Result for 1F70D9AE336C8D4E8FE735BA3FCEAA038C3ACBB9

Query result

Key Value
FileName./usr/share/doc/packages/python311-APScheduler/README.rst
FileSize3773
MD50716F19A02B880E068AC678D766A8EA1
SHA-11F70D9AE336C8D4E8FE735BA3FCEAA038C3ACBB9
SHA-256EECAACD5182EE1E0BA9D1528704ACC905E93D7C19473E05FD36188E131DE1DF7
SSDEEP96:duaMra/a3juWaHWMUAxkQEr2K0n41xgodQDtGM3DNe6a2:dKra+8gn04DEDt33DNxX
TLSHT1957173EFAA0217789F9094B9F1AD51E4EF3391EDEAD4A08CD419C5205055437D3EEA84
hashlookup:parent-total2
hashlookup:trust60

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The searched file hash is included in 2 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD5208C5115B5BB98D112D589EFE7035028
PackageArchnoarch
PackageDescriptionAdvanced Python Scheduler (APScheduler) is an in-process task scheduler that lets you schedule jobs (functions or any python callables) to be executed at any time of your choosing. This can be an alternative to externally run cron scripts for long-running applications (e.g. web applications), as it is platform neutral and can access the application's variables and functions. APscheduler provides multiple job stores. * Configurable scheduling mechanisms (triggers): * Cron-like scheduling * Delayed scheduling of single run jobs (like the UNIX "at" command) * Interval-based (run a job at specified time intervals) * Multiple, simultaneously active job stores: * RAM * File-based simple database (shelve) * SQLAlchemy (any supported RDBMS works) * MongoDB
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython311-APScheduler
PackageReleasebp156.1.1
PackageVersion3.10.4
SHA-10DCBEAE7E7B8CEC59489E9CEF7E3D11AB9D53BF2
SHA-256BCCD1763236079E23C1151E6AB933DA8723CB166FF8FA96005A8F4C3E81F5579
Key Value
MD5291EABC76E86AF4E3E1CC4D013D61E10
PackageArchnoarch
PackageDescriptionAdvanced Python Scheduler (APScheduler) is a Python library that lets you schedule your Python code to be executed later, either just once or periodically. You can add new jobs or remove old ones on the fly as you please. If you store your jobs in a database, they will also survive scheduler restarts and maintain their state. When the scheduler is restarted, it will then run all the jobs it should have run while it was offline [1].
PackageMaintainerguillomovitch <guillomovitch>
PackageNamepython3-apscheduler
PackageRelease3.mga9
PackageVersion3.9.1
SHA-1088375B3EFCF9FE237F38358C147964921A9D38D
SHA-25669D39B10B9EC59B2FBB23E1F37641FB07B961F69E21DA5DC71EDD5F4C279D5B5