blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 467 8.64k | id stringlengths 40 40 | length_bytes int64 515 49.7k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 160 3.93k | prompted_full_text stringlengths 681 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.09k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 331 8.3k | source stringclasses 1
value | source_path stringlengths 5 177 | source_repo stringlengths 6 88 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6fb26e357fe873040df4128205744e415796c2b1 | [
"results = self._convert_json_results_to_result_objects(results)\naggregated_results = defaultdict(lambda: defaultdict(list))\nfor r in results:\n build_url = 'http://ci.chromium.org/b/%s' % r.build_id\n aggregated_results[r.test][r.typ_tags].append(dt.ImageDiffTagTupleType(r.image_diff_tag[0], r.image_diff_t... | <|body_start_0|>
results = self._convert_json_results_to_result_objects(results)
aggregated_results = defaultdict(lambda: defaultdict(list))
for r in results:
build_url = 'http://ci.chromium.org/b/%s' % r.build_id
aggregated_results[r.test][r.typ_tags].append(dt.ImageDiff... | ResultProcessor | [
"GPL-1.0-or-later",
"MIT",
"LGPL-2.0-or-later",
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"LGPL-2.1-only",
"GPL-2.0-only",
"LGPL-2.0-only",
"BSD-2-Clause",
"LicenseRef-scancode-other-copyleft",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResultProcessor:
def aggregate_results(self, results: ct.QueryJsonType) -> dt.AggregatedResultsType:
"""Aggregates BigQuery results for all image comparison tests. Args: results: Parsed JSON test results from a BigQuery query. Returns: A map in the following format: { 'test_name': { 'typ... | stack_v2_sparse_classes_10k_train_005500 | 2,220 | permissive | [
{
"docstring": "Aggregates BigQuery results for all image comparison tests. Args: results: Parsed JSON test results from a BigQuery query. Returns: A map in the following format: { 'test_name': { 'typ_tags_as_tuple': [ (0, 200, 'url_1'), (3, 400, 'url_2'),], }, }",
"name": "aggregate_results",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_001933 | Implement the Python class `ResultProcessor` described below.
Class description:
Implement the ResultProcessor class.
Method signatures and docstrings:
- def aggregate_results(self, results: ct.QueryJsonType) -> dt.AggregatedResultsType: Aggregates BigQuery results for all image comparison tests. Args: results: Parse... | Implement the Python class `ResultProcessor` described below.
Class description:
Implement the ResultProcessor class.
Method signatures and docstrings:
- def aggregate_results(self, results: ct.QueryJsonType) -> dt.AggregatedResultsType: Aggregates BigQuery results for all image comparison tests. Args: results: Parse... | a401d6cf4f7bf0e2d2e964c512ebb923c3d8832c | <|skeleton|>
class ResultProcessor:
def aggregate_results(self, results: ct.QueryJsonType) -> dt.AggregatedResultsType:
"""Aggregates BigQuery results for all image comparison tests. Args: results: Parsed JSON test results from a BigQuery query. Returns: A map in the following format: { 'test_name': { 'typ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ResultProcessor:
def aggregate_results(self, results: ct.QueryJsonType) -> dt.AggregatedResultsType:
"""Aggregates BigQuery results for all image comparison tests. Args: results: Parsed JSON test results from a BigQuery query. Returns: A map in the following format: { 'test_name': { 'typ_tags_as_tuple... | the_stack_v2_python_sparse | third_party/blink/tools/blinkpy/web_tests/fuzzy_diff_analyzer/results.py | chromium/chromium | train | 17,408 | |
db21a3b853c6dbd661a00bc2ee6a1ae9393adcb6 | [
"def dfs(n, k, memo):\n if n == 0:\n return 0\n if k == 1:\n return n\n if (n, k) not in memo:\n ans = float('inf')\n for x in range(1, n + 1):\n ans = min(ans, 1 + max(dfs(x - 1, k - 1, memo), dfs(n - x, k, memo)))\n memo[n, k] = ans\n return memo[n, k]\nre... | <|body_start_0|>
def dfs(n, k, memo):
if n == 0:
return 0
if k == 1:
return n
if (n, k) not in memo:
ans = float('inf')
for x in range(1, n + 1):
ans = min(ans, 1 + max(dfs(x - 1, k - 1, memo)... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def superEggDrop(self, K: int, N: int) -> int:
"""Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)"""
<|body_0|>
def superEggDrop(self, K: int, N: int) -> int:
... | stack_v2_sparse_classes_10k_train_005501 | 5,857 | no_license | [
{
"docstring": "Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)",
"name": "superEggDrop",
"signature": "def superEggDrop(self, K: int, N: int) -> int"
},
{
"docstring": "The above algorithm got TL... | 5 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def superEggDrop(self, K: int, N: int) -> int: Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def superEggDrop(self, K: int, N: int) -> int: Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN... | 6ff1941ff213a843013100ac7033e2d4f90fbd6a | <|skeleton|>
class Solution:
def superEggDrop(self, K: int, N: int) -> int:
"""Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)"""
<|body_0|>
def superEggDrop(self, K: int, N: int) -> int:
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def superEggDrop(self, K: int, N: int) -> int:
"""Intuition: dp[n][k] = min steps to check n floors with k eggs dp[n][k] = min(1 + max(dp[x-1][k-1], dp[n-x][k]) for all x) time O(KN^2), space O(KN)"""
def dfs(n, k, memo):
if n == 0:
return 0
if... | the_stack_v2_python_sparse | Leetcode 0887. Super Egg Drop.py | Chaoran-sjsu/leetcode | train | 0 | |
cc95fc34723ddc51a7162f768f2b4cae9ab980bd | [
"assert isinstance(errors, int) or errors in ('raise', 'ignore', 'report')\nself.function = function\nself.errors = errors\nself.error_count = 0",
"try:\n return self.function(*args, **kwds)\nexcept Exception as e:\n self.error_count += 1\n if self.errors == 'raise':\n raise\n if self.errors ==... | <|body_start_0|>
assert isinstance(errors, int) or errors in ('raise', 'ignore', 'report')
self.function = function
self.errors = errors
self.error_count = 0
<|end_body_0|>
<|body_start_1|>
try:
return self.function(*args, **kwds)
except Exception as e:
... | Wraps a function call to catch and report exceptions. | LogErrors | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogErrors:
"""Wraps a function call to catch and report exceptions."""
def __init__(self, function, errors):
""":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning t... | stack_v2_sparse_classes_10k_train_005502 | 1,450 | permissive | [
{
"docstring": ":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning to raise an exception 'ignore', meaning to ignore all errors 'report', meaning to report all errors",
"name": "__init__",... | 2 | stack_v2_sparse_classes_30k_train_001784 | Implement the Python class `LogErrors` described below.
Class description:
Wraps a function call to catch and report exceptions.
Method signatures and docstrings:
- def __init__(self, function, errors): :param function: the function to wrap :param errors: either a number, indicating how many errors to report before i... | Implement the Python class `LogErrors` described below.
Class description:
Wraps a function call to catch and report exceptions.
Method signatures and docstrings:
- def __init__(self, function, errors): :param function: the function to wrap :param errors: either a number, indicating how many errors to report before i... | fd97e6c651a4bbcade64733847f4eec8f7704b7c | <|skeleton|>
class LogErrors:
"""Wraps a function call to catch and report exceptions."""
def __init__(self, function, errors):
""":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class LogErrors:
"""Wraps a function call to catch and report exceptions."""
def __init__(self, function, errors):
""":param function: the function to wrap :param errors: either a number, indicating how many errors to report before ignoring them, or one of these strings: 'raise', meaning to raise an ex... | the_stack_v2_python_sparse | bibliopixel/util/log_errors.py | dr-aryone/BiblioPixel | train | 2 |
a47b129242e4954c44511e3b5d017ba217629b99 | [
"params = dict()\nparams['applicationguid'] = applicationguid\nreturn q.workflowengine.actionmanager.startActorAction('cloudinstallservice', 'initialize', params, jobguid=jobguid, executionparams=executionparams)",
"params = dict()\nparams['machineguid'] = machineguid\nreturn q.workflowengine.actionmanager.startA... | <|body_start_0|>
params = dict()
params['applicationguid'] = applicationguid
return q.workflowengine.actionmanager.startActorAction('cloudinstallservice', 'initialize', params, jobguid=jobguid, executionparams=executionparams)
<|end_body_0|>
<|body_start_1|>
params = dict()
para... | cloudinstallservice | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class cloudinstallservice:
def initialize(self, applicationguid='', jobguid='', executionparams={}):
"""Installs and configures the cloud install service. @param applicationguid: Guid of the application which needs to be initialized @type applicationguid: guid @param jobguid: Guid of the job @... | stack_v2_sparse_classes_10k_train_005503 | 4,461 | no_license | [
{
"docstring": "Installs and configures the cloud install service. @param applicationguid: Guid of the application which needs to be initialized @type applicationguid: guid @param jobguid: Guid of the job @type jobguid: guid @param executionParams: dictionary with additional executionParams @type executionParam... | 4 | null | Implement the Python class `cloudinstallservice` described below.
Class description:
Implement the cloudinstallservice class.
Method signatures and docstrings:
- def initialize(self, applicationguid='', jobguid='', executionparams={}): Installs and configures the cloud install service. @param applicationguid: Guid of... | Implement the Python class `cloudinstallservice` described below.
Class description:
Implement the cloudinstallservice class.
Method signatures and docstrings:
- def initialize(self, applicationguid='', jobguid='', executionparams={}): Installs and configures the cloud install service. @param applicationguid: Guid of... | 53d349fa6bee0ccead29afd6676979b44c109a61 | <|skeleton|>
class cloudinstallservice:
def initialize(self, applicationguid='', jobguid='', executionparams={}):
"""Installs and configures the cloud install service. @param applicationguid: Guid of the application which needs to be initialized @type applicationguid: guid @param jobguid: Guid of the job @... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class cloudinstallservice:
def initialize(self, applicationguid='', jobguid='', executionparams={}):
"""Installs and configures the cloud install service. @param applicationguid: Guid of the application which needs to be initialized @type applicationguid: guid @param jobguid: Guid of the job @type jobguid: ... | the_stack_v2_python_sparse | apps/cloud_api_generator/actor/cloudinstallservice.py | racktivity/ext-pylabs-core | train | 0 | |
13c2070910709952904bde6c9c10bcc81d0ec81d | [
"nx, ny = np.shape(mass_map)\nif nx != ny:\n raise ValueError('Shape of mass map needs to be square!, set as %s %s' % (nx, ny))\nself._mass_map = mass_map\nself._grid_spacing = grid_spacing\nself._redshift = redshift\nself._f_x_mass, self._f_y_mass = convergence_integrals.deflection_from_kappa_grid(self._mass_ma... | <|body_start_0|>
nx, ny = np.shape(mass_map)
if nx != ny:
raise ValueError('Shape of mass map needs to be square!, set as %s %s' % (nx, ny))
self._mass_map = mass_map
self._grid_spacing = grid_spacing
self._redshift = redshift
self._f_x_mass, self._f_y_mass = ... | class to describe a single mass slice | MassSlice | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MassSlice:
"""class to describe a single mass slice"""
def __init__(self, mass_map, grid_spacing, redshift):
""":param mass_map: 2d numpy array of mass map (in units physical Msol) :param grid_spacing: grid spacing of the mass map (in units physical Mpc) :param redshift: redshift"""
... | stack_v2_sparse_classes_10k_train_005504 | 5,293 | permissive | [
{
"docstring": ":param mass_map: 2d numpy array of mass map (in units physical Msol) :param grid_spacing: grid spacing of the mass map (in units physical Mpc) :param redshift: redshift",
"name": "__init__",
"signature": "def __init__(self, mass_map, grid_spacing, redshift)"
},
{
"docstring": "sc... | 2 | null | Implement the Python class `MassSlice` described below.
Class description:
class to describe a single mass slice
Method signatures and docstrings:
- def __init__(self, mass_map, grid_spacing, redshift): :param mass_map: 2d numpy array of mass map (in units physical Msol) :param grid_spacing: grid spacing of the mass ... | Implement the Python class `MassSlice` described below.
Class description:
class to describe a single mass slice
Method signatures and docstrings:
- def __init__(self, mass_map, grid_spacing, redshift): :param mass_map: 2d numpy array of mass map (in units physical Msol) :param grid_spacing: grid spacing of the mass ... | 73c9645f26f6983fe7961104075ebe8bf7a4b54c | <|skeleton|>
class MassSlice:
"""class to describe a single mass slice"""
def __init__(self, mass_map, grid_spacing, redshift):
""":param mass_map: 2d numpy array of mass map (in units physical Msol) :param grid_spacing: grid spacing of the mass map (in units physical Mpc) :param redshift: redshift"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MassSlice:
"""class to describe a single mass slice"""
def __init__(self, mass_map, grid_spacing, redshift):
""":param mass_map: 2d numpy array of mass map (in units physical Msol) :param grid_spacing: grid spacing of the mass map (in units physical Mpc) :param redshift: redshift"""
nx, n... | the_stack_v2_python_sparse | lenstronomy/LensModel/LightConeSim/light_cone.py | lenstronomy/lenstronomy | train | 41 |
9e35f489744ead8f7f7534f38a51623ebdc2883b | [
"self.from_city = kwargs['from_city']\nself.from_stop = kwargs['from_stop'] if kwargs['from_stop'] not in ['__ANY__', 'none'] else None\nself.to_city = kwargs['to_city']\nself.to_stop = kwargs['to_stop'] if kwargs['to_stop'] not in ['__ANY__', 'none'] else None\nself.vehicle = kwargs['vehicle'] if kwargs['vehicle']... | <|body_start_0|>
self.from_city = kwargs['from_city']
self.from_stop = kwargs['from_stop'] if kwargs['from_stop'] not in ['__ANY__', 'none'] else None
self.to_city = kwargs['to_city']
self.to_stop = kwargs['to_stop'] if kwargs['to_stop'] not in ['__ANY__', 'none'] else None
self.... | Holder for starting and ending point (and other parameters) of travel. | Travel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Travel:
"""Holder for starting and ending point (and other parameters) of travel."""
def __init__(self, **kwargs):
"""Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers."""
<|body_0|>
def get_minimal_info(se... | stack_v2_sparse_classes_10k_train_005505 | 30,338 | permissive | [
{
"docstring": "Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring": "Return minimal waypoints information in the form of a stringified inform() dial... | 2 | stack_v2_sparse_classes_30k_val_000163 | Implement the Python class `Travel` described below.
Class description:
Holder for starting and ending point (and other parameters) of travel.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_tran... | Implement the Python class `Travel` described below.
Class description:
Holder for starting and ending point (and other parameters) of travel.
Method signatures and docstrings:
- def __init__(self, **kwargs): Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_tran... | e8fdc6f2d908d7a1911b18f29c218ae58d19ed6f | <|skeleton|>
class Travel:
"""Holder for starting and ending point (and other parameters) of travel."""
def __init__(self, **kwargs):
"""Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers."""
<|body_0|>
def get_minimal_info(se... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Travel:
"""Holder for starting and ending point (and other parameters) of travel."""
def __init__(self, **kwargs):
"""Initializing (just filling in data). Accepted keys: from_city, from_stop, to_city, to_stop, vehicle, max_transfers."""
self.from_city = kwargs['from_city']
self.fr... | the_stack_v2_python_sparse | alex/applications/PublicTransportInfoCS/directions.py | beka-evature/alex | train | 1 |
b40649f78e62e1a7f1cf93fe86becbb53f51a325 | [
"if not s:\n return ''\nn = len(s)\ndp = [[False] * n for _ in range(n)]\nmax_len = 1\nres = s[0]\nfor i in range(n):\n dp[i][i] = True\nfor j in range(1, n):\n for i in range(j):\n if s[i] == s[j]:\n if j - 1 - (i + 1) + 1 >= 2:\n dp[i][j] = dp[i + 1][j - 1]\n e... | <|body_start_0|>
if not s:
return ''
n = len(s)
dp = [[False] * n for _ in range(n)]
max_len = 1
res = s[0]
for i in range(n):
dp[i][i] = True
for j in range(1, n):
for i in range(j):
if s[i] == s[j]:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
"""首先想到暴力：两重循环， 第一重，从头到尾遍历字符串，i 第二重，从头到尾取j属于[0, i], 看[i, j]是否为回文 时间复杂度：n**3 所以我们继续考虑，引入动态规划，空间换时间，这是从中间往外扩散过程 状态转移方程dp[i][j] = dp[i+1][j-1] if s[i] == s[j] and (j-1)-(i+1) + 1>= 2 True if s[i] == s[j] and j-1 - (i+1) + 1< 2 表明字符串长度不足2,为1 False if... | stack_v2_sparse_classes_10k_train_005506 | 4,417 | no_license | [
{
"docstring": "首先想到暴力：两重循环， 第一重，从头到尾遍历字符串，i 第二重，从头到尾取j属于[0, i], 看[i, j]是否为回文 时间复杂度：n**3 所以我们继续考虑，引入动态规划，空间换时间，这是从中间往外扩散过程 状态转移方程dp[i][j] = dp[i+1][j-1] if s[i] == s[j] and (j-1)-(i+1) + 1>= 2 True if s[i] == s[j] and j-1 - (i+1) + 1< 2 表明字符串长度不足2,为1 False if s[i] != s[j] 表明就不是字符串 考虑初始状态：自下而上，初始状态为字符串长度==1,dp[i... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): 首先想到暴力：两重循环， 第一重，从头到尾遍历字符串，i 第二重，从头到尾取j属于[0, i], 看[i, j]是否为回文 时间复杂度：n**3 所以我们继续考虑，引入动态规划，空间换时间，这是从中间往外扩散过程 状态转移方程dp[i][j] = dp[i+1][j-1] if s[i] =... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): 首先想到暴力：两重循环， 第一重，从头到尾遍历字符串，i 第二重，从头到尾取j属于[0, i], 看[i, j]是否为回文 时间复杂度：n**3 所以我们继续考虑，引入动态规划，空间换时间，这是从中间往外扩散过程 状态转移方程dp[i][j] = dp[i+1][j-1] if s[i] =... | f1bbd6b3197cd9ac4f0d35a37539c11b02272065 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
"""首先想到暴力：两重循环， 第一重，从头到尾遍历字符串，i 第二重，从头到尾取j属于[0, i], 看[i, j]是否为回文 时间复杂度：n**3 所以我们继续考虑，引入动态规划，空间换时间，这是从中间往外扩散过程 状态转移方程dp[i][j] = dp[i+1][j-1] if s[i] == s[j] and (j-1)-(i+1) + 1>= 2 True if s[i] == s[j] and j-1 - (i+1) + 1< 2 表明字符串长度不足2,为1 False if... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def longestPalindrome(self, s):
"""首先想到暴力：两重循环， 第一重，从头到尾遍历字符串，i 第二重，从头到尾取j属于[0, i], 看[i, j]是否为回文 时间复杂度：n**3 所以我们继续考虑，引入动态规划，空间换时间，这是从中间往外扩散过程 状态转移方程dp[i][j] = dp[i+1][j-1] if s[i] == s[j] and (j-1)-(i+1) + 1>= 2 True if s[i] == s[j] and j-1 - (i+1) + 1< 2 表明字符串长度不足2,为1 False if s[i] != s[j] ... | the_stack_v2_python_sparse | leetcode/动态规划/5. 最长回文子串/longestPalindrome.py | guohaoyuan/algorithms-for-work | train | 2 | |
bac7eb9694e74420e2190ac4dda1dc34118be6d1 | [
"connected_indexes = []\nfor i in reversed(range(0, idx)):\n if row[i] == 1:\n connected_indexes.append(i)\n else:\n break\nfor i in range(idx, len(row)):\n if row[i] == 1:\n connected_indexes.append(i)\n else:\n break\nreturn connected_indexes",
"opens = [i for i in pre_tu... | <|body_start_0|>
connected_indexes = []
for i in reversed(range(0, idx)):
if row[i] == 1:
connected_indexes.append(i)
else:
break
for i in range(idx, len(row)):
if row[i] == 1:
connected_indexes.append(i)
... | Percolation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Percolation:
def expand_check(self, idx, row):
"""to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point"""
<|body_0|>
def isPercolate(self,... | stack_v2_sparse_classes_10k_train_005507 | 3,374 | no_license | [
{
"docstring": "to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point",
"name": "expand_check",
"signature": "def expand_check(self, idx, row)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_val_000044 | Implement the Python class `Percolation` described below.
Class description:
Implement the Percolation class.
Method signatures and docstrings:
- def expand_check(self, idx, row): to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes... | Implement the Python class `Percolation` described below.
Class description:
Implement the Percolation class.
Method signatures and docstrings:
- def expand_check(self, idx, row): to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Percolation:
def expand_check(self, idx, row):
"""to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point"""
<|body_0|>
def isPercolate(self,... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Percolation:
def expand_check(self, idx, row):
"""to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point"""
connected_indexes = []
for i in reversed(ra... | the_stack_v2_python_sparse | QuickProjects/Algorithm/p01_percolation.py | jxie0755/Learning_Python | train | 0 | |
74f9eafdea97ac8b9552b795b3af81549c804fc5 | [
"current_user = request.user\nhighlight_data = request.data.get('highlight_data', {})\ntry:\n article = Articles.objects.get(slug=slug)\nexcept Articles.DoesNotExist:\n return Response({'errors': HIGHLIGHT_MSGS['ARTICLE_NOT_FOUND']}, status=status.HTTP_404_NOT_FOUND)\nhighlights = Highlights.objects.filter(ar... | <|body_start_0|>
current_user = request.user
highlight_data = request.data.get('highlight_data', {})
try:
article = Articles.objects.get(slug=slug)
except Articles.DoesNotExist:
return Response({'errors': HIGHLIGHT_MSGS['ARTICLE_NOT_FOUND']}, status=status.HTTP_40... | Provide methods for creating a highlight | CreateGetDeleteMyHighlightsAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CreateGetDeleteMyHighlightsAPIView:
"""Provide methods for creating a highlight"""
def get(self, request, slug):
"""Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { "message": "message body", "hig... | stack_v2_sparse_classes_10k_train_005508 | 12,153 | permissive | [
{
"docstring": "Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { \"message\": \"message body\", \"highlights\": list of highlights and their details } OR { \"errors\": \"error details body\" }",
"name": "get",
"signa... | 2 | stack_v2_sparse_classes_30k_train_005230 | Implement the Python class `CreateGetDeleteMyHighlightsAPIView` described below.
Class description:
Provide methods for creating a highlight
Method signatures and docstrings:
- def get(self, request, slug): Get all my highlights for an article Params ------- request: Object with request data and functions. Returns --... | Implement the Python class `CreateGetDeleteMyHighlightsAPIView` described below.
Class description:
Provide methods for creating a highlight
Method signatures and docstrings:
- def get(self, request, slug): Get all my highlights for an article Params ------- request: Object with request data and functions. Returns --... | 5a31840856de4b361fe2594dfa7a33d7774d3fe2 | <|skeleton|>
class CreateGetDeleteMyHighlightsAPIView:
"""Provide methods for creating a highlight"""
def get(self, request, slug):
"""Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { "message": "message body", "hig... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CreateGetDeleteMyHighlightsAPIView:
"""Provide methods for creating a highlight"""
def get(self, request, slug):
"""Get all my highlights for an article Params ------- request: Object with request data and functions. Returns -------- Response object: { "message": "message body", "highlights": lis... | the_stack_v2_python_sparse | authors/apps/highlights/views.py | bl4ck4ndbr0wn/ah-centauri-backend | train | 0 |
e924989f2efa8f11ff98f983b4d1390146b096e1 | [
"logger.debug('Defining unique_bitcount() function...')\nwith conn.cursor() as cursor:\n cursor.execute(sql.SQL('CREATE FUNCTION unique_bitcount(n INTEGER) RETURNS INTEGER\\n LANGUAGE plpgsql IMMUTABLE PARALLEL SAFE\\n AS $$\\n ... | <|body_start_0|>
logger.debug('Defining unique_bitcount() function...')
with conn.cursor() as cursor:
cursor.execute(sql.SQL('CREATE FUNCTION unique_bitcount(n INTEGER) RETURNS INTEGER\n LANGUAGE plpgsql IMMUTABLE PARALLEL SAFE\n ... | Class use to upgrade to V84 of the schema. | SchemaMigrator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SchemaMigrator:
"""Class use to upgrade to V84 of the schema."""
def _define_unique_bitcount_func(self, logger, conn):
"""Helper method to define unique_bitcount sql function."""
<|body_0|>
def _create_index_on_device_id(self, logger, conn):
"""Method to create i... | stack_v2_sparse_classes_10k_train_005509 | 11,436 | no_license | [
{
"docstring": "Helper method to define unique_bitcount sql function.",
"name": "_define_unique_bitcount_func",
"signature": "def _define_unique_bitcount_func(self, logger, conn)"
},
{
"docstring": "Method to create index on device_id in registration_list.",
"name": "_create_index_on_device_... | 6 | stack_v2_sparse_classes_30k_train_003942 | Implement the Python class `SchemaMigrator` described below.
Class description:
Class use to upgrade to V84 of the schema.
Method signatures and docstrings:
- def _define_unique_bitcount_func(self, logger, conn): Helper method to define unique_bitcount sql function.
- def _create_index_on_device_id(self, logger, conn... | Implement the Python class `SchemaMigrator` described below.
Class description:
Class use to upgrade to V84 of the schema.
Method signatures and docstrings:
- def _define_unique_bitcount_func(self, logger, conn): Helper method to define unique_bitcount sql function.
- def _create_index_on_device_id(self, logger, conn... | ac26dc97c57216dc3c1fed1e1b17aac27d3a1a2d | <|skeleton|>
class SchemaMigrator:
"""Class use to upgrade to V84 of the schema."""
def _define_unique_bitcount_func(self, logger, conn):
"""Helper method to define unique_bitcount sql function."""
<|body_0|>
def _create_index_on_device_id(self, logger, conn):
"""Method to create i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SchemaMigrator:
"""Class use to upgrade to V84 of the schema."""
def _define_unique_bitcount_func(self, logger, conn):
"""Helper method to define unique_bitcount sql function."""
logger.debug('Defining unique_bitcount() function...')
with conn.cursor() as cursor:
curso... | the_stack_v2_python_sparse | src/dirbs/schema_migrators/v84_upgrade.py | yasirz/DIRBS-Core | train | 0 |
5f179d2316f534c147804fae97e19d3704c0ea27 | [
"if not self.created_date:\n self.created_date = datetime.utcnow()\nself.modified_date = datetime.utcnow()\nsuper(Message, self).save(*args, **kwargs)",
"logging.info('getting %s %s for Message %s (%s)' % (asset_class, mime_type, self, self.pk))\nif isinstance(asset_class, AssetClass):\n return self.assets.... | <|body_start_0|>
if not self.created_date:
self.created_date = datetime.utcnow()
self.modified_date = datetime.utcnow()
super(Message, self).save(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
logging.info('getting %s %s for Message %s (%s)' % (asset_class, mime_type, self... | Message | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Message:
def save(self, *args, **kwargs):
"""Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time"""
<|body_0|>
def get_asset(self, asset_class, mime_type)... | stack_v2_sparse_classes_10k_train_005510 | 23,088 | no_license | [
{
"docstring": "Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time",
"name": "save",
"signature": "def save(self, *args, **kwargs)"
},
{
"docstring": "Get an asset associated... | 2 | stack_v2_sparse_classes_30k_train_002075 | Implement the Python class `Message` described below.
Class description:
Implement the Message class.
Method signatures and docstrings:
- def save(self, *args, **kwargs): Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and loca... | Implement the Python class `Message` described below.
Class description:
Implement the Message class.
Method signatures and docstrings:
- def save(self, *args, **kwargs): Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and loca... | e5a0d666ff11c812518cecb0f57257c64ca5cdfd | <|skeleton|>
class Message:
def save(self, *args, **kwargs):
"""Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time"""
<|body_0|>
def get_asset(self, asset_class, mime_type)... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Message:
def save(self, *args, **kwargs):
"""Overwriting save to set created_date and modified_date to utcnow() Django uses datetime.now() We want to store and transmit only UTC time, and localize it at rendering time"""
if not self.created_date:
self.created_date = datetime.utcnow... | the_stack_v2_python_sparse | donomo_archive/lib/donomo/archive/models.py | alexissmirnov/donomo | train | 0 | |
9ea20f6c82956b473b8bd9fb7619a1b50bd8de74 | [
"params = [10000, 5, 10, 15]\nheight = 100\nwidth = 200\nworld_map = gen.generate_map(height=height, width=width, params=params)\nimage = img.get_map_overview(world_map)\npixels = image.load()\nfor x in range(width):\n for y in range(height):\n color = tuple(img.get_color(world_map[x][y]))\n self.a... | <|body_start_0|>
params = [10000, 5, 10, 15]
height = 100
width = 200
world_map = gen.generate_map(height=height, width=width, params=params)
image = img.get_map_overview(world_map)
pixels = image.load()
for x in range(width):
for y in range(height):
... | MapCase | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MapCase:
def test_map_overview_accuracy(self):
"""Test if image of map overview properly represents generated map matrix."""
<|body_0|>
def test_spreading_players(self):
"""Test if players are properly spread across."""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_10k_train_005511 | 1,357 | permissive | [
{
"docstring": "Test if image of map overview properly represents generated map matrix.",
"name": "test_map_overview_accuracy",
"signature": "def test_map_overview_accuracy(self)"
},
{
"docstring": "Test if players are properly spread across.",
"name": "test_spreading_players",
"signatur... | 2 | stack_v2_sparse_classes_30k_train_001000 | Implement the Python class `MapCase` described below.
Class description:
Implement the MapCase class.
Method signatures and docstrings:
- def test_map_overview_accuracy(self): Test if image of map overview properly represents generated map matrix.
- def test_spreading_players(self): Test if players are properly sprea... | Implement the Python class `MapCase` described below.
Class description:
Implement the MapCase class.
Method signatures and docstrings:
- def test_map_overview_accuracy(self): Test if image of map overview properly represents generated map matrix.
- def test_spreading_players(self): Test if players are properly sprea... | 1edad57d47ad975950639fc391b645e47509cf58 | <|skeleton|>
class MapCase:
def test_map_overview_accuracy(self):
"""Test if image of map overview properly represents generated map matrix."""
<|body_0|>
def test_spreading_players(self):
"""Test if players are properly spread across."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MapCase:
def test_map_overview_accuracy(self):
"""Test if image of map overview properly represents generated map matrix."""
params = [10000, 5, 10, 15]
height = 100
width = 200
world_map = gen.generate_map(height=height, width=width, params=params)
image = img.... | the_stack_v2_python_sparse | map_generation/test_map_generation.py | GabrielWechta/age-of-divisiveness | train | 0 | |
72de027ad380186edcd59b98e76f4f1eb3effbe9 | [
"self.action_n = env.action_space.n\nself.obs_low = env.observation_space.low\nself.obs_scale = env.observation_space.high - env.observation_space.low\nself.encoder = TileCoder(layers, features)\nself.w = np.zeros(features)\nself.feature_list = []\nself.trajectory = []\nself.gamma = gamma\nself.learning_rate = lear... | <|body_start_0|>
self.action_n = env.action_space.n
self.obs_low = env.observation_space.low
self.obs_scale = env.observation_space.high - env.observation_space.low
self.encoder = TileCoder(layers, features)
self.w = np.zeros(features)
self.feature_list = []
self.... | 回合更新策略梯度算法寻找最优策略 | VPGAgent | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VPGAgent:
"""回合更新策略梯度算法寻找最优策略"""
def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True):
"""学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率"""
... | stack_v2_sparse_classes_10k_train_005512 | 22,277 | no_license | [
{
"docstring": "学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率",
"name": "__init__",
"signature": "def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True)"
},
{... | 3 | stack_v2_sparse_classes_30k_train_005709 | Implement the Python class `VPGAgent` described below.
Class description:
回合更新策略梯度算法寻找最优策略
Method signatures and docstrings:
- def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True): 学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8... | Implement the Python class `VPGAgent` described below.
