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import os | |
import duckdb | |
from sqlmesh.core.config import ( | |
Config, | |
GatewayConfig, | |
ModelDefaultsConfig, | |
DuckDBConnectionConfig, | |
) | |
from sqlmesh.core.context import Context | |
from sqlmesh.core.config.format import FormatConfig |
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Panel | |
Context | |
Specify -> Sequence Attributes | |
Search -> Event Attributes | |
Select -> Focus | |
Sequence Attributes | |
Filter -> Context | |
Event Attributes | |
Insert -> Context | |
Split -> Focus |
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Panel | |
Context | |
Specify -> Sequence Attributes | |
Second State | |
Sequence Attributes | |
Event attributes |
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""" | |
This module implements a pandas extension datatype/array wrapping multidim numpy arrays. | |
The default pandas behavior is to convert it to a numpy array of type `object`, which is | |
not the most efficient. For ex - an arrow dataset of size 500MB with some multidim arrays | |
as columns explodes to 3GB. All I want is to filter on other column values, till an arrow | |
native dataframe library comes along! | |
Even so, a lot of other libraries require a pandas dataframe as input, so this gives us | |
efficient conversion. | |
""" |
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#include <stdlib.h> | |
#include <arrow-glib/arrow-glib.h> | |
int main(int argc, char **argv) | |
{ | |
int success = EXIT_FAILURE; | |
GError *error = NULL; | |
GArrowMemoryMappedInputStream *input; | |
GArrowRecordBatchFileReader *reader; |
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import uvicorn | |
from http.cookies import SimpleCookie | |
from urllib.parse import parse_qsl | |
from datasette_auth_github import GitHubAuth, utils | |
class GitHubAuthProxy(GitHubAuth): | |
login_path = "/-/login" |