Key | Value |
---|---|
FileName | snap-hashlookup-import/connectedhomeip/python_env/lib/python3.10/site-packages/dacite/dataclasses.py |
FileSize | 932 |
MD5 | 33E7C0BB0B764DD0958E99FC86972C0F |
SHA-1 | 00D23B90DF009A4844E063E42E6F53A504964E20 |
SHA-256 | 323438AE186ACC9B9143C0FDEE92516C0D62FBE87F7743DB691613B2E53568A8 |
SHA-512 | 962E47ADD26631AE97B25059B6F21F143ACB81676DC307816F25DB2C0EC4655E073BA8D22B73248CB0525C683CA3C91AAD480471146F45B860E3D13DC6DD04F0 |
SSDEEP | 24:1By+XoHue8nkQ3hkFZLybHU3v6k64w/0MLyXlBo5v44RS:eQ3huOuCf4wqXliN44I |
TLSH | T199115BB575D7E8368953A984541AC021B316FA559F207874BBF822B63F0941492E4B47 |
insert-timestamp | 1728980206.44422 |
mimetype | text/x-python |
source | snap:GBerlE9aNYdgGnboKfqZK2Fe3Go1PDd9_5 |
hashlookup:parent-total | 2 |
hashlookup:trust | 60 |
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 |
---|---|
SHA-1 | 6D5742AEAC9D2F04AB2AD6D59119333FA48BC6D8 |
snap-authority | canonical |
snap-filename | GBerlE9aNYdgGnboKfqZK2Fe3Go1PDd9_5.snap |
snap-id | GBerlE9aNYdgGnboKfqZK2Fe3Go1PDd9_5 |
snap-name | matter-bridge-tapo-lighting |
snap-publisher-id | fnEni7OOr54T1CivYaEi4sGS2RwNJLoY |
snap-signkey | BWDEoaqyr25nF5SNCvEv2v7QnM9QsfCc0PBMYD_i2NGSQ32EF2d4D0hqUel3m8ul |
snap-timestamp | 2023-06-16T21:53:39.156510Z |
source-url | https://api.snapcraft.io/api/v1/snaps/download/GBerlE9aNYdgGnboKfqZK2Fe3Go1PDd9_5.snap |
Key | Value |
---|---|
FileSize | 20452 |
MD5 | 37B6F6EF65767C588EA0ECF869792257 |
PackageDescription | Simple 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. |
PackageMaintainer | Debian Python Team <team+python@tracker.debian.org> |
PackageName | python3-dacite |
PackageSection | python |
PackageVersion | 1.8.0-1 |
SHA-1 | 29E8A86853FB71A8DDD8ED3B4DCF83E88D31DB9D |
SHA-256 | AAB3F44808C5EA9B7459F7202FFC0FE26DDA1A84CA1C912339A4C537300FA02C |