Class description:
回合更新策略梯度算法寻找最优策略
Method signatures and docstrings:
- def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True): 学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8... | e6526e9e38fcb5be91b46cb40715c15242198a0b | <|skeleton|>
class VPGAgent:
"""回合更新策略梯度算法寻找最优策略"""
def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True):
"""学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class VPGAgent:
"""回合更新策略梯度算法寻找最优策略"""
def __init__(self, env, layers=8, features=1893, gamma=1.0, learning_rate=0.03, epsilon=0.001, baseline=True):
"""学习函数 env 环境 layers 要用到几层砖瓦编码 features 砖瓦编码应该得到多少特征 总特征数 8*8 + (8+1) * (8+1) * (8-1) gamma 收益衰减速率 learning_rate 学习速率 epsilon 执行探索策略概率"""
self.a... | the_stack_v2_python_sparse | mountain_car/function_approx.py | lwzswufe/gym_learning | train | 0 |
f89a0c2b7fe5be8f2625b0618a4ca65407a53577 | [
"nodes = []\nhead = point = ListNode(0)\nfor listNode in lists:\n while listNode:\n nodes.append(listNode.val)\n listNode = listNode.next\nfor node in sorted(nodes):\n point.next = ListNode(node.val)\n point = point.next\nreturn head.next",
"from queue import PriorityQueue\nhead = point = L... | <|body_start_0|>
nodes = []
head = point = ListNode(0)
for listNode in lists:
while listNode:
nodes.append(listNode.val)
listNode = listNode.next
for node in sorted(nodes):
point.next = ListNode(node.val)
point = point.n... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeKLists(self, lists):
"""暴力遍历所有节点 排序后增添到链表中"""
<|body_0|>
def fun2(self, lists):
"""优先队列处理"""
<|body_1|>
def fun3(self, lists):
"""分而治之"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
nodes = []
head = ... | stack_v2_sparse_classes_10k_train_005513 | 2,154 | no_license | [
{
"docstring": "暴力遍历所有节点 排序后增添到链表中",
"name": "mergeKLists",
"signature": "def mergeKLists(self, lists)"
},
{
"docstring": "优先队列处理",
"name": "fun2",
"signature": "def fun2(self, lists)"
},
{
"docstring": "分而治之",
"name": "fun3",
"signature": "def fun3(self, lists)"
}
] | 3 | stack_v2_sparse_classes_30k_train_005976 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKLists(self, lists): 暴力遍历所有节点 排序后增添到链表中
- def fun2(self, lists): 优先队列处理
- def fun3(self, lists): 分而治之 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeKLists(self, lists): 暴力遍历所有节点 排序后增添到链表中
- def fun2(self, lists): 优先队列处理
- def fun3(self, lists): 分而治之
<|skeleton|>
class Solution:
def mergeKLists(self, lists):
... | 0b10f5731690da7998add288e4b0b87d5d71a97e | <|skeleton|>
class Solution:
def mergeKLists(self, lists):
"""暴力遍历所有节点 排序后增添到链表中"""
<|body_0|>
def fun2(self, lists):
"""优先队列处理"""
<|body_1|>
def fun3(self, lists):
"""分而治之"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeKLists(self, lists):
"""暴力遍历所有节点 排序后增添到链表中"""
nodes = []
head = point = ListNode(0)
for listNode in lists:
while listNode:
nodes.append(listNode.val)
listNode = listNode.next
for node in sorted(nodes):
... | the_stack_v2_python_sparse | leetcode/leetcode/23.合并K个排序列表.py | GGL12/myStudy | train | 0 | |
62316a86190dd5c044b15576f410aeab4c6db677 | [
"super().on_episode_step(worker=worker, base_env=base_env, policies=policies, episode=episode, env_index=env_index, **kwargs)\nif isinstance(episode, Episode):\n info = episode.last_info_for()\nelse:\n info = episode._last_infos.get(_DUMMY_AGENT_ID)\nif info is not None:\n for key, value in info.items():\n... | <|body_start_0|>
super().on_episode_step(worker=worker, base_env=base_env, policies=policies, episode=episode, env_index=env_index, **kwargs)
if isinstance(episode, Episode):
info = episode.last_info_for()
else:
info = episode._last_infos.get(_DUMMY_AGENT_ID)
if i... | TODO: Write documentation. Base on `rllib/examples/custom_metrics_and_callbacks.py` example. | MonitorInfoCallback | [
"MIT",
"BSL-1.0",
"MPL-2.0",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MonitorInfoCallback:
"""TODO: Write documentation. Base on `rllib/examples/custom_metrics_and_callbacks.py` example."""
def on_episode_step(self, *, worker: 'RolloutWorker', base_env: BaseEnv, policies: Optional[Dict[PolicyID, Policy]]=None, episode: Union[Episode, EpisodeV2], env_index: Opt... | stack_v2_sparse_classes_10k_train_005514 | 3,161 | permissive | [
{
"docstring": "TODO: Write documentation.",
"name": "on_episode_step",
"signature": "def on_episode_step(self, *, worker: 'RolloutWorker', base_env: BaseEnv, policies: Optional[Dict[PolicyID, Policy]]=None, episode: Union[Episode, EpisodeV2], env_index: Optional[int]=None, **kwargs: Any) -> None"
},
... | 2 | stack_v2_sparse_classes_30k_train_000345 | Implement the Python class `MonitorInfoCallback` described below.
Class description:
TODO: Write documentation. Base on `rllib/examples/custom_metrics_and_callbacks.py` example.
Method signatures and docstrings:
- def on_episode_step(self, *, worker: 'RolloutWorker', base_env: BaseEnv, policies: Optional[Dict[PolicyI... | Implement the Python class `MonitorInfoCallback` described below.
Class description:
TODO: Write documentation. Base on `rllib/examples/custom_metrics_and_callbacks.py` example.
Method signatures and docstrings:
- def on_episode_step(self, *, worker: 'RolloutWorker', base_env: BaseEnv, policies: Optional[Dict[PolicyI... | a3b244f0bcb21abe605544d1f5c4a31419946efd | <|skeleton|>
class MonitorInfoCallback:
"""TODO: Write documentation. Base on `rllib/examples/custom_metrics_and_callbacks.py` example."""
def on_episode_step(self, *, worker: 'RolloutWorker', base_env: BaseEnv, policies: Optional[Dict[PolicyID, Policy]]=None, episode: Union[Episode, EpisodeV2], env_index: Opt... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MonitorInfoCallback:
"""TODO: Write documentation. Base on `rllib/examples/custom_metrics_and_callbacks.py` example."""
def on_episode_step(self, *, worker: 'RolloutWorker', base_env: BaseEnv, policies: Optional[Dict[PolicyID, Policy]]=None, episode: Union[Episode, EpisodeV2], env_index: Optional[int]=No... | the_stack_v2_python_sparse | python/gym_jiminy/rllib/gym_jiminy/rllib/callbacks.py | duburcqa/jiminy | train | 108 |
089999c449eae46d79e91689a2c2dc53a5c68d92 | [
"self.availability_set = availability_set\nself.azure_managed_disk_params = azure_managed_disk_params\nself.compute_options = compute_options\nself.data_transfer_info = data_transfer_info\nself.network_resource_group = network_resource_group\nself.network_security_group = network_security_group\nself.resource_group... | <|body_start_0|>
self.availability_set = availability_set
self.azure_managed_disk_params = azure_managed_disk_params
self.compute_options = compute_options
self.data_transfer_info = data_transfer_info
self.network_resource_group = network_resource_group
self.network_secur... | Implementation of the 'DeployVMsToAzureParams' model. Contains Azure specific information needed to identify various resources when converting and deploying a VM to Azure. Attributes: availability_set (EntityProto): Name of the Availability set in which the VM is to be restored. azure_managed_disk_params (AzureManagedD... | DeployVMsToAzureParams | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeployVMsToAzureParams:
"""Implementation of the 'DeployVMsToAzureParams' model. Contains Azure specific information needed to identify various resources when converting and deploying a VM to Azure. Attributes: availability_set (EntityProto): Name of the Availability set in which the VM is to be ... | stack_v2_sparse_classes_10k_train_005515 | 10,381 | permissive | [
{
"docstring": "Constructor for the DeployVMsToAzureParams class",
"name": "__init__",
"signature": "def __init__(self, availability_set=None, azure_managed_disk_params=None, compute_options=None, data_transfer_info=None, network_resource_group=None, network_security_group=None, resource_group=None, sto... | 2 | null | Implement the Python class `DeployVMsToAzureParams` described below.
Class description:
Implementation of the 'DeployVMsToAzureParams' model. Contains Azure specific information needed to identify various resources when converting and deploying a VM to Azure. Attributes: availability_set (EntityProto): Name of the Ava... | Implement the Python class `DeployVMsToAzureParams` described below.
Class description:
Implementation of the 'DeployVMsToAzureParams' model. Contains Azure specific information needed to identify various resources when converting and deploying a VM to Azure. Attributes: availability_set (EntityProto): Name of the Ava... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class DeployVMsToAzureParams:
"""Implementation of the 'DeployVMsToAzureParams' model. Contains Azure specific information needed to identify various resources when converting and deploying a VM to Azure. Attributes: availability_set (EntityProto): Name of the Availability set in which the VM is to be ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DeployVMsToAzureParams:
"""Implementation of the 'DeployVMsToAzureParams' model. Contains Azure specific information needed to identify various resources when converting and deploying a VM to Azure. Attributes: availability_set (EntityProto): Name of the Availability set in which the VM is to be restored. azu... | the_stack_v2_python_sparse | cohesity_management_sdk/models/deploy_vms_to_azure_params.py | cohesity/management-sdk-python | train | 24 |
838323aff0a041d6247f646dddccf10cb0b6c602 | [
"super(Net, self).__init__()\nconv1_shape = (height, 1)\nconv2_shape = 5\npool_1_shape = 2\npool_2_shape = 2\nconv1_outshape = 20\nconv2_outshape = 40\nself.output = output_size\nself.conv1 = nn.Sequential(nn.Conv2d(in_channels=channels, out_channels=conv1_outshape, kernel_size=conv1_shape, stride=1, padding=2), nn... | <|body_start_0|>
super(Net, self).__init__()
conv1_shape = (height, 1)
conv2_shape = 5
pool_1_shape = 2
pool_2_shape = 2
conv1_outshape = 20
conv2_outshape = 40
self.output = output_size
self.conv1 = nn.Sequential(nn.Conv2d(in_channels=channels, ou... | Basic CNN. Using as basis for evantual netork Input of form: Batch Size - Channels - Height - Width | Net | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Net:
"""Basic CNN. Using as basis for evantual netork Input of form: Batch Size - Channels - Height - Width"""
def __init__(self, batch_size, channels, height, width, output_size):
"""Instances. Might make function in order to most accurately create Dense layers"""
<|body_0|>... | stack_v2_sparse_classes_10k_train_005516 | 3,331 | no_license | [
{
"docstring": "Instances. Might make function in order to most accurately create Dense layers",
"name": "__init__",
"signature": "def __init__(self, batch_size, channels, height, width, output_size)"
},
{
"docstring": "Forward. Moving the image through the convulutions have two maxpools for cha... | 4 | stack_v2_sparse_classes_30k_train_001299 | Implement the Python class `Net` described below.
Class description:
Basic CNN. Using as basis for evantual netork Input of form: Batch Size - Channels - Height - Width
Method signatures and docstrings:
- def __init__(self, batch_size, channels, height, width, output_size): Instances. Might make function in order to ... | Implement the Python class `Net` described below.
Class description:
Basic CNN. Using as basis for evantual netork Input of form: Batch Size - Channels - Height - Width
Method signatures and docstrings:
- def __init__(self, batch_size, channels, height, width, output_size): Instances. Might make function in order to ... | 4c4b8fb381c8d98980e119f7f73f393034393468 | <|skeleton|>
class Net:
"""Basic CNN. Using as basis for evantual netork Input of form: Batch Size - Channels - Height - Width"""
def __init__(self, batch_size, channels, height, width, output_size):
"""Instances. Might make function in order to most accurately create Dense layers"""
<|body_0|>... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Net:
"""Basic CNN. Using as basis for evantual netork Input of form: Batch Size - Channels - Height - Width"""
def __init__(self, batch_size, channels, height, width, output_size):
"""Instances. Might make function in order to most accurately create Dense layers"""
super(Net, self).__init... | the_stack_v2_python_sparse | Python_Scripts/network/CNN.py | jommysmoth/ECE_Music | train | 0 |
f8f1726bad3d7bea6ef1db8341607f7b26dcf439 | [
"if value in EMPTY_VALUES:\n return None\nif type(value) in [str, unicode]:\n try:\n value = value.replace(\"'\", '\"')\n value = json.loads(value)\n except ValueError:\n msg = self.error_messages['invalid']\n raise serializers.ValidationError(msg)\nif value:\n day = value.ge... | <|body_start_0|>
if value in EMPTY_VALUES:
return None
if type(value) in [str, unicode]:
try:
value = value.replace("'", '"')
value = json.loads(value)
except ValueError:
msg = self.error_messages['invalid']
... | A serializer field for handling three part date time JSON formatted datetime.date. Expected input format: { "day": 25, "month": 12, "year": 2012 } | ThreePartDateField | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThreePartDateField:
"""A serializer field for handling three part date time JSON formatted datetime.date. Expected input format: { "day": 25, "month": 12, "year": 2012 }"""
def to_internal_value(self, value):
"""Parse json data and return a date object"""
<|body_0|>
def ... | stack_v2_sparse_classes_10k_train_005517 | 4,517 | permissive | [
{
"docstring": "Parse json data and return a date object",
"name": "to_internal_value",
"signature": "def to_internal_value(self, value)"
},
{
"docstring": "Transform datetime.date object to json.",
"name": "to_representation",
"signature": "def to_representation(self, value)"
}
] | 2 | null | Implement the Python class `ThreePartDateField` described below.
Class description:
A serializer field for handling three part date time JSON formatted datetime.date. Expected input format: { "day": 25, "month": 12, "year": 2012 }
Method signatures and docstrings:
- def to_internal_value(self, value): Parse json data... | Implement the Python class `ThreePartDateField` described below.
Class description:
A serializer field for handling three part date time JSON formatted datetime.date. Expected input format: { "day": 25, "month": 12, "year": 2012 }
Method signatures and docstrings:
- def to_internal_value(self, value): Parse json data... | 51d40345b41eb68fb4d65ae273f3496d1012e2f3 | <|skeleton|>
class ThreePartDateField:
"""A serializer field for handling three part date time JSON formatted datetime.date. Expected input format: { "day": 25, "month": 12, "year": 2012 }"""
def to_internal_value(self, value):
"""Parse json data and return a date object"""
<|body_0|>
def ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ThreePartDateField:
"""A serializer field for handling three part date time JSON formatted datetime.date. Expected input format: { "day": 25, "month": 12, "year": 2012 }"""
def to_internal_value(self, value):
"""Parse json data and return a date object"""
if value in EMPTY_VALUES:
... | the_stack_v2_python_sparse | cla_backend/apps/core/drf/fields.py | ministryofjustice/cla_backend | train | 4 |
6b07d30b2c2e0afe3b73afb35604ca1e475698be | [
"super().__init__(*args, **kwargs)\nself.format = fmt\nself.size = size",
"print(f'[{amber_light}]Saving video')\nlogger.debug(f'[{amber_light}]Saving video')\nfld = os.path.join(self.tmp_dir.name, '%d.png')\nfps = int(self.fps)\nname = f'{self.name}.{self.format}'\nfmt = '-vcodec libx264 -crf 28 -pix_fmt yuv420p... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.format = fmt
self.size = size
<|end_body_0|>
<|body_start_1|>
print(f'[{amber_light}]Saving video')
logger.debug(f'[{amber_light}]Saving video')
fld = os.path.join(self.tmp_dir.name, '%d.png')
fps = int(self... | Video | [
"BSD-3-Clause",
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Video:
def __init__(self, *args, fmt='mp4', size='1620x1050', **kwargs):
"""Video class, takes care of storing screenshots (frames) as images in a temporary folder and then merging these into a single video file when the video is closed."""
<|body_0|>
def close(self):
... | stack_v2_sparse_classes_10k_train_005518 | 1,181 | permissive | [
{
"docstring": "Video class, takes care of storing screenshots (frames) as images in a temporary folder and then merging these into a single video file when the video is closed.",
"name": "__init__",
"signature": "def __init__(self, *args, fmt='mp4', size='1620x1050', **kwargs)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_train_007243 | Implement the Python class `Video` described below.
Class description:
Implement the Video class.
Method signatures and docstrings:
- def __init__(self, *args, fmt='mp4', size='1620x1050', **kwargs): Video class, takes care of storing screenshots (frames) as images in a temporary folder and then merging these into a ... | Implement the Python class `Video` described below.
Class description:
Implement the Video class.
Method signatures and docstrings:
- def __init__(self, *args, fmt='mp4', size='1620x1050', **kwargs): Video class, takes care of storing screenshots (frames) as images in a temporary folder and then merging these into a ... | a14ead80c1dbc75f20a145a49394dc467c4f7bf1 | <|skeleton|>
class Video:
def __init__(self, *args, fmt='mp4', size='1620x1050', **kwargs):
"""Video class, takes care of storing screenshots (frames) as images in a temporary folder and then merging these into a single video file when the video is closed."""
<|body_0|>
def close(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Video:
def __init__(self, *args, fmt='mp4', size='1620x1050', **kwargs):
"""Video class, takes care of storing screenshots (frames) as images in a temporary folder and then merging these into a single video file when the video is closed."""
super().__init__(*args, **kwargs)
self.format... | the_stack_v2_python_sparse | brainrender/_video.py | brainglobe/brainrender | train | 345 | |
85f47f0d3e6a9c0418d427d00de354e8fc2f4223 | [
"self.plugin = OrographicEnhancement()\ndata = np.array([[200.0, 450.0, 850.0], [320.0, 500.0, 1000.0], [230.0, 600.0, 900.0]])\nx_coord = DimCoord(np.arange(3), 'projection_x_coordinate', units='km')\ny_coord = DimCoord(np.arange(3), 'projection_y_coordinate', units='km')\nself.plugin.topography = iris.cube.Cube(d... | <|body_start_0|>
self.plugin = OrographicEnhancement()
data = np.array([[200.0, 450.0, 850.0], [320.0, 500.0, 1000.0], [230.0, 600.0, 900.0]])
x_coord = DimCoord(np.arange(3), 'projection_x_coordinate', units='km')
y_coord = DimCoord(np.arange(3), 'projection_y_coordinate', units='km')
... | Test the _orography_gradients method | Test__orography_gradients | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test__orography_gradients:
"""Test the _orography_gradients method"""
def setUp(self):
"""Set up an input cube"""
<|body_0|>
def test_basic(self):
"""Test outputs are cubes"""
<|body_1|>
def test_values(self):
"""Test output values and units"... | stack_v2_sparse_classes_10k_train_005519 | 34,979 | permissive | [
{
"docstring": "Set up an input cube",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Test outputs are cubes",
"name": "test_basic",
"signature": "def test_basic(self)"
},
{
"docstring": "Test output values and units",
"name": "test_values",
"signature... | 3 | null | Implement the Python class `Test__orography_gradients` described below.
Class description:
Test the _orography_gradients method
Method signatures and docstrings:
- def setUp(self): Set up an input cube
- def test_basic(self): Test outputs are cubes
- def test_values(self): Test output values and units | Implement the Python class `Test__orography_gradients` described below.
Class description:
Test the _orography_gradients method
Method signatures and docstrings:
- def setUp(self): Set up an input cube
- def test_basic(self): Test outputs are cubes
- def test_values(self): Test output values and units
<|skeleton|>
c... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test__orography_gradients:
"""Test the _orography_gradients method"""
def setUp(self):
"""Set up an input cube"""
<|body_0|>
def test_basic(self):
"""Test outputs are cubes"""
<|body_1|>
def test_values(self):
"""Test output values and units"... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Test__orography_gradients:
"""Test the _orography_gradients method"""
def setUp(self):
"""Set up an input cube"""
self.plugin = OrographicEnhancement()
data = np.array([[200.0, 450.0, 850.0], [320.0, 500.0, 1000.0], [230.0, 600.0, 900.0]])
x_coord = DimCoord(np.arange(3), ... | the_stack_v2_python_sparse | improver_tests/orographic_enhancement/test_OrographicEnhancement.py | metoppv/improver | train | 101 |
3775d1779fedc61c5ce12242becca5ce2182afb5 | [
"self.n_samples = n_samples\nself.ref_mask_feature = self._parse_features(ref_mask_feature, default_feature_type=FeatureType.MASK_TIMELESS)\nself.ref_labels = list(ref_labels)\nself.sample_features = self._parse_features(sample_features, new_names=True, rename_function='{}_SAMPLED'.format)\nself.return_new_eopatch ... | <|body_start_0|>
self.n_samples = n_samples
self.ref_mask_feature = self._parse_features(ref_mask_feature, default_feature_type=FeatureType.MASK_TIMELESS)
self.ref_labels = list(ref_labels)
self.sample_features = self._parse_features(sample_features, new_names=True, rename_function='{}_S... | Task for spatially sampling points from a time-series. This task performs random spatial sampling of a time-series based on a label mask. The user specifies the number of points to be sampled, the name of the `DATA` time-series, the name of the label raster image, and the name of the output sample features and sampled ... | PointSamplingTask | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PointSamplingTask:
"""Task for spatially sampling points from a time-series. This task performs random spatial sampling of a time-series based on a label mask. The user specifies the number of points to be sampled, the name of the `DATA` time-series, the name of the label raster image, and the na... | stack_v2_sparse_classes_10k_train_005520 | 17,294 | permissive | [
{
"docstring": "Initialise sampling task. The data to be sampled is supposed to be a time-series stored in `DATA` type of the eopatch, while the raster image is supposed to be stored in `MASK_TIMELESS`. The output sampled features are stored in `DATA` and have shape T x N_SAMPLES x 1 x D, where T is the number ... | 2 | stack_v2_sparse_classes_30k_train_003873 | Implement the Python class `PointSamplingTask` described below.
Class description:
Task for spatially sampling points from a time-series. This task performs random spatial sampling of a time-series based on a label mask. The user specifies the number of points to be sampled, the name of the `DATA` time-series, the nam... | Implement the Python class `PointSamplingTask` described below.
Class description:
Task for spatially sampling points from a time-series. This task performs random spatial sampling of a time-series based on a label mask. The user specifies the number of points to be sampled, the name of the `DATA` time-series, the nam... | 148189e2b92e06059b87f223b596255ccafac86d | <|skeleton|>
class PointSamplingTask:
"""Task for spatially sampling points from a time-series. This task performs random spatial sampling of a time-series based on a label mask. The user specifies the number of points to be sampled, the name of the `DATA` time-series, the name of the label raster image, and the na... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PointSamplingTask:
"""Task for spatially sampling points from a time-series. This task performs random spatial sampling of a time-series based on a label mask. The user specifies the number of points to be sampled, the name of the `DATA` time-series, the name of the label raster image, and the name of the out... | the_stack_v2_python_sparse | geometry/eolearn/geometry/sampling.py | wouellette/eo-learn | train | 2 |
55a8d31018ec74d8722fc0afe894a7a192e2d665 | [
"audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)\nif audit['submitted'] == True:\n abort(400, 'Already submitted')\nif audit['approved'] == True:\n abort(400, 'Already approved by administrator(s)')\nschema = AuditUpdateSchema(only=['submitted', 'rejected_reason'])\... | <|body_start_0|>
audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)
if audit['submitted'] == True:
abort(400, 'Already submitted')
if audit['approved'] == True:
abort(400, 'Already approved by administrator(s)')
schema = Au... | AuditSubmission | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
<|body_0|>
def delete(self, audit_uuid):
"""Withdraw the submission of the specified audit result"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
audit = AuditResou... | stack_v2_sparse_classes_10k_train_005521 | 18,857 | no_license | [
{
"docstring": "Submit the specified audit result",
"name": "post",
"signature": "def post(self, audit_uuid)"
},
{
"docstring": "Withdraw the submission of the specified audit result",
"name": "delete",
"signature": "def delete(self, audit_uuid)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001707 | Implement the Python class `AuditSubmission` described below.
Class description:
Implement the AuditSubmission class.
Method signatures and docstrings:
- def post(self, audit_uuid): Submit the specified audit result
- def delete(self, audit_uuid): Withdraw the submission of the specified audit result | Implement the Python class `AuditSubmission` described below.
Class description:
Implement the AuditSubmission class.
Method signatures and docstrings:
- def post(self, audit_uuid): Submit the specified audit result
- def delete(self, audit_uuid): Withdraw the submission of the specified audit result
<|skeleton|>
cl... | 7b67aa682d73c8a8d7f0f19b2a90e69c40761c58 | <|skeleton|>
class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
<|body_0|>
def delete(self, audit_uuid):
"""Withdraw the submission of the specified audit result"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AuditSubmission:
def post(self, audit_uuid):
"""Submit the specified audit result"""
audit = AuditResource.get_by_id(audit_uuid=audit_uuid, withContacts=False, withScans=False)
if audit['submitted'] == True:
abort(400, 'Already submitted')
if audit['approved'] == Tr... | the_stack_v2_python_sparse | rem/apis/audit.py | recruit-tech/casval | train | 6 | |
c1c03a353afa75881332d04cfbc335811935317c | [
"flowerbed = [1, 0] + flowerbed + [0, 1]\ncur = 0\nresult = 0\nfor flower in flowerbed:\n if flower == 0:\n cur += 1\n else:\n result += int((cur - 1) / 2)\n cur = 0\nreturn result >= n",
"s = ('10' + ''.join([str(x) for x in flowerbed]) + '01').split('1')\nprint(s)\nresult = 0\nfor x i... | <|body_start_0|>
flowerbed = [1, 0] + flowerbed + [0, 1]
cur = 0
result = 0
for flower in flowerbed:
if flower == 0:
cur += 1
else:
result += int((cur - 1) / 2)
cur = 0
return result >= n
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_0|>
def canPlaceFlowers1(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_10k_train_005522 | 1,040 | no_license | [
{
"docstring": ":type flowerbed: List[int] :type n: int :rtype: bool",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(self, flowerbed, n)"
},
{
"docstring": ":type flowerbed: List[int] :type n: int :rtype: bool",
"name": "canPlaceFlowers1",
"signature": "def canPlaceFlowers... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :rtype: bool
- def canPlaceFlowers1(self, flowerbed, n): :type flowerbed: List[int] :type n: int ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :rtype: bool
- def canPlaceFlowers1(self, flowerbed, n): :type flowerbed: List[int] :type n: int ... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_0|>
def canPlaceFlowers1(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
flowerbed = [1, 0] + flowerbed + [0, 1]
cur = 0
result = 0
for flower in flowerbed:
if flower == 0:
cur += 1
else:
... | the_stack_v2_python_sparse | python/leetcode/605_Can_Place_Flowers.py | bobcaoge/my-code | train | 0 | |
60fe26ac79915b57231af5608d6ae7a7ad047c37 | [
"if not hasattr(cls, _mangle(cls, 'instance')):\n setattr(cls, _mangle(cls, 'instance'), super().__new__(cls))\n setattr(cls, _mangle(cls, 'initialized'), False)\nreturn getattr(cls, _mangle(cls, 'instance'))",
"if cls.__init__ != object.__init__:\n old_init = cls.__init__\n\n def new_init(self, *args... | <|body_start_0|>
if not hasattr(cls, _mangle(cls, 'instance')):
setattr(cls, _mangle(cls, 'instance'), super().__new__(cls))
setattr(cls, _mangle(cls, 'initialized'), False)
return getattr(cls, _mangle(cls, 'instance'))
<|end_body_0|>
<|body_start_1|>
if cls.__init__ != ... | Class that is only constructed and initialized once, then future constructions return the already constructed class. When used in a class hierarchy, all children of a singleton can call their parent's constructors exactly once | Singleton | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Singleton:
"""Class that is only constructed and initialized once, then future constructions return the already constructed class. When used in a class hierarchy, all children of a singleton can call their parent's constructors exactly once"""
def __new__(cls, *args, **kwargs):
"""Co... | stack_v2_sparse_classes_10k_train_005523 | 9,712 | permissive | [
{
"docstring": "Construct a new Singleton. Checks for an instance, if one doesn't exist, creates one :param args: Ignored :param kwargs: Ignored :return: New or existing instance",
"name": "__new__",
"signature": "def __new__(cls, *args, **kwargs)"
},
{
"docstring": "Prepare a subclass to only h... | 2 | stack_v2_sparse_classes_30k_train_004269 | Implement the Python class `Singleton` described below.
Class description:
Class that is only constructed and initialized once, then future constructions return the already constructed class. When used in a class hierarchy, all children of a singleton can call their parent's constructors exactly once
Method signature... | Implement the Python class `Singleton` described below.
Class description:
Class that is only constructed and initialized once, then future constructions return the already constructed class. When used in a class hierarchy, all children of a singleton can call their parent's constructors exactly once
Method signature... | 4bf155feec7cb983e8d283d93552902ec85178a2 | <|skeleton|>
class Singleton:
"""Class that is only constructed and initialized once, then future constructions return the already constructed class. When used in a class hierarchy, all children of a singleton can call their parent's constructors exactly once"""
def __new__(cls, *args, **kwargs):
"""Co... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Singleton:
"""Class that is only constructed and initialized once, then future constructions return the already constructed class. When used in a class hierarchy, all children of a singleton can call their parent's constructors exactly once"""
def __new__(cls, *args, **kwargs):
"""Construct a new... | the_stack_v2_python_sparse | spidertools/common/clstools.py | CraftSpider/SpiderTools | train | 6 |
7b9c906d6cd3f83f63e95ab467f7d7f9b6f76781 | [
"global dev_plan_list_page, admin_page\ndev_plan_list_page = DevPlanListPage(self.driver)\nadmin_page = AdminPage(self.driver)\nadmin_page.into_subsystem('业务管理')\nadmin_page.select_menu('首页/渠道业务管理/年度发展计划')",
"admin_page.select_menu('计划列表')\ndev_plan_list_page.query_by_year(_year='2020')\nassert '2020' in dev_plan... | <|body_start_0|>
global dev_plan_list_page, admin_page
dev_plan_list_page = DevPlanListPage(self.driver)
admin_page = AdminPage(self.driver)
admin_page.into_subsystem('业务管理')
admin_page.select_menu('首页/渠道业务管理/年度发展计划')
<|end_body_0|>
<|body_start_1|>
admin_page.select_men... | TestDevPlanList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDevPlanList:
def set_up(self):
"""前置操作 :return:"""
<|body_0|>
def test_query_dev_plan(self, set_up):
"""年度计划查询 :return:"""
<|body_1|>
def test_reset_dev_plan_query(self):
"""重置年度计划查询 :return:"""
<|body_2|>
def test_click_create_d... | stack_v2_sparse_classes_10k_train_005524 | 2,658 | no_license | [
{
"docstring": "前置操作 :return:",
"name": "set_up",
"signature": "def set_up(self)"
},
{
"docstring": "年度计划查询 :return:",
"name": "test_query_dev_plan",
"signature": "def test_query_dev_plan(self, set_up)"
},
{
"docstring": "重置年度计划查询 :return:",
"name": "test_reset_dev_plan_query... | 6 | stack_v2_sparse_classes_30k_train_000769 | Implement the Python class `TestDevPlanList` described below.
Class description:
Implement the TestDevPlanList class.
Method signatures and docstrings:
- def set_up(self): 前置操作 :return:
- def test_query_dev_plan(self, set_up): 年度计划查询 :return:
- def test_reset_dev_plan_query(self): 重置年度计划查询 :return:
- def test_click_c... | Implement the Python class `TestDevPlanList` described below.
Class description:
Implement the TestDevPlanList class.
