Split readme to 2 files, fix #146

This commit is contained in:
Ram Rachum 2019-11-29 23:55:33 +02:00
parent 76b7466d4d
commit 487fa5317e
2 changed files with 90 additions and 90 deletions

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ADVANCED_USAGE.md Normal file
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# Advanced Usage #
Use `watch_explode` to expand values to see all their attributes or items of lists/dictionaries:
```python
@pysnooper.snoop(watch_explode=('foo', 'self'))
```
`watch_explode` will automatically guess how to expand the expression passed to it based on its class. You can be more specific by using one of the following classes:
```python
import pysnooper
@pysnooper.snoop(watch=(
pysnooper.Attrs('x'), # attributes
pysnooper.Keys('y'), # mapping (e.g. dict) items
pysnooper.Indices('z'), # sequence (e.g. list/tuple) items
))
```
Exclude specific keys/attributes/indices with the `exclude` parameter, e.g. `Attrs('x', exclude=('_foo', '_bar'))`.
Add a slice after `Indices` to only see the values within that slice, e.g. `Indices('z')[-3:]`.
```console
$ export PYSNOOPER_DISABLED=1 # This makes PySnooper not do any snooping
```
This will output lines like:
```
Modified var:.. foo[2] = 'whatever'
New var:....... self.baz = 8
```
Start all snoop lines with a prefix, to grep for them easily:
```python
@pysnooper.snoop(prefix='ZZZ ')
```
Remove all machine-related data (paths, timestamps, memory addresses) to compare with other traces easily:
```python
@pysnooper.snoop(normalize=True)
```
On multi-threaded apps identify which thread are snooped in output:
```python
@pysnooper.snoop(thread_info=True)
```
PySnooper supports decorating generators.
If you decorate a class with `snoop`, it'll automatically apply the decorator to all the methods. (Not including properties and other special cases.)
You can also customize the repr of an object:
```python
def large(l):
return isinstance(l, list) and len(l) > 5
def print_list_size(l):
return 'list(size={})'.format(len(l))
def print_ndarray(a):
return 'ndarray(shape={}, dtype={})'.format(a.shape, a.dtype)
@pysnooper.snoop(custom_repr=((large, print_list_size), (numpy.ndarray, print_ndarray)))
def sum_to_x(x):
l = list(range(x))
a = numpy.zeros((10,10))
return sum(l)
sum_to_x(10000)
```
You will get `l = list(size=10000)` for the list, and `a = ndarray(shape=(10, 10), dtype=float64)` for the ndarray.
The `custom_repr` are matched in order, if one condition matches, no further conditions will be checked.
Variables and exceptions get truncated to 100 characters by default. You
can customize that:
```python
@pysnooper.snoop(max_variable_length=200)
```
You can also use `max_variable_length=None` to never truncate them.

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@ -117,81 +117,13 @@ See values of some expressions that aren't local variables:
@pysnooper.snoop(watch=('foo.bar', 'self.x["whatever"]'))
```
Expand values to see all their attributes or items of lists/dictionaries:
```python
@pysnooper.snoop(watch_explode=('foo', 'self'))
```
This will output lines like:
```
Modified var:.. foo[2] = 'whatever'
New var:....... self.baz = 8
```
(see [Advanced Usage](#advanced-usage) for more control)
Show snoop lines for functions that your function calls:
```python
@pysnooper.snoop(depth=2)
```
Start all snoop lines with a prefix, to grep for them easily:
```python
@pysnooper.snoop(prefix='ZZZ ')
```
Remove all machine-related data (paths, timestamps, memory addresses) to compare with other traces easily:
```python
@pysnooper.snoop(normalize=True)
```
On multi-threaded apps identify which thread are snooped in output:
```python
@pysnooper.snoop(thread_info=True)
```
PySnooper supports decorating generators.
If you decorate a class with `snoop`, it'll automatically apply the decorator to all the methods. (Not including properties and other special cases.)
You can also customize the repr of an object:
```python
def large(l):
return isinstance(l, list) and len(l) > 5
def print_list_size(l):
return 'list(size={})'.format(len(l))
def print_ndarray(a):
return 'ndarray(shape={}, dtype={})'.format(a.shape, a.dtype)
@pysnooper.snoop(custom_repr=((large, print_list_size), (numpy.ndarray, print_ndarray)))
def sum_to_x(x):
l = list(range(x))
a = numpy.zeros((10,10))
return sum(l)
sum_to_x(10000)
```
You will get `l = list(size=10000)` for the list, and `a = ndarray(shape=(10, 10), dtype=float64)` for the ndarray.
The `custom_repr` are matched in order, if one condition matches, no further conditions will be checked.
Variables and exceptions get truncated to 100 characters by default. You
can customize that:
```python
@pysnooper.snoop(max_variable_length=200)
```
You can also use `max_variable_length=None` to never truncate them.
**See [Advanced Usage](https://github.com/cool-RR/PySnooper/blob/master/ADVANCED_USAGE.md) for more options.** <------
# Installation #
@ -208,27 +140,6 @@ $ pip install pysnooper
$ conda install -c conda-forge pysnooper
```
# Advanced Usage #
`watch_explode` will automatically guess how to expand the expression passed to it based on its class. You can be more specific by using one of the following classes:
```python
import pysnooper
@pysnooper.snoop(watch=(
pysnooper.Attrs('x'), # attributes
pysnooper.Keys('y'), # mapping (e.g. dict) items
pysnooper.Indices('z'), # sequence (e.g. list/tuple) items
))
```
Exclude specific keys/attributes/indices with the `exclude` parameter, e.g. `Attrs('x', exclude=('_foo', '_bar'))`.
Add a slice after `Indices` to only see the values within that slice, e.g. `Indices('z')[-3:]`.
```console
$ export PYSNOOPER_DISABLED=1 # This makes PySnooper not do any snooping
```
# License #