Travis build: 98

This commit is contained in:
30secondsofcode
2019-09-22 12:23:27 +00:00
parent ab3c44a5d5
commit 99374f1c2e
3 changed files with 7 additions and 10 deletions

View File

@ -513,10 +513,7 @@ Use list comprehension to map each element to the appropriate `key`.
```py
def group_by(lst, fn):
groups = {}
for key in list(map(fn,lst)):
groups[key] = [item for item in lst if fn(item) == key]
return groups
return {key : [el for el in lst if fn(el) == key] for key in map(fn,lst)}
```
<details>
@ -524,8 +521,8 @@ def group_by(lst, fn):
```py
import math
group_by([6.1, 4.2, 6.3], math.floor); # {4: [4.2], 6: [6.1, 6.3]}
group_by(['one', 'two', 'three'], len); # {3: ['one', 'two'], 5: ['three']}
group_by([6.1, 4.2, 6.3], math.floor) # {4: [4.2], 6: [6.1, 6.3]}
group_by(['one', 'two', 'three'], len) # {3: ['one', 'two'], 5: ['three']}
```
</details>

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@ -445,7 +445,7 @@
]
},
"meta": {
"hash": "8e552ea1be04303164bd9c480ebd7392bcc79ef620ce18ee6436dc1dc41c1e42"
"hash": "b3d1a5b7cd2f3b25f9d89efeba7f4eb7f9e4e6d81e108d57f94770c8f979428e"
}
},
{

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@ -580,8 +580,8 @@
"fileName": "group_by.md",
"text": "Groups the elements of a list based on the given function.\n\nUse `list()` in combination with `map()` and `fn` to map the values of the list to the keys of an object.\nUse list comprehension to map each element to the appropriate `key`.\n\n",
"codeBlocks": {
"code": "def group_by(lst, fn):\n groups = {}\n for key in list(map(fn,lst)):\n groups[key] = [item for item in lst if fn(item) == key]\n return groups",
"example": "import math\ngroup_by([6.1, 4.2, 6.3], math.floor); # {4: [4.2], 6: [6.1, 6.3]}\ngroup_by(['one', 'two', 'three'], len); # {3: ['one', 'two'], 5: ['three']}"
"code": "def group_by(lst, fn):\n return {key : [el for el in lst if fn(el) == key] for key in map(fn,lst)}",
"example": "import math\ngroup_by([6.1, 4.2, 6.3], math.floor) # {4: [4.2], 6: [6.1, 6.3]}\ngroup_by(['one', 'two', 'three'], len) # {3: ['one', 'two'], 5: ['three']}"
},
"tags": [
"list",
@ -590,7 +590,7 @@
]
},
"meta": {
"hash": "8e552ea1be04303164bd9c480ebd7392bcc79ef620ce18ee6436dc1dc41c1e42"
"hash": "b3d1a5b7cd2f3b25f9d89efeba7f4eb7f9e4e6d81e108d57f94770c8f979428e"
}
},
{