Method signatures and docstrings:
- def set_up(self): 前置操作 :return:
- def test_query_dev_plan(self, set_up): 年度计划查询 :return:
- def test_reset_dev_plan_query(self): 重置年度计划查询 :return:
- def test_click_c... | 86d1b085af2d3808ac8472d541f4bf26d26591e0 | <|skeleton|>
class TestDevPlanList:
def set_up(self):
"""前置操作 :return:"""
<|body_0|>
def test_query_dev_plan(self, set_up):
"""年度计划查询 :return:"""
<|body_1|>
def test_reset_dev_plan_query(self):
"""重置年度计划查询 :return:"""
<|body_2|>
def test_click_create_d... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestDevPlanList:
def set_up(self):
"""前置操作 :return:"""
global dev_plan_list_page, admin_page
dev_plan_list_page = DevPlanListPage(self.driver)
admin_page = AdminPage(self.driver)
admin_page.into_subsystem('业务管理')
admin_page.select_menu('首页/渠道业务管理/年度发展计划')
d... | the_stack_v2_python_sparse | src/cases/business_manage/channel_business_manage/developmentPlan/test_dev_plan_list_page_170.py | 102244653/SeleniumByPython | train | 2 | |
00aebdf3dfd86c7ea7580ca6118a1db55fb135ab | [
"self.y = np.empty(0)\nself.ts_period = ts_period\nself.timestamp_interval = -1\nself.last_timestamp = -1\nself._fitted = False\nself.copy = copy\nif self.ts_period is None:\n raise ValueError(\"'ts_period' must be given.\")",
"if X.size != y.size:\n raise ValueError(\"'X' and 'y' size must match.\")\nif se... | <|body_start_0|>
self.y = np.empty(0)
self.ts_period = ts_period
self.timestamp_interval = -1
self.last_timestamp = -1
self._fitted = False
self.copy = copy
if self.ts_period is None:
raise ValueError("'ts_period' must be given.")
<|end_body_0|>
<|bod... | Seasonal Naive model for time-series forecasting. This model is similar to the Naive model, but instead of using only the very last observation from the fitted time-series, it is used the whole past period. Then, each prediction is equal to the value in the corresponding timestamp of the previous period. | TSNaiveSeasonal | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TSNaiveSeasonal:
"""Seasonal Naive model for time-series forecasting. This model is similar to the Naive model, but instead of using only the very last observation from the fitted time-series, it is used the whole past period. Then, each prediction is equal to the value in the corresponding times... | stack_v2_sparse_classes_10k_train_005525 | 12,299 | permissive | [
{
"docstring": "Init a Seasonal Naive Model.",
"name": "__init__",
"signature": "def __init__(self, ts_period: int, copy: bool=False)"
},
{
"docstring": "Fit a Seasonal Naive model.",
"name": "fit",
"signature": "def fit(self, X: np.ndarray, y: np.ndarray, **kwargs) -> 'TSNaiveSeasonal'"... | 3 | stack_v2_sparse_classes_30k_train_003775 | Implement the Python class `TSNaiveSeasonal` described below.
Class description:
Seasonal Naive model for time-series forecasting. This model is similar to the Naive model, but instead of using only the very last observation from the fitted time-series, it is used the whole past period. Then, each prediction is equal ... | Implement the Python class `TSNaiveSeasonal` described below.
Class description:
Seasonal Naive model for time-series forecasting. This model is similar to the Naive model, but instead of using only the very last observation from the fitted time-series, it is used the whole past period. Then, each prediction is equal ... | 61cc1f63fa055c7466151cfefa7baff8df1702b7 | <|skeleton|>
class TSNaiveSeasonal:
"""Seasonal Naive model for time-series forecasting. This model is similar to the Naive model, but instead of using only the very last observation from the fitted time-series, it is used the whole past period. Then, each prediction is equal to the value in the corresponding times... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TSNaiveSeasonal:
"""Seasonal Naive model for time-series forecasting. This model is similar to the Naive model, but instead of using only the very last observation from the fitted time-series, it is used the whole past period. Then, each prediction is equal to the value in the corresponding timestamp of the p... | the_stack_v2_python_sparse | tspymfe/_models.py | FelSiq/ts-pymfe | train | 9 |
15840d207be8cfbe0239573bf8d5694867192449 | [
"if strs == []:\n return '-.'\nreturn '+&*+'.join(strs)",
"if s == '-.':\n return []\nreturn s.split('+&*+')"
] | <|body_start_0|>
if strs == []:
return '-.'
return '+&*+'.join(strs)
<|end_body_0|>
<|body_start_1|>
if s == '-.':
return []
return s.split('+&*+')
<|end_body_1|>
| Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k_train_005526 | 722 | no_license | [
{
"docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str",
"name": "encode",
"signature": "def encode(self, strs)"
},
{
"docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]",
"name": "decode",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_val_000161 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | 30bfafb6a7727c9305b22933b63d9d645182c633 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
if strs == []:
return '-.'
return '+&*+'.join(strs)
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: L... | the_stack_v2_python_sparse | leetcode/String/encode-and-decode-strings.py | iCodeIN/competitive-programming-5 | train | 0 | |
e0adfb50c1bd69ef89412b53925f436a7192be76 | [
"if intervals == None or len(intervals) == 0:\n return [newInterval]\nres = []\ni = 0\nwhile i < len(intervals):\n if intervals[i].end < newInterval.start:\n res.append(intervals[i])\n i += 1\n continue\n if intervals[i].start > newInterval.end:\n res.append(newInterval)\n ... | <|body_start_0|>
if intervals == None or len(intervals) == 0:
return [newInterval]
res = []
i = 0
while i < len(intervals):
if intervals[i].end < newInterval.start:
res.append(intervals[i])
i += 1
continue
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def insert_before(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
<|body_0|>
def insert(self, intervals, newInterval):
""":type intervals: List[List[int]] :type newInterval: List[int] :... | stack_v2_sparse_classes_10k_train_005527 | 2,021 | no_license | [
{
"docstring": ":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]",
"name": "insert_before",
"signature": "def insert_before(self, intervals, newInterval)"
},
{
"docstring": ":type intervals: List[List[int]] :type newInterval: List[int] :rtype: List[List[int]]",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insert_before(self, intervals, newInterval): :type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]
- def insert(self, intervals, newInterval): :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insert_before(self, intervals, newInterval): :type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]
- def insert(self, intervals, newInterval): :t... | 238995bd23c8a6c40c6035890e94baa2473d4bbc | <|skeleton|>
class Solution:
def insert_before(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
<|body_0|>
def insert(self, intervals, newInterval):
""":type intervals: List[List[int]] :type newInterval: List[int] :... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def insert_before(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
if intervals == None or len(intervals) == 0:
return [newInterval]
res = []
i = 0
while i < len(intervals):
... | the_stack_v2_python_sparse | problems/InsertInterval.py | wan-catherine/Leetcode | train | 5 | |
cbb8cd4e8e83e23e52ee1c5079569069ea4233df | [
"if not api.base.is_service_enabled(request, 'compute'):\n raise rest_utils.AjaxError(501, _('Service Nova is disabled.'))\nquota_set = api.nova.default_quota_get(request, request.user.tenant_id)\ndisabled_quotas = quotas.get_disabled_quotas(request)\nfiltered_quotas = [quota for quota in quota_set if quota.name... | <|body_start_0|>
if not api.base.is_service_enabled(request, 'compute'):
raise rest_utils.AjaxError(501, _('Service Nova is disabled.'))
quota_set = api.nova.default_quota_get(request, request.user.tenant_id)
disabled_quotas = quotas.get_disabled_quotas(request)
filtered_quot... | API for getting default quotas for nova | DefaultQuotaSets | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DefaultQuotaSets:
"""API for getting default quotas for nova"""
def get(self, request):
"""Get the values for Nova specific quotas Example GET: http://localhost/api/nova/quota-sets/defaults/"""
<|body_0|>
def patch(self, request):
"""Update the values for Nova sp... | stack_v2_sparse_classes_10k_train_005528 | 28,240 | permissive | [
{
"docstring": "Get the values for Nova specific quotas Example GET: http://localhost/api/nova/quota-sets/defaults/",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "Update the values for Nova specific quotas This method returns HTTP 204 (no content) on success.",
"na... | 2 | null | Implement the Python class `DefaultQuotaSets` described below.
Class description:
API for getting default quotas for nova
Method signatures and docstrings:
- def get(self, request): Get the values for Nova specific quotas Example GET: http://localhost/api/nova/quota-sets/defaults/
- def patch(self, request): Update t... | Implement the Python class `DefaultQuotaSets` described below.
Class description:
API for getting default quotas for nova
Method signatures and docstrings:
- def get(self, request): Get the values for Nova specific quotas Example GET: http://localhost/api/nova/quota-sets/defaults/
- def patch(self, request): Update t... | 7896fd8c77a6766a1156a520946efaf792b76ca5 | <|skeleton|>
class DefaultQuotaSets:
"""API for getting default quotas for nova"""
def get(self, request):
"""Get the values for Nova specific quotas Example GET: http://localhost/api/nova/quota-sets/defaults/"""
<|body_0|>
def patch(self, request):
"""Update the values for Nova sp... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DefaultQuotaSets:
"""API for getting default quotas for nova"""
def get(self, request):
"""Get the values for Nova specific quotas Example GET: http://localhost/api/nova/quota-sets/defaults/"""
if not api.base.is_service_enabled(request, 'compute'):
raise rest_utils.AjaxError(... | the_stack_v2_python_sparse | openstack_dashboard/api/rest/nova.py | openstack/horizon | train | 1,060 |
39c40f6306e92855a045c0841c63d574ffe680c0 | [
"binning = '1,1' if hdu is None else self.get_meta_value(self.get_headarr(hdu), 'binning')\ndetector_dict = dict(binning=binning, det=1, dataext=1, specaxis=0, specflip=False, spatflip=False, platescale=0.2, darkcurr=0.0, saturation=65535.0, nonlinear=0.76, mincounts=-10000000000.0, numamplifiers=1, gain=np.atleast... | <|body_start_0|>
binning = '1,1' if hdu is None else self.get_meta_value(self.get_headarr(hdu), 'binning')
detector_dict = dict(binning=binning, det=1, dataext=1, specaxis=0, specflip=False, spatflip=False, platescale=0.2, darkcurr=0.0, saturation=65535.0, nonlinear=0.76, mincounts=-10000000000.0, numam... | Child to handle WHT/ISIS blue specific code | WHTISISBlueSpectrograph | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WHTISISBlueSpectrograph:
"""Child to handle WHT/ISIS blue specific code"""
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with t... | stack_v2_sparse_classes_10k_train_005529 | 16,230 | permissive | [
{
"docstring": "Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with the raw image of interest. If not provided, frame-dependent parameters are set to a default. Returns: :class:`~pypeit.images.detector_... | 4 | stack_v2_sparse_classes_30k_train_003628 | Implement the Python class `WHTISISBlueSpectrograph` described below.
Class description:
Child to handle WHT/ISIS blue specific code
Method signatures and docstrings:
- def get_detector_par(self, det, hdu=None): Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astrop... | Implement the Python class `WHTISISBlueSpectrograph` described below.
Class description:
Child to handle WHT/ISIS blue specific code
Method signatures and docstrings:
- def get_detector_par(self, det, hdu=None): Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astrop... | 0d2e2196afc6904050b1af4d572f5c643bb07e38 | <|skeleton|>
class WHTISISBlueSpectrograph:
"""Child to handle WHT/ISIS blue specific code"""
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class WHTISISBlueSpectrograph:
"""Child to handle WHT/ISIS blue specific code"""
def get_detector_par(self, det, hdu=None):
"""Return metadata for the selected detector. Args: det (:obj:`int`): 1-indexed detector number. hdu (`astropy.io.fits.HDUList`_, optional): The open fits file with the raw image ... | the_stack_v2_python_sparse | pypeit/spectrographs/wht_isis.py | pypeit/PypeIt | train | 136 |
a02aae8b0ad9829c94253ecbd7d633c80ff9b73a | [
"super().__init__(config)\nself.in_proj_weight = nn.Parameter(torch.cat([mbart_layer.self_attn.q_proj.weight, mbart_layer.self_attn.k_proj.weight, mbart_layer.self_attn.v_proj.weight]))\nself.in_proj_bias = nn.Parameter(torch.cat([mbart_layer.self_attn.q_proj.bias, mbart_layer.self_attn.k_proj.bias, mbart_layer.sel... | <|body_start_0|>
super().__init__(config)
self.in_proj_weight = nn.Parameter(torch.cat([mbart_layer.self_attn.q_proj.weight, mbart_layer.self_attn.k_proj.weight, mbart_layer.self_attn.v_proj.weight]))
self.in_proj_bias = nn.Parameter(torch.cat([mbart_layer.self_attn.q_proj.bias, mbart_layer.self... | MBartEncoderLayerBetterTransformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MBartEncoderLayerBetterTransformer:
def __init__(self, mbart_layer, config):
"""A simple conversion of the `MBartEncoderLayer` to its `BetterTransformer` implementation. Args: mbart_layer (`torch.nn.Module`): The original `MBartEncoderLayer` where the weights needs to be retrieved."""
... | stack_v2_sparse_classes_10k_train_005530 | 43,670 | no_license | [
{
"docstring": "A simple conversion of the `MBartEncoderLayer` to its `BetterTransformer` implementation. Args: mbart_layer (`torch.nn.Module`): The original `MBartEncoderLayer` where the weights needs to be retrieved.",
"name": "__init__",
"signature": "def __init__(self, mbart_layer, config)"
},
{... | 2 | stack_v2_sparse_classes_30k_train_006983 | Implement the Python class `MBartEncoderLayerBetterTransformer` described below.
Class description:
Implement the MBartEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, mbart_layer, config): A simple conversion of the `MBartEncoderLayer` to its `BetterTransformer` implementat... | Implement the Python class `MBartEncoderLayerBetterTransformer` described below.
Class description:
Implement the MBartEncoderLayerBetterTransformer class.
Method signatures and docstrings:
- def __init__(self, mbart_layer, config): A simple conversion of the `MBartEncoderLayer` to its `BetterTransformer` implementat... | 7e55a422588c1d1e00f35a3d3a3ff896cce59e18 | <|skeleton|>
class MBartEncoderLayerBetterTransformer:
def __init__(self, mbart_layer, config):
"""A simple conversion of the `MBartEncoderLayer` to its `BetterTransformer` implementation. Args: mbart_layer (`torch.nn.Module`): The original `MBartEncoderLayer` where the weights needs to be retrieved."""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MBartEncoderLayerBetterTransformer:
def __init__(self, mbart_layer, config):
"""A simple conversion of the `MBartEncoderLayer` to its `BetterTransformer` implementation. Args: mbart_layer (`torch.nn.Module`): The original `MBartEncoderLayer` where the weights needs to be retrieved."""
super().... | the_stack_v2_python_sparse | generated/test_huggingface_optimum.py | jansel/pytorch-jit-paritybench | train | 35 | |
8088bc5b2311607af3c9946eb29481f6881a7730 | [
"if instance is None:\n raise ValueError('Class instance binding must be non-empty')\nself._instance = instance",
"inst = self._instance\nif isinstance(inst, ReferenceType):\n inst = inst()\n if inst is None:\n raise InjectionError('Weakref instance expired')\nreturn inst"
] | <|body_start_0|>
if instance is None:
raise ValueError('Class instance binding must be non-empty')
self._instance = instance
<|end_body_0|>
<|body_start_1|>
inst = self._instance
if isinstance(inst, ReferenceType):
inst = inst()
if inst is None:
... | Provider for a previously-created instance. | InstanceProvider | [
"LicenseRef-scancode-dco-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InstanceProvider:
"""Provider for a previously-created instance."""
def __init__(self, instance):
"""Initialize the instance provider."""
<|body_0|>
def provide(self, config: BaseSettings, injector: BaseInjector):
"""Provide the object instance given a config and... | stack_v2_sparse_classes_10k_train_005531 | 4,857 | permissive | [
{
"docstring": "Initialize the instance provider.",
"name": "__init__",
"signature": "def __init__(self, instance)"
},
{
"docstring": "Provide the object instance given a config and injector.",
"name": "provide",
"signature": "def provide(self, config: BaseSettings, injector: BaseInjecto... | 2 | null | Implement the Python class `InstanceProvider` described below.
Class description:
Provider for a previously-created instance.
Method signatures and docstrings:
- def __init__(self, instance): Initialize the instance provider.
- def provide(self, config: BaseSettings, injector: BaseInjector): Provide the object instan... | Implement the Python class `InstanceProvider` described below.
Class description:
Provider for a previously-created instance.
Method signatures and docstrings:
- def __init__(self, instance): Initialize the instance provider.
- def provide(self, config: BaseSettings, injector: BaseInjector): Provide the object instan... | 39cac36d8937ce84a9307ce100aaefb8bc05ec04 | <|skeleton|>
class InstanceProvider:
"""Provider for a previously-created instance."""
def __init__(self, instance):
"""Initialize the instance provider."""
<|body_0|>
def provide(self, config: BaseSettings, injector: BaseInjector):
"""Provide the object instance given a config and... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class InstanceProvider:
"""Provider for a previously-created instance."""
def __init__(self, instance):
"""Initialize the instance provider."""
if instance is None:
raise ValueError('Class instance binding must be non-empty')
self._instance = instance
def provide(self, ... | the_stack_v2_python_sparse | aries_cloudagent/config/provider.py | hyperledger/aries-cloudagent-python | train | 370 |
385e6c0fd733bb2146de322917e44fc635480985 | [
"manager = self.request.registry.queryMultiAdapter((self.request, self.context), IManager)\nrepresentation_manager = manager.get_representation_manager()\ndocument_type = type(manager.context).documents.model_class\nreturn representation_manager.represent_listing(implementedBy(document_type))",
"manager = self.re... | <|body_start_0|>
manager = self.request.registry.queryMultiAdapter((self.request, self.context), IManager)
representation_manager = manager.get_representation_manager()
document_type = type(manager.context).documents.model_class
return representation_manager.represent_listing(implemented... | AuctionCancellationDocumentResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuctionCancellationDocumentResource:
def collection_get(self):
"""Auction Cancellation Documents List"""
<|body_0|>
def collection_post(self):
"""Auction Cancellation Document Post"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
manager = self.reque... | stack_v2_sparse_classes_10k_train_005532 | 2,068 | permissive | [
{
"docstring": "Auction Cancellation Documents List",
"name": "collection_get",
"signature": "def collection_get(self)"
},
{
"docstring": "Auction Cancellation Document Post",
"name": "collection_post",
"signature": "def collection_post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000999 | Implement the Python class `AuctionCancellationDocumentResource` described below.
Class description:
Implement the AuctionCancellationDocumentResource class.
Method signatures and docstrings:
- def collection_get(self): Auction Cancellation Documents List
- def collection_post(self): Auction Cancellation Document Pos... | Implement the Python class `AuctionCancellationDocumentResource` described below.
Class description:
Implement the AuctionCancellationDocumentResource class.
Method signatures and docstrings:
- def collection_get(self): Auction Cancellation Documents List
- def collection_post(self): Auction Cancellation Document Pos... | 05c9ea3db1b1d290521b1430286ff2e5064819cd | <|skeleton|>
class AuctionCancellationDocumentResource:
def collection_get(self):
"""Auction Cancellation Documents List"""
<|body_0|>
def collection_post(self):
"""Auction Cancellation Document Post"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AuctionCancellationDocumentResource:
def collection_get(self):
"""Auction Cancellation Documents List"""
manager = self.request.registry.queryMultiAdapter((self.request, self.context), IManager)
representation_manager = manager.get_representation_manager()
document_type = type(... | the_stack_v2_python_sparse | openprocurement/auctions/geb/views/cancellation_document.py | andrey484/openprocurement.auctions.geb | train | 0 | |
b9590dc6d5cbe2c1720c51260df40e6f771b61e9 | [
"if root is None:\n return True\nnode_bounds_stack = [(root, -float('inf'), float('inf'))]\nwhile len(node_bounds_stack):\n node, lb, ub = node_bounds_stack.pop()\n if node.val <= lb or node.val >= ub:\n return False\n if node.left:\n node_bounds_stack.append((node.left, lb, node.val))\n ... | <|body_start_0|>
if root is None:
return True
node_bounds_stack = [(root, -float('inf'), float('inf'))]
while len(node_bounds_stack):
node, lb, ub = node_bounds_stack.pop()
if node.val <= lb or node.val >= ub:
return False
if node.l... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidBST1(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isValidBST(self, root, lb=-float('inf'), ub=float('inf')):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if root is ... | stack_v2_sparse_classes_10k_train_005533 | 2,250 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isValidBST1",
"signature": "def isValidBST1(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: bool",
"name": "isValidBST",
"signature": "def isValidBST(self, root, lb=-float('inf'), ub=float('inf'))"
}
] | 2 | stack_v2_sparse_classes_30k_train_000103 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST1(self, root): :type root: TreeNode :rtype: bool
- def isValidBST(self, root, lb=-float('inf'), ub=float('inf')): :type root: TreeNode :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST1(self, root): :type root: TreeNode :rtype: bool
- def isValidBST(self, root, lb=-float('inf'), ub=float('inf')): :type root: TreeNode :rtype: bool
<|skeleton|>
cl... | d181f2075c6c3881772dfbf54df3ac3390936079 | <|skeleton|>
class Solution:
def isValidBST1(self, root):
""":type root: TreeNode :rtype: bool"""
<|body_0|>
def isValidBST(self, root, lb=-float('inf'), ub=float('inf')):
""":type root: TreeNode :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidBST1(self, root):
""":type root: TreeNode :rtype: bool"""
if root is None:
return True
node_bounds_stack = [(root, -float('inf'), float('inf'))]
while len(node_bounds_stack):
node, lb, ub = node_bounds_stack.pop()
if node... | the_stack_v2_python_sparse | 98. Validate Binary Search Tree.py | melekoktay/Leetcode-Practice | train | 0 | |
783e9b570e018918288117da37259f3e7e2b6e5c | [
"self.update_norm_coordinates((config.SCREEN_WIDTH, config.SCREEN_HEIGHT))\nvh = view_hierarchy.ViewHierarchy()\nvh.load_xml(screen_info.view_hierarchy.xml.encode('utf-8'))\nif dedup:\n vh.dedup((self.coordinates_x_pixel[0], self.coordinates_y_pixel[0]))\nself.leaf_nodes = vh.get_leaf_nodes()\nui_object_list = v... | <|body_start_0|>
self.update_norm_coordinates((config.SCREEN_WIDTH, config.SCREEN_HEIGHT))
vh = view_hierarchy.ViewHierarchy()
vh.load_xml(screen_info.view_hierarchy.xml.encode('utf-8'))
if dedup:
vh.dedup((self.coordinates_x_pixel[0], self.coordinates_y_pixel[0]))
se... | This class defines ActionEvent class. ActionEvent is high level event summarized from low level android event logs. This example shows the android event logs and the extracted ActionEvent object: Android Event Logs: [ 42.407808] EV_ABS ABS_MT_TRACKING_ID 00000000 [ 42.407808] EV_ABS ABS_MT_TOUCH_MAJOR 00000004 [ 42.407... | ActionEvent | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionEvent:
"""This class defines ActionEvent class. ActionEvent is high level event summarized from low level android event logs. This example shows the android event logs and the extracted ActionEvent object: Android Event Logs: [ 42.407808] EV_ABS ABS_MT_TRACKING_ID 00000000 [ 42.407808] EV_A... | stack_v2_sparse_classes_10k_train_005534 | 14,083 | permissive | [
{
"docstring": "Updates action event attributes from screen_info. Updates coordinates_x(y)_pixel and object_id from the screen_info proto. Args: screen_info: ScreenInfo protobuf dedup: whether dedup the UI objs with same text or content desc. Raises: ValueError when fail to find object id.",
"name": "update... | 3 | null | Implement the Python class `ActionEvent` described below.
Class description:
This class defines ActionEvent class. ActionEvent is high level event summarized from low level android event logs. This example shows the android event logs and the extracted ActionEvent object: Android Event Logs: [ 42.407808] EV_ABS ABS_MT... | Implement the Python class `ActionEvent` described below.
Class description:
This class defines ActionEvent class. ActionEvent is high level event summarized from low level android event logs. This example shows the android event logs and the extracted ActionEvent object: Android Event Logs: [ 42.407808] EV_ABS ABS_MT... | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | <|skeleton|>
class ActionEvent:
"""This class defines ActionEvent class. ActionEvent is high level event summarized from low level android event logs. This example shows the android event logs and the extracted ActionEvent object: Android Event Logs: [ 42.407808] EV_ABS ABS_MT_TRACKING_ID 00000000 [ 42.407808] EV_A... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ActionEvent:
"""This class defines ActionEvent class. ActionEvent is high level event summarized from low level android event logs. This example shows the android event logs and the extracted ActionEvent object: Android Event Logs: [ 42.407808] EV_ABS ABS_MT_TRACKING_ID 00000000 [ 42.407808] EV_ABS ABS_MT_TOU... | the_stack_v2_python_sparse | seq2act/data_generation/common.py | Ayoob7/google-research | train | 2 |
aff02d4421deb6518184ae189d1198bf8ce7bf12 | [
"result = bfs.setup()\nvertices = result[0]\nnode_edges = result[1]\nself.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')\nexpected = [149, 155, 52, 87, 120, 39, 160, 137, 27, 79, 131, 100, 25, 55, 23, 126, 84, 166, 150, 62, 67, 1, 69, 35]\nself.assertEqual(node_edges[200], expected)... | <|body_start_0|>
result = bfs.setup()
vertices = result[0]
node_edges = result[1]
self.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')
expected = [149, 155, 52, 87, 120, 39, 160, 137, 27, 79, 131, 100, 25, 55, 23, 126, 84, 166, 150, 62, 67, 1, 69, ... | TestBFS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBFS:
def test_setup(self):
"""Test to ensure lists are set up correctly for the problem."""
<|body_0|>
def test_breadth_first_search(self):
"""Tests the three possible outcomes of a breadth first search: 1) A path exists between two seperate nodes. 2) A node is a... | stack_v2_sparse_classes_10k_train_005535 | 3,240 | permissive | [
{
"docstring": "Test to ensure lists are set up correctly for the problem.",
"name": "test_setup",
"signature": "def test_setup(self)"
},
{
"docstring": "Tests the three possible outcomes of a breadth first search: 1) A path exists between two seperate nodes. 2) A node is a path unto itself, dis... | 3 | stack_v2_sparse_classes_30k_train_002048 | Implement the Python class `TestBFS` described below.
Class description:
Implement the TestBFS class.
Method signatures and docstrings:
- def test_setup(self): Test to ensure lists are set up correctly for the problem.
- def test_breadth_first_search(self): Tests the three possible outcomes of a breadth first search:... | Implement the Python class `TestBFS` described below.
Class description:
Implement the TestBFS class.
Method signatures and docstrings:
- def test_setup(self): Test to ensure lists are set up correctly for the problem.
- def test_breadth_first_search(self): Tests the three possible outcomes of a breadth first search:... | 82605a1dea4e52480f006956645e812fe2cb02dc | <|skeleton|>
class TestBFS:
def test_setup(self):
"""Test to ensure lists are set up correctly for the problem."""
<|body_0|>
def test_breadth_first_search(self):
"""Tests the three possible outcomes of a breadth first search: 1) A path exists between two seperate nodes. 2) A node is a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestBFS:
def test_setup(self):
"""Test to ensure lists are set up correctly for the problem."""
result = bfs.setup()
vertices = result[0]
node_edges = result[1]
self.assertEqual(vertices[-1], 200, 'The vertices list has not imported correctly.')
expected = [149,... | the_stack_v2_python_sparse | Stanford/08_GraphSearch/BreadthFirstSearch/test_breadth_first_search.py | jeffvswanson/DataStructuresAndAlgorithms | train | 4 | |
3f214bf7e19242bdc070d885246f61f3d9edfc95 | [
"result = []\nnums.sort()\n\ndef backtrack(tmpList, idx):\n newList = [item for item in tmpList]\n result.add(newList)\n for i in range(idx, len(nums)):\n tmpList.append(nums[i])\n backtrack(tmpList, i + 1)\n _ = tmpList.pop()\nbacktrack([], 0)\nreturn result",
"result = [[]]\nfor it... | <|body_start_0|>
result = []
nums.sort()
def backtrack(tmpList, idx):
newList = [item for item in tmpList]
result.add(newList)
for i in range(idx, len(nums)):
tmpList.append(nums[i])
backtrack(tmpList, i + 1)
_ ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def solve2(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = []
nums.sort(... | stack_v2_sparse_classes_10k_train_005536 | 1,225 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "subsets",
"signature": "def subsets(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "solve2",
"signature": "def solve2(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001574 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def solve2(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def solve2(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class Solution:
... | a5cb862f0c5a3cfd21468141800568c2dedded0a | <|skeleton|>
class Solution:
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def solve2(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def subsets(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
result = []
nums.sort()
def backtrack(tmpList, idx):
newList = [item for item in tmpList]
result.add(newList)
for i in range(idx, len(nums)):
... | the_stack_v2_python_sparse | python/leetcode/combinatorial/subsets/78_subsets.py | Levintsky/topcoder | train | 0 | |
2e75f3f70ab13799d3b163d4f2873035a0de5839 | [
"clickndrag.Plane.__init__(self, name, rect, draggable=False, grab=False)\nself.background_color = self.cached_color = self.current_color = BACKGROUND_COLOR\nif background_color is not None:\n self.background_color = self.cached_color = self.current_color = background_color\nif text is not None:\n self.text =... | <|body_start_0|>
clickndrag.Plane.__init__(self, name, rect, draggable=False, grab=False)
self.background_color = self.cached_color = self.current_color = BACKGROUND_COLOR
if background_color is not None:
self.background_color = self.cached_color = self.current_color = background_col... | A clickndrag.Plane which displays a text. Additional attributes: Label.text The text to be written on the Label Label.cached_text Cache to catch changes Label.background_color The original background color for this Label Label.current_color The current background color Label.cached_color A cache for color changes | Label | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Label:
"""A clickndrag.Plane which displays a text. Additional attributes: Label.text The text to be written on the Label Label.cached_text Cache to catch changes Label.background_color The original background color for this Label Label.current_color The current background color Label.cached_colo... | stack_v2_sparse_classes_10k_train_005537 | 27,668 | permissive | [
{
"docstring": "Initialise the Label. text is the text to be written on the Label. If text is None, it is replaced by an empty string.",
"name": "__init__",
"signature": "def __init__(self, name, text, rect, background_color=None)"
},
{
"docstring": "Renew the text on the label, then call the ba... | 3 | stack_v2_sparse_classes_30k_train_001487 | Implement the Python class `Label` described below.
Class description:
A clickndrag.Plane which displays a text. Additional attributes: Label.text The text to be written on the Label Label.cached_text Cache to catch changes Label.background_color The original background color for this Label Label.current_color The cur... | Implement the Python class `Label` described below.
Class description:
A clickndrag.Plane which displays a text. Additional attributes: Label.text The text to be written on the Label Label.cached_text Cache to catch changes Label.background_color The original background color for this Label Label.current_color The cur... | c2fc3d4e9beedb8487cfa4bfa13bdf55ec36af97 | <|skeleton|>
class Label:
"""A clickndrag.Plane which displays a text. Additional attributes: Label.text The text to be written on the Label Label.cached_text Cache to catch changes Label.background_color The original background color for this Label Label.current_color The current background color Label.cached_colo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Label:
"""A clickndrag.Plane which displays a text. Additional attributes: Label.text The text to be written on the Label Label.cached_text Cache to catch changes Label.background_color The original background color for this Label Label.current_color The current background color Label.cached_color A cache for... | the_stack_v2_python_sparse | reference_scripts/clickndrag-0.4.1/clickndrag/gui.py | stivosaurus/rpi-snippets | train | 1 |
63be88ee34c7a7c99cee6fb3528d4ecf9bfd7578 | [
"self._with_bkg_par = bool(with_bkg_par)\nself._t_start = float(t_start)\nself._exposure = float(exposure)\nself._seed = int(seed)\nself._simput = simput\nself._data_dir = data_dir\nself._ra_cen = ra_cen\nself._dec_cen = dec_cen",
"try:\n os.makedirs(self._data_dir)\nexcept OSError as e:\n print('already ex... | <|body_start_0|>
self._with_bkg_par = bool(with_bkg_par)
self._t_start = float(t_start)
self._exposure = float(exposure)
self._seed = int(seed)
self._simput = simput
self._data_dir = data_dir
self._ra_cen = ra_cen
self._dec_cen = dec_cen
<|end_body_0|>
<|... | SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up. | Simulator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Simulator:
"""SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up."""
def __init__(self, with_bkg_par, t_start, exposure, seed, simput, data_dir, ra_cen, dec_cen):
""":param with_bkg_p... | stack_v2_sparse_classes_10k_train_005538 | 5,418 | no_license | [
{
"docstring": ":param with_bkg_par: Simulate with particle background. :param t_start: Start time of simulation. Input units of [s] :param exposure: Length of time to simulate for after t_start :param seed: Seed for random number generator. :param simput: Simput file (ie. the sky model)",
"name": "__init__... | 5 | stack_v2_sparse_classes_30k_train_003851 | Implement the Python class `Simulator` described below.
