Result for FF7EB4B4E9FD5F1F66D8098CFE942D20FB9FC306

Query result

Key Value
FileName./usr/lib/python3/dist-packages/dacite/types.py
FileSize5783
MD5AA021667E51448A2AB75428A651D9E32
SHA-1FF7EB4B4E9FD5F1F66D8098CFE942D20FB9FC306
SHA-2562F719F0FF09F3C9FEDEA85391B54B6B52E0C9B0CE666DF0792F9EB8CF5DB6DB1
SSDEEP96:0r+O837MYOpZNHaR45kYWJeeWCSCd0JLkWulsS9o36GwENuxIqCCoxMHMTuELjvF:0rELQZN6R45kYWAeWVu0YWyEwENFqIMq
TLSHT1ECC18C767BD1F031C6D39A185883C050A61ABD83924A58F57EFC41B4AF6563A92F338E
hashlookup:parent-total4
hashlookup:trust70

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Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD535237CB89F8F086B83EDD69EEEF96C9E
PackageArcharmv7hl
PackageDescriptionpcs is a corosync and pacemaker configuration tool. It permits users to easily view, modify and create pacemaker based clusters.
PackageMaintainerFedora Project
PackageNamepcs
PackageRelease1.fc33
PackageVersion0.10.7
SHA-1C357C53609146374528754A7A9FBD9AFDC9A88A5
SHA-256855807A02999D9234283C71C563F454E786AAAA231D500F114630C85A5CF5B46
Key Value
MD54A7A0662384B3EB0D45B29523207C6ED
PackageArchx86_64
PackageDescriptionpcs is a corosync and pacemaker configuration tool. It permits users to easily view, modify and create pacemaker based clusters.
PackageMaintainerFedora Project
PackageNamepcs
PackageRelease1.fc33
PackageVersion0.10.7
SHA-189108ABDF4C134E3B443AF565753FA880AA2BD8F
SHA-2569994129B200DC74C8C1DC41903584D421B096E699901704F72DC9C09FF144AF7
Key Value
MD5E6E3034F41BFBF3E986CE133A79F2FC3
PackageArchaarch64
PackageDescriptionpcs is a corosync and pacemaker configuration tool. It permits users to easily view, modify and create pacemaker based clusters.
PackageMaintainerFedora Project
PackageNamepcs
PackageRelease1.fc33
PackageVersion0.10.7
SHA-1DE5501A58496B518AC268281123D7ED6F75484CF
SHA-256D4745414B732A88CF89FE6A4B7427D4CD55D85AC85AD2988EAB7FE1976278EBA
Key Value
FileSize17088
MD53D1D9FEF147CCE949AE5EFB93FDF21D5
PackageDescriptionSimple creation of data classes from dictionaries Passing plain dictionaries as a data container between your functions or methods isn't a good practice. Of course you can always create your custom class instead, but this solution is an overkill if you only want to merge a few fields within a single object. . Fortunately Python has a good solution to this problem - data classes. Thanks to `@dataclass` decorator you can easily create a new custom type with a list of given fields in a declarative manner. Data classes support type hints by design. . However, even if you are using data classes, you have to create their instances somehow. In many such cases, your input is a dictionary - it can be a payload from a HTTP request or a raw data from a database. If you want to convert those dictionaries into data classes, `dacite` is your best friend. . This library was originally created to simplify creation of type hinted data transfer objects (DTO) which can cross the boundaries in the application architecture. . It's important to mention that `dacite` is not a data validation library. There are dozens of awesome data validation projects and it doesn't make sense to duplicate this functionality within `dacite`. If you want to validate your data first, you should combine `dacite` with one of data validation library.
PackageMaintainerUbuntu Developers <ubuntu-devel-discuss@lists.ubuntu.com>
PackageNamepython3-dacite
PackageSectionpython
PackageVersion1.5.1-1
SHA-1AE2C306F33660AD48B81369C8399A4408CD0546F
SHA-256766D8A4B306472E90BB5C34352DBC09EC5C44E86954890BBD10ED637F46540FB