"""Specify the da.lwc.search._dirname_filtered_os_walk_gen() function."""
def it_filtering_nothing_at_all(self, dirpath_testdata):
"""Test the use of an expression that matches nothing to exclude."""
dirpath_test_tree = os.path.join(dirpath_testdata, 'dir... | the_stack_v2_python_sparse | a3_src/h70_internal/da/lwc/spec/spec_search.py | wtpayne/hiai | train | 5 |
e088a3e8bba98315e09e0a13a25074ca6c3c1d32 | [
"if n < 1 or n > 7:\n raise ValueError('Not a valid period. Must be 1-7')\nreturn np.array([elem for elem in cls.table[n - 1, :] if elem != ''])",
"if n < 1 or n > 18:\n raise ValueError('Not a valid group. Must be 1-18')\nreturn np.array([elem for elem in cls.table[:, n - 1] if elem != ''])",
"try:\n ... | <|body_start_0|>
if n < 1 or n > 7:
raise ValueError('Not a valid period. Must be 1-7')
return np.array([elem for elem in cls.table[n - 1, :] if elem != ''])
<|end_body_0|>
<|body_start_1|>
if n < 1 or n > 18:
raise ValueError('Not a valid group. Must be 1-18')
r... | PeriodicTable | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PeriodicTable:
def period(cls, n: int):
"""Period of the periodic table, with 1 being the first period Arguments: n (int): Returns: (np.ndarray(str)): Raises: (ValueError): If n is not valid period index"""
<|body_0|>
def group(cls, n: int):
"""Group of the periodic ... | stack_v2_sparse_classes_36k_train_017965 | 35,279 | permissive | [
{
"docstring": "Period of the periodic table, with 1 being the first period Arguments: n (int): Returns: (np.ndarray(str)): Raises: (ValueError): If n is not valid period index",
"name": "period",
"signature": "def period(cls, n: int)"
},
{
"docstring": "Group of the periodic table, with 1 being... | 4 | stack_v2_sparse_classes_30k_train_019306 | Implement the Python class `PeriodicTable` described below.
Class description:
Implement the PeriodicTable class.
Method signatures and docstrings:
- def period(cls, n: int): Period of the periodic table, with 1 being the first period Arguments: n (int): Returns: (np.ndarray(str)): Raises: (ValueError): If n is not v... | Implement the Python class `PeriodicTable` described below.
Class description:
Implement the PeriodicTable class.
Method signatures and docstrings:
- def period(cls, n: int): Period of the periodic table, with 1 being the first period Arguments: n (int): Returns: (np.ndarray(str)): Raises: (ValueError): If n is not v... | 6505d5bbbd1906f57e4102e13f177510f166bbed | <|skeleton|>
class PeriodicTable:
def period(cls, n: int):
"""Period of the periodic table, with 1 being the first period Arguments: n (int): Returns: (np.ndarray(str)): Raises: (ValueError): If n is not valid period index"""
<|body_0|>
def group(cls, n: int):
"""Group of the periodic ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PeriodicTable:
def period(cls, n: int):
"""Period of the periodic table, with 1 being the first period Arguments: n (int): Returns: (np.ndarray(str)): Raises: (ValueError): If n is not valid period index"""
if n < 1 or n > 7:
raise ValueError('Not a valid period. Must be 1-7')
... | the_stack_v2_python_sparse | autode/atoms.py | jdelev/autodE | train | 0 | |
ffe564834733640b6ff36c8b4b668289a9d11558 | [
"def canSplit(target):\n sm = 0\n cnt = 0\n for n in nums:\n if sm + n > target:\n sm = n\n cnt += 1\n else:\n sm += n\n cnt += 1\n return cnt <= m\nl = 1\nr = 0\nfor i in nums:\n l = max(l, i)\n r += i\nwhile l + 1 < r:\n mid = l + (r - l) // 2... | <|body_start_0|>
def canSplit(target):
sm = 0
cnt = 0
for n in nums:
if sm + n > target:
sm = n
cnt += 1
else:
sm += n
cnt += 1
return cnt <= m
l = 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def splitArray(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_0|>
def splitArrayBetterCode(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def c... | stack_v2_sparse_classes_36k_train_017966 | 2,394 | no_license | [
{
"docstring": ":type nums: List[int] :type m: int :rtype: int",
"name": "splitArray",
"signature": "def splitArray(self, nums, m)"
},
{
"docstring": ":type nums: List[int] :type m: int :rtype: int",
"name": "splitArrayBetterCode",
"signature": "def splitArrayBetterCode(self, nums, m)"
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitArray(self, nums, m): :type nums: List[int] :type m: int :rtype: int
- def splitArrayBetterCode(self, nums, m): :type nums: List[int] :type m: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def splitArray(self, nums, m): :type nums: List[int] :type m: int :rtype: int
- def splitArrayBetterCode(self, nums, m): :type nums: List[int] :type m: int :rtype: int
<|skeleto... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def splitArray(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_0|>
def splitArrayBetterCode(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def splitArray(self, nums, m):
""":type nums: List[int] :type m: int :rtype: int"""
def canSplit(target):
sm = 0
cnt = 0
for n in nums:
if sm + n > target:
sm = n
cnt += 1
else... | the_stack_v2_python_sparse | S/SplitArrayLargestSum.py | bssrdf/pyleet | train | 2 | |
e89cf719cbee9ae8e5a17e318946c6c7fe9d74ce | [
"self.X_train, self.X_val, self.X_test = (None, None, None)\nself.y_train, self.y_val, self.y_test = (None, None, None)\nself.idx_train, self.idx_val, self.idx_test = (0, 0, 0)\nself.X_train, self.y_train = self.load(train, data_folder)\nif isinstance(val, str):\n self.X_val, self.y_val = self.load(val, data_fol... | <|body_start_0|>
self.X_train, self.X_val, self.X_test = (None, None, None)
self.y_train, self.y_val, self.y_test = (None, None, None)
self.idx_train, self.idx_val, self.idx_test = (0, 0, 0)
self.X_train, self.y_train = self.load(train, data_folder)
if isinstance(val, str):
... | Load image data that has only a single label. Example: line OCR images. # Arguments data_folder [str]: the path that contain data train [str]: the path to train version file val [str]: the path to validation version file test [str]: the path to test version file helper [Helper object]: the helper that customize the out... | SingleLabelLoader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SingleLabelLoader:
"""Load image data that has only a single label. Example: line OCR images. # Arguments data_folder [str]: the path that contain data train [str]: the path to train version file val [str]: the path to validation version file test [str]: the path to test version file helper [Help... | stack_v2_sparse_classes_36k_train_017967 | 4,631 | no_license | [
{
"docstring": "Initialize the object",
"name": "__init__",
"signature": "def __init__(self, data_folder, train, val=None, test=None, helper=None)"
},
{
"docstring": "Load filepath and label from version text file # Arguments version_path [str]: the path to version file data_folder [str]: the pa... | 4 | stack_v2_sparse_classes_30k_train_017524 | Implement the Python class `SingleLabelLoader` described below.
Class description:
Load image data that has only a single label. Example: line OCR images. # Arguments data_folder [str]: the path that contain data train [str]: the path to train version file val [str]: the path to validation version file test [str]: the... | Implement the Python class `SingleLabelLoader` described below.
Class description:
Load image data that has only a single label. Example: line OCR images. # Arguments data_folder [str]: the path that contain data train [str]: the path to train version file val [str]: the path to validation version file test [str]: the... | 825ea87508b4d107b2425f37be89597cce5e0484 | <|skeleton|>
class SingleLabelLoader:
"""Load image data that has only a single label. Example: line OCR images. # Arguments data_folder [str]: the path that contain data train [str]: the path to train version file val [str]: the path to validation version file test [str]: the path to test version file helper [Help... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SingleLabelLoader:
"""Load image data that has only a single label. Example: line OCR images. # Arguments data_folder [str]: the path that contain data train [str]: the path to train version file val [str]: the path to validation version file test [str]: the path to test version file helper [Helper object]: t... | the_stack_v2_python_sparse | text_normalizer/cinnamon/versioning/loader.py | lionelcinnamon/AnsonOCR | train | 0 |
f5aeacbf3509ee7c4a8ec0445f76c7bd00ac0551 | [
"roman_int = {'I': 1, 'IV': 4, 'V': 5, 'IX': 9, 'X': 10, 'XL': 40, 'L': 50, 'XC': 90, 'C': 100, 'CD': 400, 'D': 500, 'CM': 900, 'M': 1000}\nresult = 0\ni = 0\nn = len(string)\nwhile i < n:\n if i < n - 1 and roman_int[string[i]] < roman_int[string[i + 1]]:\n result += roman_int[string[i:i + 2]]\n i... | <|body_start_0|>
roman_int = {'I': 1, 'IV': 4, 'V': 5, 'IX': 9, 'X': 10, 'XL': 40, 'L': 50, 'XC': 90, 'C': 100, 'CD': 400, 'D': 500, 'CM': 900, 'M': 1000}
result = 0
i = 0
n = len(string)
while i < n:
if i < n - 1 and roman_int[string[i]] < roman_int[string[i + 1]]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def roman_to_int(self, string):
"""Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to ... | stack_v2_sparse_classes_36k_train_017968 | 2,904 | no_license | [
{
"docstring": "Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to take 2 characters to evaluate number. 3) Otherwise, w... | 2 | stack_v2_sparse_classes_30k_train_017107 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def roman_to_int(self, string): Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def roman_to_int(self, string): Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of ... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def roman_to_int(self, string):
"""Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def roman_to_int(self, string):
"""Converts Roman numerals to decimal integer. Intuitive algorithm. Algorithm description: 1) Scan the string from left to right. 2) If the value of current Roman character is less than the value of next Roman character, it means that we need to take 2 charact... | the_stack_v2_python_sparse | Strings/roman_numerals/roman_to_integer.py | vladn90/Algorithms | train | 0 | |
8cb2df592dccc89c46eb895bfe4c05ec1b405819 | [
"self.item_code = item_code\nself.description = description\nself.market_price = market_price\nself.rental_price = rental_price",
"output_dict = {}\noutput_dict['item_code'] = self.item_code\noutput_dict['description'] = self.description\noutput_dict['market_price'] = self.market_price\noutput_dict['rental_price'... | <|body_start_0|>
self.item_code = item_code
self.description = description
self.market_price = market_price
self.rental_price = rental_price
<|end_body_0|>
<|body_start_1|>
output_dict = {}
output_dict['item_code'] = self.item_code
output_dict['description'] = se... | Contains inventory class methods and attributes. | Inventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inventory:
"""Contains inventory class methods and attributes."""
def __init__(self, item_code, description, market_price, rental_price):
"""Create inventory item."""
<|body_0|>
def return_as_dictionary(self):
"""Return inventory item information as dictionary.""... | stack_v2_sparse_classes_36k_train_017969 | 751 | no_license | [
{
"docstring": "Create inventory item.",
"name": "__init__",
"signature": "def __init__(self, item_code, description, market_price, rental_price)"
},
{
"docstring": "Return inventory item information as dictionary.",
"name": "return_as_dictionary",
"signature": "def return_as_dictionary(... | 2 | null | Implement the Python class `Inventory` described below.
Class description:
Contains inventory class methods and attributes.
Method signatures and docstrings:
- def __init__(self, item_code, description, market_price, rental_price): Create inventory item.
- def return_as_dictionary(self): Return inventory item informa... | Implement the Python class `Inventory` described below.
Class description:
Contains inventory class methods and attributes.
Method signatures and docstrings:
- def __init__(self, item_code, description, market_price, rental_price): Create inventory item.