Class description:
SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up.
Method signatures and docstrings:
- def __init__(self, with_bkg_par, t_start, exposure, se... | Implement the Python class `Simulator` described below.
Class description:
SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up.
Method signatures and docstrings:
- def __init__(self, with_bkg_par, t_start, exposure, se... | 2b8ac686b1d445a39fcd28dbe07ef467c0b14c7e | <|skeleton|>
class Simulator:
"""SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up."""
def __init__(self, with_bkg_par, t_start, exposure, seed, simput, data_dir, ra_cen, dec_cen):
""":param with_bkg_p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Simulator:
"""SIXTE simulator for eROSITA observations. 1. Compute GTI file for given simput 2. Simulate eROSITA observations of simput, using GTI to speed things up."""
def __init__(self, with_bkg_par, t_start, exposure, seed, simput, data_dir, ra_cen, dec_cen):
""":param with_bkg_par: Simulate ... | the_stack_v2_python_sparse | python/sixte/simulate_agn_only.py | HuiboZhou/mocks_high_fidelity | train | 0 |
354bf43e403d1e54cac76c21082af39a39f11656 | [
"super(ContainerSpec, cls)._ApplyFlags(config_values, flag_values)\nif flag_values['image'].present:\n config_values['image'] = flag_values.image\nif flag_values['static_container_image'].present:\n config_values['static_image'] = flag_values.static_container_image",
"result = super(ContainerSpec, cls)._Get... | <|body_start_0|>
super(ContainerSpec, cls)._ApplyFlags(config_values, flag_values)
if flag_values['image'].present:
config_values['image'] = flag_values.image
if flag_values['static_container_image'].present:
config_values['static_image'] = flag_values.static_container_im... | Class containing options for creating containers. | ContainerSpec | [
"Classpath-exception-2.0",
"BSD-3-Clause",
"AGPL-3.0-only",
"MIT",
"GPL-2.0-only",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContainerSpec:
"""Class containing options for creating containers."""
def _ApplyFlags(cls, config_values, flag_values):
"""Apply flag settings to the container spec."""
<|body_0|>
def _GetOptionDecoderConstructions(cls):
"""Gets decoder classes and constructor a... | stack_v2_sparse_classes_10k_train_005539 | 34,074 | permissive | [
{
"docstring": "Apply flag settings to the container spec.",
"name": "_ApplyFlags",
"signature": "def _ApplyFlags(cls, config_values, flag_values)"
},
{
"docstring": "Gets decoder classes and constructor args for each configurable option. Can be overridden by derived classes to add options or im... | 2 | stack_v2_sparse_classes_30k_train_004449 | Implement the Python class `ContainerSpec` described below.
Class description:
Class containing options for creating containers.
Method signatures and docstrings:
- def _ApplyFlags(cls, config_values, flag_values): Apply flag settings to the container spec.
- def _GetOptionDecoderConstructions(cls): Gets decoder clas... | Implement the Python class `ContainerSpec` described below.
Class description:
Class containing options for creating containers.
Method signatures and docstrings:
- def _ApplyFlags(cls, config_values, flag_values): Apply flag settings to the container spec.
- def _GetOptionDecoderConstructions(cls): Gets decoder clas... | d0699f32998898757b036704fba39e5471641f01 | <|skeleton|>
class ContainerSpec:
"""Class containing options for creating containers."""
def _ApplyFlags(cls, config_values, flag_values):
"""Apply flag settings to the container spec."""
<|body_0|>
def _GetOptionDecoderConstructions(cls):
"""Gets decoder classes and constructor a... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ContainerSpec:
"""Class containing options for creating containers."""
def _ApplyFlags(cls, config_values, flag_values):
"""Apply flag settings to the container spec."""
super(ContainerSpec, cls)._ApplyFlags(config_values, flag_values)
if flag_values['image'].present:
... | the_stack_v2_python_sparse | perfkitbenchmarker/container_service.py | GoogleCloudPlatform/PerfKitBenchmarker | train | 1,923 |
18d469840d0f33d2799d913dd1cad491db1d907a | [
"ret = []\nencoder = ': '\nfor string in strs:\n for char in string:\n if char == ':':\n ret.append('::')\n else:\n ret.append(char)\n ret.append(encoder)\nreturn ''.join(ret)",
"encoder = ': '\nret = []\ntemp = []\nindex = 0\nwhile index < len(s):\n if s[index] == ':'... | <|body_start_0|>
ret = []
encoder = ': '
for string in strs:
for char in string:
if char == ':':
ret.append('::')
else:
ret.append(char)
ret.append(encoder)
return ''.join(ret)
<|end_body_0|>
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = []
... | stack_v2_sparse_classes_10k_train_005540 | 1,233 | no_license | [
{
"docstring": "Encodes a list of strings to a single string.",
"name": "encode",
"signature": "def encode(self, strs: [str]) -> str"
},
{
"docstring": "Decodes a single string to a list of strings.",
"name": "decode",
"signature": "def decode(self, s: str) -> [str]"
}
] | 2 | stack_v2_sparse_classes_30k_train_005726 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs: [str]) -> str: Encodes a list of strings to a single string.
- def decode(self, s: str) -> [str]: Decodes a single string to a list of strings.
<|skeleton|>
cla... | fdb6bcb4c721e03e853890dd89122f2c4196a1ea | <|skeleton|>
class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
<|body_0|>
def decode(self, s: str) -> [str]:
"""Decodes a single string to a list of strings."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs: [str]) -> str:
"""Encodes a list of strings to a single string."""
ret = []
encoder = ': '
for string in strs:
for char in string:
if char == ':':
ret.append('::')
else:
... | the_stack_v2_python_sparse | python/string/encode_decode_string.py | XifeiNi/LeetCode-Traversal | train | 2 | |
c89969d2dc917bef875f0ea8d6aacb561278d585 | [
"self._msw = magicseaweed.MSW_Forecast(api_key, spot_id, None, units)\nself.currently = None\nself.hourly = {}\nself.update = Throttle(MIN_TIME_BETWEEN_UPDATES)(self._update)",
"try:\n forecasts = self._msw.get_future()\n self.currently = forecasts.data[0]\n for forecast in forecasts.data[:8]:\n h... | <|body_start_0|>
self._msw = magicseaweed.MSW_Forecast(api_key, spot_id, None, units)
self.currently = None
self.hourly = {}
self.update = Throttle(MIN_TIME_BETWEEN_UPDATES)(self._update)
<|end_body_0|>
<|body_start_1|>
try:
forecasts = self._msw.get_future()
... | Get the latest data from MagicSeaweed. | MagicSeaweedData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MagicSeaweedData:
"""Get the latest data from MagicSeaweed."""
def __init__(self, api_key, spot_id, units):
"""Initialize the data object."""
<|body_0|>
def _update(self):
"""Get the latest data from MagicSeaweed."""
<|body_1|>
<|end_skeleton|>
<|body_s... | stack_v2_sparse_classes_10k_train_005541 | 6,249 | permissive | [
{
"docstring": "Initialize the data object.",
"name": "__init__",
"signature": "def __init__(self, api_key, spot_id, units)"
},
{
"docstring": "Get the latest data from MagicSeaweed.",
"name": "_update",
"signature": "def _update(self)"
}
] | 2 | null | Implement the Python class `MagicSeaweedData` described below.
Class description:
Get the latest data from MagicSeaweed.
Method signatures and docstrings:
- def __init__(self, api_key, spot_id, units): Initialize the data object.
- def _update(self): Get the latest data from MagicSeaweed. | Implement the Python class `MagicSeaweedData` described below.
Class description:
Get the latest data from MagicSeaweed.
Method signatures and docstrings:
- def __init__(self, api_key, spot_id, units): Initialize the data object.
- def _update(self): Get the latest data from MagicSeaweed.
<|skeleton|>
class MagicSea... | 2fee32fce03bc49e86cf2e7b741a15621a97cce5 | <|skeleton|>
class MagicSeaweedData:
"""Get the latest data from MagicSeaweed."""
def __init__(self, api_key, spot_id, units):
"""Initialize the data object."""
<|body_0|>
def _update(self):
"""Get the latest data from MagicSeaweed."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MagicSeaweedData:
"""Get the latest data from MagicSeaweed."""
def __init__(self, api_key, spot_id, units):
"""Initialize the data object."""
self._msw = magicseaweed.MSW_Forecast(api_key, spot_id, None, units)
self.currently = None
self.hourly = {}
self.update = T... | the_stack_v2_python_sparse | homeassistant/components/magicseaweed/sensor.py | BenWoodford/home-assistant | train | 11 |
05ebf26c1a0213d51fa6ffadcc85ab2ab5272c1b | [
"nodes = [(root, 0)]\nvalues = []\nwhile nodes:\n cur, h = nodes.pop()\n values.append(cur.val)\n if cur.left:\n nodes.append((cur.left, h + 1))\n if cur.right:\n nodes.append((cur.right, h + 1))\nvalues.sort()\nnew = [values[i + 1] - values[i] for i in range(len(values) - 1)]\nres = min(n... | <|body_start_0|>
nodes = [(root, 0)]
values = []
while nodes:
cur, h = nodes.pop()
values.append(cur.val)
if cur.left:
nodes.append((cur.left, h + 1))
if cur.right:
nodes.append((cur.right, h + 1))
values.sor... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getMinimumDifference(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def getMinimumDifference2(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
nodes = [(root, 0)]
... | stack_v2_sparse_classes_10k_train_005542 | 1,588 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "getMinimumDifference",
"signature": "def getMinimumDifference(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "getMinimumDifference2",
"signature": "def getMinimumDifference2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_test_000296 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getMinimumDifference(self, root): :type root: TreeNode :rtype: int
- def getMinimumDifference2(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getMinimumDifference(self, root): :type root: TreeNode :rtype: int
- def getMinimumDifference2(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
... | 0fc4c7af59246e3064db41989a45d9db413a624b | <|skeleton|>
class Solution:
def getMinimumDifference(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def getMinimumDifference2(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def getMinimumDifference(self, root):
""":type root: TreeNode :rtype: int"""
nodes = [(root, 0)]
values = []
while nodes:
cur, h = nodes.pop()
values.append(cur.val)
if cur.left:
nodes.append((cur.left, h + 1))
... | the_stack_v2_python_sparse | 530. Minimum Absolute Difference in BST/difference.py | Macielyoung/LeetCode | train | 1 | |
1ee3e1395dee58c16774f54cd8adb21df5225f24 | [
"super().__init__(*args, **kwargs)\nself.gx = gx\nself.gy = gy\nself.gz = gz",
"if gridpoi == 'x':\n self.background_color = BCKGRND_CLR\nelif type(gridpoi) == list:\n if gridpoi[0] == 'D':\n self.background_color = [1, 1, 0, 1]\n elif gridpoi[0] == 'M':\n self.background_color = [1, 0, 1, ... | <|body_start_0|>
super().__init__(*args, **kwargs)
self.gx = gx
self.gy = gy
self.gz = gz
<|end_body_0|>
<|body_start_1|>
if gridpoi == 'x':
self.background_color = BCKGRND_CLR
elif type(gridpoi) == list:
if gridpoi[0] == 'D':
self... | Square | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Square:
def __init__(self, gx, gy, gz, *args, **kwargs):
"""params:- gx : int : grid x coordinate gy : int : grid y coordinate gz : int : grid z coordinate"""
<|body_0|>
def update_square(self, gx, gy, gz, gridpoi):
"""params:- gx : int : grid x coordinate, used to w... | stack_v2_sparse_classes_10k_train_005543 | 6,851 | no_license | [
{
"docstring": "params:- gx : int : grid x coordinate gy : int : grid y coordinate gz : int : grid z coordinate",
"name": "__init__",
"signature": "def __init__(self, gx, gy, gz, *args, **kwargs)"
},
{
"docstring": "params:- gx : int : grid x coordinate, used to workout black or white square gy ... | 2 | stack_v2_sparse_classes_30k_train_000459 | Implement the Python class `Square` described below.
Class description:
Implement the Square class.
Method signatures and docstrings:
- def __init__(self, gx, gy, gz, *args, **kwargs): params:- gx : int : grid x coordinate gy : int : grid y coordinate gz : int : grid z coordinate
- def update_square(self, gx, gy, gz,... | Implement the Python class `Square` described below.
Class description:
Implement the Square class.
Method signatures and docstrings:
- def __init__(self, gx, gy, gz, *args, **kwargs): params:- gx : int : grid x coordinate gy : int : grid y coordinate gz : int : grid z coordinate
- def update_square(self, gx, gy, gz,... | 020a6f05e17fd9ef8d8a10f22a0482352d18ddd5 | <|skeleton|>
class Square:
def __init__(self, gx, gy, gz, *args, **kwargs):
"""params:- gx : int : grid x coordinate gy : int : grid y coordinate gz : int : grid z coordinate"""
<|body_0|>
def update_square(self, gx, gy, gz, gridpoi):
"""params:- gx : int : grid x coordinate, used to w... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Square:
def __init__(self, gx, gy, gz, *args, **kwargs):
"""params:- gx : int : grid x coordinate gy : int : grid y coordinate gz : int : grid z coordinate"""
super().__init__(*args, **kwargs)
self.gx = gx
self.gy = gy
self.gz = gz
def update_square(self, gx, gy, g... | the_stack_v2_python_sparse | bin/Visualliser/visualliser.py | HarryBurge/StarTrekChessAI | train | 0 | |
3022ddf851225d4782231737bcfd0a5dcc33cfd9 | [
"for i in range(len(flowerbed)):\n if (i == 0 or flowerbed[i - 1] == 0) and flowerbed[i] == 0 and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):\n flowerbed[i] = 1\n n -= 1\n if n <= 0:\n return True\nreturn n <= 0",
"planted = n\nnot_planted = n\nfor x in flowerbed:\n if not x:... | <|body_start_0|>
for i in range(len(flowerbed)):
if (i == 0 or flowerbed[i - 1] == 0) and flowerbed[i] == 0 and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):
flowerbed[i] = 1
n -= 1
if n <= 0:
return True
return n <= 0
<|end_b... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Jan 31, 2022 14:52"""
<|body_0|>
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Apr 23, 2023 18:53"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
for... | stack_v2_sparse_classes_10k_train_005544 | 2,070 | no_license | [
{
"docstring": "Jan 31, 2022 14:52",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool"
},
{
"docstring": "Apr 23, 2023 18:53",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Jan 31, 2022 14:52
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Apr 23, 2023 18:53 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Jan 31, 2022 14:52
- def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool: Apr 23, 2023 18:53
<|skele... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Jan 31, 2022 14:52"""
<|body_0|>
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Apr 23, 2023 18:53"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def canPlaceFlowers(self, flowerbed: List[int], n: int) -> bool:
"""Jan 31, 2022 14:52"""
for i in range(len(flowerbed)):
if (i == 0 or flowerbed[i - 1] == 0) and flowerbed[i] == 0 and (i == len(flowerbed) - 1 or flowerbed[i + 1] == 0):
flowerbed[i] = 1
... | the_stack_v2_python_sparse | leetcode/solved/605_Can_Place_Flowers/solution.py | sungminoh/algorithms | train | 0 | |
622f265f10cd073d10096cfffdc1e7b0a1f0fde5 | [
"self.next = [None] * 26\nself.word = False\nif len(suffix) == 0:\n self.word = True\n return\nidx = ord(suffix[0]) - BaseA\nif self.next[idx] is None:\n self.next[idx] = PrefixNode(suffix[1:])\nelse:\n self.next[idx].add(suffix[1:])",
"if suffix == '':\n if self.word:\n return False\n se... | <|body_start_0|>
self.next = [None] * 26
self.word = False
if len(suffix) == 0:
self.word = True
return
idx = ord(suffix[0]) - BaseA
if self.next[idx] is None:
self.next[idx] = PrefixNode(suffix[1:])
else:
self.next[idx].add... | PrefixNode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrefixNode:
def __init__(self, suffix):
"""Node in a Prefix Tree."""
<|body_0|>
def add(self, suffix):
"""Add rest of suffix."""
<|body_1|>
def remove(self, suffix):
"""Remove rest of suffix."""
<|body_2|>
def __repr__(self):
... | stack_v2_sparse_classes_10k_train_005545 | 3,958 | no_license | [
{
"docstring": "Node in a Prefix Tree.",
"name": "__init__",
"signature": "def __init__(self, suffix)"
},
{
"docstring": "Add rest of suffix.",
"name": "add",
"signature": "def add(self, suffix)"
},
{
"docstring": "Remove rest of suffix.",
"name": "remove",
"signature": "... | 4 | stack_v2_sparse_classes_30k_train_000657 | Implement the Python class `PrefixNode` described below.
Class description:
Implement the PrefixNode class.
Method signatures and docstrings:
- def __init__(self, suffix): Node in a Prefix Tree.
- def add(self, suffix): Add rest of suffix.
- def remove(self, suffix): Remove rest of suffix.
- def __repr__(self): Repre... | Implement the Python class `PrefixNode` described below.
Class description:
Implement the PrefixNode class.
Method signatures and docstrings:
- def __init__(self, suffix): Node in a Prefix Tree.
- def add(self, suffix): Add rest of suffix.
- def remove(self, suffix): Remove rest of suffix.
- def __repr__(self): Repre... | ec8837af1df91167fdc8666863ac9b390095a441 | <|skeleton|>
class PrefixNode:
def __init__(self, suffix):
"""Node in a Prefix Tree."""
<|body_0|>
def add(self, suffix):
"""Add rest of suffix."""
<|body_1|>
def remove(self, suffix):
"""Remove rest of suffix."""
<|body_2|>
def __repr__(self):
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrefixNode:
def __init__(self, suffix):
"""Node in a Prefix Tree."""
self.next = [None] * 26
self.word = False
if len(suffix) == 0:
self.word = True
return
idx = ord(suffix[0]) - BaseA
if self.next[idx] is None:
self.next[idx]... | the_stack_v2_python_sparse | 3. Pointer Structures/prefixTreeLinkedList.py | RANUX/python-algorithms | train | 0 | |
23885620ff0ef8f70d2d8bc5d8f2e0f0c21f5447 | [
"try:\n user = await get_data_from_req(self.request).administrators.get(user_id)\nexcept ResourceNotFoundError:\n raise NotFound()\nreturn json_response(user)",
"if not await check_can_edit_user(get_authorization_client_from_req(self.request), self.request['client'].user_id, user_id):\n raise HTTPForbidd... | <|body_start_0|>
try:
user = await get_data_from_req(self.request).administrators.get(user_id)
except ResourceNotFoundError:
raise NotFound()
return json_response(user)
<|end_body_0|>
<|body_start_1|>
if not await check_can_edit_user(get_authorization_client_from... | AdminUserView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AdminUserView:
async def get(self, user_id: str, /) -> Union[r200[UserResponse], r404]:
"""Get a user. Fetches the details of a user. Status Codes: 200: Successful operation 404: User not found"""
<|body_0|>
async def patch(self, user_id: str, /, data: UpdateUserRequest) -> ... | stack_v2_sparse_classes_10k_train_005546 | 6,189 | permissive | [
{
"docstring": "Get a user. Fetches the details of a user. Status Codes: 200: Successful operation 404: User not found",
"name": "get",
"signature": "async def get(self, user_id: str, /) -> Union[r200[UserResponse], r404]"
},
{
"docstring": "Update a user. Status Codes: 200: Successful operation... | 2 | stack_v2_sparse_classes_30k_train_006772 | Implement the Python class `AdminUserView` described below.
Class description:
Implement the AdminUserView class.
Method signatures and docstrings:
- async def get(self, user_id: str, /) -> Union[r200[UserResponse], r404]: Get a user. Fetches the details of a user. Status Codes: 200: Successful operation 404: User no... | Implement the Python class `AdminUserView` described below.
Class description:
Implement the AdminUserView class.
Method signatures and docstrings:
- async def get(self, user_id: str, /) -> Union[r200[UserResponse], r404]: Get a user. Fetches the details of a user. Status Codes: 200: Successful operation 404: User no... | 1d17d2ba570cf5487e7514bec29250a5b368bb0a | <|skeleton|>
class AdminUserView:
async def get(self, user_id: str, /) -> Union[r200[UserResponse], r404]:
"""Get a user. Fetches the details of a user. Status Codes: 200: Successful operation 404: User not found"""
<|body_0|>
async def patch(self, user_id: str, /, data: UpdateUserRequest) -> ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AdminUserView:
async def get(self, user_id: str, /) -> Union[r200[UserResponse], r404]:
"""Get a user. Fetches the details of a user. Status Codes: 200: Successful operation 404: User not found"""
try:
user = await get_data_from_req(self.request).administrators.get(user_id)
... | the_stack_v2_python_sparse | virtool/administrators/api.py | virtool/virtool | train | 45 | |
4f8948521bc9ecc91b2ace6e440b943ab943bc8e | [
"uid = getSecurityManager().getUser().getId()\nif uid == 'Anonymous':\n return ()\nbook = component.getUtility(IAddressBookUtility).get(uid)\nentry_names = list(book.keys())\nentry_names.sort()\nentry_dict = {}\nfor entry_name in entry_names:\n second_line = ''\n if book[entry_name].ship_second_line:\n ... | <|body_start_0|>
uid = getSecurityManager().getUser().getId()
if uid == 'Anonymous':
return ()
book = component.getUtility(IAddressBookUtility).get(uid)
entry_names = list(book.keys())
entry_names.sort()
entry_dict = {}
for entry_name in entry_names:
... | AddressBookView | [
"ZPL-2.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddressBookView:
def getEntryNames(self):
"""get a list of entry names"""
<|body_0|>
def getEntryScripts(self):
"""Returns javascript function that fill the fields with the data"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
uid = getSecurityManage... | stack_v2_sparse_classes_10k_train_005547 | 37,142 | permissive | [
{
"docstring": "get a list of entry names",
"name": "getEntryNames",
"signature": "def getEntryNames(self)"
},
{
"docstring": "Returns javascript function that fill the fields with the data",
"name": "getEntryScripts",
"signature": "def getEntryScripts(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000259 | Implement the Python class `AddressBookView` described below.
Class description:
Implement the AddressBookView class.
Method signatures and docstrings:
- def getEntryNames(self): get a list of entry names
- def getEntryScripts(self): Returns javascript function that fill the fields with the data | Implement the Python class `AddressBookView` described below.
Class description:
Implement the AddressBookView class.
Method signatures and docstrings:
- def getEntryNames(self): get a list of entry names
- def getEntryScripts(self): Returns javascript function that fill the fields with the data
<|skeleton|>
class A... | 95ebc05678cb8db7510e0de0857ad41253800fb1 | <|skeleton|>
class AddressBookView:
def getEntryNames(self):
"""get a list of entry names"""
<|body_0|>
def getEntryScripts(self):
"""Returns javascript function that fill the fields with the data"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddressBookView:
def getEntryNames(self):
"""get a list of entry names"""
uid = getSecurityManager().getUser().getId()
if uid == 'Anonymous':
return ()
book = component.getUtility(IAddressBookUtility).get(uid)
entry_names = list(book.keys())
entry_na... | the_stack_v2_python_sparse | Products/PloneGetPaid/browser/checkout.py | Martronic-SA/Products.PloneGetPaid | train | 0 | |
162d0fdc1f6466634341acc039c5baca02ec03f3 | [
"if isinstance(size, int):\n self.size = size\nelif isinstance(size, collections.abc.Iterable) and len(size) == 3:\n if type(size) == list:\n size = tuple(size)\n self.size = size\nelse:\n raise ValueError('Unknown inputs for size: {}'.format(size))\nself.order = order\nsuper().__init__()",
"im... | <|body_start_0|>
if isinstance(size, int):
self.size = size
elif isinstance(size, collections.abc.Iterable) and len(size) == 3:
if type(size) == list:
size = tuple(size)
self.size = size
else:
raise ValueError('Unknown inputs for si... | Resize the input numpy ndarray to the given size. Args: size order (int, optional): Desired order | Resize3D | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Resize3D:
"""Resize the input numpy ndarray to the given size. Args: size order (int, optional): Desired order"""
def __init__(self, size, order=1):
"""resize"""
<|body_0|>
def __call__(self, img, label=None):
"""Args: img (numpy ndarray): Image to be scaled. lab... | stack_v2_sparse_classes_10k_train_005548 | 34,927 | permissive | [
{
"docstring": "resize",
"name": "__init__",
"signature": "def __init__(self, size, order=1)"
},
{
"docstring": "Args: img (numpy ndarray): Image to be scaled. label (numpy ndarray) : Label to be scaled Returns: numpy ndarray: Rescaled image. numpy ndarray: Rescaled label.",
"name": "__call_... | 2 | null | Implement the Python class `Resize3D` described below.
Class description:
Resize the input numpy ndarray to the given size. Args: size order (int, optional): Desired order
Method signatures and docstrings:
- def __init__(self, size, order=1): resize
- def __call__(self, img, label=None): Args: img (numpy ndarray): Im... | Implement the Python class `Resize3D` described below.
Class description:
Resize the input numpy ndarray to the given size. Args: size order (int, optional): Desired order
Method signatures and docstrings:
- def __init__(self, size, order=1): resize
- def __call__(self, img, label=None): Args: img (numpy ndarray): Im... | 2c8c35a8949fef74599f5ec557d340a14415f20d | <|skeleton|>
class Resize3D:
"""Resize the input numpy ndarray to the given size. Args: size order (int, optional): Desired order"""
def __init__(self, size, order=1):
"""resize"""
<|body_0|>
def __call__(self, img, label=None):
"""Args: img (numpy ndarray): Image to be scaled. lab... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Resize3D:
"""Resize the input numpy ndarray to the given size. Args: size order (int, optional): Desired order"""
def __init__(self, size, order=1):
"""resize"""
if isinstance(size, int):
self.size = size
elif isinstance(size, collections.abc.Iterable) and len(size) ==... | the_stack_v2_python_sparse | contrib/MedicalSeg/medicalseg/transforms/transform.py | PaddlePaddle/PaddleSeg | train | 8,531 |
7839938c10c11e00708856e0dc9081aa58c7c434 | [
"try:\n verify_token(request.headers)\nexcept Exception as err:\n ns.abort(401, message=err)\ntry:\n acc = acciones.read(org_fiscal_id, id)\nexcept EmptySetError:\n ns.abort(404, message=self.accion_not_found)\nexcept Exception as err:\n ns.abort(400, message=err)\nreturn acc",
"try:\n verify_to... | <|body_start_0|>
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
try:
acc = acciones.read(org_fiscal_id, id)
except EmptySetError:
ns.abort(404, message=self.accion_not_found)
except Exception ... | Accion | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Accion:
def get(self, org_fiscal_id, id):
"""Recuperar una Acción"""
<|body_0|>
def put(self, org_fiscal_id, id):
"""Actualizar una Acción"""
<|body_1|>
def delete(self, org_fiscal_id, id):
"""Eliminar una Acción"""
<|body_2|>
<|end_skel... | stack_v2_sparse_classes_10k_train_005549 | 6,129 | no_license | [
{
"docstring": "Recuperar una Acción",
"name": "get",
"signature": "def get(self, org_fiscal_id, id)"
},
{
"docstring": "Actualizar una Acción",
"name": "put",
"signature": "def put(self, org_fiscal_id, id)"
},
{
"docstring": "Eliminar una Acción",
"name": "delete",
"sign... | 3 | stack_v2_sparse_classes_30k_train_003042 | Implement the Python class `Accion` described below.
Class description:
Implement the Accion class.
Method signatures and docstrings:
- def get(self, org_fiscal_id, id): Recuperar una Acción
- def put(self, org_fiscal_id, id): Actualizar una Acción
- def delete(self, org_fiscal_id, id): Eliminar una Acción | Implement the Python class `Accion` described below.
Class description:
Implement the Accion class.
Method signatures and docstrings:
- def get(self, org_fiscal_id, id): Recuperar una Acción
- def put(self, org_fiscal_id, id): Actualizar una Acción
- def delete(self, org_fiscal_id, id): Eliminar una Acción
<|skeleto... | e00610fac26ef3ca078fd037c0649b70fa0e9a09 | <|skeleton|>
class Accion:
def get(self, org_fiscal_id, id):
"""Recuperar una Acción"""
<|body_0|>
def put(self, org_fiscal_id, id):
"""Actualizar una Acción"""
<|body_1|>
def delete(self, org_fiscal_id, id):
"""Eliminar una Acción"""
<|body_2|>
<|end_skel... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Accion:
def get(self, org_fiscal_id, id):
"""Recuperar una Acción"""
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
try:
acc = acciones.read(org_fiscal_id, id)
except EmptySetError:
... | the_stack_v2_python_sparse | DOS/soa/service/genl/endpoints/acciones.py | Telematica/knight-rider | train | 1 | |
2a64914a782066498ca488e831698892cbece572 | [
"super().__init__()\nlogging_levels = {val: val for val in LEVELS.values()}\nlogging_levels.update(LEVELS)\nself._ignore_exceptions = []\nfor exc_name, exc_level in ignore_exceptions:\n try:\n self._ignore_exceptions.append((logging_levels[exc_level], exc_name))\n except KeyError as err:\n raise... | <|body_start_0|>
super().__init__()
logging_levels = {val: val for val in LEVELS.values()}
logging_levels.update(LEVELS)
self._ignore_exceptions = []
for exc_name, exc_level in ignore_exceptions:
try:
self._ignore_exceptions.append((logging_levels[exc_... | Filter out the specified exceptions with specified logging level. | ExceptionFilter | [
"BSD-2-Clause",
"BSD-3-Clause",
"BSD-2-Clause-Views"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExceptionFilter:
"""Filter out the specified exceptions with specified logging level."""
def __init__(self, ignore_exceptions):
"""Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will... | stack_v2_sparse_classes_10k_train_005550 | 1,804 | permissive | [
{
"docstring": "Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will filter out all exceptions with that name. ignore_exceptions: a tuple of tuples ((exception name, loglevel)) example: ((\"ReadTimeout\", \"WARN... | 2 | null | Implement the Python class `ExceptionFilter` described below.
Class description:
Filter out the specified exceptions with specified logging level.
Method signatures and docstrings:
- def __init__(self, ignore_exceptions): Configure filtering out of the specified exceptions with specified logging level. Note if there ... | Implement the Python class `ExceptionFilter` described below.
Class description:
Filter out the specified exceptions with specified logging level.
