Large nested datashapes can be troublesome for humans to parse if printed linearly. Consider the following data
In [11]: x
Out[11]:
nd.array([],
type="0 * {actor : {avatar_url : string, gravatar_id : string, id : int64,
login : string, url : string}, created_at : datetime, id : int64, payload : {before :
string, commits : 1 * {author : {email : string, name : string}, distinct : bool,
message : string, sha : string, url : string}, distinct_size : int64, head : string,
push_id : int64, ref : string, size : int64}, public : bool, repo : {id : int64, name :
string, url : string}, type : string}")
It's really not clear what's going on here. If we print things in a nested way then the situation becomes more clear.
{
actor: {
avatar_url: string,
gravatar_id: string,
id: int64,
login: string,
url: string
},
created_at: datetime,
id: int64,
payload: {
before: string,
commits: 1 * {
author: {email: string, name: string},
distinct: bool,
message: string,
sha: string,
url: string
},
distinct_size: int64,
head: string,
push_id: int64,
ref: string,
size: int64
},
public: bool,
repo: {id: int64, name: string, url: string},
type: string
}
Large nested datashapes can be troublesome for humans to parse if printed linearly. Consider the following data
It's really not clear what's going on here. If we print things in a nested way then the situation becomes more clear.