- def return_as_dictionary(self): Return inventory item informa... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class Inventory:
"""Contains inventory class methods and attributes."""
def __init__(self, item_code, description, market_price, rental_price):
"""Create inventory item."""
<|body_0|>
def return_as_dictionary(self):
"""Return inventory item information as dictionary.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Inventory:
"""Contains inventory class methods and attributes."""
def __init__(self, item_code, description, market_price, rental_price):
"""Create inventory item."""
self.item_code = item_code
self.description = description
self.market_price = market_price
self.re... | the_stack_v2_python_sparse | students/Reem_Alqaysi/Lesson_01/inventory_management/inventory_class.py | JavaRod/SP_Python220B_2019 | train | 1 |
21acedd6f3a72f7dccbded54ea59267487054d26 | [
"self.vector_size = vector_size\nself.item_vectors = {}\nself.embeddings_model = None\nself.id_index_dict = None",
"self.id_index_dict, _ = Utils.build_item_indices(list(train_seqs.values()), id_index_dict_file)\nvocab_size = len(self.id_index_dict)\nprint('building context and negative sampling pairs')\ndata_cou... | <|body_start_0|>
self.vector_size = vector_size
self.item_vectors = {}
self.embeddings_model = None
self.id_index_dict = None
<|end_body_0|>
<|body_start_1|>
self.id_index_dict, _ = Utils.build_item_indices(list(train_seqs.values()), id_index_dict_file)
vocab_size = len(... | Model to train embedding network on product sequences. Neural network is trained and resulting embeddings are used to create recommendations | Prod2VecModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Prod2VecModel:
"""Model to train embedding network on product sequences. Neural network is trained and resulting embeddings are used to create recommendations"""
def __init__(self, vector_size=100):
"""initializes Prod2Vec recommendation model Parameters ---------- vector_size : int,... | stack_v2_sparse_classes_36k_train_017970 | 5,418 | no_license | [
{
"docstring": "initializes Prod2Vec recommendation model Parameters ---------- vector_size : int, embedding layer size Attributes ---------- vector_size item_vectors : dict of (song_id => p2v vectors) embeddings_model : Keras model to train embeddings id_index_dict : dict (item_id => index in embeddings layer)... | 3 | stack_v2_sparse_classes_30k_train_011209 | Implement the Python class `Prod2VecModel` described below.
Class description:
Model to train embedding network on product sequences. Neural network is trained and resulting embeddings are used to create recommendations
Method signatures and docstrings:
- def __init__(self, vector_size=100): initializes Prod2Vec reco... | Implement the Python class `Prod2VecModel` described below.
Class description:
Model to train embedding network on product sequences. Neural network is trained and resulting embeddings are used to create recommendations
Method signatures and docstrings:
- def __init__(self, vector_size=100): initializes Prod2Vec reco... | f9ccc8b3289b5b2de36321cd5d2f1058d411e578 | <|skeleton|>
class Prod2VecModel:
"""Model to train embedding network on product sequences. Neural network is trained and resulting embeddings are used to create recommendations"""
def __init__(self, vector_size=100):
"""initializes Prod2Vec recommendation model Parameters ---------- vector_size : int,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Prod2VecModel:
"""Model to train embedding network on product sequences. Neural network is trained and resulting embeddings are used to create recommendations"""
def __init__(self, vector_size=100):
"""initializes Prod2Vec recommendation model Parameters ---------- vector_size : int, embedding la... | the_stack_v2_python_sparse | KGRec/Prod2Vec.py | joerenner/TextBasedRecommendation | train | 3 |
fbc5b75791e9f60c6e12bd01e5f593eeb4acbecc | [
"alpha = 0.001\nk2, p = normaltest(data)\nif p < alpha:\n return True\nelse:\n return False",
"beta = 0.001\nif skew(data) < beta:\n return True\nelse:\n return False",
"if question == 'normal?':\n try:\n return cls.check_normal_population(experimental_data)\n except:\n return Fa... | <|body_start_0|>
alpha = 0.001
k2, p = normaltest(data)
if p < alpha:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
beta = 0.001
if skew(data) < beta:
return True
else:
return False
<|end_body_1|>
... | **Checks for situations for which Hypothesis Testing About Means is valid, i.e, is t-Test (or standard z-score) valid?** **Situation-1** For large sample sizes and randomly collected individuals one may assume that the population of the measurements (of interest) is normal. Thus condition for hypothesis testing about m... | NecessaryForHTMeans | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NecessaryForHTMeans:
"""**Checks for situations for which Hypothesis Testing About Means is valid, i.e, is t-Test (or standard z-score) valid?** **Situation-1** For large sample sizes and randomly collected individuals one may assume that the population of the measurements (of interest) is normal... | stack_v2_sparse_classes_36k_train_017971 | 6,047 | permissive | [
{
"docstring": "Tests if sample is from a normal distribution. Algorithm to check if population is normal -------- | **Given:** data | **Parameter:** :math:`\\\\alpha = 0.001` | **Compute:** p :math:`\\\\leftarrow` normaltest(data) | **if** p < :math:`\\\\alpha` | \"data is normal\" | **else** | \"data is not n... | 3 | stack_v2_sparse_classes_30k_train_004777 | Implement the Python class `NecessaryForHTMeans` described below.
Class description:
**Checks for situations for which Hypothesis Testing About Means is valid, i.e, is t-Test (or standard z-score) valid?** **Situation-1** For large sample sizes and randomly collected individuals one may assume that the population of t... | Implement the Python class `NecessaryForHTMeans` described below.
Class description:
**Checks for situations for which Hypothesis Testing About Means is valid, i.e, is t-Test (or standard z-score) valid?** **Situation-1** For large sample sizes and randomly collected individuals one may assume that the population of t... | 1f12ec3c5559467b6cc48c12384e93d0ca0d2a45 | <|skeleton|>
class NecessaryForHTMeans:
"""**Checks for situations for which Hypothesis Testing About Means is valid, i.e, is t-Test (or standard z-score) valid?** **Situation-1** For large sample sizes and randomly collected individuals one may assume that the population of the measurements (of interest) is normal... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NecessaryForHTMeans:
"""**Checks for situations for which Hypothesis Testing About Means is valid, i.e, is t-Test (or standard z-score) valid?** **Situation-1** For large sample sizes and randomly collected individuals one may assume that the population of the measurements (of interest) is normal. Thus condit... | the_stack_v2_python_sparse | cerebstats/data_conditions/forHTmeans.py | HarshKhilawala/cerebstats | train | 0 |
659df4336699a99c4801fe23ed733bf7a7dd971c | [
"self.arr = vec2d\nself.row = 0\nself.col = 0",
"nextVar = self.arr[self.row][self.col]\nself.col += 1\nreturn nextVar",
"while self.row <= len(self.arr) - 1:\n if self.col <= len(self.arr[self.row]) - 1:\n return True\n self.col = 0\n self.row += 1\nreturn False"
] | <|body_start_0|>
self.arr = vec2d
self.row = 0
self.col = 0
<|end_body_0|>
<|body_start_1|>
nextVar = self.arr[self.row][self.col]
self.col += 1
return nextVar
<|end_body_1|>
<|body_start_2|>
while self.row <= len(self.arr) - 1:
if self.col <= len(se... | Vector2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_36k_train_017972 | 1,182 | no_license | [
{
"docstring": "Initialize your data structure here. :type vec2d: List[List[int]]",
"name": "__init__",
"signature": "def __init__(self, vec2d)"
},
{
"docstring": ":rtype: int",
"name": "next",
"signature": "def next(self)"
},
{
"docstring": ":rtype: bool",
"name": "hasNext",... | 3 | null | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool | Implement the Python class `Vector2D` described below.
Class description:
Implement the Vector2D class.
Method signatures and docstrings:
- def __init__(self, vec2d): Initialize your data structure here. :type vec2d: List[List[int]]
- def next(self): :rtype: int
- def hasNext(self): :rtype: bool
<|skeleton|>
class V... | d1666d44226274f13af25cf878cd63a24e1c5528 | <|skeleton|>
class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
<|body_0|>
def next(self):
""":rtype: int"""
<|body_1|>
def hasNext(self):
""":rtype: bool"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Vector2D:
def __init__(self, vec2d):
"""Initialize your data structure here. :type vec2d: List[List[int]]"""
self.arr = vec2d
self.row = 0
self.col = 0
def next(self):
""":rtype: int"""
nextVar = self.arr[self.row][self.col]
self.col += 1
re... | the_stack_v2_python_sparse | Array+HashTable/LeetCode251_Flatten2DVector.py | rexhzhang/LeetCodeProbelms | train | 0 | |
cc5ab69f1468a10c31c063c1110edba44ba2bc7e | [
"youtube_form = YoutubeForm(request.GET, page_token=page_token)\nif youtube_form.is_valid():\n\n def move_to_library_form(youtube_result):\n form = MoveToYoutubeForm(initial={'name': youtube_result['snippet']['title'], 'video_id': youtube_result['id']['videoId']})\n return {'result': youtube_result... | <|body_start_0|>
youtube_form = YoutubeForm(request.GET, page_token=page_token)
if youtube_form.is_valid():
def move_to_library_form(youtube_result):
form = MoveToYoutubeForm(initial={'name': youtube_result['snippet']['title'], 'video_id': youtube_result['id']['videoId']})
... | Give additional options for user to have search over youtube enabled | YoutubeAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class YoutubeAdmin:
"""Give additional options for user to have search over youtube enabled"""
def changelist_view(self, request, extra_context=None, page_token=None):
"""Extend normal admin changelist view to add youtube video searchs. We search only if youtube form is valid. (Youtube for... | stack_v2_sparse_classes_36k_train_017973 | 3,435 | no_license | [
{
"docstring": "Extend normal admin changelist view to add youtube video searchs. We search only if youtube form is valid. (Youtube form requires query phrase to be available in get) We also might push page_token to youtube. We can not put page_token in GET b'coz django admin check params and will make redirect... | 3 | stack_v2_sparse_classes_30k_train_002078 | Implement the Python class `YoutubeAdmin` described below.
Class description:
Give additional options for user to have search over youtube enabled
Method signatures and docstrings:
- def changelist_view(self, request, extra_context=None, page_token=None): Extend normal admin changelist view to add youtube video searc... | Implement the Python class `YoutubeAdmin` described below.
Class description:
Give additional options for user to have search over youtube enabled
Method signatures and docstrings:
- def changelist_view(self, request, extra_context=None, page_token=None): Extend normal admin changelist view to add youtube video searc... | 3d2a3efc44dae59f0c36127ec090365f63bebcdd | <|skeleton|>
class YoutubeAdmin:
"""Give additional options for user to have search over youtube enabled"""
def changelist_view(self, request, extra_context=None, page_token=None):
"""Extend normal admin changelist view to add youtube video searchs. We search only if youtube form is valid. (Youtube for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class YoutubeAdmin:
"""Give additional options for user to have search over youtube enabled"""
def changelist_view(self, request, extra_context=None, page_token=None):
"""Extend normal admin changelist view to add youtube video searchs. We search only if youtube form is valid. (Youtube form requires qu... | the_stack_v2_python_sparse | filebrowser_extensions/youtube/admin.py | tomaszroszko/django_filebrowser_extension | train | 0 |
f07806006c298a28ad82d28de5280161094c355f | [
"vals = super(PurchaseOrder, self)._prepare_picking()\nif self.inter_company_transfer_id:\n vals.update({'inter_company_transfer_id': self.inter_company_transfer_id.id})\nreturn vals",
"action = super(PurchaseOrder, self).action_view_invoice()\nif self.env.context.get('create_bill', False) and self.inter_compa... | <|body_start_0|>
vals = super(PurchaseOrder, self)._prepare_picking()
if self.inter_company_transfer_id:
vals.update({'inter_company_transfer_id': self.inter_company_transfer_id.id})
return vals
<|end_body_0|>
<|body_start_1|>
action = super(PurchaseOrder, self).action_view_... | Inherited for adding relation with inter company transfer. @author: Maulik Barad on Date 24-Sep-2019. | PurchaseOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PurchaseOrder:
"""Inherited for adding relation with inter company transfer. @author: Maulik Barad on Date 24-Sep-2019."""
def _prepare_picking(self):
"""Inherited for adding relation with ICT if created by it. @author: Maulik Barad on Date 16-Oct-2019. @return: Dictionary for creati... | stack_v2_sparse_classes_36k_train_017974 | 1,503 | no_license | [
{
"docstring": "Inherited for adding relation with ICT if created by it. @author: Maulik Barad on Date 16-Oct-2019. @return: Dictionary for creating picking.",
"name": "_prepare_picking",
"signature": "def _prepare_picking(self)"
},
{
"docstring": "Inherited for adding relation with ICT if creat... | 2 | null | Implement the Python class `PurchaseOrder` described below.