Method signatures and docstrings:
- def __init__(self, ignore_exceptions): Configure filtering out of the specified exceptions with specified logging level. Note if there ... | 232446d776fdb906d2fb253cf0a409c6813a08d6 | <|skeleton|>
class ExceptionFilter:
"""Filter out the specified exceptions with specified logging level."""
def __init__(self, ignore_exceptions):
"""Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ExceptionFilter:
"""Filter out the specified exceptions with specified logging level."""
def __init__(self, ignore_exceptions):
"""Configure filtering out of the specified exceptions with specified logging level. Note if there are multiple exceptions that have the same name this will filter out a... | the_stack_v2_python_sparse | h/util/logging_filters.py | hypothesis/h | train | 2,558 |
dc840657645421dbdce14ac53e42865e44af777d | [
"global gf\nclocks_to_check = self.SYSTEM_CLOCK_SOURCES.keys()\nfrequencies = gf.apis.selftest.measure_clock_frequencies(*clocks_to_check)\nfor clock_number, measured_frequency in zip(clocks_to_check, frequencies):\n parameters = self.SYSTEM_CLOCK_SOURCES[clock_number]\n with self.subTest(parameters['name']):... | <|body_start_0|>
global gf
clocks_to_check = self.SYSTEM_CLOCK_SOURCES.keys()
frequencies = gf.apis.selftest.measure_clock_frequencies(*clocks_to_check)
for clock_number, measured_frequency in zip(clocks_to_check, frequencies):
parameters = self.SYSTEM_CLOCK_SOURCES[clock_num... | Ensures each of the GreatFET's clocks are up and running. | ValidateSystemClocks | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ValidateSystemClocks:
"""Ensures each of the GreatFET's clocks are up and running."""
def test_system_clocks(self):
"""Test of each of the system's clocks"""
<|body_0|>
def test_usb_pll_stability(self):
"""Test that the USB-PLL is exactly in spec."""
<|bo... | stack_v2_sparse_classes_10k_train_005551 | 4,375 | permissive | [
{
"docstring": "Test of each of the system's clocks",
"name": "test_system_clocks",
"signature": "def test_system_clocks(self)"
},
{
"docstring": "Test that the USB-PLL is exactly in spec.",
"name": "test_usb_pll_stability",
"signature": "def test_usb_pll_stability(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002552 | Implement the Python class `ValidateSystemClocks` described below.
Class description:
Ensures each of the GreatFET's clocks are up and running.
Method signatures and docstrings:
- def test_system_clocks(self): Test of each of the system's clocks
- def test_usb_pll_stability(self): Test that the USB-PLL is exactly in ... | Implement the Python class `ValidateSystemClocks` described below.
Class description:
Ensures each of the GreatFET's clocks are up and running.
Method signatures and docstrings:
- def test_system_clocks(self): Test of each of the system's clocks
- def test_usb_pll_stability(self): Test that the USB-PLL is exactly in ... | 2409575d28fc7c9cae44c9085c7457ddfb54f893 | <|skeleton|>
class ValidateSystemClocks:
"""Ensures each of the GreatFET's clocks are up and running."""
def test_system_clocks(self):
"""Test of each of the system's clocks"""
<|body_0|>
def test_usb_pll_stability(self):
"""Test that the USB-PLL is exactly in spec."""
<|bo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ValidateSystemClocks:
"""Ensures each of the GreatFET's clocks are up and running."""
def test_system_clocks(self):
"""Test of each of the system's clocks"""
global gf
clocks_to_check = self.SYSTEM_CLOCK_SOURCES.keys()
frequencies = gf.apis.selftest.measure_clock_frequenci... | the_stack_v2_python_sparse | host/greatfet/commands/greatfet_selftest.py | greatscottgadgets/greatfet | train | 273 |
7827ddd9f4cfc18c123f16a5583632fe720d95b8 | [
"self.nums = nums\nself.lens = len(nums)\nself.BIT = [0] * (self.lens + 1)\nfor i in range(self.lens):\n k = i + 1\n while k <= self.lens:\n self.BIT[k] += nums[i]\n k += k & -k",
"diff = val - self.nums[i]\nself.nums[i] = val\ni += 1\nwhile i <= self.lens:\n self.BIT[i] += diff\n i += i... | <|body_start_0|>
self.nums = nums
self.lens = len(nums)
self.BIT = [0] * (self.lens + 1)
for i in range(self.lens):
k = i + 1
while k <= self.lens:
self.BIT[k] += nums[i]
k += k & -k
<|end_body_0|>
<|body_start_1|>
diff = v... | NumArray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
"""update 操作一直都是遍历左侧 :type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
"""sum: 遍历右侧 上一层已经把左侧的值加上去了，而左侧的索引又是小于右侧，所以... | stack_v2_sparse_classes_10k_train_005552 | 1,921 | no_license | [
{
"docstring": ":type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, nums)"
},
{
"docstring": "update 操作一直都是遍历左侧 :type i: int :type val: int :rtype: void",
"name": "update",
"signature": "def update(self, i, val)"
},
{
"docstring": "sum: 遍历右侧 上一层已经把左侧的值加上去... | 3 | stack_v2_sparse_classes_30k_train_003442 | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): update 操作一直都是遍历左侧 :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): sum: 遍历右侧 上一层已经... | Implement the Python class `NumArray` described below.
Class description:
Implement the NumArray class.
Method signatures and docstrings:
- def __init__(self, nums): :type nums: List[int]
- def update(self, i, val): update 操作一直都是遍历左侧 :type i: int :type val: int :rtype: void
- def sumRange(self, i, j): sum: 遍历右侧 上一层已经... | 212f8b83d6ac22db1a777f980075d9e12ce521d2 | <|skeleton|>
class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
<|body_0|>
def update(self, i, val):
"""update 操作一直都是遍历左侧 :type i: int :type val: int :rtype: void"""
<|body_1|>
def sumRange(self, i, j):
"""sum: 遍历右侧 上一层已经把左侧的值加上去了，而左侧的索引又是小于右侧，所以... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NumArray:
def __init__(self, nums):
""":type nums: List[int]"""
self.nums = nums
self.lens = len(nums)
self.BIT = [0] * (self.lens + 1)
for i in range(self.lens):
k = i + 1
while k <= self.lens:
self.BIT[k] += nums[i]
... | the_stack_v2_python_sparse | Data Structures and Algorithm Analysis/tree/Binary Indexed Tree.py | FrankieZhen/Lookoop | train | 1 | |
d953f3efe6f392b5e513e38617f88f57835d2c79 | [
"self.sequence = A\nself.cursor = 0\nself.length = len(A)",
"while self.cursor < self.length and self.sequence[self.cursor] < n:\n n -= self.sequence[self.cursor]\n self.cursor += 2\nif self.cursor < self.length:\n self.sequence[self.cursor] -= n\n return self.sequence[self.cursor + 1]\nelse:\n ret... | <|body_start_0|>
self.sequence = A
self.cursor = 0
self.length = len(A)
<|end_body_0|>
<|body_start_1|>
while self.cursor < self.length and self.sequence[self.cursor] < n:
n -= self.sequence[self.cursor]
self.cursor += 2
if self.cursor < self.length:
... | RLEIterator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.sequence = A
self.cursor = 0
self.length = len(A)
<|end_body_... | stack_v2_sparse_classes_10k_train_005553 | 699 | no_license | [
{
"docstring": ":type A: List[int]",
"name": "__init__",
"signature": "def __init__(self, A)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "next",
"signature": "def next(self, n)"
}
] | 2 | null | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int | Implement the Python class `RLEIterator` described below.
Class description:
Implement the RLEIterator class.
Method signatures and docstrings:
- def __init__(self, A): :type A: List[int]
- def next(self, n): :type n: int :rtype: int
<|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: Lis... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
<|body_0|>
def next(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RLEIterator:
def __init__(self, A):
""":type A: List[int]"""
self.sequence = A
self.cursor = 0
self.length = len(A)
def next(self, n):
""":type n: int :rtype: int"""
while self.cursor < self.length and self.sequence[self.cursor] < n:
n -= self.s... | the_stack_v2_python_sparse | python/leetcode/900_RLE_Iterator.py | bobcaoge/my-code | train | 0 | |
c377090f48a4ed5ad7e380a62919aff933334352 | [
"self.dtype = dtype\nself.dim = dim\nself.units = units",
"if self.dtype is None:\n return False\nelif self.dtype == dtype:\n return False\nelse:\n return True",
"if self.dim is None:\n return False\nelif self.dim == dim:\n return False\nelse:\n return True",
"if self.units is None:\n ret... | <|body_start_0|>
self.dtype = dtype
self.dim = dim
self.units = units
<|end_body_0|>
<|body_start_1|>
if self.dtype is None:
return False
elif self.dtype == dtype:
return False
else:
return True
<|end_body_1|>
<|body_start_2|>
... | A class for holding and checking netCDF variables. Parameters ---------- dtype : type or None Expected dtype of the variable, None for no expected type. dim : tuple of str Expected dimensions of the variable, None for no expected dimensions. units : str Expected units attribute of the variable. None for no expected uni... | Variable | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Variable:
"""A class for holding and checking netCDF variables. Parameters ---------- dtype : type or None Expected dtype of the variable, None for no expected type. dim : tuple of str Expected dimensions of the variable, None for no expected dimensions. units : str Expected units attribute of th... | stack_v2_sparse_classes_10k_train_005554 | 40,072 | permissive | [
{
"docstring": "initalize the object.",
"name": "__init__",
"signature": "def __init__(self, dtype=None, dim=None, units=None)"
},
{
"docstring": "True if the provided dtype does not match the expected dtype.",
"name": "dtype_bad",
"signature": "def dtype_bad(self, dtype)"
},
{
"... | 4 | stack_v2_sparse_classes_30k_train_001779 | Implement the Python class `Variable` described below.
Class description:
A class for holding and checking netCDF variables. Parameters ---------- dtype : type or None Expected dtype of the variable, None for no expected type. dim : tuple of str Expected dimensions of the variable, None for no expected dimensions. uni... | Implement the Python class `Variable` described below.
Class description:
A class for holding and checking netCDF variables. Parameters ---------- dtype : type or None Expected dtype of the variable, None for no expected type. dim : tuple of str Expected dimensions of the variable, None for no expected dimensions. uni... | 172bbcf1cf3bcdb953c76ebae72c27c95dc2e606 | <|skeleton|>
class Variable:
"""A class for holding and checking netCDF variables. Parameters ---------- dtype : type or None Expected dtype of the variable, None for no expected type. dim : tuple of str Expected dimensions of the variable, None for no expected dimensions. units : str Expected units attribute of th... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Variable:
"""A class for holding and checking netCDF variables. Parameters ---------- dtype : type or None Expected dtype of the variable, None for no expected type. dim : tuple of str Expected dimensions of the variable, None for no expected dimensions. units : str Expected units attribute of the variable. N... | the_stack_v2_python_sparse | scripts/check_cfradial | ARM-DOE/pyart | train | 455 |
2282d991bf310ae63d2249a689bf1a818c3e6b8b | [
"def outer(self, *args, **kwargs):\n logging.info('MetaView Outer: '.format(self.request))\n if self.request.get('google_login') == 'true':\n if self.get_current_user():\n refresh_url = util.set_query_parameters(self.request.url, google_login='')\n self.redirect(refresh_url)\n ... | <|body_start_0|>
def outer(self, *args, **kwargs):
logging.info('MetaView Outer: '.format(self.request))
if self.request.get('google_login') == 'true':
if self.get_current_user():
refresh_url = util.set_query_parameters(self.request.url, google_login='... | Allows code to be run before and after get and post methods. See: http://stackoverflow.com/questions/6780907/python-wrap-class-method | MetaView | [
"CC-BY-4.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-public-domain",
"CC0-1.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MetaView:
"""Allows code to be run before and after get and post methods. See: http://stackoverflow.com/questions/6780907/python-wrap-class-method"""
def wrap(method):
"""Return a wrapped instance method"""
<|body_0|>
def __new__(cls, name, bases, attrs):
"""If t... | stack_v2_sparse_classes_10k_train_005555 | 38,138 | permissive | [
{
"docstring": "Return a wrapped instance method",
"name": "wrap",
"signature": "def wrap(method)"
},
{
"docstring": "If the class has an http GET method, wrap it.",
"name": "__new__",
"signature": "def __new__(cls, name, bases, attrs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004043 | Implement the Python class `MetaView` described below.
Class description:
Allows code to be run before and after get and post methods. See: http://stackoverflow.com/questions/6780907/python-wrap-class-method
Method signatures and docstrings:
- def wrap(method): Return a wrapped instance method
- def __new__(cls, name... | Implement the Python class `MetaView` described below.
Class description:
Allows code to be run before and after get and post methods. See: http://stackoverflow.com/questions/6780907/python-wrap-class-method
Method signatures and docstrings:
- def wrap(method): Return a wrapped instance method
- def __new__(cls, name... | 14fbcf0830e47fb0c7a6af798ed01f7181147979 | <|skeleton|>
class MetaView:
"""Allows code to be run before and after get and post methods. See: http://stackoverflow.com/questions/6780907/python-wrap-class-method"""
def wrap(method):
"""Return a wrapped instance method"""
<|body_0|>
def __new__(cls, name, bases, attrs):
"""If t... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MetaView:
"""Allows code to be run before and after get and post methods. See: http://stackoverflow.com/questions/6780907/python-wrap-class-method"""
def wrap(method):
"""Return a wrapped instance method"""
def outer(self, *args, **kwargs):
logging.info('MetaView Outer: '.form... | the_stack_v2_python_sparse | mindsetkit.py | Stanford-PERTS/mindsetkit | train | 0 |
e8d7ee81f44fb5bcce2a22f7bdc785bdf4dd6fd7 | [
"super(EvaluateEnsemblePartial, self).__init__()\nself.evaluate_ensemble_partial = evaluate_ensemble_partial\nself.result_labels = result_labels\nself.every_x_epoch = every_x_epoch",
"if epoch % self.every_x_epoch == self.every_x_epoch - 1:\n results = self.evaluate_ensemble_partial()\n if results is not No... | <|body_start_0|>
super(EvaluateEnsemblePartial, self).__init__()
self.evaluate_ensemble_partial = evaluate_ensemble_partial
self.result_labels = result_labels
self.every_x_epoch = every_x_epoch
<|end_body_0|>
<|body_start_1|>
if epoch % self.every_x_epoch == self.every_x_epoch -... | Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop. | EvaluateEnsemblePartial | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvaluateEnsemblePartial:
"""Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop."""
def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1):
"""Evaluate ensemble using a ensemble.evaluate partial. Can be used in combi... | stack_v2_sparse_classes_10k_train_005556 | 20,794 | permissive | [
{
"docstring": "Evaluate ensemble using a ensemble.evaluate partial. Can be used in combination with EvaluateEnsemblePartial to evaluate the ensemble at regular intervals inside a keras model.fit() loop. Note: only ScalarStatistic's are supported. Args: evaluate_ensemble_partial: bnn.ensemble.Ensemble.evaluate ... | 2 | stack_v2_sparse_classes_30k_train_000120 | Implement the Python class `EvaluateEnsemblePartial` described below.
Class description:
Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop.
Method signatures and docstrings:
- def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1): Evaluate ensembl... | Implement the Python class `EvaluateEnsemblePartial` described below.
Class description:
Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop.
Method signatures and docstrings:
- def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1): Evaluate ensembl... | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | <|skeleton|>
class EvaluateEnsemblePartial:
"""Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop."""
def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1):
"""Evaluate ensemble using a ensemble.evaluate partial. Can be used in combi... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EvaluateEnsemblePartial:
"""Evaluate Ensemble after every epoch. Enables ensemble evaluation inside a keras model.fit() loop."""
def __init__(self, evaluate_ensemble_partial, result_labels, every_x_epoch=1):
"""Evaluate ensemble using a ensemble.evaluate partial. Can be used in combination with E... | the_stack_v2_python_sparse | cold_posterior_bnn/core/keras_utils.py | Ayoob7/google-research | train | 2 |
b9e15a7a0d8ab884552ac29b91dc1c465decd9be | [
"super().__init__(creator, flock_size, buffer_size)\nself._delay_used = delay_used\nself.inputs = self._create_storage('inputs', (flock_size, buffer_size, *input_shape), force_cpu=False)\nself.targets = self._create_storage('targets', (flock_size, buffer_size, *target_shape))\nself.learning_coefficients = self._cre... | <|body_start_0|>
super().__init__(creator, flock_size, buffer_size)
self._delay_used = delay_used
self.inputs = self._create_storage('inputs', (flock_size, buffer_size, *input_shape), force_cpu=False)
self.targets = self._create_storage('targets', (flock_size, buffer_size, *target_shape)... | Defines a circular buffer for a flock of neural networks. It has two storages: for inputs (flock_size, buffer_size, input_size) and for outputs. Then there are learning_coefficients (flock_size, 1) determining how much each network should learn the particular IO. | NetworkFlockBuffer | [
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkFlockBuffer:
"""Defines a circular buffer for a flock of neural networks. It has two storages: for inputs (flock_size, buffer_size, input_size) and for outputs. Then there are learning_coefficients (flock_size, 1) determining how much each network should learn the particular IO."""
de... | stack_v2_sparse_classes_10k_train_005557 | 3,879 | permissive | [
{
"docstring": "Initialize the buffer Args: flock_size (int): Number of networks in the flock buffer_size (int): Number of elements that can be stored in the buffer before rewriting occurs input_shape (Tuple): The shape of the inputs target_shape (Tuple): The shape of the target delay_used (bool): whether any o... | 4 | null | Implement the Python class `NetworkFlockBuffer` described below.
Class description:
Defines a circular buffer for a flock of neural networks. It has two storages: for inputs (flock_size, buffer_size, input_size) and for outputs. Then there are learning_coefficients (flock_size, 1) determining how much each network sho... | Implement the Python class `NetworkFlockBuffer` described below.
Class description:
Defines a circular buffer for a flock of neural networks. It has two storages: for inputs (flock_size, buffer_size, input_size) and for outputs. Then there are learning_coefficients (flock_size, 1) determining how much each network sho... | 81d72b82ec96948c26d292d709f18c9c77a17ba4 | <|skeleton|>
class NetworkFlockBuffer:
"""Defines a circular buffer for a flock of neural networks. It has two storages: for inputs (flock_size, buffer_size, input_size) and for outputs. Then there are learning_coefficients (flock_size, 1) determining how much each network should learn the particular IO."""
de... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NetworkFlockBuffer:
"""Defines a circular buffer for a flock of neural networks. It has two storages: for inputs (flock_size, buffer_size, input_size) and for outputs. Then there are learning_coefficients (flock_size, 1) determining how much each network should learn the particular IO."""
def __init__(se... | the_stack_v2_python_sparse | torchsim/core/models/neural_network/network_flock_buffer.py | andreofner/torchsim | train | 0 |
551d351319962976d1c5729157cc9c054385d368 | [
"def call(user, perm):\n return getattr(self, perm)(obj, cls, user)\nfor func in inspect.getmembers(type(self), predicate=inspect.ismethod):\n if not isinstance(self, func[1].__self__.__class__):\n setattr(call, func[0], functools.partial(func[1], obj, cls))\n else:\n setattr(call, func[0], f... | <|body_start_0|>
def call(user, perm):
return getattr(self, perm)(obj, cls, user)
for func in inspect.getmembers(type(self), predicate=inspect.ismethod):
if not isinstance(self, func[1].__self__.__class__):
setattr(call, func[0], functools.partial(func[1], obj, cl... | Base class used for defining class and instance permissions. Enabling an ''intuitive'' interface for checking permissions: # Define permissions class NodePermission(Permission): def change(self, obj, cls, user): return obj.user == user # Provide permissions Node.has_permission = NodePermission() # Check class permissio... | Permission | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Permission:
"""Base class used for defining class and instance permissions. Enabling an ''intuitive'' interface for checking permissions: # Define permissions class NodePermission(Permission): def change(self, obj, cls, user): return obj.user == user # Provide permissions Node.has_permission = No... | stack_v2_sparse_classes_10k_train_005558 | 3,550 | permissive | [
{
"docstring": "Hacking object internals to provide means for the mentioned interface",
"name": "__get__",
"signature": "def __get__(self, obj, cls)"
},
{
"docstring": "Aggregates cls methods to self class",
"name": "_aggregate",
"signature": "def _aggregate(self, obj, cls, perm)"
}
] | 2 | null | Implement the Python class `Permission` described below.
Class description:
Base class used for defining class and instance permissions. Enabling an ''intuitive'' interface for checking permissions: # Define permissions class NodePermission(Permission): def change(self, obj, cls, user): return obj.user == user # Provi... | Implement the Python class `Permission` described below.
Class description:
Base class used for defining class and instance permissions. Enabling an ''intuitive'' interface for checking permissions: # Define permissions class NodePermission(Permission): def change(self, obj, cls, user): return obj.user == user # Provi... | 49c84f13a8f92427b01231615136549fb5be3a78 | <|skeleton|>
class Permission:
"""Base class used for defining class and instance permissions. Enabling an ''intuitive'' interface for checking permissions: # Define permissions class NodePermission(Permission): def change(self, obj, cls, user): return obj.user == user # Provide permissions Node.has_permission = No... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Permission:
"""Base class used for defining class and instance permissions. Enabling an ''intuitive'' interface for checking permissions: # Define permissions class NodePermission(Permission): def change(self, obj, cls, user): return obj.user == user # Provide permissions Node.has_permission = NodePermission(... | the_stack_v2_python_sparse | orchestra/permissions/options.py | Ro9ueAdmin/django-orchestra | train | 0 |
e42462dd0a4417d7d473fe26708c502fd5b28a28 | [
"self.ontology_file_path = path\nself.ontology = self.load_ontology()\nself.agent_requestable = self.ontology['system_requestable']\nself.user_requestable = self.ontology['user_requestable']\nself.slots_not_required_NLU = self.ontology['slots_not_required_NLU']\nself.slots_annotation = self.ontology['slots_annotati... | <|body_start_0|>
self.ontology_file_path = path
self.ontology = self.load_ontology()
self.agent_requestable = self.ontology['system_requestable']
self.user_requestable = self.ontology['user_requestable']
self.slots_not_required_NLU = self.ontology['slots_not_required_NLU']
... | Ontology is a class that loads ontology files (in .json format) into IAI MovieBot. | Ontology | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ontology:
"""Ontology is a class that loads ontology files (in .json format) into IAI MovieBot."""
def __init__(self, path):
"""Initializes the internal structures of the Domain Args: path: path to load the ontology from"""
<|body_0|>
def load_ontology(self):
"""... | stack_v2_sparse_classes_10k_train_005559 | 1,114 | permissive | [
{
"docstring": "Initializes the internal structures of the Domain Args: path: path to load the ontology from",
"name": "__init__",
"signature": "def __init__(self, path)"
},
{
"docstring": "Loads the ontology file Returns: nothing",
"name": "load_ontology",
"signature": "def load_ontolog... | 2 | stack_v2_sparse_classes_30k_train_001907 | Implement the Python class `Ontology` described below.
Class description:
Ontology is a class that loads ontology files (in .json format) into IAI MovieBot.
Method signatures and docstrings:
- def __init__(self, path): Initializes the internal structures of the Domain Args: path: path to load the ontology from
- def ... | Implement the Python class `Ontology` described below.
Class description:
Ontology is a class that loads ontology files (in .json format) into IAI MovieBot.
Method signatures and docstrings:
- def __init__(self, path): Initializes the internal structures of the Domain Args: path: path to load the ontology from
- def ... | 172966ba2b90e22037b17467d69068dad5e26b09 | <|skeleton|>
class Ontology:
"""Ontology is a class that loads ontology files (in .json format) into IAI MovieBot."""
def __init__(self, path):
"""Initializes the internal structures of the Domain Args: path: path to load the ontology from"""
<|body_0|>
def load_ontology(self):
"""... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Ontology:
"""Ontology is a class that loads ontology files (in .json format) into IAI MovieBot."""
def __init__(self, path):
"""Initializes the internal structures of the Domain Args: path: path to load the ontology from"""
self.ontology_file_path = path
self.ontology = self.load_... | the_stack_v2_python_sparse | moviebot/ontology/ontology.py | fseimb/moviebot-1 | train | 0 |
b4f2bf194cce2fd88682429504a88de29c1b1245 | [
"ctxt = context.get_admin_context()\nservices = db.service_get_all(ctxt)\nprint_format = '%-16s %-36s %-16s %-10s %-5s %-10s'\nprint(print_format % (_('Binary'), _('Host'), _('Zone'), _('Status'), _('State'), _('Updated At')))\nfor svc in services:\n alive = utils.service_is_up(svc)\n art = ':-)' if alive els... | <|body_start_0|>
ctxt = context.get_admin_context()
services = db.service_get_all(ctxt)
print_format = '%-16s %-36s %-16s %-10s %-5s %-10s'
print(print_format % (_('Binary'), _('Host'), _('Zone'), _('Status'), _('State'), _('Updated At')))
for svc in services:
alive =... | Methods for managing services. | ServiceCommands | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceCommands:
"""Methods for managing services."""
def list(self):
"""Show a list of all manila services."""
<|body_0|>
def cleanup(self):
"""Remove manila services reporting as 'down'."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ctxt = c... | stack_v2_sparse_classes_10k_train_005560 | 19,425 | permissive | [
{
"docstring": "Show a list of all manila services.",
"name": "list",
"signature": "def list(self)"
},
{
"docstring": "Remove manila services reporting as 'down'.",
"name": "cleanup",
"signature": "def cleanup(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000067 | Implement the Python class `ServiceCommands` described below.
Class description:
Methods for managing services.
Method signatures and docstrings:
- def list(self): Show a list of all manila services.
- def cleanup(self): Remove manila services reporting as 'down'. | Implement the Python class `ServiceCommands` described below.
Class description:
Methods for managing services.
Method signatures and docstrings:
- def list(self): Show a list of all manila services.
- def cleanup(self): Remove manila services reporting as 'down'.
<|skeleton|>
class ServiceCommands:
"""Methods f... | a93a844398a11a8a85f204782fb9456f7caccdbe | <|skeleton|>
class ServiceCommands:
"""Methods for managing services."""
def list(self):
"""Show a list of all manila services."""
<|body_0|>
def cleanup(self):
"""Remove manila services reporting as 'down'."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ServiceCommands:
"""Methods for managing services."""
def list(self):
"""Show a list of all manila services."""
ctxt = context.get_admin_context()
services = db.service_get_all(ctxt)
print_format = '%-16s %-36s %-16s %-10s %-5s %-10s'
print(print_format % (_('Binar... | the_stack_v2_python_sparse | manila/cmd/manage.py | openstack/manila | train | 178 |
0d321699c64a7e3af7180aacae9be4171af93cd7 | [
"X = _is_dataframe(X)\nself.variables = _find_numerical_variables(X, self.variables)\n_check_contains_na(X, self.variables)\nreturn X",
"check_is_fitted(self)\nX = _is_dataframe(X)\n_check_contains_na(X, self.variables)\n_check_input_matches_training_df(X, self.input_shape_[1])\nreturn X"
] | <|body_start_0|>
X = _is_dataframe(X)
self.variables = _find_numerical_variables(X, self.variables)
_check_contains_na(X, self.variables)
return X
<|end_body_0|>
<|body_start_1|>
check_is_fitted(self)
X = _is_dataframe(X)
_check_contains_na(X, self.variables)
... | BaseNumericalTransformer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseNumericalTransformer:
def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame:
"""Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults... | stack_v2_sparse_classes_10k_train_005561 | 2,119 | permissive | [
{
"docstring": "Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults to None. Alternatively takes Pandas Series. Returns: DataFrame with fitted transformation",
"name": "fit",
... | 2 | stack_v2_sparse_classes_30k_train_003591 | Implement the Python class `BaseNumericalTransformer` described below.
Class description:
Implement the BaseNumericalTransformer class.
Method signatures and docstrings:
- def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame: Fits the transformation to the DataFrame. Args: X: Pandas DataFrame t... | Implement the Python class `BaseNumericalTransformer` described below.
Class description:
Implement the BaseNumericalTransformer class.
Method signatures and docstrings:
- def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame: Fits the transformation to the DataFrame. Args: X: Pandas DataFrame t... | 74a2902c129452c96cc434df70127b7fa61b7f8a | <|skeleton|>
class BaseNumericalTransformer:
def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame:
"""Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BaseNumericalTransformer:
def fit(self, X: pd.DataFrame, y: Optional[pd.Series]=None) -> pd.DataFrame:
"""Fits the transformation to the DataFrame. Args: X: Pandas DataFrame to fit the transformation y: This parameter exists only for compatibility with sklearn.pipeline.Pipeline. Defaults to None. Alte... | the_stack_v2_python_sparse | feature_engine/base_transformers.py | mlaricobar/feature_engine | train | 0 | |
7d2bf70a1736b50409a315ef6f4f601f3d63e250 | [
"super(RBF, self).__init__(n_dims=n_dims, active_dims=active_dims, name=name)\nlogger.debug('Initializing %s kernel.' % self.name)\nassert np.size(variance) == 1\nassert np.size(lengthscale) == 1\nself.variance = np.float64(variance)\nself.lengthscale = np.float64(lengthscale)\nself.parameter_list = ['variance', 'l... | <|body_start_0|>
super(RBF, self).__init__(n_dims=n_dims, active_dims=active_dims, name=name)
logger.debug('Initializing %s kernel.' % self.name)
assert np.size(variance) == 1
assert np.size(lengthscale) == 1
self.variance = np.float64(variance)
self.lengthscale = np.floa... | squared exponential kernel with the same shape parameter in each dimension | RBF | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RBF:
"""squared exponential kernel with the same shape parameter in each dimension"""
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: (very much the same as in GPy.kern.RBF) n_dims : number of dimensions va... | stack_v2_sparse_classes_10k_train_005562 | 9,047 | no_license | [
{
"docstring": "squared exponential kernel Inputs: (very much the same as in GPy.kern.RBF) n_dims : number of dimensions variance : kernel variance lengthscale : kernel lengthscale active_dims : all dims active by default, subset can be specified",
"name": "__init__",
"signature": "def __init__(self, n_... | 2 | stack_v2_sparse_classes_30k_train_007044 | Implement the Python class `RBF` described below.
Class description:
squared exponential kernel with the same shape parameter in each dimension
Method signatures and docstrings:
- def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None): squared exponential kernel Inputs: (very much the ... | Implement the Python class `RBF` described below.
Class description:
squared exponential kernel with the same shape parameter in each dimension
Method signatures and docstrings:
- def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None): squared exponential kernel Inputs: (very much the ... | 1bed882b8a94ee58fd0bde6920ee85f81ffb77bb | <|skeleton|>
class RBF:
"""squared exponential kernel with the same shape parameter in each dimension"""
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: (very much the same as in GPy.kern.RBF) n_dims : number of dimensions va... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class RBF:
"""squared exponential kernel with the same shape parameter in each dimension"""
def __init__(self, n_dims, variance=1.0, lengthscale=1.0, active_dims=None, name=None):
"""squared exponential kernel Inputs: (very much the same as in GPy.kern.RBF) n_dims : number of dimensions variance : kern... | the_stack_v2_python_sparse | gp_grief/kern/stationary.py | scwolof/gp_grief | train | 2 |
0a709c3f0eec183fc3c8fb349c6ed5fc1322b43b | [
"if len(queryset) > 1:\n self.message_user(request, 'You can only choose one certificate.', level=messages.ERROR)\n return None\nresponse = HttpResponse(content_type='text/plain')\ncert = queryset.first()\nresponse.write(crypto.dump_certificate(crypto.FILETYPE_TEXT, cert.get_certificate()))\nreturn response",... | <|body_start_0|>
if len(queryset) > 1:
self.message_user(request, 'You can only choose one certificate.', level=messages.ERROR)
return None
response = HttpResponse(content_type='text/plain')
cert = queryset.first()
response.write(crypto.dump_certificate(crypto.FIL... | Admin model for certificates. | CertificateAdmin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CertificateAdmin:
"""Admin model for certificates."""
def view_certificate(self, request, queryset):
"""View a text version of the certificate."""
<|body_0|>
def download_certificate(self, request, queryset):
"""Download a certificate."""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k_train_005563 | 4,814 | permissive | [
{
"docstring": "View a text version of the certificate.",
"name": "view_certificate",
"signature": "def view_certificate(self, request, queryset)"
},
{
"docstring": "Download a certificate.",
"name": "download_certificate",
"signature": "def download_certificate(self, request, queryset)"... | 2 | stack_v2_sparse_classes_30k_train_002205 | Implement the Python class `CertificateAdmin` described below.
Class description:
Admin model for certificates.
