fromstringfromfile behave badly with malformed data trac 883
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Okay, let's delve into the potential pitfalls of using `numpy.fromstring` and `numpy.fromfile` with malformed or unexpected data, focusing on how these functions can behave unexpectedly and the implications of these behaviors, especially in the context of Trac 883 (though that specific Trac ticket might be older, the underlying issues are still relevant).
**Understanding the Basics: `fromstring` and `fromfile`**
Before diving into the problems, let's quickly recap what these NumPy functions do:
* **`numpy.fromstring(string, dtype=float, count=-1, sep='')`:** This function takes a string as input and interprets it as a raw byte stream. It then converts the byte stream into a NumPy array according to the specified `dtype` (data type). `count` specifies the number of elements to read. `sep` allows you to specify a separator when the string contains text-based data (e.g., comma-separated values).
* **`numpy.fromfile(file, dtype=float, count=-1, sep='')`:** This function reads data directly from a file. Like `fromstring`, it interprets the data as a raw byte stream and converts it to a NumPy array according to `dtype`. `count` specifies the number of elements to read. `sep` (as of NumPy 1.14) can be used to read text files using delimiters. Earlier versions were primarily intended for binary data.
**The Problem: What Does "Malformed Data" Mean?**
"Malformed data" in this context can refer to several things:
1. **Incorrect Data Type:** The data in the file or string doesn't conform to the `dtype` you're trying to interpret it as. For instance, you're trying to read a file containing text characters as `float64`.
2. **Incomplete Data:** The file or string ends prematurely, not providing enough data to create the full array as specified by `count` or the implicitly defined size based on the `dtype`.
3. **Binary Format Issues:** In the case of binary files, endianness mismatches or incorrect data formatting (e.g., using a float where an integer is expect ...
#numpy #numpy #numpy
Видео fromstringfromfile behave badly with malformed data trac 883 канала CodeTime
Okay, let's delve into the potential pitfalls of using `numpy.fromstring` and `numpy.fromfile` with malformed or unexpected data, focusing on how these functions can behave unexpectedly and the implications of these behaviors, especially in the context of Trac 883 (though that specific Trac ticket might be older, the underlying issues are still relevant).
**Understanding the Basics: `fromstring` and `fromfile`**
Before diving into the problems, let's quickly recap what these NumPy functions do:
* **`numpy.fromstring(string, dtype=float, count=-1, sep='')`:** This function takes a string as input and interprets it as a raw byte stream. It then converts the byte stream into a NumPy array according to the specified `dtype` (data type). `count` specifies the number of elements to read. `sep` allows you to specify a separator when the string contains text-based data (e.g., comma-separated values).
* **`numpy.fromfile(file, dtype=float, count=-1, sep='')`:** This function reads data directly from a file. Like `fromstring`, it interprets the data as a raw byte stream and converts it to a NumPy array according to `dtype`. `count` specifies the number of elements to read. `sep` (as of NumPy 1.14) can be used to read text files using delimiters. Earlier versions were primarily intended for binary data.
**The Problem: What Does "Malformed Data" Mean?**
"Malformed data" in this context can refer to several things:
1. **Incorrect Data Type:** The data in the file or string doesn't conform to the `dtype` you're trying to interpret it as. For instance, you're trying to read a file containing text characters as `float64`.
2. **Incomplete Data:** The file or string ends prematurely, not providing enough data to create the full array as specified by `count` or the implicitly defined size based on the `dtype`.
3. **Binary Format Issues:** In the case of binary files, endianness mismatches or incorrect data formatting (e.g., using a float where an integer is expect ...
#numpy #numpy #numpy
Видео fromstringfromfile behave badly with malformed data trac 883 канала CodeTime
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