Class description:
Inherited for adding relation with inter company transfer. @author: Maulik Barad on Date 24-Sep-2019.
Method signatures and docstrings:
- def _prepare_picking(self): Inherited for adding relation with ICT if created by it. @author: Maulik ... | Implement the Python class `PurchaseOrder` described below.
Class description:
Inherited for adding relation with inter company transfer. @author: Maulik Barad on Date 24-Sep-2019.
Method signatures and docstrings:
- def _prepare_picking(self): Inherited for adding relation with ICT if created by it. @author: Maulik ... | 45749da5cc82d0a50cdf5627072b9bd43a4206dc | <|skeleton|>
class PurchaseOrder:
"""Inherited for adding relation with inter company transfer. @author: Maulik Barad on Date 24-Sep-2019."""
def _prepare_picking(self):
"""Inherited for adding relation with ICT if created by it. @author: Maulik Barad on Date 16-Oct-2019. @return: Dictionary for creati... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PurchaseOrder:
"""Inherited for adding relation with inter company transfer. @author: Maulik Barad on Date 24-Sep-2019."""
def _prepare_picking(self):
"""Inherited for adding relation with ICT if created by it. @author: Maulik Barad on Date 16-Oct-2019. @return: Dictionary for creating picking.""... | the_stack_v2_python_sparse | intercompany_transaction_ept/models/purchase.py | ecgroupca/ECGroup | train | 1 |
a9ceafab490122dac75b3d293f5f2c34a175258a | [
"kwargs_dict = {'loadpath_controller': LoadSteppingControl(), 'loadpath_controller_options': {'nonlinear_solver_options': {'log_iterations': True, 'rtol': 1e-08}, 'N_steps': 1}}\nkwargs_dict.update(kwargs)\nsuper().__init__(integrator_dict, B_dict, t0, t_end, q0_dict, dq0_dict, ddq0_dict, **kwargs_dict)\nself._nonl... | <|body_start_0|>
kwargs_dict = {'loadpath_controller': LoadSteppingControl(), 'loadpath_controller_options': {'nonlinear_solver_options': {'log_iterations': True, 'rtol': 1e-08}, 'N_steps': 1}}
kwargs_dict.update(kwargs)
super().__init__(integrator_dict, B_dict, t0, t_end, q0_dict, dq0_dict, ddq... | FETI-solver for nonlinear dynamic problems Attributes ---------- _nonlinear_solver : ControlBase nonlinear global solver _solver_manager : SolverManagerBase solver manager for the global problem _local_problem : LocalProblemBase local problem _config_dict : dict solver-configuration _dual_solution_length : int number o... | NonlinearDynamicFetiSolver | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NonlinearDynamicFetiSolver:
"""FETI-solver for nonlinear dynamic problems Attributes ---------- _nonlinear_solver : ControlBase nonlinear global solver _solver_manager : SolverManagerBase solver manager for the global problem _local_problem : LocalProblemBase local problem _config_dict : dict sol... | stack_v2_sparse_classes_36k_train_017975 | 13,384 | permissive | [
{
"docstring": "Parameters ---------- integrator_dict : dict integrator-objects describing the dynamic behavior of the local problems. For detailed specifications on the Integrator-class see `Basics of time-integration` or `Requirements to an Integrator-Class` and for the required API the :class:`~amfeti.local_... | 5 | stack_v2_sparse_classes_30k_train_000597 | Implement the Python class `NonlinearDynamicFetiSolver` described below.
Class description:
FETI-solver for nonlinear dynamic problems Attributes ---------- _nonlinear_solver : ControlBase nonlinear global solver _solver_manager : SolverManagerBase solver manager for the global problem _local_problem : LocalProblemBas... | Implement the Python class `NonlinearDynamicFetiSolver` described below.
Class description:
FETI-solver for nonlinear dynamic problems Attributes ---------- _nonlinear_solver : ControlBase nonlinear global solver _solver_manager : SolverManagerBase solver manager for the global problem _local_problem : LocalProblemBas... | be209dffe4d170aca735f1e912fd5cb448502119 | <|skeleton|>
class NonlinearDynamicFetiSolver:
"""FETI-solver for nonlinear dynamic problems Attributes ---------- _nonlinear_solver : ControlBase nonlinear global solver _solver_manager : SolverManagerBase solver manager for the global problem _local_problem : LocalProblemBase local problem _config_dict : dict sol... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NonlinearDynamicFetiSolver:
"""FETI-solver for nonlinear dynamic problems Attributes ---------- _nonlinear_solver : ControlBase nonlinear global solver _solver_manager : SolverManagerBase solver manager for the global problem _local_problem : LocalProblemBase local problem _config_dict : dict solver-configura... | the_stack_v2_python_sparse | amfeti/feti_solvers/dynamic_feti_solver.py | AppliedMechanics/AMfeti | train | 3 |
2f5431ff48b1ec9144b37c5220fc2ad296c24d58 | [
"super().__init__(with_jokers=with_jokers)\nif with_jokers:\n for _ in range(2):\n self._cards.append(Card(JOKER_RANK, JOKER_SUIT))\nfor suit in POSSIBLE_SUIT:\n for rank in POSSIBLE_RANK:\n self._cards.append(Card(rank, suit))",
"total_possible_cards = 2 * (13 * 4 + (2 if self._with_jokers el... | <|body_start_0|>
super().__init__(with_jokers=with_jokers)
if with_jokers:
for _ in range(2):
self._cards.append(Card(JOKER_RANK, JOKER_SUIT))
for suit in POSSIBLE_SUIT:
for rank in POSSIBLE_RANK:
self._cards.append(Card(rank, suit))
<|end_... | A DoubleDeck object A new double deck starts out ordered. If jokers are included, contains 2 * (2 + 4 * 13) :class:`deck_of_cards.card.Card` objects If no jokers are included, contains 2 * (4 * 13) :class:`deck_of_cards.card.Card` objects | DoubleDeck | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoubleDeck:
"""A DoubleDeck object A new double deck starts out ordered. If jokers are included, contains 2 * (2 + 4 * 13) :class:`deck_of_cards.card.Card` objects If no jokers are included, contains 2 * (4 * 13) :class:`deck_of_cards.card.Card` objects"""
def __init__(self, with_jokers=True... | stack_v2_sparse_classes_36k_train_017976 | 2,704 | no_license | [
{
"docstring": ":param bool with_jokers: include jokers if True",
"name": "__init__",
"signature": "def __init__(self, with_jokers=True)"
},
{
"docstring": "Check to make sure all the cards are accounted :returns: True if all cards are accounted :rtype: bool",
"name": "check_deck",
"sign... | 2 | stack_v2_sparse_classes_30k_train_008201 | Implement the Python class `DoubleDeck` described below.
Class description:
A DoubleDeck object A new double deck starts out ordered. If jokers are included, contains 2 * (2 + 4 * 13) :class:`deck_of_cards.card.Card` objects If no jokers are included, contains 2 * (4 * 13) :class:`deck_of_cards.card.Card` objects
Met... | Implement the Python class `DoubleDeck` described below.
Class description:
A DoubleDeck object A new double deck starts out ordered. If jokers are included, contains 2 * (2 + 4 * 13) :class:`deck_of_cards.card.Card` objects If no jokers are included, contains 2 * (4 * 13) :class:`deck_of_cards.card.Card` objects
Met... | 3cf666cb7f88fb0e317401b0c017c30fa742aead | <|skeleton|>
class DoubleDeck:
"""A DoubleDeck object A new double deck starts out ordered. If jokers are included, contains 2 * (2 + 4 * 13) :class:`deck_of_cards.card.Card` objects If no jokers are included, contains 2 * (4 * 13) :class:`deck_of_cards.card.Card` objects"""
def __init__(self, with_jokers=True... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoubleDeck:
"""A DoubleDeck object A new double deck starts out ordered. If jokers are included, contains 2 * (2 + 4 * 13) :class:`deck_of_cards.card.Card` objects If no jokers are included, contains 2 * (4 * 13) :class:`deck_of_cards.card.Card` objects"""
def __init__(self, with_jokers=True):
""... | the_stack_v2_python_sparse | base/cards/double_deck.py | MichielRuelens/Canasta | train | 0 |
9b70c7c1460040908010eb17edc77510fe4e1ff1 | [
"node = _Node(value)\nif self._root is None:\n self._root = node\n return\ncurrent = self._root\nwhile True:\n if value < current.value:\n if not current.left:\n current.left = node\n return\n else:\n current = current.left\n elif not current.right:\n ... | <|body_start_0|>
node = _Node(value)
if self._root is None:
self._root = node
return
current = self._root
while True:
if value < current.value:
if not current.left:
current.left = node
return
... | BinarySearchTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinarySearchTree:
def add(self, value):
"""Adds node to a tree and places it dependent upon the rest of the tree"""
<|body_0|>
def contains(self, value):
"""returns boolean that expresses whether or not value exists in binary tree"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k_train_017977 | 5,591 | no_license | [
{
"docstring": "Adds node to a tree and places it dependent upon the rest of the tree",
"name": "add",
"signature": "def add(self, value)"
},
{
"docstring": "returns boolean that expresses whether or not value exists in binary tree",
"name": "contains",
"signature": "def contains(self, v... | 2 | stack_v2_sparse_classes_30k_train_017868 | Implement the Python class `BinarySearchTree` described below.
Class description:
Implement the BinarySearchTree class.
Method signatures and docstrings:
- def add(self, value): Adds node to a tree and places it dependent upon the rest of the tree
- def contains(self, value): returns boolean that expresses whether or... | Implement the Python class `BinarySearchTree` described below.
Class description:
Implement the BinarySearchTree class.