Method signatures and docstrings:
- def view_certificate(self, request, queryset): View a text version of the certificate.
- def download_certificate(self, request, queryset): Download a certificate. | Implement the Python class `CertificateAdmin` described below.
Class description:
Admin model for certificates.
Method signatures and docstrings:
- def view_certificate(self, request, queryset): View a text version of the certificate.
- def download_certificate(self, request, queryset): Download a certificate.
<|ske... | 1c3608e0a02aaba9bd8594d80a247d692cbd04ad | <|skeleton|>
class CertificateAdmin:
"""Admin model for certificates."""
def view_certificate(self, request, queryset):
"""View a text version of the certificate."""
<|body_0|>
def download_certificate(self, request, queryset):
"""Download a certificate."""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CertificateAdmin:
"""Admin model for certificates."""
def view_certificate(self, request, queryset):
"""View a text version of the certificate."""
if len(queryset) > 1:
self.message_user(request, 'You can only choose one certificate.', level=messages.ERROR)
return ... | the_stack_v2_python_sparse | webca/webca/web/admin.py | jesusfer/webca | train | 0 |
529ab3eaed51a00812b913032462f0c325d590b8 | [
"host = self.app_host\nheaders = self.headers\nlujing = '/customer/v1/member/check_phone'\nprint(self.phone)\ndata = {'phone': self.phone}\nres = RunMethod().run_main('post', host, lujing, data, headers)\nself.assertTrue(res['code'] == 0, msg=res['msg'])\nmiaoshu(url=host + lujing, method='post', data=data, check={... | <|body_start_0|>
host = self.app_host
headers = self.headers
lujing = '/customer/v1/member/check_phone'
print(self.phone)
data = {'phone': self.phone}
res = RunMethod().run_main('post', host, lujing, data, headers)
self.assertTrue(res['code'] == 0, msg=res['msg'])... | Creat_user | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Creat_user:
def test1_member_check_phone(self):
"""验证手机号是否注册 :return:"""
<|body_0|>
def test2_message_code_send(self):
"""发送注册验证码 :return:"""
<|body_1|>
def test3_message_code_check(self):
"""注册用户-检查验证码 :return:"""
<|body_2|>
def tes... | stack_v2_sparse_classes_10k_train_005564 | 4,078 | no_license | [
{
"docstring": "验证手机号是否注册 :return:",
"name": "test1_member_check_phone",
"signature": "def test1_member_check_phone(self)"
},
{
"docstring": "发送注册验证码 :return:",
"name": "test2_message_code_send",
"signature": "def test2_message_code_send(self)"
},
{
"docstring": "注册用户-检查验证码 :retu... | 5 | stack_v2_sparse_classes_30k_train_002311 | Implement the Python class `Creat_user` described below.
Class description:
Implement the Creat_user class.
Method signatures and docstrings:
- def test1_member_check_phone(self): 验证手机号是否注册 :return:
- def test2_message_code_send(self): 发送注册验证码 :return:
- def test3_message_code_check(self): 注册用户-检查验证码 :return:
- def t... | Implement the Python class `Creat_user` described below.
Class description:
Implement the Creat_user class.
Method signatures and docstrings:
- def test1_member_check_phone(self): 验证手机号是否注册 :return:
- def test2_message_code_send(self): 发送注册验证码 :return:
- def test3_message_code_check(self): 注册用户-检查验证码 :return:
- def t... | 7377a2d7306421d9deae88eb2edff7c9df7f125e | <|skeleton|>
class Creat_user:
def test1_member_check_phone(self):
"""验证手机号是否注册 :return:"""
<|body_0|>
def test2_message_code_send(self):
"""发送注册验证码 :return:"""
<|body_1|>
def test3_message_code_check(self):
"""注册用户-检查验证码 :return:"""
<|body_2|>
def tes... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Creat_user:
def test1_member_check_phone(self):
"""验证手机号是否注册 :return:"""
host = self.app_host
headers = self.headers
lujing = '/customer/v1/member/check_phone'
print(self.phone)
data = {'phone': self.phone}
res = RunMethod().run_main('post', host, lujing... | the_stack_v2_python_sparse | Case/test2_creat_user.py | qq252223804/66ifuel | train | 1 | |
8213564301aa39c8f4182908fa25f7539981a669 | [
"toggle = NanpyGPIOToggle(self.mudpi, config)\nif toggle:\n node = self.extension.nodes[config['node']]\n if node:\n toggle.node = node\n self.add_component(toggle)\n else:\n raise MudPiError(f\"Nanpy node {config['node']} not found trying to connect {config['key']}.\")\nreturn True",
... | <|body_start_0|>
toggle = NanpyGPIOToggle(self.mudpi, config)
if toggle:
node = self.extension.nodes[config['node']]
if node:
toggle.node = node
self.add_component(toggle)
else:
raise MudPiError(f"Nanpy node {config['nod... | Interface | [
"BSD-4-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Interface:
def load(self, config):
"""Load Nanpy Toggle components from configs"""
<|body_0|>
def validate(self, config):
"""Validate the Nanpy control config"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
toggle = NanpyGPIOToggle(self.mudpi, confi... | stack_v2_sparse_classes_10k_train_005565 | 5,292 | permissive | [
{
"docstring": "Load Nanpy Toggle components from configs",
"name": "load",
"signature": "def load(self, config)"
},
{
"docstring": "Validate the Nanpy control config",
"name": "validate",
"signature": "def validate(self, config)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000837 | Implement the Python class `Interface` described below.
Class description:
Implement the Interface class.
Method signatures and docstrings:
- def load(self, config): Load Nanpy Toggle components from configs
- def validate(self, config): Validate the Nanpy control config | Implement the Python class `Interface` described below.
Class description:
Implement the Interface class.
Method signatures and docstrings:
- def load(self, config): Load Nanpy Toggle components from configs
- def validate(self, config): Validate the Nanpy control config
<|skeleton|>
class Interface:
def load(s... | fb206b1136f529c7197f1e6b29629ed05630d377 | <|skeleton|>
class Interface:
def load(self, config):
"""Load Nanpy Toggle components from configs"""
<|body_0|>
def validate(self, config):
"""Validate the Nanpy control config"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Interface:
def load(self, config):
"""Load Nanpy Toggle components from configs"""
toggle = NanpyGPIOToggle(self.mudpi, config)
if toggle:
node = self.extension.nodes[config['node']]
if node:
toggle.node = node
self.add_component(... | the_stack_v2_python_sparse | mudpi/extensions/nanpy/toggle.py | mistasp0ck/mudpi-core | train | 0 | |
e71679f4724cb5fef6718719cff5f0a1f7e6fb65 | [
"value = value.strip()\nwhile value.endswith('/'):\n value = value[:-1]\nself.getField('branch').set(self, value)",
"list = DisplayList()\ntypes = self.aq_inner.aq_parent.getProposalTypes()\nfor type in types:\n list.add(type, type)\nreturn list",
"parent = self.aq_inner.aq_parent\nmaxId = 0\nfor id in pa... | <|body_start_0|>
value = value.strip()
while value.endswith('/'):
value = value[:-1]
self.getField('branch').set(self, value)
<|end_body_0|>
<|body_start_1|>
list = DisplayList()
types = self.aq_inner.aq_parent.getProposalTypes()
for type in types:
... | What used to be a PLIP. | PSCImprovementProposal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PSCImprovementProposal:
"""What used to be a PLIP."""
def setBranch(self, value):
"""Set the repository branch, stripping off whitespace and any trailing slashes"""
<|body_0|>
def getProposalTypesVocab(self):
"""Get the allowed proposal types."""
<|body_1... | stack_v2_sparse_classes_10k_train_005566 | 10,955 | no_license | [
{
"docstring": "Set the repository branch, stripping off whitespace and any trailing slashes",
"name": "setBranch",
"signature": "def setBranch(self, value)"
},
{
"docstring": "Get the allowed proposal types.",
"name": "getProposalTypesVocab",
"signature": "def getProposalTypesVocab(self... | 3 | stack_v2_sparse_classes_30k_train_001523 | Implement the Python class `PSCImprovementProposal` described below.
Class description:
What used to be a PLIP.
Method signatures and docstrings:
- def setBranch(self, value): Set the repository branch, stripping off whitespace and any trailing slashes
- def getProposalTypesVocab(self): Get the allowed proposal types... | Implement the Python class `PSCImprovementProposal` described below.
Class description:
What used to be a PLIP.
Method signatures and docstrings:
- def setBranch(self, value): Set the repository branch, stripping off whitespace and any trailing slashes
- def getProposalTypesVocab(self): Get the allowed proposal types... | 8a7bdbdb98c3f9fc1073c6061cd2d3a0ec80caf5 | <|skeleton|>
class PSCImprovementProposal:
"""What used to be a PLIP."""
def setBranch(self, value):
"""Set the repository branch, stripping off whitespace and any trailing slashes"""
<|body_0|>
def getProposalTypesVocab(self):
"""Get the allowed proposal types."""
<|body_1... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PSCImprovementProposal:
"""What used to be a PLIP."""
def setBranch(self, value):
"""Set the repository branch, stripping off whitespace and any trailing slashes"""
value = value.strip()
while value.endswith('/'):
value = value[:-1]
self.getField('branch').set(... | the_stack_v2_python_sparse | buildout-cache/eggs/Products.PloneSoftwareCenter-1.6.4-py2.7.egg/Products/PloneSoftwareCenter/content/proposal.py | renansfs/Plone_SP | train | 0 |
4dbe354bcbb961bd1170a72e3f0b30afc0d11572 | [
"instance, version = more_data\nif self.INSTANCE is not None and self.INSTANCE != instance:\n raise ValueError('invalid instance {0} for {1}'.format(instance, self))\nelif self.INSTANCE is not None and instance not in (0, 1):\n try:\n min_val, max_val = INSTANCE_EXCEPTIONS[self.type]\n is_ok = m... | <|body_start_0|>
instance, version = more_data
if self.INSTANCE is not None and self.INSTANCE != instance:
raise ValueError('invalid instance {0} for {1}'.format(instance, self))
elif self.INSTANCE is not None and instance not in (0, 1):
try:
min_val, max_... | A Record within a ppt file; has instance and version fields | PptRecord | [
"MIT",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PptRecord:
"""A Record within a ppt file; has instance and version fields"""
def finish_constructing(self, more_data):
"""check and save instance and version"""
<|body_0|>
def _type_str(self):
"""helper for __str__, base implementation"""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k_train_005567 | 29,559 | permissive | [
{
"docstring": "check and save instance and version",
"name": "finish_constructing",
"signature": "def finish_constructing(self, more_data)"
},
{
"docstring": "helper for __str__, base implementation",
"name": "_type_str",
"signature": "def _type_str(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000181 | Implement the Python class `PptRecord` described below.
Class description:
A Record within a ppt file; has instance and version fields
Method signatures and docstrings:
- def finish_constructing(self, more_data): check and save instance and version
- def _type_str(self): helper for __str__, base implementation | Implement the Python class `PptRecord` described below.
Class description:
A Record within a ppt file; has instance and version fields
Method signatures and docstrings:
- def finish_constructing(self, more_data): check and save instance and version
- def _type_str(self): helper for __str__, base implementation
<|ske... | fb4546ec1be5f46d53856161e46ea53d7b7e532a | <|skeleton|>
class PptRecord:
"""A Record within a ppt file; has instance and version fields"""
def finish_constructing(self, more_data):
"""check and save instance and version"""
<|body_0|>
def _type_str(self):
"""helper for __str__, base implementation"""
<|body_1|>
<|en... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PptRecord:
"""A Record within a ppt file; has instance and version fields"""
def finish_constructing(self, more_data):
"""check and save instance and version"""
instance, version = more_data
if self.INSTANCE is not None and self.INSTANCE != instance:
raise ValueError('... | the_stack_v2_python_sparse | oletools/ppt_record_parser.py | decalage2/oletools | train | 2,601 |
71a15946fd8337a225ed43f2b13fb68057be0f2e | [
"def helper(node):\n if not node:\n return ''\n return helper(node.left) + ',' + helper(node.right) + ',' + str(node.val)\nres = helper(root)\nprint(res)\nreturn res",
"def helper(lower, upper):\n if not values or values[-1] < lower or values[-1] > upper:\n return None\n val = values.pop... | <|body_start_0|>
def helper(node):
if not node:
return ''
return helper(node.left) + ',' + helper(node.right) + ',' + str(node.val)
res = helper(root)
print(res)
return res
<|end_body_0|>
<|body_start_1|>
def helper(lower, upper):
... | 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_10k_train_005568 | 1,280 | 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 | 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:... | 5b14b6f42baf59b04cbcc8e115df4272029b64c8 | <|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_10k | 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 helper(node):
if not node:
return ''
return helper(node.left) + ',' + helper(node.right) + ',' + str(node.val)
res = helper(root)
... | the_stack_v2_python_sparse | LeetCode/0449.Serialize-And-Deserialize-Bst/Serialize-And-Deserialize-Bst.py | htingwang/HandsOnAlgoDS | train | 12 | |
ae79bf3327ff9e665d8177d85461e20ef100b9ce | [
"self.last_day_num_job_errors = last_day_num_job_errors\nself.last_day_num_job_runs = last_day_num_job_runs\nself.last_day_num_job_sla_violations = last_day_num_job_sla_violations\nself.num_job_running = num_job_running\nself.objects_protected_by_policy = objects_protected_by_policy",
"if dictionary is None:\n ... | <|body_start_0|>
self.last_day_num_job_errors = last_day_num_job_errors
self.last_day_num_job_runs = last_day_num_job_runs
self.last_day_num_job_sla_violations = last_day_num_job_sla_violations
self.num_job_running = num_job_running
self.objects_protected_by_policy = objects_prot... | Implementation of the 'JobRunsTile' model. Jon Runs information. Attributes: last_day_num_job_errors (int): Number of Error runs in the last 24 hours. last_day_num_job_runs (int): Number of Job Runs in the last 24 hours. last_day_num_job_sla_violations (int): Number of SLA Violations in the last 24 hours. num_job_runni... | JobRunsTile | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobRunsTile:
"""Implementation of the 'JobRunsTile' model. Jon Runs information. Attributes: last_day_num_job_errors (int): Number of Error runs in the last 24 hours. last_day_num_job_runs (int): Number of Job Runs in the last 24 hours. last_day_num_job_sla_violations (int): Number of SLA Violati... | stack_v2_sparse_classes_10k_train_005569 | 3,291 | permissive | [
{
"docstring": "Constructor for the JobRunsTile class",
"name": "__init__",
"signature": "def __init__(self, last_day_num_job_errors=None, last_day_num_job_runs=None, last_day_num_job_sla_violations=None, num_job_running=None, objects_protected_by_policy=None)"
},
{
"docstring": "Creates an inst... | 2 | null | Implement the Python class `JobRunsTile` described below.
Class description:
Implementation of the 'JobRunsTile' model. Jon Runs information. Attributes: last_day_num_job_errors (int): Number of Error runs in the last 24 hours. last_day_num_job_runs (int): Number of Job Runs in the last 24 hours. last_day_num_job_sla_... | Implement the Python class `JobRunsTile` described below.
Class description:
Implementation of the 'JobRunsTile' model. Jon Runs information. Attributes: last_day_num_job_errors (int): Number of Error runs in the last 24 hours. last_day_num_job_runs (int): Number of Job Runs in the last 24 hours. last_day_num_job_sla_... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class JobRunsTile:
"""Implementation of the 'JobRunsTile' model. Jon Runs information. Attributes: last_day_num_job_errors (int): Number of Error runs in the last 24 hours. last_day_num_job_runs (int): Number of Job Runs in the last 24 hours. last_day_num_job_sla_violations (int): Number of SLA Violati... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class JobRunsTile:
"""Implementation of the 'JobRunsTile' model. Jon Runs information. Attributes: last_day_num_job_errors (int): Number of Error runs in the last 24 hours. last_day_num_job_runs (int): Number of Job Runs in the last 24 hours. last_day_num_job_sla_violations (int): Number of SLA Violations in the la... | the_stack_v2_python_sparse | cohesity_management_sdk/models/job_runs_tile.py | cohesity/management-sdk-python | train | 24 |
2006349a88ac9f86999dbcd899d206755ed8d7df | [
"related_models = [f.related_model for f in Cell._meta.get_fields() if f.one_to_one]\nrelated_qs = [cls.objects.filter(cell=self) for cls in related_models if len(cls.objects.filter(cell=self)) > 0]\nif len(related_qs) > 1:\n raise DashBoardException('Cell data with id %d assosiated with multiple Cell types' % s... | <|body_start_0|>
related_models = [f.related_model for f in Cell._meta.get_fields() if f.one_to_one]
related_qs = [cls.objects.filter(cell=self) for cls in related_models if len(cls.objects.filter(cell=self)) > 0]
if len(related_qs) > 1:
raise DashBoardException('Cell data with id %d... | Cell | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cell:
def get_related_object(self):
"""Get the related model instance object for this model via a onetoone relationship."""
<|body_0|>
def get_related_model(cls, name):
"""Given a name, get the related model that matches the name"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_10k_train_005570 | 2,344 | no_license | [
{
"docstring": "Get the related model instance object for this model via a onetoone relationship.",
"name": "get_related_object",
"signature": "def get_related_object(self)"
},
{
"docstring": "Given a name, get the related model that matches the name",
"name": "get_related_model",
"signa... | 2 | stack_v2_sparse_classes_30k_train_001246 | Implement the Python class `Cell` described below.
Class description:
Implement the Cell class.
Method signatures and docstrings:
- def get_related_object(self): Get the related model instance object for this model via a onetoone relationship.
- def get_related_model(cls, name): Given a name, get the related model th... | Implement the Python class `Cell` described below.
Class description:
Implement the Cell class.
Method signatures and docstrings:
- def get_related_object(self): Get the related model instance object for this model via a onetoone relationship.
- def get_related_model(cls, name): Given a name, get the related model th... | 825c64f0148767883272c5be1e867660c969ab56 | <|skeleton|>
class Cell:
def get_related_object(self):
"""Get the related model instance object for this model via a onetoone relationship."""
<|body_0|>
def get_related_model(cls, name):
"""Given a name, get the related model that matches the name"""
<|body_1|>
<|end_skeleton... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Cell:
def get_related_object(self):
"""Get the related model instance object for this model via a onetoone relationship."""
related_models = [f.related_model for f in Cell._meta.get_fields() if f.one_to_one]
related_qs = [cls.objects.filter(cell=self) for cls in related_models if len(c... | the_stack_v2_python_sparse | p3app/dash_board/models.py | vdazrat/id8 | train | 0 | |
d223d1b46c524734f9d1613f821b143e6909a891 | [
"if stdin is None:\n stdin = sys.stdin.fileno()\nelif hasattr(stdin, 'fileno'):\n stdin = stdin.fileno()\nif stdout is None:\n stdout = sys.stdout.fileno()\nelif hasattr(stdout, 'fileno'):\n stdout = stdout.fileno()\nwith self._client() as podman:\n attach = podman.GetAttachSockets(self._id)\nio_sock... | <|body_start_0|>
if stdin is None:
stdin = sys.stdin.fileno()
elif hasattr(stdin, 'fileno'):
stdin = stdin.fileno()
if stdout is None:
stdout = sys.stdout.fileno()
elif hasattr(stdout, 'fileno'):
stdout = stdout.fileno()
with self._... | Publish attach() for inclusion in Container class. | Mixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Mixin:
"""Publish attach() for inclusion in Container class."""
def attach(self, eot=4, stdin=None, stdout=None):
"""Attach to container's PID1 stdin and stdout. stderr is ignored. PseudoTTY work is done in start()."""
<|body_0|>
def resize_handler(self):
"""Send... | stack_v2_sparse_classes_10k_train_005571 | 2,635 | permissive | [
{
"docstring": "Attach to container's PID1 stdin and stdout. stderr is ignored. PseudoTTY work is done in start().",
"name": "attach",
"signature": "def attach(self, eot=4, stdin=None, stdout=None)"
},
{
"docstring": "Send the new window size to conmon.",
"name": "resize_handler",
"signa... | 3 | null | Implement the Python class `Mixin` described below.
Class description:
Publish attach() for inclusion in Container class.
Method signatures and docstrings:
- def attach(self, eot=4, stdin=None, stdout=None): Attach to container's PID1 stdin and stdout. stderr is ignored. PseudoTTY work is done in start().
- def resiz... | Implement the Python class `Mixin` described below.
Class description:
Publish attach() for inclusion in Container class.
Method signatures and docstrings:
- def attach(self, eot=4, stdin=None, stdout=None): Attach to container's PID1 stdin and stdout. stderr is ignored. PseudoTTY work is done in start().
- def resiz... | ce2a8734f8b4203ec38078207297062263c49f6f | <|skeleton|>
class Mixin:
"""Publish attach() for inclusion in Container class."""
def attach(self, eot=4, stdin=None, stdout=None):
"""Attach to container's PID1 stdin and stdout. stderr is ignored. PseudoTTY work is done in start()."""
<|body_0|>
def resize_handler(self):
"""Send... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Mixin:
"""Publish attach() for inclusion in Container class."""
def attach(self, eot=4, stdin=None, stdout=None):
"""Attach to container's PID1 stdin and stdout. stderr is ignored. PseudoTTY work is done in start()."""
if stdin is None:
stdin = sys.stdin.fileno()
elif ... | the_stack_v2_python_sparse | tobiko/podman/_podman1/libs/_containers_attach.py | FedericoRessi/tobiko | train | 1 |
e94417b36416adbfe227ab0f03b7116556e310e3 | [
"self.common_acl = common_acl\nself.grant_vec = grant_vec\nself.keystone_acl = keystone_acl\nself.swift_read_acl = swift_read_acl\nself.swift_write_acl = swift_write_acl",
"if dictionary is None:\n return None\ncommon_acl = cohesity_management_sdk.models.common_acl_proto.CommonACLProto.from_dictionary(dictiona... | <|body_start_0|>
self.common_acl = common_acl
self.grant_vec = grant_vec
self.keystone_acl = keystone_acl
self.swift_read_acl = swift_read_acl
self.swift_write_acl = swift_write_acl
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
co... | Implementation of the 'ACLProto' model. Protobuf that describes the access control list (ACL) permissions for a bucket or for an object. Attributes: common_acl (CommonACLProto): CommonACL of the Swift container. grant_vec (list of ACLProto_Grant): TODO: Type description here. keystone_acl (KeystoneACLProto): KeystoneAC... | ACLProto | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ACLProto:
"""Implementation of the 'ACLProto' model. Protobuf that describes the access control list (ACL) permissions for a bucket or for an object. Attributes: common_acl (CommonACLProto): CommonACL of the Swift container. grant_vec (list of ACLProto_Grant): TODO: Type description here. keyston... | stack_v2_sparse_classes_10k_train_005572 | 3,081 | permissive | [
{
"docstring": "Constructor for the ACLProto class",
"name": "__init__",
"signature": "def __init__(self, common_acl=None, grant_vec=None, keystone_acl=None, swift_read_acl=None, swift_write_acl=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dicti... | 2 | null | Implement the Python class `ACLProto` described below.
Class description:
Implementation of the 'ACLProto' model. Protobuf that describes the access control list (ACL) permissions for a bucket or for an object. Attributes: common_acl (CommonACLProto): CommonACL of the Swift container. grant_vec (list of ACLProto_Grant... | Implement the Python class `ACLProto` described below.
Class description:
Implementation of the 'ACLProto' model. Protobuf that describes the access control list (ACL) permissions for a bucket or for an object. Attributes: common_acl (CommonACLProto): CommonACL of the Swift container. grant_vec (list of ACLProto_Grant... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ACLProto:
"""Implementation of the 'ACLProto' model. Protobuf that describes the access control list (ACL) permissions for a bucket or for an object. Attributes: common_acl (CommonACLProto): CommonACL of the Swift container. grant_vec (list of ACLProto_Grant): TODO: Type description here. keyston... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class ACLProto:
"""Implementation of the 'ACLProto' model. Protobuf that describes the access control list (ACL) permissions for a bucket or for an object. Attributes: common_acl (CommonACLProto): CommonACL of the Swift container. grant_vec (list of ACLProto_Grant): TODO: Type description here. keystone_acl (Keysto... | the_stack_v2_python_sparse | cohesity_management_sdk/models/acl_proto.py | cohesity/management-sdk-python | train | 24 |
df1ef78c6479f5da68addb41e3f82c2f3815efa1 | [
"if not v:\n raise ValueError('courier_id is required')\nif type(v) != int:\n raise ValueError('courier_id must be integer')\nif v < 0 or v > 9223372036854775807:\n raise ValueError('courier_id out of allowed range')\nreturn v",
"excess_fields = set(values.keys()).difference({'courier_id'})\nif excess_fi... | <|body_start_0|>
if not v:
raise ValueError('courier_id is required')
if type(v) != int:
raise ValueError('courier_id must be integer')
if v < 0 or v > 9223372036854775807:
raise ValueError('courier_id out of allowed range')
return v
<|end_body_0|>
<|... | Описывает стрктуру данных для назначения заказов | AssignDataModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AssignDataModel:
"""Описывает стрктуру данных для назначения заказов"""
def validate_courier_id(cls, v: int) -> int:
"""Валидирует courier_id"""
<|body_0|>
def validate_excess_fields(cls, values: Dict) -> Dict:
"""Валидирует отсутствие лишних полей"""
<|b... | stack_v2_sparse_classes_10k_train_005573 | 8,762 | no_license | [
{
"docstring": "Валидирует courier_id",
"name": "validate_courier_id",
"signature": "def validate_courier_id(cls, v: int) -> int"
},
{
"docstring": "Валидирует отсутствие лишних полей",
"name": "validate_excess_fields",
"signature": "def validate_excess_fields(cls, values: Dict) -> Dict"... | 2 | stack_v2_sparse_classes_30k_train_001538 | Implement the Python class `AssignDataModel` described below.
Class description:
Описывает стрктуру данных для назначения заказов
Method signatures and docstrings:
- def validate_courier_id(cls, v: int) -> int: Валидирует courier_id
- def validate_excess_fields(cls, values: Dict) -> Dict: Валидирует отсутствие лишних... | Implement the Python class `AssignDataModel` described below.
Class description:
Описывает стрктуру данных для назначения заказов
Method signatures and docstrings:
- def validate_courier_id(cls, v: int) -> int: Валидирует courier_id
- def validate_excess_fields(cls, values: Dict) -> Dict: Валидирует отсутствие лишних... | f1a908e5d6b30b826c38d24c52a721764f056fde | <|skeleton|>
class AssignDataModel:
"""Описывает стрктуру данных для назначения заказов"""
def validate_courier_id(cls, v: int) -> int:
"""Валидирует courier_id"""
<|body_0|>
def validate_excess_fields(cls, values: Dict) -> Dict:
"""Валидирует отсутствие лишних полей"""
<|b... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AssignDataModel:
"""Описывает стрктуру данных для назначения заказов"""
def validate_courier_id(cls, v: int) -> int:
"""Валидирует courier_id"""
if not v:
raise ValueError('courier_id is required')
if type(v) != int:
raise ValueError('courier_id must be int... | the_stack_v2_python_sparse | candyapi/orders/validators.py | IntAlgambra/candyapi | train | 0 |
650684a8f27da05721aa830d84e3adbd3e2b8d0c | [
"weight_scale_factor, n = (None, None)\nlogger.debug(f'input: {input}')\nwith torch.no_grad():\n if mode == quantization.QType.DETER:\n binarized_weight = deterministic_quantize(weight)\n s = torch.sum(torch.abs(weight))\n n = prod(weight.shape)\n weight_scale_factor = s / n\n elif... | <|body_start_0|>
weight_scale_factor, n = (None, None)
logger.debug(f'input: {input}')
with torch.no_grad():
if mode == quantization.QType.DETER:
binarized_weight = deterministic_quantize(weight)
s = torch.sum(torch.abs(weight))
n = pro... | binarized tensor를 입력으로 하여, scale factor와 binarized weights로 linear 연산을 수행하는 operation function Binarize operation method는 BinaryConnect의 `Deterministic`과 `Stochastic` method를 사용하며, scale factor와 weights를 binarize하는 방법은 XNOR-Net의 method를 사용함. .. note: Weights binarize method는 forward에서 binarized wegiths를 사용하고, gradient ... | BinarizedLinear | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinarizedLinear:
"""binarized tensor를 입력으로 하여, scale factor와 binarized weights로 linear 연산을 수행하는 operation function Binarize operation method는 BinaryConnect의 `Deterministic`과 `Stochastic` method를 사용하며, scale factor와 weights를 binarize하는 방법은 XNOR-Net의 method를 사용함. .. note: Weights binarize method는 f... | stack_v2_sparse_classes_10k_train_005574 | 5,021 | permissive | [
{
"docstring": "Real-value weights를 binarized weight와 scale factor로 변환한다. binarized tensor이를입력으로 받으면 이를 다음과 같이 계산한다. .. math:: output=I_{b} \\\\odot W_{b} \\\\times \\\\alpha_{W_{b}} Args: ctx (object): forward/backward간 정보를 공유하기위한 데이터 컨테이너 input (torch.Tensor): binairzed tensor weight (torch.Tensor): :math:`(o... | 2 | stack_v2_sparse_classes_30k_train_004030 | Implement the Python class `BinarizedLinear` described below.
Class description:
binarized tensor를 입력으로 하여, scale factor와 binarized weights로 linear 연산을 수행하는 operation function Binarize operation method는 BinaryConnect의 `Deterministic`과 `Stochastic` method를 사용하며, scale factor와 weights를 binarize하는 방법은 XNOR-Net의 method를 사... | Implement the Python class `BinarizedLinear` described below.
Class description:
binarized tensor를 입력으로 하여, scale factor와 binarized weights로 linear 연산을 수행하는 operation function Binarize operation method는 BinaryConnect의 `Deterministic`과 `Stochastic` method를 사용하며, scale factor와 weights를 binarize하는 방법은 XNOR-Net의 method를 사... | 2c02429d6ee052fe70a17ced4755d5814a4ef60a | <|skeleton|>
class BinarizedLinear:
"""binarized tensor를 입력으로 하여, scale factor와 binarized weights로 linear 연산을 수행하는 operation function Binarize operation method는 BinaryConnect의 `Deterministic`과 `Stochastic` method를 사용하며, scale factor와 weights를 binarize하는 방법은 XNOR-Net의 method를 사용함. .. note: Weights binarize method는 f... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BinarizedLinear:
"""binarized tensor를 입력으로 하여, scale factor와 binarized weights로 linear 연산을 수행하는 operation function Binarize operation method는 BinaryConnect의 `Deterministic`과 `Stochastic` method를 사용하며, scale factor와 weights를 binarize하는 방법은 XNOR-Net의 method를 사용함. .. note: Weights binarize method는 forward에서 bina... | the_stack_v2_python_sparse | src/ops/binarized_linear.py | ssaru/pytorch-XNOR-YOLO | train | 1 |
1ab9e1704ba27d6d4d61b2718f9d1c53d61571ba | [
"if not os.path.exists(base_path):\n os.makedirs(base_path)\nfor fn in NAIPTileIndex.INDEX_FNS:\n if not os.path.exists(os.path.join(base_path, fn)):\n download_url(NAIPTileIndex.NAIP_INDEX_BLOB_ROOT + fn, os.path.join(base_path, fn), verbose)\nself.base_path = base_path\nself.tile_rtree = rtree.index.... | <|body_start_0|>
if not os.path.exists(base_path):
os.makedirs(base_path)
for fn in NAIPTileIndex.INDEX_FNS:
if not os.path.exists(os.path.join(base_path, fn)):
download_url(NAIPTileIndex.NAIP_INDEX_BLOB_ROOT + fn, os.path.join(base_path, fn), verbose)
sel... | Utility class for performing NAIP tile lookups by location | NAIPTileIndex | [
"MIT",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NAIPTileIndex:
"""Utility class for performing NAIP tile lookups by location"""
def __init__(self, base_path, verbose=False):
"""Loads the tile index into memory (~400 MB) for use by `self.lookup()`. Downloads the index files from the blob container if they do not exist in the `base_... | stack_v2_sparse_classes_10k_train_005575 | 5,605 | permissive | [
{
"docstring": "Loads the tile index into memory (~400 MB) for use by `self.lookup()`. Downloads the index files from the blob container if they do not exist in the `base_path/` directory. Args: base_path (str): The path on the local system to look for/store the three files that make up the tile index. This pat... | 3 | stack_v2_sparse_classes_30k_train_007157 | Implement the Python class `NAIPTileIndex` described below.
Class description:
Utility class for performing NAIP tile lookups by location
Method signatures and docstrings:
- def __init__(self, base_path, verbose=False): Loads the tile index into memory (~400 MB) for use by `self.lookup()`. Downloads the index files f... | Implement the Python class `NAIPTileIndex` described below.
Class description:
Utility class for performing NAIP tile lookups by location
Method signatures and docstrings:
- def __init__(self, base_path, verbose=False): Loads the tile index into memory (~400 MB) for use by `self.lookup()`. Downloads the index files f... | ff141cd6b7a7b504c18b0987fbfd58ec6552df43 | <|skeleton|>
class NAIPTileIndex:
"""Utility class for performing NAIP tile lookups by location"""
def __init__(self, base_path, verbose=False):
"""Loads the tile index into memory (~400 MB) for use by `self.lookup()`. Downloads the index files from the blob container if they do not exist in the `base_... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class NAIPTileIndex:
"""Utility class for performing NAIP tile lookups by location"""
def __init__(self, base_path, verbose=False):
"""Loads the tile index into memory (~400 MB) for use by `self.lookup()`. Downloads the index files from the blob container if they do not exist in the `base_path/` direct... | the_stack_v2_python_sparse | geospatial/data/NAIPTileIndex.py | microsoft/ai4eutils | train | 40 |
a6cb4bd1c560abaad1a0deaffc2214891c6453fa | [
"super(TemplateAngleEmbedder, self).__init__()\nself.c_out = c_out\nself.c_in = c_in\nself.linear_1 = Linear(self.c_in, self.c_out, init='relu')\nself.relu = nn.ReLU()\nself.linear_2 = Linear(self.c_out, self.c_out, init='relu')",
"x = self.linear_1(x)\nx = self.relu(x)\nx = self.linear_2(x)\nreturn x"
] | <|body_start_0|>
super(TemplateAngleEmbedder, self).__init__()
self.c_out = c_out
self.c_in = c_in
self.linear_1 = Linear(self.c_in, self.c_out, init='relu')
self.relu = nn.ReLU()
self.linear_2 = Linear(self.c_out, self.c_out, init='relu')
<|end_body_0|>
<|body_start_1|>... | Embeds the "template_angle_feat" feature. Implements Algorithm 2, line 7. | TemplateAngleEmbedder | [
"Apache-2.0",
"CC-BY-4.0",
"LicenseRef-scancode-other-permissive",
"CC-BY-NC-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateAngleEmbedder:
"""Embeds the "template_angle_feat" feature. Implements Algorithm 2, line 7."""
def __init__(self, c_in: int, c_out: int, **kwargs):
"""Args: c_in: Final dimension of "template_angle_feat" c_out: Output channel dimension"""
<|body_0|>
def forward(s... | stack_v2_sparse_classes_10k_train_005576 | 9,577 | permissive | [
{
"docstring": "Args: c_in: Final dimension of \"template_angle_feat\" c_out: Output channel dimension",
"name": "__init__",
"signature": "def __init__(self, c_in: int, c_out: int, **kwargs)"
},
{
"docstring": "Args: x: [*, N_templ, N_res, c_in] \"template_angle_feat\" features Returns: x: [*, N... | 2 | stack_v2_sparse_classes_30k_train_002229 | Implement the Python class `TemplateAngleEmbedder` described below.
Class description:
Embeds the "template_angle_feat" feature. Implements Algorithm 2, line 7.
Method signatures and docstrings:
- def __init__(self, c_in: int, c_out: int, **kwargs): Args: c_in: Final dimension of "template_angle_feat" c_out: Output c... | Implement the Python class `TemplateAngleEmbedder` described below.
Class description:
Embeds the "template_angle_feat" feature. Implements Algorithm 2, line 7.
Method signatures and docstrings:
- def __init__(self, c_in: int, c_out: int, **kwargs): Args: c_in: Final dimension of "template_angle_feat" c_out: Output c... | 2134cc09b3994b6280e6e3c569dd7d761e4da7a0 | <|skeleton|>
class TemplateAngleEmbedder:
"""Embeds the "template_angle_feat" feature. Implements Algorithm 2, line 7."""
def __init__(self, c_in: int, c_out: int, **kwargs):
"""Args: c_in: Final dimension of "template_angle_feat" c_out: Output channel dimension"""
<|body_0|>
def forward(s... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TemplateAngleEmbedder:
"""Embeds the "template_angle_feat" feature. Implements Algorithm 2, line 7."""
def __init__(self, c_in: int, c_out: int, **kwargs):
"""Args: c_in: Final dimension of "template_angle_feat" c_out: Output channel dimension"""
super(TemplateAngleEmbedder, self).__init_... | the_stack_v2_python_sparse | openfold/model/embedders.py | aqlaboratory/openfold | train | 2,033 |
1c7cc4ed9032d5b9e3b050b369f0c068b0598dcb | [
"self.error = error\nself.source = source\nself.stats = stats\nself.status = status\nself.task_end_time_usecs = task_end_time_usecs\nself.task_start_time_usecs = task_start_time_usecs",
"if dictionary is None:\n return None\nerror = dictionary.get('error')\nsource = cohesity_management_sdk.models.protection_so... | <|body_start_0|>
self.error = error
self.source = source
self.stats = stats
self.status = status
self.task_end_time_usecs = task_end_time_usecs
self.task_start_time_usecs = task_start_time_usecs
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
r... | Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is populated when the status is equal to 'kFailure'. sou... | CopySnapshotTaskStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CopySnapshotTaskStatus:
"""Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is pop... | stack_v2_sparse_classes_10k_train_005577 | 4,290 | permissive | [
{
"docstring": "Constructor for the CopySnapshotTaskStatus class",
"name": "__init__",
"signature": "def __init__(self, error=None, source=None, stats=None, status=None, task_end_time_usecs=None, task_start_time_usecs=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary ... | 2 | null | Implement the Python class `CopySnapshotTaskStatus` described below.
Class description:
Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) whi... | Implement the Python class `CopySnapshotTaskStatus` described below.
Class description:
Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) whi... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class CopySnapshotTaskStatus:
"""Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is pop... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CopySnapshotTaskStatus:
"""Implementation of the 'CopySnapshotTaskStatus' model. Specifies the status of the copy task that copies the snapshot of a Protection Source object to a target. Attributes: error (string): Specifies if an error occurred (if any) while running this task. This field is populated when t... | the_stack_v2_python_sparse | cohesity_management_sdk/models/copy_snapshot_task_status.py | cohesity/management-sdk-python | train | 24 |
5163a39a3ba3038af6cae509580ddedbda2cbc1a | [
"params = dict(((key, val) for key, val in request.QUERY_PARAMS.iteritems()))\nparams['image_id'] = image_id\nform = MultiGetForm(params)\nif not form.is_valid():\n raise BadRequestException()\nreturn Response(form.submit(request))",
"params = dict(((key, val) for key, val in request.DATA.iteritems()))\nparams... | <|body_start_0|>
params = dict(((key, val) for key, val in request.QUERY_PARAMS.iteritems()))
params['image_id'] = image_id
form = MultiGetForm(params)
if not form.is_valid():
raise BadRequestException()
return Response(form.submit(request))
<|end_body_0|>
<|body_sta... | Class for rendering the view for creating TagGroups and searching through the TagGroups. | TagGroupList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagGroupList:
"""Class for rendering the view for creating TagGroups and searching through the TagGroups."""
def get(self, request, image_id):
"""Method for getting multiple TagGroups either through search or general listing."""
<|body_0|>
def post(self, request, image_i... | stack_v2_sparse_classes_10k_train_005578 | 2,816 | no_license | [
{
"docstring": "Method for getting multiple TagGroups either through search or general listing.",
"name": "get",
"signature": "def get(self, request, image_id)"
},
{
"docstring": "Method for creating a new TagGroup.",
"name": "post",
"signature": "def post(self, request, image_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_007148 | Implement the Python class `TagGroupList` described below.
Class description:
Class for rendering the view for creating TagGroups and searching through the TagGroups.
Method signatures and docstrings:
- def get(self, request, image_id): Method for getting multiple TagGroups either through search or general listing.
-... | Implement the Python class `TagGroupList` described below.
Class description:
Class for rendering the view for creating TagGroups and searching through the TagGroups.
Method signatures and docstrings:
- def get(self, request, image_id): Method for getting multiple TagGroups either through search or general listing.
-... | 22c1ce3c5a8e4ed99c2f014672d60ad3c5a4003c | <|skeleton|>
class TagGroupList:
"""Class for rendering the view for creating TagGroups and searching through the TagGroups."""
def get(self, request, image_id):
"""Method for getting multiple TagGroups either through search or general listing."""
<|body_0|>
def post(self, request, image_i... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TagGroupList:
"""Class for rendering the view for creating TagGroups and searching through the TagGroups."""
def get(self, request, image_id):
"""Method for getting multiple TagGroups either through search or general listing."""
params = dict(((key, val) for key, val in request.QUERY_PARA... | the_stack_v2_python_sparse | biodig/rest/v2/TagGroups/views.py | asmariyaz23/BioDIG | train | 0 |
a968df34f71aabf553e511073d426d30dda445c9 | [
"original_ents = [{'ID': 'test-ID', 'Type': 'test-Type', 'Metadata': {'tags': 'test-tags', 'category': 'test-category', 'created': 'test-created', 'modified': 'test-modified'}}]\noutput_ents = {'Entry': [{'ID': 'test-ID', 'Type': 'test-Type', 'Tags': 'test-tags', 'Category': 'test-category', 'Created': 'test-create... | <|body_start_0|>
original_ents = [{'ID': 'test-ID', 'Type': 'test-Type', 'Metadata': {'tags': 'test-tags', 'category': 'test-category', 'created': 'test-created', 'modified': 'test-modified'}}]
output_ents = {'Entry': [{'ID': 'test-ID', 'Type': 'test-Type', 'Tags': 'test-tags', 'Category': 'test-categor... | TestGetEntries | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestGetEntries:
def test_main(self, mocker):
"""Given: - A entry returns from getEntries. When: - No argument parameters are provided. Then: - The fields are being parsed properly in to context."""
<|body_0|>
def test_main_no_ents(self, mocker):
"""Given: - No entrie... | stack_v2_sparse_classes_10k_train_005579 | 3,454 | permissive | [
{
"docstring": "Given: - A entry returns from getEntries. When: - No argument parameters are provided. Then: - The fields are being parsed properly in to context.",
"name": "test_main",
"signature": "def test_main(self, mocker)"
},
{
"docstring": "Given: - No entries returns from getEntries. Whe... | 3 | stack_v2_sparse_classes_30k_train_003730 | Implement the Python class `TestGetEntries` described below.
Class description:
Implement the TestGetEntries class.
Method signatures and docstrings:
- def test_main(self, mocker): Given: - A entry returns from getEntries. When: - No argument parameters are provided. Then: - The fields are being parsed properly in to... | Implement the Python class `TestGetEntries` described below.
Class description:
Implement the TestGetEntries class.
Method signatures and docstrings:
- def test_main(self, mocker): Given: - A entry returns from getEntries. When: - No argument parameters are provided. Then: - The fields are being parsed properly in to... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class TestGetEntries:
def test_main(self, mocker):
"""Given: - A entry returns from getEntries. When: - No argument parameters are provided. Then: - The fields are being parsed properly in to context."""
<|body_0|>
def test_main_no_ents(self, mocker):
"""Given: - No entrie... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestGetEntries:
def test_main(self, mocker):
"""Given: - A entry returns from getEntries. When: - No argument parameters are provided. Then: - The fields are being parsed properly in to context."""
original_ents = [{'ID': 'test-ID', 'Type': 'test-Type', 'Metadata': {'tags': 'test-tags', 'categ... | the_stack_v2_python_sparse | Packs/CommonScripts/Scripts/GetEntries/GetEntries_test.py | demisto/content | train | 1,023 | |
f86d102d5d66e59c6f41a664a2ca48a3920d5eb0 | [
"if 1 == ver:\n return True\nelse:\n return False",
"if isinstance(data, SerializableObject) is False:\n raise UnsupportedTypeException()\ndataStream = ApplicationSerializer.ApplicationSerializer.serialize(data, writeMeta=True)\nDS = DigitalSignature(dataStream)\nDS.sign()\ndsStream = DS.serialize()\ncrc... | <|body_start_0|>
if 1 == ver:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
if isinstance(data, SerializableObject) is False:
raise UnsupportedTypeException()
dataStream = ApplicationSerializer.ApplicationSerializer.serialize(data, wr... | Description: An instance of this class is used to contruct/deconstruct messages sent to and received from the Lynx | MessageFactory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MessageFactory:
"""Description: An instance of this class is used to contruct/deconstruct messages sent to and received from the Lynx"""
def supportsMsgVersion(ver):
"""Description: This method validates the version information Arguments: ver (in, int) The version to validate Returns... | stack_v2_sparse_classes_10k_train_005580 | 3,196 | no_license | [
{
"docstring": "Description: This method validates the version information Arguments: ver (in, int) The version to validate Returns: bool True==valid version",
"name": "supportsMsgVersion",
"signature": "def supportsMsgVersion(ver)"
},
{
"docstring": "Description: This method serializes the data... | 3 | stack_v2_sparse_classes_30k_train_006776 | Implement the Python class `MessageFactory` described below.
Class description:
Description: An instance of this class is used to contruct/deconstruct messages sent to and received from the Lynx
Method signatures and docstrings:
- def supportsMsgVersion(ver): Description: This method validates the version information... | Implement the Python class `MessageFactory` described below.
Class description:
Description: An instance of this class is used to contruct/deconstruct messages sent to and received from the Lynx
Method signatures and docstrings:
- def supportsMsgVersion(ver): Description: This method validates the version information... | bdeeb78b58466ec8696d4fadb05051c1b06ef25e | <|skeleton|>
class MessageFactory:
"""Description: An instance of this class is used to contruct/deconstruct messages sent to and received from the Lynx"""
def supportsMsgVersion(ver):
"""Description: This method validates the version information Arguments: ver (in, int) The version to validate Returns... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class MessageFactory:
"""Description: An instance of this class is used to contruct/deconstruct messages sent to and received from the Lynx"""
def supportsMsgVersion(ver):
"""Description: This method validates the version information Arguments: ver (in, int) The version to validate Returns: bool True==... | the_stack_v2_python_sparse | src/DataTypes/MessageFactory.py | philliptay/nuclear-detection | train | 0 |
9ed3a748839efd3332f60186124b32c57035f82d | [
"user = context.get('user', None)\nviewing_user = context.get('viewing_user', None)\nif not viewing_user or not user.is_authenticated():\n return ''\nkeyid = self.gpg_key_id.get_value(viewing_user.username)\nsend_private_link = '<a href=\"\" title=\"%s;%s\" class=\"private_message\">%s</a>' % (viewing_user.usern... | <|body_start_0|>
user = context.get('user', None)
viewing_user = context.get('viewing_user', None)
if not viewing_user or not user.is_authenticated():
return ''
keyid = self.gpg_key_id.get_value(viewing_user.username)
send_private_link = '<a href="" title="%s;%s" clas... | With this plugin users can send a private and encrypted message to somebody, which will be shown only in the private timeline of that user. The message will be encrypted with GPG using a HTML extension currently only available in Khtml/Konqueror. Each user can access their private timeline with a link added by this plu... | PrivateTimelinePlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PrivateTimelinePlugin:
"""With this plugin users can send a private and encrypted message to somebody, which will be shown only in the private timeline of that user. The message will be encrypted with GPG using a HTML extension currently only available in Khtml/Konqueror. Each user can access the... | stack_v2_sparse_classes_10k_train_005581 | 3,475 | no_license | [
{
"docstring": "Shows a button to 'Send Private Message to <username>' in the headbar, next to \"(un)follow\" button",
"name": "headbar",
"signature": "def headbar(self, context)"
},
{
"docstring": "Shows a link to 'Send Private Message' in the sidebar when browsing a profile",
"name": "side... | 3 | stack_v2_sparse_classes_30k_train_007116 | Implement the Python class `PrivateTimelinePlugin` described below.
Class description:
With this plugin users can send a private and encrypted message to somebody, which will be shown only in the private timeline of that user. The message will be encrypted with GPG using a HTML extension currently only available in Kh... | Implement the Python class `PrivateTimelinePlugin` described below.
Class description:
With this plugin users can send a private and encrypted message to somebody, which will be shown only in the private timeline of that user. The message will be encrypted with GPG using a HTML extension currently only available in Kh... | a9eb05514e8788d7c290f88eae383c0f4d9179ad | <|skeleton|>
class PrivateTimelinePlugin:
"""With this plugin users can send a private and encrypted message to somebody, which will be shown only in the private timeline of that user. The message will be encrypted with GPG using a HTML extension currently only available in Khtml/Konqueror. Each user can access the... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class PrivateTimelinePlugin:
"""With this plugin users can send a private and encrypted message to somebody, which will be shown only in the private timeline of that user. The message will be encrypted with GPG using a HTML extension currently only available in Khtml/Konqueror. Each user can access their private ti... | the_stack_v2_python_sparse | contrib/privatetimeline/PrivateTimelinePlugin.py | lilac/totem | train | 0 |
2519e1703ef84943371b66707ded39c477ec4a9e | [
"if not isinstance(origin, math3d.VectorN) or not isinstance(direction, math3d.VectorN) or len(origin) != len(direction):\n raise ValueError(\"You must pass two equal-dimension VectorN's for the origin and direction.\")\nself.mOrigin = origin.copy()\nself.mDirection = direction.normalized()",
"if not isinstanc... | <|body_start_0|>
if not isinstance(origin, math3d.VectorN) or not isinstance(direction, math3d.VectorN) or len(origin) != len(direction):
raise ValueError("You must pass two equal-dimension VectorN's for the origin and direction.")
self.mOrigin = origin.copy()
self.mDirection = direc... | An n-dimensional ray [by definition a ray is an origin point and a direction | Ray | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ray:
"""An n-dimensional ray [by definition a ray is an origin point and a direction"""
def __init__(self, origin, direction):
""":param origin: the origin POSITION of the ray (a copy of the passed vector is created) :param direction: the DIRECTION of the ray (the vector passed in is... | stack_v2_sparse_classes_10k_train_005582 | 10,671 | no_license | [
{
"docstring": ":param origin: the origin POSITION of the ray (a copy of the passed vector is created) :param direction: the DIRECTION of the ray (the vector passed in is normalized) :return: N/A",
"name": "__init__",
"signature": "def __init__(self, origin, direction)"
},
{
"docstring": ":param... | 4 | stack_v2_sparse_classes_30k_train_002372 | Implement the Python class `Ray` described below.
Class description:
An n-dimensional ray [by definition a ray is an origin point and a direction
Method signatures and docstrings:
- def __init__(self, origin, direction): :param origin: the origin POSITION of the ray (a copy of the passed vector is created) :param dir... | Implement the Python class `Ray` described below.
Class description:
An n-dimensional ray [by definition a ray is an origin point and a direction
Method signatures and docstrings:
- def __init__(self, origin, direction): :param origin: the origin POSITION of the ray (a copy of the passed vector is created) :param dir... | 5916caa83fd57fd1400875d74ffff8e89b7bb0bc | <|skeleton|>
class Ray:
"""An n-dimensional ray [by definition a ray is an origin point and a direction"""
def __init__(self, origin, direction):
""":param origin: the origin POSITION of the ray (a copy of the passed vector is created) :param direction: the DIRECTION of the ray (the vector passed in is... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Ray:
"""An n-dimensional ray [by definition a ray is an origin point and a direction"""
def __init__(self, origin, direction):
""":param origin: the origin POSITION of the ray (a copy of the passed vector is created) :param direction: the DIRECTION of the ray (the vector passed in is normalized) ... | the_stack_v2_python_sparse | ConceptsOf3DGraphics/Lab05/objects3d.py | kjakar/Portfolio | train | 0 |
2cb9d8f7283ad29fff2a4732f8e29636e4e8ff2f | [
"num_cases, num_dim = X.shape\noutput_df = pd.DataFrame()\nfor dim in range(num_dim):\n dim_data = X.iloc[:, dim]\n out = self.row_wise_get_der(dim_data)\n output_df['der_dim_' + str(dim)] = pd.Series(out)\nreturn output_df",
"def get_der(x):\n der = []\n for i in range(1, len(x) - 1):\n der... | <|body_start_0|>
num_cases, num_dim = X.shape
output_df = pd.DataFrame()
for dim in range(num_dim):
dim_data = X.iloc[:, dim]
out = self.row_wise_get_der(dim_data)
output_df['der_dim_' + str(dim)] = pd.Series(out)
return output_df
<|end_body_0|>
<|bod... | Derivative slope transformer. | DerivativeSlopeTransformer | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DerivativeSlopeTransformer:
"""Derivative slope transformer."""
def _transform(self, X, y=None):
"""Transform X."""
<|body_0|>
def row_wise_get_der(X):
"""Get derivatives."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
num_cases, num_dim = X.sh... | stack_v2_sparse_classes_10k_train_005583 | 16,453 | permissive | [
{
"docstring": "Transform X.",
"name": "_transform",
"signature": "def _transform(self, X, y=None)"
},
{
"docstring": "Get derivatives.",
"name": "row_wise_get_der",
"signature": "def row_wise_get_der(X)"
}
] | 2 | stack_v2_sparse_classes_30k_train_001119 | Implement the Python class `DerivativeSlopeTransformer` described below.
Class description:
Derivative slope transformer.
Method signatures and docstrings:
- def _transform(self, X, y=None): Transform X.
- def row_wise_get_der(X): Get derivatives. | Implement the Python class `DerivativeSlopeTransformer` described below.
Class description:
Derivative slope transformer.
Method signatures and docstrings:
- def _transform(self, X, y=None): Transform X.
- def row_wise_get_der(X): Get derivatives.
<|skeleton|>
class DerivativeSlopeTransformer:
"""Derivative slop... | 70b2bfaaa597eb31bc3a1032366dcc0e1f4c8a9f | <|skeleton|>
class DerivativeSlopeTransformer:
"""Derivative slope transformer."""
def _transform(self, X, y=None):
"""Transform X."""
<|body_0|>
def row_wise_get_der(X):
"""Get derivatives."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DerivativeSlopeTransformer:
"""Derivative slope transformer."""
def _transform(self, X, y=None):
"""Transform X."""
num_cases, num_dim = X.shape
output_df = pd.DataFrame()
for dim in range(num_dim):
dim_data = X.iloc[:, dim]
out = self.row_wise_get_... | the_stack_v2_python_sparse | sktime/transformations/panel/summarize/_extract.py | sktime/sktime | train | 1,117 |
98a0e702cc5df157fd32d387767acc8b2f588187 | [
"super(AttENC, self).__init__()\nself.cnn = CNN(n_in * 2, n_hid, n_hid, do_prob)\nself.n2e_i = MLP(n_hid, n_hid, n_hid, do_prob)\nself.e2n = MLP(n_hid, n_hid, n_hid, do_prob)\nself.n2e_o = MLP(n_hid * 3, n_hid, n_hid, do_prob)\nself.intra_att = SelfAtt(n_hid, n_hid)\nself.inter_att = SelfAtt(n_hid, n_hid)\nself.fc_... | <|body_start_0|>
super(AttENC, self).__init__()
self.cnn = CNN(n_in * 2, n_hid, n_hid, do_prob)
self.n2e_i = MLP(n_hid, n_hid, n_hid, do_prob)
self.e2n = MLP(n_hid, n_hid, n_hid, do_prob)
self.n2e_o = MLP(n_hid * 3, n_hid, n_hid, do_prob)
self.intra_att = SelfAtt(n_hid, n... | Encoder using the relation interaction mechanism implemented by self-attention. | AttENC | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttENC:
"""Encoder using the relation interaction mechanism implemented by self-attention."""
def __init__(self, n_in: int, n_hid: int, n_out: int, do_prob: float=0.0):
"""Parameters ---------- n_in : int input dimension. n_hid : int dimension of hidden layers. n_out : int output dim... | stack_v2_sparse_classes_10k_train_005584 | 12,491 | permissive | [
{
"docstring": "Parameters ---------- n_in : int input dimension. n_hid : int dimension of hidden layers. n_out : int output dimension, i.e., number of edge types. do_prob : float, optional rate of dropout. The default is 0.. factor : bool, optional using a factor graph or not. The default is True. reducer : st... | 5 | null | Implement the Python class `AttENC` described below.
Class description:
Encoder using the relation interaction mechanism implemented by self-attention.
Method signatures and docstrings:
- def __init__(self, n_in: int, n_hid: int, n_out: int, do_prob: float=0.0): Parameters ---------- n_in : int input dimension. n_hid... | Implement the Python class `AttENC` described below.
Class description:
Encoder using the relation interaction mechanism implemented by self-attention.
Method signatures and docstrings:
- def __init__(self, n_in: int, n_hid: int, n_out: int, do_prob: float=0.0): Parameters ---------- n_in : int input dimension. n_hid... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class AttENC:
"""Encoder using the relation interaction mechanism implemented by self-attention."""
def __init__(self, n_in: int, n_hid: int, n_out: int, do_prob: float=0.0):
"""Parameters ---------- n_in : int input dimension. n_hid : int dimension of hidden layers. n_out : int output dim... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AttENC:
"""Encoder using the relation interaction mechanism implemented by self-attention."""
def __init__(self, n_in: int, n_hid: int, n_out: int, do_prob: float=0.0):
"""Parameters ---------- n_in : int input dimension. n_hid : int dimension of hidden layers. n_out : int output dimension, i.e.,... | the_stack_v2_python_sparse | research/gnn/nri-mpm/models/nri.py | mindspore-ai/models | train | 301 |
d45662f4dd4be5a127e11579b8d510877b610a82 | [
"self.ss = ss\nself.n_step = n_step\nself.mu = mu\nself.sigma = sigma\nself.step_time = step_time\nself.saw_time = saw_time / delta_t",
"step_vector = np.abs([round(gauss(self.mu, self.sigma), 1) for _ in range(self.n_step)])\nstep_vector[0] = self.ss\nu = np.zeros(shape=dim)\nj = 0\nramp_Step = self.saw_time\nco... | <|body_start_0|>
self.ss = ss
self.n_step = n_step
self.mu = mu
self.sigma = sigma
self.step_time = step_time
self.saw_time = saw_time / delta_t
<|end_body_0|>
<|body_start_1|>
step_vector = np.abs([round(gauss(self.mu, self.sigma), 1) for _ in range(self.n_step)... | SawGaussStep | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SawGaussStep:
def __init__(self, step_time, saw_time, delta_t, mu=None, sigma=None, n_step=None, ss=None):
"""Settings for a random step sequence Args: step_time: Time to perform step change n_step (int): Number of steps"""
<|body_0|>
def out(self, t: any, dim=(None, None)) ... | stack_v2_sparse_classes_10k_train_005585 | 8,036 | no_license | [
{
"docstring": "Settings for a random step sequence Args: step_time: Time to perform step change n_step (int): Number of steps",
"name": "__init__",
"signature": "def __init__(self, step_time, saw_time, delta_t, mu=None, sigma=None, n_step=None, ss=None)"
},
{
"docstring": "Generate a random seq... | 2 | stack_v2_sparse_classes_30k_train_000560 | Implement the Python class `SawGaussStep` described below.
Class description:
Implement the SawGaussStep class.
Method signatures and docstrings:
- def __init__(self, step_time, saw_time, delta_t, mu=None, sigma=None, n_step=None, ss=None): Settings for a random step sequence Args: step_time: Time to perform step cha... | Implement the Python class `SawGaussStep` described below.
Class description:
Implement the SawGaussStep class.
Method signatures and docstrings:
- def __init__(self, step_time, saw_time, delta_t, mu=None, sigma=None, n_step=None, ss=None): Settings for a random step sequence Args: step_time: Time to perform step cha... | cf548475295f25407ba968546c2fc85c26f9343c | <|skeleton|>
class SawGaussStep:
def __init__(self, step_time, saw_time, delta_t, mu=None, sigma=None, n_step=None, ss=None):
"""Settings for a random step sequence Args: step_time: Time to perform step change n_step (int): Number of steps"""
<|body_0|>
def out(self, t: any, dim=(None, None)) ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SawGaussStep:
def __init__(self, step_time, saw_time, delta_t, mu=None, sigma=None, n_step=None, ss=None):
"""Settings for a random step sequence Args: step_time: Time to perform step change n_step (int): Number of steps"""
self.ss = ss
self.n_step = n_step
self.mu = mu
... | the_stack_v2_python_sparse | SourceCode/simulation/signal.py | martin-bachorik/Master-Thesis-Project | train | 0 | |
bf52cdb366bf2827c2168f9a33a80c59443be497 | [
"super().__init__()\nself._use_condition = use_condition\nself._model = self._get_coupling_layers(num_layers=4, num_channels_hidden=[32, 32], compression_size=compression_size)",
"mask = tf.range(4096, dtype=tf.float32)\nmask = tf.reshape(mask, shape=[64, 64, 1]) % 2\nlayers = []\nfor _ in range(num_layers):\n ... | <|body_start_0|>
super().__init__()
self._use_condition = use_condition
self._model = self._get_coupling_layers(num_layers=4, num_channels_hidden=[32, 32], compression_size=compression_size)
<|end_body_0|>
<|body_start_1|>
mask = tf.range(4096, dtype=tf.float32)
mask = tf.reshap... | Embedding conditioned flow model. Attributes: _use_condition: | EmbeddingConditionedFlow | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmbeddingConditionedFlow:
"""Embedding conditioned flow model. Attributes: _use_condition:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
<|body_0|>
def _get_coupling_layers(self, num_layers, n... | stack_v2_sparse_classes_10k_train_005586 | 12,897 | no_license | [
{
"docstring": "Initializes the object. Args: use_condition: compression_size:",
"name": "__init__",
"signature": "def __init__(self, use_condition, compression_size)"
},
{
"docstring": "Returns a list of convolutional affine coupling layers. Args: num_layers: num_channels_hidden: compression_si... | 3 | stack_v2_sparse_classes_30k_train_001540 | Implement the Python class `EmbeddingConditionedFlow` described below.
Class description:
Embedding conditioned flow model. Attributes: _use_condition:
Method signatures and docstrings:
- def __init__(self, use_condition, compression_size): Initializes the object. Args: use_condition: compression_size:
- def _get_cou... | Implement the Python class `EmbeddingConditionedFlow` described below.
Class description:
Embedding conditioned flow model. Attributes: _use_condition:
Method signatures and docstrings:
- def __init__(self, use_condition, compression_size): Initializes the object. Args: use_condition: compression_size:
- def _get_cou... | 6d04861ef87ba2ba2a4182ad36f3b322fcf47cfa | <|skeleton|>
class EmbeddingConditionedFlow:
"""Embedding conditioned flow model. Attributes: _use_condition:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
<|body_0|>
def _get_coupling_layers(self, num_layers, n... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EmbeddingConditionedFlow:
"""Embedding conditioned flow model. Attributes: _use_condition:"""
def __init__(self, use_condition, compression_size):
"""Initializes the object. Args: use_condition: compression_size:"""
super().__init__()
self._use_condition = use_condition
se... | the_stack_v2_python_sparse | flow.py | gaotianxiang/text-to-image-synthesis | train | 0 |
79fc6a1fda36ac7cc0ab0c296780db2c3fcd26a9 | [
"from poHomework.page.contact_page import Contact\nself.driver.find_element_by_id('username').send_keys('jiang2')\nself.driver.find_element_by_id('memberAdd_acctid').send_keys('jiang2')\nself.driver.find_element_by_id('memberAdd_phone').send_keys('15010236359')\nself.driver.execute_script('window.scrollTo(0,documen... | <|body_start_0|>
from poHomework.page.contact_page import Contact
self.driver.find_element_by_id('username').send_keys('jiang2')
self.driver.find_element_by_id('memberAdd_acctid').send_keys('jiang2')
self.driver.find_element_by_id('memberAdd_phone').send_keys('15010236359')
self.... | AddMember | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddMember:
def add_member(self):
"""保存成员信息 :return:"""
<|body_0|>
def add_member_fail(self, acctid, phone):
"""添加成员报错 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from poHomework.page.contact_page import Contact
self.driver.find_... | stack_v2_sparse_classes_10k_train_005587 | 1,281 | no_license | [
{
"docstring": "保存成员信息 :return:",
"name": "add_member",
"signature": "def add_member(self)"
},
{
"docstring": "添加成员报错 :return:",
"name": "add_member_fail",
"signature": "def add_member_fail(self, acctid, phone)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003382 | Implement the Python class `AddMember` described below.