Method signatures and docstrings:
- def add(self, value): Adds node to a tree and places it dependent upon the rest of the tree
- def contains(self, value): returns boolean that expresses whether or... | 677f071a04a429b6ec8c307bd32cfb654bc8ec11 | <|skeleton|>
class BinarySearchTree:
def add(self, value):
"""Adds node to a tree and places it dependent upon the rest of the tree"""
<|body_0|>
def contains(self, value):
"""returns boolean that expresses whether or not value exists in binary tree"""
<|body_1|>
<|end_skeleto... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinarySearchTree:
def add(self, value):
"""Adds node to a tree and places it dependent upon the rest of the tree"""
node = _Node(value)
if self._root is None:
self._root = node
return
current = self._root
while True:
if value < curren... | the_stack_v2_python_sparse | data-structures/tree/tree.py | Rayxclockwork/python-data-structures-and-algorithms | train | 0 | |
6f361577959126e469cd2343037be532f7c49eec | [
"try:\n payload = {'exp': datetime.utcnow() + timedelta(days=app.config.get('TOKEN_EXPIRATION_DAYS', 0), seconds=app.config.get('TOKEN_EXPIRATION_SECONDS', 0)), 'iat': datetime.utcnow(), 'sub': user_id, 'role': role}\n return jwt.encode(payload=payload, key=app.config.get('SECRET_KEY', None), algorithm='HS256... | <|body_start_0|>
try:
payload = {'exp': datetime.utcnow() + timedelta(days=app.config.get('TOKEN_EXPIRATION_DAYS', 0), seconds=app.config.get('TOKEN_EXPIRATION_SECONDS', 0)), 'iat': datetime.utcnow(), 'sub': user_id, 'role': role}
return jwt.encode(payload=payload, key=app.config.get('SE... | AuthService | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthService:
def encode_auth_token(user_id: ObjectId, role: str='user') -> Union[bytes, None]:
"""Generates JWT auth token that is returned as bytes. Args: user_id: an ObjectId for the User. role: the role of user. Must be one of: `admin` or `user`. Returns: A valid JWT token as bytes.""... | stack_v2_sparse_classes_36k_train_017978 | 4,615 | permissive | [
{
"docstring": "Generates JWT auth token that is returned as bytes. Args: user_id: an ObjectId for the User. role: the role of user. Must be one of: `admin` or `user`. Returns: A valid JWT token as bytes.",
"name": "encode_auth_token",
"signature": "def encode_auth_token(user_id: ObjectId, role: str='us... | 4 | stack_v2_sparse_classes_30k_train_006202 | Implement the Python class `AuthService` described below.
Class description:
Implement the AuthService class.
Method signatures and docstrings:
- def encode_auth_token(user_id: ObjectId, role: str='user') -> Union[bytes, None]: Generates JWT auth token that is returned as bytes. Args: user_id: an ObjectId for the Use... | Implement the Python class `AuthService` described below.
Class description:
Implement the AuthService class.
Method signatures and docstrings:
- def encode_auth_token(user_id: ObjectId, role: str='user') -> Union[bytes, None]: Generates JWT auth token that is returned as bytes. Args: user_id: an ObjectId for the Use... | e04eaa315c76b0295d3d7450cf59b8b0b4a7f22b | <|skeleton|>
class AuthService:
def encode_auth_token(user_id: ObjectId, role: str='user') -> Union[bytes, None]:
"""Generates JWT auth token that is returned as bytes. Args: user_id: an ObjectId for the User. role: the role of user. Must be one of: `admin` or `user`. Returns: A valid JWT token as bytes.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthService:
def encode_auth_token(user_id: ObjectId, role: str='user') -> Union[bytes, None]:
"""Generates JWT auth token that is returned as bytes. Args: user_id: an ObjectId for the User. role: the role of user. Must be one of: `admin` or `user`. Returns: A valid JWT token as bytes."""
try:... | the_stack_v2_python_sparse | services/simcct/sim_api/auth_service.py | NeuralDev-io/arclytics_simcct | train | 2 | |
347099a8a6826dc74c7b0b29878d5277d6a29cb7 | [
"self._dictionary = dictionary\nself._source = source\nself._filepath = filepath\nif self._validate(source=self._source, filepath=self._filepath):\n if self._source.lower() == 'json':\n dict_ = self._read_json(filepath=self._filepath)\n else:\n dict_ = self._dictionary\n for k, v in dict_.ite... | <|body_start_0|>
self._dictionary = dictionary
self._source = source
self._filepath = filepath
if self._validate(source=self._source, filepath=self._filepath):
if self._source.lower() == 'json':
dict_ = self._read_json(filepath=self._filepath)
else... | Create a Python object from a standard dictionary, or JSON file. Args: dictionary (dict): A standard Python dictionary where all key/value pairs will be converted into an object. source (str): Source for the conversion. * 'dict': a standard Python dictionary * 'json': uses content from a JSON file filepath (str): Full ... | Dict2Obj | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dict2Obj:
"""Create a Python object from a standard dictionary, or JSON file. Args: dictionary (dict): A standard Python dictionary where all key/value pairs will be converted into an object. source (str): Source for the conversion. * 'dict': a standard Python dictionary * 'json': uses content fr... | stack_v2_sparse_classes_36k_train_017979 | 5,971 | permissive | [
{
"docstring": "Class initialiser.",
"name": "__init__",
"signature": "def __init__(self, dictionary=None, source='dict', filepath=None)"
},
{
"docstring": "Run the following validation tests: * The 'source' value is valid * If 'json' source, a file path is provided * If 'json' source, the provi... | 6 | stack_v2_sparse_classes_30k_train_018603 | Implement the Python class `Dict2Obj` described below.
Class description:
Create a Python object from a standard dictionary, or JSON file. Args: dictionary (dict): A standard Python dictionary where all key/value pairs will be converted into an object. source (str): Source for the conversion. * 'dict': a standard Pyth... | Implement the Python class `Dict2Obj` described below.
Class description:
Create a Python object from a standard dictionary, or JSON file. Args: dictionary (dict): A standard Python dictionary where all key/value pairs will be converted into an object. source (str): Source for the conversion. * 'dict': a standard Pyth... | 824bee75ecd756b9097581e5cf5929b389a74240 | <|skeleton|>
class Dict2Obj:
"""Create a Python object from a standard dictionary, or JSON file. Args: dictionary (dict): A standard Python dictionary where all key/value pairs will be converted into an object. source (str): Source for the conversion. * 'dict': a standard Python dictionary * 'json': uses content fr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Dict2Obj:
"""Create a Python object from a standard dictionary, or JSON file. Args: dictionary (dict): A standard Python dictionary where all key/value pairs will be converted into an object. source (str): Source for the conversion. * 'dict': a standard Python dictionary * 'json': uses content from a JSON fil... | the_stack_v2_python_sparse | build/lib/utils3/dict2obj.py | S3DEV/utils3 | train | 0 |
0e085728259f974c4846f38b245b7871f79f56bd | [
"s = set()\n\ndef helper(n, s):\n if n == 1:\n return True\n if n in s:\n return False\n l = list(str(n))\n res = 0\n for i in range(len(l)):\n res += pow(int(l[i]), 2)\n s.add(n)\n return helper(res, s)\nreturn helper(n, s)",
"n = str(n)\nslow = n\nfast = str(sum((int(i)... | <|body_start_0|>
s = set()
def helper(n, s):
if n == 1:
return True
if n in s:
return False
l = list(str(n))
res = 0
for i in range(len(l)):
res += pow(int(l[i]), 2)
s.add(n)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isHappy(self, n: int) -> bool:
"""集合解法"""
<|body_0|>
def isHappy1(self, n: int) -> bool:
"""快慢指针"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
s = set()
def helper(n, s):
if n == 1:
return True
... | stack_v2_sparse_classes_36k_train_017980 | 1,817 | no_license | [
{
"docstring": "集合解法",
"name": "isHappy",
"signature": "def isHappy(self, n: int) -> bool"
},
{
"docstring": "快慢指针",
"name": "isHappy1",
"signature": "def isHappy1(self, n: int) -> bool"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHappy(self, n: int) -> bool: 集合解法
- def isHappy1(self, n: int) -> bool: 快慢指针 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isHappy(self, n: int) -> bool: 集合解法
- def isHappy1(self, n: int) -> bool: 快慢指针
<|skeleton|>
class Solution:
def isHappy(self, n: int) -> bool:
"""集合解法"""
... | 40726506802d2d60028fdce206696b1df2f63ece | <|skeleton|>
class Solution:
def isHappy(self, n: int) -> bool:
"""集合解法"""
<|body_0|>
def isHappy1(self, n: int) -> bool:
"""快慢指针"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isHappy(self, n: int) -> bool:
"""集合解法"""
s = set()
def helper(n, s):
if n == 1:
return True
if n in s:
return False
l = list(str(n))
res = 0
for i in range(len(l)):
... | the_stack_v2_python_sparse | 二刷+题解/每日一题/isHappy.py | 1oser5/LeetCode | train | 0 | |
8a533219aa03c524c720b82351c1350bae4d5db5 | [
"self._image = str(image)\nself._nodes = int(nodes)\nself._cores_per_node = int(cores_per_node)\nself._mem_per_core = str(mem_per_core)\nself._gpus_per_node = int(gpus_per_node)\nif shape is not None:\n self._shape = str(shape)\nelse:\n self._shape = None\nself._tmp_disk_per_node = str(tmp_disk_per_node)\nsel... | <|body_start_0|>
self._image = str(image)
self._nodes = int(nodes)
self._cores_per_node = int(cores_per_node)
self._mem_per_core = str(mem_per_core)
self._gpus_per_node = int(gpus_per_node)
if shape is not None:
self._shape = str(shape)
else:
... | This class holds the full set of requestable resources needed for a Job submitted to the system. This includes the container URL for any container images used by the job, the number of nodes and processors, the amount of memory per node, the amount of disk space needed etc. | Resources | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Resources:
"""This class holds the full set of requestable resources needed for a Job submitted to the system. This includes the container URL for any container images used by the job, the number of nodes and processors, the amount of memory per node, the amount of disk space needed etc."""
... | stack_v2_sparse_classes_36k_train_017981 | 2,450 | permissive | [
{
"docstring": "Construct a set of resources specifying everything that may be needed to obtain sufficient resource to run a job",
"name": "__init__",
"signature": "def __init__(self, image=None, nodes=1, cores_per_node=1, mem_per_core='100MB', gpus_per_node=0, shape=None, tmp_disk_per_node='4GB', scrat... | 3 | null | Implement the Python class `Resources` described below.
Class description:
This class holds the full set of requestable resources needed for a Job submitted to the system. This includes the container URL for any container images used by the job, the number of nodes and processors, the amount of memory per node, the am... | Implement the Python class `Resources` described below.
Class description:
This class holds the full set of requestable resources needed for a Job submitted to the system. This includes the container URL for any container images used by the job, the number of nodes and processors, the amount of memory per node, the am... | fe4c9cb2b90374b386d5ea38e514faa96661701a | <|skeleton|>
class Resources:
"""This class holds the full set of requestable resources needed for a Job submitted to the system. This includes the container URL for any container images used by the job, the number of nodes and processors, the amount of memory per node, the amount of disk space needed etc."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Resources:
"""This class holds the full set of requestable resources needed for a Job submitted to the system. This includes the container URL for any container images used by the job, the number of nodes and processors, the amount of memory per node, the amount of disk space needed etc."""
def __init__(... | the_stack_v2_python_sparse | Acquire/Client/_resources.py | chryswoods/acquire | train | 21 |
4a074abdf5792d7f80754ec250e0060d95518f0f | [
"self.arg_parser.add_argument('--operation', choices=('wifi_on', 'wifi_off'), default='', required=True, help='Operation to perform.')\nself.arg_parser.add_argument('--serial', default='', required=True, help='The device serial.')\nself.arg_parser.add_argument('--ap', default='', help=\"Access point (AP) name for '... | <|body_start_0|>
self.arg_parser.add_argument('--operation', choices=('wifi_on', 'wifi_off'), default='', required=True, help='Operation to perform.')
self.arg_parser.add_argument('--serial', default='', required=True, help='The device serial.')
self.arg_parser.add_argument('--ap', default='', h... | Command processor for DUT command. Attributes: arg_parser: ConsoleArgumentParser object, argument parser. console: cmd.Cmd console object. command: string, command name which this processor will handle. command_detail: string, detailed explanation for the command. | CommandDUT | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommandDUT:
"""Command processor for DUT command. Attributes: arg_parser: ConsoleArgumentParser object, argument parser. console: cmd.Cmd console object. command: string, command name which this processor will handle. command_detail: string, detailed explanation for the command."""
def SetUp... | stack_v2_sparse_classes_36k_train_017982 | 2,952 | no_license | [
{
"docstring": "Initializes the parser for dut command.",
"name": "SetUp",
"signature": "def SetUp(self)"
},
{
"docstring": "Performs the requested operation on the selected DUT.",
"name": "Run",
"signature": "def Run(self, arg_line)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003015 | Implement the Python class `CommandDUT` described below.
Class description:
Command processor for DUT command. Attributes: arg_parser: ConsoleArgumentParser object, argument parser. console: cmd.Cmd console object. command: string, command name which this processor will handle. command_detail: string, detailed explana... | Implement the Python class `CommandDUT` described below.
Class description:
Command processor for DUT command. Attributes: arg_parser: ConsoleArgumentParser object, argument parser. console: cmd.Cmd console object. command: string, command name which this processor will handle. command_detail: string, detailed explana... | 5ed3caff05cae4777c0a49a9704b2bf73376489f | <|skeleton|>
class CommandDUT:
"""Command processor for DUT command. Attributes: arg_parser: ConsoleArgumentParser object, argument parser. console: cmd.Cmd console object. command: string, command name which this processor will handle. command_detail: string, detailed explanation for the command."""
def SetUp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CommandDUT:
"""Command processor for DUT command. Attributes: arg_parser: ConsoleArgumentParser object, argument parser. console: cmd.Cmd console object. command: string, command name which this processor will handle. command_detail: string, detailed explanation for the command."""
def SetUp(self):
... | the_stack_v2_python_sparse | harnesses/host_controller/command_processor/command_dut.py | MIPS/test-framework | train | 0 |
1104099e67c7aab03e383f51abd0bb50b28196a4 | [
"if password == '':\n raise serializers.ValidationError(_('fill the password field'))\nreturn password",
"username = data.get('username')\npassword = self.validate_password(data.get('password'))\ntry:\n user = User.objects.get(username=username)\nexcept User.DoesNotExist:\n raise serializers.ValidationEr... | <|body_start_0|>
if password == '':
raise serializers.ValidationError(_('fill the password field'))
return password
<|end_body_0|>
<|body_start_1|>
username = data.get('username')
password = self.validate_password(data.get('password'))
try:
user = User.ob... | Serializer for user login. | LoginSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginSerializer:
"""Serializer for user login."""
def validate_password(self, password):
"""Check password validation."""
<|body_0|>
def validate(self, data):
"""Validation on both of the fields."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
i... | stack_v2_sparse_classes_36k_train_017983 | 1,296 | no_license | [
{
"docstring": "Check password validation.",
"name": "validate_password",
"signature": "def validate_password(self, password)"
},
{
"docstring": "Validation on both of the fields.",
"name": "validate",
"signature": "def validate(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011673 | Implement the Python class `LoginSerializer` described below.
Class description:
Serializer for user login.
Method signatures and docstrings:
- def validate_password(self, password): Check password validation.
- def validate(self, data): Validation on both of the fields. | Implement the Python class `LoginSerializer` described below.
Class description:
Serializer for user login.
Method signatures and docstrings:
- def validate_password(self, password): Check password validation.
- def validate(self, data): Validation on both of the fields.
<|skeleton|>
class LoginSerializer:
"""Se... | 74c9eba52b4f47d60fad17b6cba874e3547b37d4 | <|skeleton|>
class LoginSerializer:
"""Serializer for user login."""
def validate_password(self, password):
"""Check password validation."""
<|body_0|>
def validate(self, data):
"""Validation on both of the fields."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LoginSerializer:
"""Serializer for user login."""
def validate_password(self, password):
"""Check password validation."""
if password == '':
raise serializers.ValidationError(_('fill the password field'))
return password
def validate(self, data):
"""Valida... | the_stack_v2_python_sparse | apps/registration/serializers.py | cisin-python/django-rest-sample | train | 0 |
81b8e26b34bb9608030d522a626fc988576dee4b | [
"hook_name, key = value.split('::')\nwarnings.warn(cls.DEPRECATION_MSG, DeprecationWarning)\nLOGGER.warning(cls.DEPRECATION_MSG)\nreturn ('{}.{}'.format(hook_name, key), {})",
"try:\n query, args = cls.parse(value)\nexcept ValueError:\n query, args = cls.legacy_parse(value)\nresult = context.hook_data.find(... | <|body_start_0|>
hook_name, key = value.split('::')
warnings.warn(cls.DEPRECATION_MSG, DeprecationWarning)
LOGGER.warning(cls.DEPRECATION_MSG)
return ('{}.{}'.format(hook_name, key), {})
<|end_body_0|>
<|body_start_1|>
try:
query, args = cls.parse(value)
exce... | Hook data lookup. | HookDataLookup | [
"BSD-2-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HookDataLookup:
"""Hook data lookup."""
def legacy_parse(cls, value):
"""Retain support for legacy lookup syntax. Args: value (str): Parameter(s) given to this lookup. Format of value: <hook_name>::<key>"""
<|body_0|>
def handle(cls, value, context=None, provider=None, *... | stack_v2_sparse_classes_36k_train_017984 | 2,074 | permissive | [
{
"docstring": "Retain support for legacy lookup syntax. Args: value (str): Parameter(s) given to this lookup. Format of value: <hook_name>::<key>",
"name": "legacy_parse",
"signature": "def legacy_parse(cls, value)"
},
{
"docstring": "Return the data from ``hook_data``. Args: value (str): Param... | 2 | null | Implement the Python class `HookDataLookup` described below.
Class description:
Hook data lookup.
Method signatures and docstrings:
- def legacy_parse(cls, value): Retain support for legacy lookup syntax. Args: value (str): Parameter(s) given to this lookup. Format of value: <hook_name>::<key>
- def handle(cls, value... | Implement the Python class `HookDataLookup` described below.
Class description:
Hook data lookup.
Method signatures and docstrings:
- def legacy_parse(cls, value): Retain support for legacy lookup syntax. Args: value (str): Parameter(s) given to this lookup. Format of value: <hook_name>::<key>
- def handle(cls, value... | 94aebff4f83b294653192a1b74111f6a9f114de2 | <|skeleton|>
class HookDataLookup:
"""Hook data lookup."""
def legacy_parse(cls, value):
"""Retain support for legacy lookup syntax. Args: value (str): Parameter(s) given to this lookup. Format of value: <hook_name>::<key>"""
<|body_0|>
def handle(cls, value, context=None, provider=None, *... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HookDataLookup:
"""Hook data lookup."""
def legacy_parse(cls, value):
"""Retain support for legacy lookup syntax. Args: value (str): Parameter(s) given to this lookup. Format of value: <hook_name>::<key>"""
hook_name, key = value.split('::')
warnings.warn(cls.DEPRECATION_MSG, Depr... | the_stack_v2_python_sparse | runway/cfngin/lookups/handlers/hook_data.py | edgarpoce/runway | train | 1 |
2740d84036bfd6135852408dd98769908d737f9d | [
"print(self.token)\nheaders = {'Authorization': 'Bearer ' + self.token}\nr = self.send('GET', 'https://open.feishu.cn/open-apis/okr/v1/periods', headers=headers)\nreturn r.json()",
"url = 'https://open.feishu.cn/open-apis/okr/v1/users/:%s/okrs' % user_id\nprint(url)\nparams = {'user_id_type': user_id, 'offset': '... | <|body_start_0|>
print(self.token)
headers = {'Authorization': 'Bearer ' + self.token}
r = self.send('GET', 'https://open.feishu.cn/open-apis/okr/v1/periods', headers=headers)
return r.json()
<|end_body_0|>
<|body_start_1|>
url = 'https://open.feishu.cn/open-apis/okr/v1/users/:%... | FeishuOkr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeishuOkr:
def get_information(self):
"""获取OKR周期列表信息 :param :return:"""
<|body_0|>
def get_user_information(self, user_id: str):
"""获取某个用户的OKR周期列表信息 :param :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
print(self.token)
headers = ... | stack_v2_sparse_classes_36k_train_017985 | 1,053 | no_license | [
{
"docstring": "获取OKR周期列表信息 :param :return:",
"name": "get_information",
"signature": "def get_information(self)"
},
{
"docstring": "获取某个用户的OKR周期列表信息 :param :return:",
"name": "get_user_information",
"signature": "def get_user_information(self, user_id: str)"
}
] | 2 | null | Implement the Python class `FeishuOkr` described below.
Class description:
Implement the FeishuOkr class.
Method signatures and docstrings:
- def get_information(self): 获取OKR周期列表信息 :param :return:
- def get_user_information(self, user_id: str): 获取某个用户的OKR周期列表信息 :param :return: | Implement the Python class `FeishuOkr` described below.
Class description:
Implement the FeishuOkr class.
Method signatures and docstrings:
- def get_information(self): 获取OKR周期列表信息 :param :return:
- def get_user_information(self, user_id: str): 获取某个用户的OKR周期列表信息 :param :return:
<|skeleton|>
class FeishuOkr:
def ... | 6648dbfb640b065ff2c76cb6889a8f9e4f124b91 | <|skeleton|>
class FeishuOkr:
def get_information(self):
"""获取OKR周期列表信息 :param :return:"""
<|body_0|>
def get_user_information(self, user_id: str):
"""获取某个用户的OKR周期列表信息 :param :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeishuOkr:
def get_information(self):
"""获取OKR周期列表信息 :param :return:"""
print(self.token)
headers = {'Authorization': 'Bearer ' + self.token}
r = self.send('GET', 'https://open.feishu.cn/open-apis/okr/v1/periods', headers=headers)
return r.json()
def get_user_infor... | the_stack_v2_python_sparse | test_feishu/feishu/feishu_okr.py | Veraun/HogwartsSDET17-1 | train | 0 | |
2c8107e7a8d8da7babf3458be79656bf6ddf9cf4 | [
"super(SelfAttention, self).__init__()\nself.units = units\nself.W = tf.keras.layers.Dense(units)\nself.U = tf.keras.layers.Dense(units)\nself.V = tf.keras.layers.Dense(1)",
"prev = tf.expand_dims(s_prev, axis=1)\nscore = self.V(tf.nn.tanh(self.W(prev) + self.U(hidden_states)))\nweights = tf.nn.softmax(score, axi... | <|body_start_0|>
super(SelfAttention, self).__init__()
self.units = units
self.W = tf.keras.layers.Dense(units)
self.U = tf.keras.layers.Dense(units)
self.V = tf.keras.layers.Dense(1)
<|end_body_0|>
<|body_start_1|>
prev = tf.expand_dims(s_prev, axis=1)
score = s... | class SelfAttention | SelfAttention | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""Class constructor"""
<|body_0|>
def call(self, s_prev, hidden_states):
"""call function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(SelfAttention, self).__init__()
... | stack_v2_sparse_classes_36k_train_017986 | 754 | no_license | [
{
"docstring": "Class constructor",
"name": "__init__",
"signature": "def __init__(self, units)"
},
{
"docstring": "call function",
"name": "call",
"signature": "def call(self, s_prev, hidden_states)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015769 | Implement the Python class `SelfAttention` described below.