Class description:
Implement the AddMember class.
Method signatures and docstrings:
- def add_member(self): 保存成员信息 :return:
- def add_member_fail(self, acctid, phone): 添加成员报错 :return: | Implement the Python class `AddMember` described below.
Class description:
Implement the AddMember class.
Method signatures and docstrings:
- def add_member(self): 保存成员信息 :return:
- def add_member_fail(self, acctid, phone): 添加成员报错 :return:
<|skeleton|>
class AddMember:
def add_member(self):
"""保存成员信息 :r... | bd677551a324887bed4c3919b4645ebdeff107d1 | <|skeleton|>
class AddMember:
def add_member(self):
"""保存成员信息 :return:"""
<|body_0|>
def add_member_fail(self, acctid, phone):
"""添加成员报错 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class AddMember:
def add_member(self):
"""保存成员信息 :return:"""
from poHomework.page.contact_page import Contact
self.driver.find_element_by_id('username').send_keys('jiang2')
self.driver.find_element_by_id('memberAdd_acctid').send_keys('jiang2')
self.driver.find_element_by_id('... | the_stack_v2_python_sparse | poHomework/page/add_memeber_page.py | jyl4944204/study-homework | train | 0 | |
76b7ecea7bfcd392342ffc9b6bdb3578616006ec | [
"x_ = x - ra_0\ny_ = y - dec_0\nf_ = 1 / 2.0 * (gamma1 * x_ * x_ + 2 * gamma2 * x_ * y_ - gamma1 * y_ * y_)\nreturn f_",
"x_ = x - ra_0\ny_ = y - dec_0\nf_x = gamma1 * x_ + gamma2 * y_\nf_y = +gamma2 * x_ - gamma1 * y_\nreturn (f_x, f_y)",
"gamma1 = gamma1\ngamma2 = gamma2\nkappa = 0\nf_xx = kappa + gamma1\nf_y... | <|body_start_0|>
x_ = x - ra_0
y_ = y - dec_0
f_ = 1 / 2.0 * (gamma1 * x_ * x_ + 2 * gamma2 * x_ * y_ - gamma1 * y_ * y_)
return f_
<|end_body_0|>
<|body_start_1|>
x_ = x - ra_0
y_ = y - dec_0
f_x = gamma1 * x_ + gamma2 * y_
f_y = +gamma2 * x_ - gamma1 * ... | class for external shear gamma1, gamma2 expression | Shear | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Shear:
"""class for external shear gamma1, gamma2 expression"""
def function(self, x, y, gamma1, gamma2, ra_0=0, dec_0=0):
""":param x: x-coordinate (angle) :param y: y0-coordinate (angle) :param gamma1: shear component :param gamma2: shear component :param ra_0: x/ra position where ... | stack_v2_sparse_classes_10k_train_005588 | 7,557 | permissive | [
{
"docstring": ":param x: x-coordinate (angle) :param y: y0-coordinate (angle) :param gamma1: shear component :param gamma2: shear component :param ra_0: x/ra position where shear deflection is 0 :param dec_0: y/dec position where shear deflection is 0 :return: lensing potential",
"name": "function",
"s... | 3 | stack_v2_sparse_classes_30k_train_002202 | Implement the Python class `Shear` described below.
Class description:
class for external shear gamma1, gamma2 expression
Method signatures and docstrings:
- def function(self, x, y, gamma1, gamma2, ra_0=0, dec_0=0): :param x: x-coordinate (angle) :param y: y0-coordinate (angle) :param gamma1: shear component :param ... | Implement the Python class `Shear` described below.
Class description:
class for external shear gamma1, gamma2 expression
Method signatures and docstrings:
- def function(self, x, y, gamma1, gamma2, ra_0=0, dec_0=0): :param x: x-coordinate (angle) :param y: y0-coordinate (angle) :param gamma1: shear component :param ... | 73c9645f26f6983fe7961104075ebe8bf7a4b54c | <|skeleton|>
class Shear:
"""class for external shear gamma1, gamma2 expression"""
def function(self, x, y, gamma1, gamma2, ra_0=0, dec_0=0):
""":param x: x-coordinate (angle) :param y: y0-coordinate (angle) :param gamma1: shear component :param gamma2: shear component :param ra_0: x/ra position where ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Shear:
"""class for external shear gamma1, gamma2 expression"""
def function(self, x, y, gamma1, gamma2, ra_0=0, dec_0=0):
""":param x: x-coordinate (angle) :param y: y0-coordinate (angle) :param gamma1: shear component :param gamma2: shear component :param ra_0: x/ra position where shear deflect... | the_stack_v2_python_sparse | lenstronomy/LensModel/Profiles/shear.py | lenstronomy/lenstronomy | train | 41 |
99f6281c1a3a20480785de966d0f780fea322734 | [
"nums.sort()\nmin_dist, max_dist = (nums[-1] - nums[0], nums[-1] - nums[0])\nfor i in xrange(1, len(nums)):\n min_dist = min(min_dist, nums[i] - nums[i - 1])\nleft, right = (min_dist, max_dist)\nwhile left < right:\n mid = left + (right - left >> 1)\n if self.countPairs(nums, mid) < k:\n left = mid ... | <|body_start_0|>
nums.sort()
min_dist, max_dist = (nums[-1] - nums[0], nums[-1] - nums[0])
for i in xrange(1, len(nums)):
min_dist = min(min_dist, nums[i] - nums[i - 1])
left, right = (min_dist, max_dist)
while left < right:
mid = left + (right - left >> 1... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def countPairs(self, nums, dist):
"""number of pairs whose distance is no more than dist"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_10k_train_005589 | 1,663 | no_license | [
{
"docstring": ":type nums: List[int] :type k: int :rtype: int",
"name": "smallestDistancePair",
"signature": "def smallestDistancePair(self, nums, k)"
},
{
"docstring": "number of pairs whose distance is no more than dist",
"name": "countPairs",
"signature": "def countPairs(self, nums, ... | 2 | stack_v2_sparse_classes_30k_train_004357 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def countPairs(self, nums, dist): number of pairs whose distance is no more than dist | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def smallestDistancePair(self, nums, k): :type nums: List[int] :type k: int :rtype: int
- def countPairs(self, nums, dist): number of pairs whose distance is no more than dist
<... | ee79d3437cf47b26a4bca0ec798dc54d7b623453 | <|skeleton|>
class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
<|body_0|>
def countPairs(self, nums, dist):
"""number of pairs whose distance is no more than dist"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def smallestDistancePair(self, nums, k):
""":type nums: List[int] :type k: int :rtype: int"""
nums.sort()
min_dist, max_dist = (nums[-1] - nums[0], nums[-1] - nums[0])
for i in xrange(1, len(nums)):
min_dist = min(min_dist, nums[i] - nums[i - 1])
l... | the_stack_v2_python_sparse | Algorithm/Python/719. Find K-th Smallest Pair Distance.py | WuLC/LeetCode | train | 29 | |
2ed079ce585737cb64624f56788bfd8ae5b34666 | [
"d = defaultdict(int)\n\ndef dfs(root, level):\n if not root:\n return\n d[level] += root.val\n dfs(root.left, level + 1)\n dfs(root.right, level + 1)\ndfs(root, 0)\nreturn d[max(d.keys())]",
"queue = [root]\nsum_ = 0\nwhile queue:\n count = len(queue)\n sum_ = 0\n while count:\n ... | <|body_start_0|>
d = defaultdict(int)
def dfs(root, level):
if not root:
return
d[level] += root.val
dfs(root.left, level + 1)
dfs(root.right, level + 1)
dfs(root, 0)
return d[max(d.keys())]
<|end_body_0|>
<|body_start_1|>... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deepestLeavesSum(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def deepestLeavesSumIterative(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
d = defaultdict(int)
... | stack_v2_sparse_classes_10k_train_005590 | 1,718 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "deepestLeavesSum",
"signature": "def deepestLeavesSum(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "deepestLeavesSumIterative",
"signature": "def deepestLeavesSumIterative(self, root)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deepestLeavesSum(self, root): :type root: TreeNode :rtype: int
- def deepestLeavesSumIterative(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deepestLeavesSum(self, root): :type root: TreeNode :rtype: int
- def deepestLeavesSumIterative(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
... | 546cbce06fcd4bc34e16d42b5d5eb68fb25e16a9 | <|skeleton|>
class Solution:
def deepestLeavesSum(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def deepestLeavesSumIterative(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def deepestLeavesSum(self, root):
""":type root: TreeNode :rtype: int"""
d = defaultdict(int)
def dfs(root, level):
if not root:
return
d[level] += root.val
dfs(root.left, level + 1)
dfs(root.right, level + 1)
... | the_stack_v2_python_sparse | leetcode/solution_1302.py | eselyavka/python | train | 0 | |
88f54374ec43f587394d36325a3ca57441be734a | [
"dummy_node = current = ListNode(None)\nwhile l1 and l2:\n if l1.val <= l2.val:\n current.next = l1\n l1 = l1.next\n else:\n current.next = l2\n l2 = l2.next\n current = current.next\ncurrent.next = l1 or l2\nreturn dummy_node.next",
"if not l1 or not l2:\n return l1 or l2\... | <|body_start_0|>
dummy_node = current = ListNode(None)
while l1 and l2:
if l1.val <= l2.val:
current.next = l1
l1 = l1.next
else:
current.next = l2
l2 = l2.next
current = current.next
current.next... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""非递归：生成哨兵结点。每次比较l1和l2的大小，新head每次指向值比较小的结点。"""
<|body_0|>
def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode:
"""递归：递归比较下一个结点和另一方结点。"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_10k_train_005591 | 1,995 | no_license | [
{
"docstring": "非递归：生成哨兵结点。每次比较l1和l2的大小，新head每次指向值比较小的结点。",
"name": "mergeTwoLists1",
"signature": "def mergeTwoLists1(self, l1: ListNode, l2: ListNode) -> ListNode"
},
{
"docstring": "递归：递归比较下一个结点和另一方结点。",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(self, l1: ListNode, l2: ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists1(self, l1: ListNode, l2: ListNode) -> ListNode: 非递归：生成哨兵结点。每次比较l1和l2的大小，新head每次指向值比较小的结点。
- def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode: 递归：... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists1(self, l1: ListNode, l2: ListNode) -> ListNode: 非递归：生成哨兵结点。每次比较l1和l2的大小，新head每次指向值比较小的结点。
- def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode: 递归：... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
def mergeTwoLists1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""非递归：生成哨兵结点。每次比较l1和l2的大小，新head每次指向值比较小的结点。"""
<|body_0|>
def mergeTwoLists(self, l1: ListNode, l2: ListNode) -> ListNode:
"""递归：递归比较下一个结点和另一方结点。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists1(self, l1: ListNode, l2: ListNode) -> ListNode:
"""非递归：生成哨兵结点。每次比较l1和l2的大小，新head每次指向值比较小的结点。"""
dummy_node = current = ListNode(None)
while l1 and l2:
if l1.val <= l2.val:
current.next = l1
l1 = l1.next
... | the_stack_v2_python_sparse | 021_merge-two-sorted-lists.py | helloocc/algorithm | train | 1 | |
7acfaad2df0755913dd9ea8e663b7639942ece3b | [
"if f is not None:\n self.f = f\n if hasattr(f, '__name__'):\n self.__name__ = f.__name__\n else:\n self.__name__ = f.__name__\n self.__module__ = f.__module__\n self.af = ArgumentFixer(f)\nif name is not None:\n self.name = name\nself.options = options",
"options = self.options\ni... | <|body_start_0|>
if f is not None:
self.f = f
if hasattr(f, '__name__'):
self.__name__ = f.__name__
else:
self.__name__ = f.__name__
self.__module__ = f.__module__
self.af = ArgumentFixer(f)
if name is not None:
... | Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the example below. EXAMPLES:: sage: from sage.sets.set_from_iterator import ... | EnumeratedSetFromIterator_function_decorator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnumeratedSetFromIterator_function_decorator:
"""Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the ... | stack_v2_sparse_classes_10k_train_005592 | 34,216 | no_license | [
{
"docstring": "Initialize ``self``. TESTS:: sage: from sage.sets.set_from_iterator import set_from_function sage: F = set_from_function(category=FiniteEnumeratedSets())(xsrange) sage: TestSuite(F(100)).run() sage: TestSuite(F(1,5,2)).run() sage: TestSuite(F(0)).run()",
"name": "__init__",
"signature": ... | 2 | stack_v2_sparse_classes_30k_train_002227 | Implement the Python class `EnumeratedSetFromIterator_function_decorator` described below.
Class description:
Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place ... | Implement the Python class `EnumeratedSetFromIterator_function_decorator` described below.
Class description:
Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place ... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class EnumeratedSetFromIterator_function_decorator:
"""Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the ... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class EnumeratedSetFromIterator_function_decorator:
"""Decorator for :class:`EnumeratedSetFromIterator`. Name could be string or a function ``(args,kwds) -> string``. .. WARNING:: If you are going to use this with the decorator ``cached_function``, you must place the ``cached_function`` first. See the example below... | the_stack_v2_python_sparse | sage/src/sage/sets/set_from_iterator.py | bopopescu/geosci | train | 0 |
54ba03d7405958dd2f00fa5e2fd869f5f51a04df | [
"self.maxlen = maxlen\nself.val_range = val_range\nself.img = np.ones((maxlen, maxlen))\nself.time_step = 0\nself.one_img = np.ones((maxlen, maxlen))",
"assert isinstance(data, np.ndarray)\ndata = np.expand_dims(data, 1)\ndata = np.resize(data, (1, self.maxlen))\nif self.time_step >= self.maxlen:\n self.img = ... | <|body_start_0|>
self.maxlen = maxlen
self.val_range = val_range
self.img = np.ones((maxlen, maxlen))
self.time_step = 0
self.one_img = np.ones((maxlen, maxlen))
<|end_body_0|>
<|body_start_1|>
assert isinstance(data, np.ndarray)
data = np.expand_dims(data, 1)
... | Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image`` | DistributionTimeImage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DistributionTimeImage:
"""Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``"""
def __init__(self, maxlen: int=600, val_range: Optional[dic... | stack_v2_sparse_classes_10k_train_005593 | 6,951 | permissive | [
{
"docstring": "Overview: Init the ``DistributionTimeImage`` class Arguments: - maxlen (:obj:`int`): The max length of data inputs - val_range (:obj:`dict` or :obj:`None`): Dict with ``val_range['min']`` and ``val_range['max']``.",
"name": "__init__",
"signature": "def __init__(self, maxlen: int=600, va... | 3 | null | Implement the Python class `DistributionTimeImage` described below.
Class description:
Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``
Method signatures and docst... | Implement the Python class `DistributionTimeImage` described below.
Class description:
Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``
Method signatures and docst... | eb483fa6e46602d58c8e7d2ca1e566adca28e703 | <|skeleton|>
class DistributionTimeImage:
"""Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``"""
def __init__(self, maxlen: int=600, val_range: Optional[dic... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class DistributionTimeImage:
"""Overview: ``DistributionTimeImage`` can be used to store images accorrding to ``time_steps``, for data with 3 dims``(time, category, value)`` Interface: ``__init__``, ``add_one_time_step``, ``get_image``"""
def __init__(self, maxlen: int=600, val_range: Optional[dict]=None):
... | the_stack_v2_python_sparse | ding/utils/log_helper.py | shengxuesun/DI-engine | train | 1 |
383deee568bade880bee06ca2ff2ed83b49a2bd0 | [
"fig_legend = self.get_legend()\nif self.show_legend is not False and fig_legend is not None:\n fig_legend.set_visible(True)\nself.grid(grid_on=True)",
"classes = dataset.classes\nif colors is None:\n if classes.size <= 6:\n colors = ['blue', 'red', 'lightgreen', 'black', 'gray', 'cyan']\n fro... | <|body_start_0|>
fig_legend = self.get_legend()
if self.show_legend is not False and fig_legend is not None:
fig_legend.set_visible(True)
self.grid(grid_on=True)
<|end_body_0|>
<|body_start_1|>
classes = dataset.classes
if colors is None:
if classes.size ... | Plots a Dataset. Custom plotting parameters can be specified. Currently parameters default: - show_legend: True - grid: True See Also -------- .CDataset : store and manage a dataset. .CPlot : basic subplot functions. .CFigure : creates and handle figures. | CPlotDataset | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CPlotDataset:
"""Plots a Dataset. Custom plotting parameters can be specified. Currently parameters default: - show_legend: True - grid: True See Also -------- .CDataset : store and manage a dataset. .CPlot : basic subplot functions. .CFigure : creates and handle figures."""
def apply_params... | stack_v2_sparse_classes_10k_train_005594 | 3,292 | permissive | [
{
"docstring": "Apply defined parameters to active subplot.",
"name": "apply_params_ds",
"signature": "def apply_params_ds(self)"
},
{
"docstring": "Plot patterns of each class with a different color/marker. Parameters ---------- dataset : CDataset Dataset that contain samples which we want plot... | 2 | stack_v2_sparse_classes_30k_train_006317 | Implement the Python class `CPlotDataset` described below.
Class description:
Plots a Dataset. Custom plotting parameters can be specified. Currently parameters default: - show_legend: True - grid: True See Also -------- .CDataset : store and manage a dataset. .CPlot : basic subplot functions. .CFigure : creates and h... | Implement the Python class `CPlotDataset` described below.
Class description:
Plots a Dataset. Custom plotting parameters can be specified. Currently parameters default: - show_legend: True - grid: True See Also -------- .CDataset : store and manage a dataset. .CPlot : basic subplot functions. .CFigure : creates and h... | 431373e65d8cfe2cb7cf042ce1a6c9519ea5a14a | <|skeleton|>
class CPlotDataset:
"""Plots a Dataset. Custom plotting parameters can be specified. Currently parameters default: - show_legend: True - grid: True See Also -------- .CDataset : store and manage a dataset. .CPlot : basic subplot functions. .CFigure : creates and handle figures."""
def apply_params... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class CPlotDataset:
"""Plots a Dataset. Custom plotting parameters can be specified. Currently parameters default: - show_legend: True - grid: True See Also -------- .CDataset : store and manage a dataset. .CPlot : basic subplot functions. .CFigure : creates and handle figures."""
def apply_params_ds(self):
... | the_stack_v2_python_sparse | src/secml/figure/_plots/c_plot_ds.py | Cinofix/secml | train | 0 |
3b3cfc32aaddc1273f740d65b7261f4cfe82dbce | [
"if self.oriented_from == oriented_segment:\n return self.oriented_to\nelif self.oriented_to == oriented_segment:\n return self.oriented_from\nelif tolerant:\n return None\nelse:\n raise gfapy.NotFoundError(\"Oriented segment '{}' not found\\n\".format(repr(oriented_segment)) + 'Line: {}'.format(self))"... | <|body_start_0|>
if self.oriented_from == oriented_segment:
return self.oriented_to
elif self.oriented_to == oriented_segment:
return self.oriented_from
elif tolerant:
return None
else:
raise gfapy.NotFoundError("Oriented segment '{}' not f... | Other | [
"ISC"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Other:
def other_oriented_segment(self, oriented_segment, tolerant=False):
"""Parameters ---------- oriented_segment : gfapy.OrientedLine One of the two oriented segments of the line. Returns ------- gfapy.OrientedLine The other oriented segment. Raises ------ gfapy.NotFoundError If segm... | stack_v2_sparse_classes_10k_train_005595 | 1,564 | permissive | [
{
"docstring": "Parameters ---------- oriented_segment : gfapy.OrientedLine One of the two oriented segments of the line. Returns ------- gfapy.OrientedLine The other oriented segment. Raises ------ gfapy.NotFoundError If segment_end is not a segment end of the line.",
"name": "other_oriented_segment",
... | 2 | stack_v2_sparse_classes_30k_train_001962 | Implement the Python class `Other` described below.
Class description:
Implement the Other class.
Method signatures and docstrings:
- def other_oriented_segment(self, oriented_segment, tolerant=False): Parameters ---------- oriented_segment : gfapy.OrientedLine One of the two oriented segments of the line. Returns --... | Implement the Python class `Other` described below.
Class description:
Implement the Other class.
Method signatures and docstrings:
- def other_oriented_segment(self, oriented_segment, tolerant=False): Parameters ---------- oriented_segment : gfapy.OrientedLine One of the two oriented segments of the line. Returns --... | 12b31daac26ab137b6ee4a29b4f14554ba962dcb | <|skeleton|>
class Other:
def other_oriented_segment(self, oriented_segment, tolerant=False):
"""Parameters ---------- oriented_segment : gfapy.OrientedLine One of the two oriented segments of the line. Returns ------- gfapy.OrientedLine The other oriented segment. Raises ------ gfapy.NotFoundError If segm... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Other:
def other_oriented_segment(self, oriented_segment, tolerant=False):
"""Parameters ---------- oriented_segment : gfapy.OrientedLine One of the two oriented segments of the line. Returns ------- gfapy.OrientedLine The other oriented segment. Raises ------ gfapy.NotFoundError If segment_end is not... | the_stack_v2_python_sparse | gfapy/line/edge/gfa1/other.py | ggonnella/gfapy | train | 63 | |
43014415d4e4b7c3a2ca6aa1907409479c864587 | [
"self.item = item\nself.key = key\nself.left = left\nself.right = right\nself._size = 1",
"if self.key == key:\n self.item = item\nelif self.key < key:\n if self.right:\n self.right.insert(item, key)\n else:\n self.right = BSTreeNode(item, key)\nelif self.left:\n self.left.insert(item, k... | <|body_start_0|>
self.item = item
self.key = key
self.left = left
self.right = right
self._size = 1
<|end_body_0|>
<|body_start_1|>
if self.key == key:
self.item = item
elif self.key < key:
if self.right:
self.right.insert(... | Binary search tree node (subtree) | BSTreeNode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BSTreeNode:
"""Binary search tree node (subtree)"""
def __init__(self, item, key, left=None, right=None):
"""Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)"""
... | stack_v2_sparse_classes_10k_train_005596 | 3,986 | no_license | [
{
"docstring": "Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)",
"name": "__init__",
"signature": "def __init__(self, item, key, left=None, right=None)"
},
{
"docstring": "Assi... | 6 | stack_v2_sparse_classes_30k_train_005122 | Implement the Python class `BSTreeNode` described below.
Class description:
Binary search tree node (subtree)
Method signatures and docstrings:
- def __init__(self, item, key, left=None, right=None): Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) ... | Implement the Python class `BSTreeNode` described below.
Class description:
Binary search tree node (subtree)
Method signatures and docstrings:
- def __init__(self, item, key, left=None, right=None): Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) ... | 61746b48482eb0701f5c7211b153a3726c24f355 | <|skeleton|>
class BSTreeNode:
"""Binary search tree node (subtree)"""
def __init__(self, item, key, left=None, right=None):
"""Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)"""
... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class BSTreeNode:
"""Binary search tree node (subtree)"""
def __init__(self, item, key, left=None, right=None):
"""Tree node constructor. :param item: node's item :param key: item's key :param left (BSTreeNode): left child (subtree) :param right (BSTreeNode): right child (subtree)"""
self.item ... | the_stack_v2_python_sparse | mpiaa/search/bstree_node.py | sergey-suslov/mpiaa-sem3 | train | 0 |
cf967a935018f6e82afc1273024f54b8213986bb | [
"logging.Handler.__init__(self)\nself.address = address\nself.port = port\nself.certfile = cert_path\nself.facility = facility\nself.level = log_level\nssl_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)\nssl_context = ssl.SSLContext(ssl.PROTOCOL_TLS_CLIENT)\nssl_context.minimum_version = ssl.TLSVersion.TL... | <|body_start_0|>
logging.Handler.__init__(self)
self.address = address
self.port = port
self.certfile = cert_path
self.facility = facility
self.level = log_level
ssl_sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
ssl_context = ssl.SSLContext(ssl.... | SyslogHandlerTLS | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SyslogHandlerTLS:
def __init__(self, address: str, port: int, log_level: int, facility: int, cert_path: str, if_self_sign_cert: bool):
"""Initialize a handler."""
<|body_0|>
def emit(self, record):
"""Emit a record. The record is formatted, and then sent to the syslo... | stack_v2_sparse_classes_10k_train_005597 | 14,986 | permissive | [
{
"docstring": "Initialize a handler.",
"name": "__init__",
"signature": "def __init__(self, address: str, port: int, log_level: int, facility: int, cert_path: str, if_self_sign_cert: bool)"
},
{
"docstring": "Emit a record. The record is formatted, and then sent to the syslog server. If excepti... | 2 | stack_v2_sparse_classes_30k_train_003458 | Implement the Python class `SyslogHandlerTLS` described below.
Class description:
Implement the SyslogHandlerTLS class.
Method signatures and docstrings:
- def __init__(self, address: str, port: int, log_level: int, facility: int, cert_path: str, if_self_sign_cert: bool): Initialize a handler.
- def emit(self, record... | Implement the Python class `SyslogHandlerTLS` described below.
Class description:
Implement the SyslogHandlerTLS class.
Method signatures and docstrings:
- def __init__(self, address: str, port: int, log_level: int, facility: int, cert_path: str, if_self_sign_cert: bool): Initialize a handler.
- def emit(self, record... | 890def5a0e0ae8d6eaa538148249ddbc851dbb6b | <|skeleton|>
class SyslogHandlerTLS:
def __init__(self, address: str, port: int, log_level: int, facility: int, cert_path: str, if_self_sign_cert: bool):
"""Initialize a handler."""
<|body_0|>
def emit(self, record):
"""Emit a record. The record is formatted, and then sent to the syslo... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class SyslogHandlerTLS:
def __init__(self, address: str, port: int, log_level: int, facility: int, cert_path: str, if_self_sign_cert: bool):
"""Initialize a handler."""
logging.Handler.__init__(self)
self.address = address
self.port = port
self.certfile = cert_path
se... | the_stack_v2_python_sparse | Packs/Syslog/Integrations/SyslogSender/SyslogSender.py | demisto/content | train | 1,023 | |
d5545ef4c14a64e270322d54020cb0e931776ac4 | [
"conn, cursor = get_db_cursor()\nbuild = 'toy_build'\ntranscript_dict = init_refs.make_transcript_dict(cursor, build)\nconn.close()\nedges = (100, 200, 300)\nmatches = talon.search_for_ISM(edges, transcript_dict)\nassert matches == None",
"conn, cursor = get_db_cursor()\nbuild = 'toy_build'\ntranscript_dict = ini... | <|body_start_0|>
conn, cursor = get_db_cursor()
build = 'toy_build'
transcript_dict = init_refs.make_transcript_dict(cursor, build)
conn.close()
edges = (100, 200, 300)
matches = talon.search_for_ISM(edges, transcript_dict)
assert matches == None
<|end_body_0|>
<... | TestSearchForISM | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSearchForISM:
def test_find_no_match(self):
"""Example where the toy transcript database contains no matches for the edge set."""
<|body_0|>
def test_find_match(self):
"""Example where the toy transcript database contains exactly one ISM match for the transcript.... | stack_v2_sparse_classes_10k_train_005598 | 1,789 | permissive | [
{
"docstring": "Example where the toy transcript database contains no matches for the edge set.",
"name": "test_find_no_match",
"signature": "def test_find_no_match(self)"
},
{
"docstring": "Example where the toy transcript database contains exactly one ISM match for the transcript.",
"name"... | 3 | stack_v2_sparse_classes_30k_train_005725 | Implement the Python class `TestSearchForISM` described below.
Class description:
Implement the TestSearchForISM class.
Method signatures and docstrings:
- def test_find_no_match(self): Example where the toy transcript database contains no matches for the edge set.
- def test_find_match(self): Example where the toy t... | Implement the Python class `TestSearchForISM` described below.
Class description:
Implement the TestSearchForISM class.
Method signatures and docstrings:
- def test_find_no_match(self): Example where the toy transcript database contains no matches for the edge set.
- def test_find_match(self): Example where the toy t... | 8014faed5f982e5e106ec05239e47d65878e76c3 | <|skeleton|>
class TestSearchForISM:
def test_find_no_match(self):
"""Example where the toy transcript database contains no matches for the edge set."""
<|body_0|>
def test_find_match(self):
"""Example where the toy transcript database contains exactly one ISM match for the transcript.... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class TestSearchForISM:
def test_find_no_match(self):
"""Example where the toy transcript database contains no matches for the edge set."""
conn, cursor = get_db_cursor()
build = 'toy_build'
transcript_dict = init_refs.make_transcript_dict(cursor, build)
conn.close()
... | the_stack_v2_python_sparse | testing_suite/test_search_for_ISM_match.py | kopardev/TALON | train | 0 | |
68b7e1d666c8e12f2128e3e382243f1bafa60ee0 | [
"super().__init__(dat, frame, box_size, centre, arrow_width=arrow_width, arrow_head_width=arrow_head_width, arrow_head_length=arrow_head_length)\nself.orientations = dat.getOrientations(frame, *self.particles) % (2 * np.pi)\nself.colorbar(0, 2, cmap=plt.cm.hsv)\nself.colormap.set_label('$\\\\theta_i/\\\\pi$', label... | <|body_start_0|>
super().__init__(dat, frame, box_size, centre, arrow_width=arrow_width, arrow_head_width=arrow_head_width, arrow_head_length=arrow_head_length)
self.orientations = dat.getOrientations(frame, *self.particles) % (2 * np.pi)
self.colorbar(0, 2, cmap=plt.cm.hsv)
self.colorma... | Plotting class specific to 'orientation' mode. | Orientation | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Orientation:
"""Plotting class specific to 'orientation' mode."""
def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_label_pad, label=False, **kwargs):
"""Initialises and p... | stack_v2_sparse_classes_10k_train_005599 | 24,676 | permissive | [
{
"docstring": "Initialises and plots figure. Parameters ---------- dat : active_work.read.Dat Data object. frame : int Frame to render. box_size : float Length of the square box to render. centre : 2-uple like Centre of the box to render. arrow_width : float Width of the arrows. arrow_head_width : float Width ... | 3 | stack_v2_sparse_classes_30k_train_007137 | Implement the Python class `Orientation` described below.
Class description:
Plotting class specific to 'orientation' mode.
Method signatures and docstrings:
- def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colo... | Implement the Python class `Orientation` described below.
Class description:
Plotting class specific to 'orientation' mode.
Method signatures and docstrings:
- def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colo... | 99107a0d4935296b673f67469c1e2bd258954b9b | <|skeleton|>
class Orientation:
"""Plotting class specific to 'orientation' mode."""
def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_label_pad, label=False, **kwargs):
"""Initialises and p... | stack_v2_sparse_classes_10k | data/stack_v2_sparse_classes_30k | class Orientation:
"""Plotting class specific to 'orientation' mode."""
def __init__(self, dat, frame, box_size, centre, arrow_width=_arrow_width, arrow_head_width=_arrow_head_width, arrow_head_length=_arrow_head_length, pad=_colormap_label_pad, label=False, **kwargs):
"""Initialises and plots figure. ... | the_stack_v2_python_sparse | frame.py | yketa/active_work | train | 1 |
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