Class description:
class SelfAttention
Method signatures and docstrings:
- def __init__(self, units): Class constructor
- def call(self, s_prev, hidden_states): call function | Implement the Python class `SelfAttention` described below.
Class description:
class SelfAttention
Method signatures and docstrings:
- def __init__(self, units): Class constructor
- def call(self, s_prev, hidden_states): call function
<|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(... | a49eb348ff994f35b0efbbd5ac3ac8ae8ccb57d2 | <|skeleton|>
class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""Class constructor"""
<|body_0|>
def call(self, s_prev, hidden_states):
"""call function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SelfAttention:
"""class SelfAttention"""
def __init__(self, units):
"""Class constructor"""
super(SelfAttention, self).__init__()
self.units = units
self.W = tf.keras.layers.Dense(units)
self.U = tf.keras.layers.Dense(units)
self.V = tf.keras.layers.Dense(1... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/1-self_attention.py | salmenz/holbertonschool-machine_learning | train | 4 |
22e5e62e5ce6f2a0ce16c5fb276d3c0675432bb0 | [
"self.conn = MySQLdb.connect(host=config_reader.get('host'), db=config_reader.get('dbname'), read_default_file=config_reader.get('defaultcnf'), use_unicode=1, charset='utf8')\nself.cursor = self.conn.cursor()\nself.queries = hb_queries.Query(config_reader.get('wikidb'), config_reader.get('invitee_table'))",
"quer... | <|body_start_0|>
self.conn = MySQLdb.connect(host=config_reader.get('host'), db=config_reader.get('dbname'), read_default_file=config_reader.get('defaultcnf'), use_unicode=1, charset='utf8')
self.cursor = self.conn.cursor()
self.queries = hb_queries.Query(config_reader.get('wikidb'), config_read... | Create, parse, and post formatted messages to wiki. | Samples | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Samples:
"""Create, parse, and post formatted messages to wiki."""
def __init__(self):
"""Set up the db connection."""
<|body_0|>
def insertInvitees(self, query_key):
"""Insert today's potential invitees into the database"""
<|body_1|>
def updateTalk... | stack_v2_sparse_classes_36k_train_017987 | 5,945 | no_license | [
{
"docstring": "Set up the db connection.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Insert today's potential invitees into the database",
"name": "insertInvitees",
"signature": "def insertInvitees(self, query_key)"
},
{
"docstring": "Updates the d... | 5 | stack_v2_sparse_classes_30k_train_004000 | Implement the Python class `Samples` described below.
Class description:
Create, parse, and post formatted messages to wiki.
Method signatures and docstrings:
- def __init__(self): Set up the db connection.
- def insertInvitees(self, query_key): Insert today's potential invitees into the database
- def updateTalkPage... | Implement the Python class `Samples` described below.
Class description:
Create, parse, and post formatted messages to wiki.
Method signatures and docstrings:
- def __init__(self): Set up the db connection.
- def insertInvitees(self, query_key): Insert today's potential invitees into the database
- def updateTalkPage... | 5359b875e9c22f2b517368b22e42e1304dd75bb3 | <|skeleton|>
class Samples:
"""Create, parse, and post formatted messages to wiki."""
def __init__(self):
"""Set up the db connection."""
<|body_0|>
def insertInvitees(self, query_key):
"""Insert today's potential invitees into the database"""
<|body_1|>
def updateTalk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Samples:
"""Create, parse, and post formatted messages to wiki."""
def __init__(self):
"""Set up the db connection."""
self.conn = MySQLdb.connect(host=config_reader.get('host'), db=config_reader.get('dbname'), read_default_file=config_reader.get('defaultcnf'), use_unicode=1, charset='utf... | the_stack_v2_python_sparse | hb_profiles.py | Wikimedia-Sverige/hostbot | train | 2 |
d7cb0186b42ee8e9d8f7ce06bc2b376b7c3cb4c1 | [
"self.set_counts = set_counts\nself.max_set = max(set_counts)\nnum_sets = len(set_counts)\nself.ranks = [1] * num_sets\nself.parents = list(range(num_sets))",
"src_parent = self.get_parent(src)\ndst_parent = self.get_parent(dst)\nif src_parent == dst_parent:\n return False\nif self.ranks[dst_parent] >= self.ra... | <|body_start_0|>
self.set_counts = set_counts
self.max_set = max(set_counts)
num_sets = len(set_counts)
self.ranks = [1] * num_sets
self.parents = list(range(num_sets))
<|end_body_0|>
<|body_start_1|>
src_parent = self.get_parent(src)
dst_parent = self.get_parent... | DisjointSet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DisjointSet:
def __init__(self, set_counts: list) -> None:
"""Initialize with a list of the number of items in each set and with rank = 1 for each set"""
<|body_0|>
def merge(self, src: int, dst: int) -> bool:
"""Merge two sets together using Union by rank heuristic ... | stack_v2_sparse_classes_36k_train_017988 | 2,192 | permissive | [
{
"docstring": "Initialize with a list of the number of items in each set and with rank = 1 for each set",
"name": "__init__",
"signature": "def __init__(self, set_counts: list) -> None"
},
{
"docstring": "Merge two sets together using Union by rank heuristic Return True if successful Merge two ... | 3 | null | Implement the Python class `DisjointSet` described below.
Class description:
Implement the DisjointSet class.
Method signatures and docstrings:
- def __init__(self, set_counts: list) -> None: Initialize with a list of the number of items in each set and with rank = 1 for each set
- def merge(self, src: int, dst: int)... | Implement the Python class `DisjointSet` described below.
Class description:
Implement the DisjointSet class.
Method signatures and docstrings:
- def __init__(self, set_counts: list) -> None: Initialize with a list of the number of items in each set and with rank = 1 for each set
- def merge(self, src: int, dst: int)... | 421ace81edb0d9af3a173f4ca7e66cc900078c1d | <|skeleton|>
class DisjointSet:
def __init__(self, set_counts: list) -> None:
"""Initialize with a list of the number of items in each set and with rank = 1 for each set"""
<|body_0|>
def merge(self, src: int, dst: int) -> bool:
"""Merge two sets together using Union by rank heuristic ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DisjointSet:
def __init__(self, set_counts: list) -> None:
"""Initialize with a list of the number of items in each set and with rank = 1 for each set"""
self.set_counts = set_counts
self.max_set = max(set_counts)
num_sets = len(set_counts)
self.ranks = [1] * num_sets
... | the_stack_v2_python_sparse | data_structures/disjoint_set/alternate_disjoint_set.py | TheAlgorithms/Python | train | 184,217 | |
b9bbee9ca458b3f4c3b13eb532817ee302b8bda5 | [
"if root is None:\n return '[]'\nfrom collections import deque\nqueue = deque([root])\nresult = [root.val]\nwhile queue:\n node = queue.popleft()\n if node.left:\n queue.append(node.left)\n if node.right:\n queue.append(node.right)\n result.append(node.left.val if node.left else 'null')... | <|body_start_0|>
if root is None:
return '[]'
from collections import deque
queue = deque([root])
result = [root.val]
while queue:
node = queue.popleft()
if node.left:
queue.append(node.left)
if node.right:
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_017989 | 3,660 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | stack_v2_sparse_classes_30k_train_020315 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | c34b55bb42dc44a9026a902f6afcc018b4154662 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
if root is None:
return '[]'
from collections import deque
queue = deque([root])
result = [root.val]
while queue:
node = queue.pop... | the_stack_v2_python_sparse | Algorithm/Serialize and Deserialize Binary Tree.py | superpigBB/Happy-Coding | train | 0 | |
a211044d92f003de27782e8b3e066f1423236d0c | [
"memo = defaultdict(list)\n\ndef tree2list(r, d=0):\n if d == 0:\n memo.clear()\n if not r:\n return\n memo[d].append(r.val)\n tree2list(r.left, d + 1)\n tree2list(r.right, d + 1)\ntree2list(root)\nreturn [v for k, v in sorted(memo.items(), key=lambda x: x[0])]",
"if not root:\n re... | <|body_start_0|>
memo = defaultdict(list)
def tree2list(r, d=0):
if d == 0:
memo.clear()
if not r:
return
memo[d].append(r.val)
tree2list(r.left, d + 1)
tree2list(r.right, d + 1)
tree2list(root)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def levelOrder(self, root):
"""05/06/2018 22:20"""
<|body_0|>
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""06/01/2021 14:48"""
<|body_1|>
def levelOrder(self, root: Optional[TreeNode]) -> List[List[int]]:
"""07/30/2022 18... | stack_v2_sparse_classes_36k_train_017990 | 2,850 | no_license | [
{
"docstring": "05/06/2018 22:20",
"name": "levelOrder",
"signature": "def levelOrder(self, root)"
},
{
"docstring": "06/01/2021 14:48",
"name": "levelOrder",
"signature": "def levelOrder(self, root: TreeNode) -> List[List[int]]"
},
{
"docstring": "07/30/2022 18:30",
"name": ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): 05/06/2018 22:20
- def levelOrder(self, root: TreeNode) -> List[List[int]]: 06/01/2021 14:48
- def levelOrder(self, root: Optional[TreeNode]) -> List[... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def levelOrder(self, root): 05/06/2018 22:20
- def levelOrder(self, root: TreeNode) -> List[List[int]]: 06/01/2021 14:48
- def levelOrder(self, root: Optional[TreeNode]) -> List[... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def levelOrder(self, root):
"""05/06/2018 22:20"""
<|body_0|>
def levelOrder(self, root: TreeNode) -> List[List[int]]:
"""06/01/2021 14:48"""
<|body_1|>
def levelOrder(self, root: Optional[TreeNode]) -> List[List[int]]:
"""07/30/2022 18... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def levelOrder(self, root):
"""05/06/2018 22:20"""
memo = defaultdict(list)
def tree2list(r, d=0):
if d == 0:
memo.clear()
if not r:
return
memo[d].append(r.val)
tree2list(r.left, d + 1)
... | the_stack_v2_python_sparse | leetcode/solved/102_Binary_Tree_Level_Order_Traversal/solution.py | sungminoh/algorithms | train | 0 | |
426b8b52dbe77606a7859c50635fd81da02f943a | [
"config.LoadConfig()\npsq_publisher = pubsub.PublisherClient()\npsq_subscriber = pubsub.SubscriberClient()\ndatastore_client = datastore.Client(project=config.TURBINIA_PROJECT)\ntry:\n self.psq = psq.Queue(psq_publisher, psq_subscriber, config.TURBINIA_PROJECT, name=config.PSQ_TOPIC, storage=psq.DatastoreStorage... | <|body_start_0|>
config.LoadConfig()
psq_publisher = pubsub.PublisherClient()
psq_subscriber = pubsub.SubscriberClient()
datastore_client = datastore.Client(project=config.TURBINIA_PROJECT)
try:
self.psq = psq.Queue(psq_publisher, psq_subscriber, config.TURBINIA_PROJE... | Turbinia PSQ Worker class. Attributes: worker (psq.Worker): PSQ Worker object psq (psq.Queue): A Task queue object Raises: TurbiniaException: When errors occur | TurbiniaPsqWorker | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TurbiniaPsqWorker:
"""Turbinia PSQ Worker class. Attributes: worker (psq.Worker): PSQ Worker object psq (psq.Queue): A Task queue object Raises: TurbiniaException: When errors occur"""
def __init__(self, jobs_denylist=None, jobs_allowlist=None):
"""Initialization for PSQ Worker. Args... | stack_v2_sparse_classes_36k_train_017991 | 46,828 | permissive | [
{
"docstring": "Initialization for PSQ Worker. Args: jobs_denylist (Optional[list[str]]): Jobs we will exclude from running jobs_allowlist (Optional[list[str]]): The only Jobs we will include to run",
"name": "__init__",
"signature": "def __init__(self, jobs_denylist=None, jobs_allowlist=None)"
},
{... | 2 | stack_v2_sparse_classes_30k_train_016399 | Implement the Python class `TurbiniaPsqWorker` described below.
Class description:
Turbinia PSQ Worker class. Attributes: worker (psq.Worker): PSQ Worker object psq (psq.Queue): A Task queue object Raises: TurbiniaException: When errors occur
Method signatures and docstrings:
- def __init__(self, jobs_denylist=None, ... | Implement the Python class `TurbiniaPsqWorker` described below.
Class description:
Turbinia PSQ Worker class. Attributes: worker (psq.Worker): PSQ Worker object psq (psq.Queue): A Task queue object Raises: TurbiniaException: When errors occur
Method signatures and docstrings:
- def __init__(self, jobs_denylist=None, ... | e73717549c6919e869ce4963449c36f227e3ccd6 | <|skeleton|>
class TurbiniaPsqWorker:
"""Turbinia PSQ Worker class. Attributes: worker (psq.Worker): PSQ Worker object psq (psq.Queue): A Task queue object Raises: TurbiniaException: When errors occur"""
def __init__(self, jobs_denylist=None, jobs_allowlist=None):
"""Initialization for PSQ Worker. Args... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TurbiniaPsqWorker:
"""Turbinia PSQ Worker class. Attributes: worker (psq.Worker): PSQ Worker object psq (psq.Queue): A Task queue object Raises: TurbiniaException: When errors occur"""
def __init__(self, jobs_denylist=None, jobs_allowlist=None):
"""Initialization for PSQ Worker. Args: jobs_denyli... | the_stack_v2_python_sparse | turbinia/client.py | Ash515/turbinia | train | 6 |
4291729ce43ce1d71195d016ba3a46f016bc7ca6 | [
"self.d = dict()\nfor i in range(len(dictionary)):\n if len(dictionary[i]) > 2:\n abbr = dictionary[i][0] + str(len(dictionary[i]) - 2) + dictionary[i][-1]\n else:\n abbr = dictionary[i]\n self.d[abbr] = self.d.get(abbr, set())\n self.d[abbr].add(dictionary[i])",
"if len(word) > 2:\n ... | <|body_start_0|>
self.d = dict()
for i in range(len(dictionary)):
if len(dictionary[i]) > 2:
abbr = dictionary[i][0] + str(len(dictionary[i]) - 2) + dictionary[i][-1]
else:
abbr = dictionary[i]
self.d[abbr] = self.d.get(abbr, set())
... | ValidWordAbbr | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.d = dict()
for i in range(len(dictiona... | stack_v2_sparse_classes_36k_train_017992 | 1,910 | no_license | [
{
"docstring": ":type dictionary: List[str]",
"name": "__init__",
"signature": "def __init__(self, dictionary)"
},
{
"docstring": ":type word: str :rtype: bool",
"name": "isUnique",
"signature": "def isUnique(self, word)"
}
] | 2 | null | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool | Implement the Python class `ValidWordAbbr` described below.
Class description:
Implement the ValidWordAbbr class.
Method signatures and docstrings:
- def __init__(self, dictionary): :type dictionary: List[str]
- def isUnique(self, word): :type word: str :rtype: bool
<|skeleton|>
class ValidWordAbbr:
def __init_... | 9eb44afa4233fdedc2e5c72be0fdf54b25d1c45c | <|skeleton|>
class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
<|body_0|>
def isUnique(self, word):
""":type word: str :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ValidWordAbbr:
def __init__(self, dictionary):
""":type dictionary: List[str]"""
self.d = dict()
for i in range(len(dictionary)):
if len(dictionary[i]) > 2:
abbr = dictionary[i][0] + str(len(dictionary[i]) - 2) + dictionary[i][-1]
else:
... | the_stack_v2_python_sparse | Google/Pro288. Unique Word Abbreviation.py | YoyinZyc/Leetcode_Python | train | 0 | |
4224c8405a9967bed6d36b1ffd83b909f7cb0f8f | [
"modules = script.split('.')\nself.scriptname = modules[0]\nself.script = import_module('scripts.' + self.scriptname)\nfor m in modules:\n self.script = getattr(self.script, m)\nself.messages = {}\nfor msg in args:\n if hasattr(self.script, msg):\n self.messages[msg] = msg\n else:\n print(f'm... | <|body_start_0|>
modules = script.split('.')
self.scriptname = modules[0]
self.script = import_module('scripts.' + self.scriptname)
for m in modules:
self.script = getattr(self.script, m)
self.messages = {}
for msg in args:
if hasattr(self.script, ... | I18n bot. | i18nBot | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class i18nBot:
"""I18n bot."""
def __init__(self, script, *args, **kwargs):
"""Initializer."""
<|body_0|>
def print_all(self):
"""Pretty print the dict as a file content to screen."""
<|body_1|>
def read(self, oldmsg, newmsg=None):
"""Read a single... | stack_v2_sparse_classes_36k_train_017993 | 5,029 | permissive | [
{
"docstring": "Initializer.",
"name": "__init__",
"signature": "def __init__(self, script, *args, **kwargs)"
},
{
"docstring": "Pretty print the dict as a file content to screen.",
"name": "print_all",
"signature": "def print_all(self)"
},
{
"docstring": "Read a single message f... | 5 | stack_v2_sparse_classes_30k_test_000037 | Implement the Python class `i18nBot` described below.
Class description:
I18n bot.
Method signatures and docstrings:
- def __init__(self, script, *args, **kwargs): Initializer.
- def print_all(self): Pretty print the dict as a file content to screen.
- def read(self, oldmsg, newmsg=None): Read a single message from s... | Implement the Python class `i18nBot` described below.
Class description:
I18n bot.
Method signatures and docstrings:
- def __init__(self, script, *args, **kwargs): Initializer.
- def print_all(self): Pretty print the dict as a file content to screen.
- def read(self, oldmsg, newmsg=None): Read a single message from s... | 5c01e6bfcd328bc6eae643e661f1a0ae57612808 | <|skeleton|>
class i18nBot:
"""I18n bot."""
def __init__(self, script, *args, **kwargs):
"""Initializer."""
<|body_0|>
def print_all(self):
"""Pretty print the dict as a file content to screen."""
<|body_1|>
def read(self, oldmsg, newmsg=None):
"""Read a single... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class i18nBot:
"""I18n bot."""
def __init__(self, script, *args, **kwargs):
"""Initializer."""
modules = script.split('.')
self.scriptname = modules[0]
self.script = import_module('scripts.' + self.scriptname)
for m in modules:
self.script = getattr(self.scri... | the_stack_v2_python_sparse | scripts/maintenance/make_i18n_dict.py | wikimedia/pywikibot | train | 432 |
6a5e0a13c38a5a06b9751fbbe26122eb6c10b4bc | [
"if not nums:\n return False\nn = len(nums)\npreSum = [0] * (n + 1)\nfor i in range(n):\n preSum[i + 1] = preSum[i] + nums[i]\nfor i in range(n):\n for j in range(i + 1, n):\n sums = preSum[j + 1] - preSum[i]\n if sums == 0 and k == 0:\n return True\n elif k != 0 and sums % ... | <|body_start_0|>
if not nums:
return False
n = len(nums)
preSum = [0] * (n + 1)
for i in range(n):
preSum[i + 1] = preSum[i] + nums[i]
for i in range(n):
for j in range(i + 1, n):
sums = preSum[j + 1] - preSum[i]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkSubarraySum(self, nums: list, k: int) -> bool:
"""前缀和法 开辟一个数组来记录前缀和 注意： 前缀和记录的只是从0开始，一直到长度n的和 如： [1,2,3] 其前缀和数组为[0, 1, 3, 6], 即0， 0+1， 0+1+2(index) 所以，要双循环计算某个范围的和 特别注意当k=0的情况"""
<|body_0|>
def checkSubarraySum_2(self, nums, k):
"""优化版 1. 前缀和不用全部保存... | stack_v2_sparse_classes_36k_train_017994 | 1,960 | no_license | [
{
"docstring": "前缀和法 开辟一个数组来记录前缀和 注意： 前缀和记录的只是从0开始，一直到长度n的和 如： [1,2,3] 其前缀和数组为[0, 1, 3, 6], 即0， 0+1， 0+1+2(index) 所以，要双循环计算某个范围的和 特别注意当k=0的情况",
"name": "checkSubarraySum",
"signature": "def checkSubarraySum(self, nums: list, k: int) -> bool"
},
{
"docstring": "优化版 1. 前缀和不用全部保存，只需要记录好前面的和+当前值即可 2... | 2 | stack_v2_sparse_classes_30k_train_020943 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkSubarraySum(self, nums: list, k: int) -> bool: 前缀和法 开辟一个数组来记录前缀和 注意： 前缀和记录的只是从0开始，一直到长度n的和 如： [1,2,3] 其前缀和数组为[0, 1, 3, 6], 即0， 0+1， 0+1+2(index) 所以，要双循环计算某个范围的和 特别注意当k=0... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkSubarraySum(self, nums: list, k: int) -> bool: 前缀和法 开辟一个数组来记录前缀和 注意： 前缀和记录的只是从0开始，一直到长度n的和 如： [1,2,3] 其前缀和数组为[0, 1, 3, 6], 即0， 0+1， 0+1+2(index) 所以，要双循环计算某个范围的和 特别注意当k=0... | 3508e1ce089131b19603c3206aab4cf43023bb19 | <|skeleton|>
class Solution:
def checkSubarraySum(self, nums: list, k: int) -> bool:
"""前缀和法 开辟一个数组来记录前缀和 注意： 前缀和记录的只是从0开始，一直到长度n的和 如： [1,2,3] 其前缀和数组为[0, 1, 3, 6], 即0， 0+1， 0+1+2(index) 所以，要双循环计算某个范围的和 特别注意当k=0的情况"""
<|body_0|>
def checkSubarraySum_2(self, nums, k):
"""优化版 1. 前缀和不用全部保存... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkSubarraySum(self, nums: list, k: int) -> bool:
"""前缀和法 开辟一个数组来记录前缀和 注意： 前缀和记录的只是从0开始，一直到长度n的和 如： [1,2,3] 其前缀和数组为[0, 1, 3, 6], 即0， 0+1， 0+1+2(index) 所以，要双循环计算某个范围的和 特别注意当k=0的情况"""
if not nums:
return False
n = len(nums)
preSum = [0] * (n + 1)
... | the_stack_v2_python_sparse | algorithm/leetcode/list/18-连续的子数组和.py | lxconfig/UbuntuCode_bak | train | 0 | |
81f8768c46ebce0b9835ff90b40f6ab4fc860c1f | [
"mock_warn = mock.Mock()\ntest_class = deprecated.MovedHelper(urls.Url, 'grow.common.urls.Url', warn=mock_warn)\n_ = test_class('/')\nmock_warn.assert_called_with('The grow.common.urls.Url class has moved to grow.common.urls.Url and will be removed in a future version.')",
"mock_warn = mock.Mock()\ntest_class = d... | <|body_start_0|>
mock_warn = mock.Mock()
test_class = deprecated.MovedHelper(urls.Url, 'grow.common.urls.Url', warn=mock_warn)
_ = test_class('/')
mock_warn.assert_called_with('The grow.common.urls.Url class has moved to grow.common.urls.Url and will be removed in a future version.')
<|e... | Test the terminal colors. | MovedHelperTestCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovedHelperTestCase:
"""Test the terminal colors."""
def test_moved(self):
"""Warning message when the class has moved."""
<|body_0|>
def test_static_method(self):
"""Moved warning also works with static methods."""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_017995 | 1,175 | permissive | [
{
"docstring": "Warning message when the class has moved.",
"name": "test_moved",
"signature": "def test_moved(self)"
},
{
"docstring": "Moved warning also works with static methods.",
"name": "test_static_method",
"signature": "def test_static_method(self)"
}
] | 2 | null | Implement the Python class `MovedHelperTestCase` described below.
Class description:
Test the terminal colors.
Method signatures and docstrings:
- def test_moved(self): Warning message when the class has moved.
- def test_static_method(self): Moved warning also works with static methods. | Implement the Python class `MovedHelperTestCase` described below.
Class description:
Test the terminal colors.
Method signatures and docstrings:
- def test_moved(self): Warning message when the class has moved.
- def test_static_method(self): Moved warning also works with static methods.
<|skeleton|>
class MovedHelp... | 17471c436621ebfd978b51225fa4de05367a53e1 | <|skeleton|>
class MovedHelperTestCase:
"""Test the terminal colors."""
def test_moved(self):
"""Warning message when the class has moved."""
<|body_0|>
def test_static_method(self):
"""Moved warning also works with static methods."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovedHelperTestCase:
"""Test the terminal colors."""
def test_moved(self):
"""Warning message when the class has moved."""
mock_warn = mock.Mock()
test_class = deprecated.MovedHelper(urls.Url, 'grow.common.urls.Url', warn=mock_warn)
_ = test_class('/')
mock_warn.as... | the_stack_v2_python_sparse | grow/common/deprecated_test.py | grow/grow | train | 352 |
925178fb4714793ca037188df98996cf78aeec71 | [
"st = ''\nlength = 0\nfor i in s:\n index = st.find(i)\n if index >= 0:\n if len(st) > length:\n length = len(st)\n st = st[index + 1:]\n st += i\nreturn len(st) if len(st) > length else length",
"index = 0\nmax_count = 0\ndata = {}\nwhile index < len(s):\n if s[index] not in ... | <|body_start_0|>
st = ''
length = 0
for i in s:
index = st.find(i)
if index >= 0:
if len(st) > length:
length = len(st)
st = st[index + 1:]
st += i
return len(st) if len(st) > length else length
<|end... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def __lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def ___lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int""... | stack_v2_sparse_classes_36k_train_017996 | 3,690 | permissive | [
{
"docstring": ":type s: str :rtype: int",
"name": "_lengthOfLongestSubstring",
"signature": "def _lengthOfLongestSubstring(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "__lengthOfLongestSubstring",
"signature": "def __lengthOfLongestSubstring(self, s)"
},
{
"d... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def __lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def ___lengthOfLongestSubstring(self, s): :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def __lengthOfLongestSubstring(self, s): :type s: str :rtype: int
- def ___lengthOfLongestSubstring(self, s): :... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_0|>
def __lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
<|body_1|>
def ___lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _lengthOfLongestSubstring(self, s):
""":type s: str :rtype: int"""
st = ''
length = 0
for i in s:
index = st.find(i)
if index >= 0:
if len(st) > length:
length = len(st)
st = st[index + 1:... | the_stack_v2_python_sparse | 3.longest-substring-without-repeating-characters.py | windard/leeeeee | train | 0 | |
f8a67518f1dcfe885fee0215fa76191d0a4bc8d8 | [
"self.parse_arguments(arguments)\nself.load_config(self.args.config)\nself.yesterday = datetime.date.today() - datetime.timedelta(days=1)",
"parser = argparse.ArgumentParser(description='HEG data collector')\nparser.add_argument('-v', '--verbose', action='store_true', help='Make output more verbose.')\nparser.add... | <|body_start_0|>
self.parse_arguments(arguments)
self.load_config(self.args.config)
self.yesterday = datetime.date.today() - datetime.timedelta(days=1)
<|end_body_0|>
<|body_start_1|>
parser = argparse.ArgumentParser(description='HEG data collector')
parser.add_argument('-v', '-... | App | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class App:
def __init__(self, arguments=[]):
"""Keyword Arguments: arguments {list} -- The cli options as a list (default: {[]})"""
<|body_0|>
def parse_arguments(self, arguments):
"""Parses cli options/arguments given as a list. Arguments: arguments {list} -- The cli opti... | stack_v2_sparse_classes_36k_train_017997 | 2,146 | permissive | [
{
"docstring": "Keyword Arguments: arguments {list} -- The cli options as a list (default: {[]})",
"name": "__init__",
"signature": "def __init__(self, arguments=[])"
},
{
"docstring": "Parses cli options/arguments given as a list. Arguments: arguments {list} -- The cli options/list",
"name"... | 3 | stack_v2_sparse_classes_30k_train_019164 | Implement the Python class `App` described below.
Class description:
Implement the App class.
Method signatures and docstrings:
- def __init__(self, arguments=[]): Keyword Arguments: arguments {list} -- The cli options as a list (default: {[]})
- def parse_arguments(self, arguments): Parses cli options/arguments give... | Implement the Python class `App` described below.
Class description:
Implement the App class.
Method signatures and docstrings:
- def __init__(self, arguments=[]): Keyword Arguments: arguments {list} -- The cli options as a list (default: {[]})
- def parse_arguments(self, arguments): Parses cli options/arguments give... | c4f47444369151c606a4597aed5562503842e2f3 | <|skeleton|>
class App:
def __init__(self, arguments=[]):
"""Keyword Arguments: arguments {list} -- The cli options as a list (default: {[]})"""
<|body_0|>
def parse_arguments(self, arguments):
"""Parses cli options/arguments given as a list. Arguments: arguments {list} -- The cli opti... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class App:
def __init__(self, arguments=[]):
"""Keyword Arguments: arguments {list} -- The cli options as a list (default: {[]})"""
self.parse_arguments(arguments)
self.load_config(self.args.config)
self.yesterday = datetime.date.today() - datetime.timedelta(days=1)
def parse_ar... | the_stack_v2_python_sparse | heg/app.py | morris-frank/heg-plant-monitor | train | 0 | |
19e116b07caeafdd93845f253511a52907a00973 | [
"super().__init__(independent_variables, equations)\nself.single_variable_sample = single_variable_sample\nself.single_equation_sample = single_equation_sample",
"variable_samples = [self.single_variable_sample() for _ in range(size)]\nequation_samples = [self.single_equation_sample() for _ in range(size)]\nvaria... | <|body_start_0|>
super().__init__(independent_variables, equations)
self.single_variable_sample = single_variable_sample
self.single_equation_sample = single_equation_sample
<|end_body_0|>
<|body_start_1|>
variable_samples = [self.single_variable_sample() for _ in range(size)]
e... | AnonymousSampler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnonymousSampler:
def __init__(self, independent_variables, equations, single_variable_sample, single_equation_sample):
"""Class for samplers that can be constructed on the fly."""
<|body_0|>
def get_sample(self, size):
"""Retrieve a batch of samples from the sampler... | stack_v2_sparse_classes_36k_train_017998 | 1,886 | no_license | [
{
"docstring": "Class for samplers that can be constructed on the fly.",
"name": "__init__",
"signature": "def __init__(self, independent_variables, equations, single_variable_sample, single_equation_sample)"
},
{
"docstring": "Retrieve a batch of samples from the sampler. Each sample should be ... | 2 | stack_v2_sparse_classes_30k_train_002162 | Implement the Python class `AnonymousSampler` described below.
Class description:
Implement the AnonymousSampler class.
Method signatures and docstrings:
- def __init__(self, independent_variables, equations, single_variable_sample, single_equation_sample): Class for samplers that can be constructed on the fly.
- def... | Implement the Python class `AnonymousSampler` described below.
Class description:
Implement the AnonymousSampler class.
Method signatures and docstrings:
- def __init__(self, independent_variables, equations, single_variable_sample, single_equation_sample): Class for samplers that can be constructed on the fly.
- def... | 5f353012a9ed14dc957211b9f3d3e9620ce82a42 | <|skeleton|>
class AnonymousSampler:
def __init__(self, independent_variables, equations, single_variable_sample, single_equation_sample):
"""Class for samplers that can be constructed on the fly."""
<|body_0|>
def get_sample(self, size):
"""Retrieve a batch of samples from the sampler... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AnonymousSampler:
def __init__(self, independent_variables, equations, single_variable_sample, single_equation_sample):
"""Class for samplers that can be constructed on the fly."""
super().__init__(independent_variables, equations)
self.single_variable_sample = single_variable_sample
... | the_stack_v2_python_sparse | puddle/api/samplers/anonymous.py | aatack/puddle | train | 0 | |
387ae31a89d3274ae806680007108354037fc40b | [
"if _id is None:\n _id = (id(self) >> 16 ^ id(self) & 65535) & 65535\nself.id: int = _id\nsessionid = session.short_session_id()\nlocalname = f'gt.{self.id}.{sessionid}'\nname = f'{localname}p'\nsuper().__init__(0, name, localname, session.use_ovs(), mtu, node, server)\nself.transport_type: TransportType = Trans... | <|body_start_0|>
if _id is None:
_id = (id(self) >> 16 ^ id(self) & 65535) & 65535
self.id: int = _id
sessionid = session.short_session_id()
localname = f'gt.{self.id}.{sessionid}'
name = f'{localname}p'
super().__init__(0, name, localname, session.use_ovs(), ... | GRE TAP device for tunneling between emulation servers. Uses the "gretap" tunnel device type from Linux which is a GRE device having a MAC address. The MAC address is required for bridging. | GreTap | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GreTap:
"""GRE TAP device for tunneling between emulation servers. Uses the "gretap" tunnel device type from Linux which is a GRE device having a MAC address. The MAC address is required for bridging."""
def __init__(self, session: 'Session', remoteip: str, key: int=None, node: 'CoreNode'=No... | stack_v2_sparse_classes_36k_train_017999 | 13,109 | permissive | [
{
"docstring": "Creates a GreTap instance. :param session: session for this gre tap :param remoteip: remote address :param key: gre tap key :param node: related core node :param mtu: interface mtu :param _id: object id :param localip: local address :param ttl: ttl value :param server: remote server node will ru... | 3 | null | Implement the Python class `GreTap` described below.
Class description:
GRE TAP device for tunneling between emulation servers. Uses the "gretap" tunnel device type from Linux which is a GRE device having a MAC address. The MAC address is required for bridging.
Method signatures and docstrings:
- def __init__(self, s... | Implement the Python class `GreTap` described below.
Class description:
GRE TAP device for tunneling between emulation servers. Uses the "gretap" tunnel device type from Linux which is a GRE device having a MAC address. The MAC address is required for bridging.
Method signatures and docstrings:
- def __init__(self, s... | 20071eed2e73a2287aa385698dd604f4933ae7ff | <|skeleton|>
class GreTap:
"""GRE TAP device for tunneling between emulation servers. Uses the "gretap" tunnel device type from Linux which is a GRE device having a MAC address. The MAC address is required for bridging."""
def __init__(self, session: 'Session', remoteip: str, key: int=None, node: 'CoreNode'=No... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GreTap:
"""GRE TAP device for tunneling between emulation servers. Uses the "gretap" tunnel device type from Linux which is a GRE device having a MAC address. The MAC address is required for bridging."""
def __init__(self, session: 'Session', remoteip: str, key: int=None, node: 'CoreNode'=None, mtu: int=... | the_stack_v2_python_sparse | daemon/core/nodes/interface.py | coreemu/core | train | 606 |
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