ssp/README.md

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# Static split parser
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A header only "csv" parser which is fast and versatile with modern C++ api. Requires compiler with C++17 support.
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Conversion for numeric values taken from [Oliver Schönrock](https://gist.github.com/oschonrock/67fc870ba067ebf0f369897a9d52c2dd) .
Function traits taken from [qt-creator](https://code.woboq.org/qt5/qt-creator/src/libs/utils/functiontraits.h.html) .
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# Example
Lets say we have a csv file containing students in the
following format <name,age,grade>:
```
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$ cat students.csv
James Bailey,65,2.5
Brian S. Wolfe,40,11.9
Nathan Fielder,37,Really good grades
Bill (Heath) Gates,65,3.3
```
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```cpp
#include <iostream>
#include <ss/parser.hpp>
int main() {
ss::parser p{"students.csv", ","};
if (!p.valid()) {
std::cout << p.error_msg() << std::endl;
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exit(EXIT_FAILURE);
}
while (!p.eof()) {
auto [name, age, grade] = p.get_next<std::string, int, double>();
if (p.valid()) {
std::cout << name << ' ' << age << ' ' << grade << std::endl;
}
}
return 0;
}
```
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And if we compile and execute the program we get the following output:
```
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$ ./a.out
James Bailey 65 2.5
Brian S. Wolfe 40 11.9
Bill (Heath) Gates 65 3.3
```
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# Features
* Works on any type
* Easy to use
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* No exceptions
* Columns and rows can be ignored
* Works with any type of delimiter
* Can return whole objects composed of converted values
* Descriptive error handling can be enabled
* Restrictions can be added for each column
* Works with `std::optional` and `std::variant`
* Works with **CRLF** and **LF**
* Conversions can be chained if invalid
* Fast
# Instalation
```
$ git clone https://github.com/red0124/ssp
$ cd ssp
$ sudo make install
```
Run tests (optional):
```
$ make test
```
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# Usage
## Error handling
Detailed error messages can be accessed via the **error_msg** method, and to
enable them the error mode has to be changed to **error_mode::String** using
the **set_error_mode** method:
```cpp
void parser::set_error_mode(ss::error_mode);
const std::string& parser::error_msg();
bool parser::valid();
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bool parser::eof();
```
Error messages can always be disabled by setting the error mode to
**error_mode::Bool**. An error can be detected using the **valid** method which
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would return **false** if the file could not be opened, or if the conversion
could not be made (invalid types, invalid number of columns, ...).
The **eof** method can be used to detect if the end of the file was reached.
## Conversions
The above example will be used to show some of the features of the library.
As seen above, the **get_next** method returns a tuple of objects specified
inside the template type list.
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If a conversion could not be applied, the method would return a tuple of
default constructed objects, and **valid** would return **false**, for example
if the third (grade) column in our csv could not be converted to a double
the conversion would fail.
If **get_next** is called with a **tuple** it would behave identically to passing
the same tuple parameters to **get_next**:
```cpp
using student = std::tuple<std::string, int, double>;
// returns std::tuple<std::string, int, double>
auto [name, age, grade] = p.get_next<student>();
```
*Note, it does not always return a student tuple since the returned tuples
parameters may be altered as explained below (no void, no restrictions, ...)*
Whole objects can be returned using the **get_object** function which takes the
tuple, created in a similar way as **get_next** does it, and creates an object
out of it:
```cpp
struct student {
std::string name;
int age;
double grade;
};
```
```cpp
// returns student
auto student = p.get_object<student, std::string, int, double>();
```
This works with any object if the constructor could be invoked using the
template arguments given to **get_object**:
```cpp
// returns std::vector<std::string> containing 3 elements
auto vec = p.get_object<std::vector<std::string>, std::string, std::string,
std::string>();
```
And finally, using something I personally like to do, a struct (class) with a **tied**
method witch returns a tuple of references to to the members of the struct.
```cpp
struct student {
std::string name;
int age;
double grade;
auto tied() { return std::tie(name, age, grade); }
};
```
The method can be used to compare the object, serialize it, deserialize it, etc.
Now **get_next** can accept such a struct and deduce the types to which to convert the csv.
```cpp
// returns student
auto s = p.get_next<student>();
```
*Note, the order in which the members of the tied method are returned must
match the order of the elements in the csv*
### Special types
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Passing **void** makes the parser ignore a column.
In the given example **void** could be given as the second
template parameter to ignore the second (age) column in the csv, a tuple
of only 2 parameters would be retuned:
```cpp
// returns std::tuple<std::string, double>
auto [name, grade] = p.get_next<std::string, void, double>();
```
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Works with different types of conversions too:
```cpp
using student = std::tuple<std::string, void, double>;
// returns std::tuple<std::string, double>
auto [name, grade] = p.get_next<student>();
```
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To ignore a whole row, **ignore_next** could be used, returns **false** if **eof**:
```cpp
bool parser::ignore_next();
```
**std::optional** could be passed if we wanted the conversion to proceed in the
case of a failure returning **std::nullopt** for the specified column:
```cpp
// returns std::tuple<std::string, int, std::optional<double>>
auto [name, age, grade] = p.get_next<std::string, int, std::optional<double>();
if(grade) {
// do something with grade
}
```
Similar to **std::optional**, **std::variant** could be used to try other
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conversions if the previous failed _(Note, conversion to std::string will
always pass)_:
```cpp
// returns std::tuple<std::string, int, std::variant<double, char>>
auto [name, age, grade] =
p.get_next<std::string, int, std::variant<double, char>();
if(std::holds_alternative<double>(grade)) {
// grade set as double
} else if(std::holds_alternative<char>(grade)) {
// grade set as char
}
```
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### Restrictions
Custom **restrictions** can be used to narrow down the conversions of unwanted
values. **ss::ir** (in range) and **ss::ne** (none empty) are one of those:
```cpp
// ss::ne makes sure that the name is not empty
// ss::ir makes sure that the grade will be in range [0, 10]
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// returns std::tuple<std::string, int, double>
auto [name, age, grade] =
p.get_next<ss::ne<std::string>, int, ss::ir<double, 0, 10>>();
```
If the restrictions are not met, the conversion will fail.
Other predefined restrictions are **ss::ax** (all except), **ss::nx** (none except)
and **ss::oor** (out of range):
```cpp
// all ints exept 10 and 20
ss::ax<int, 10, 20>
// only 10 and 20
ss::nx<int, 10, 20>
// all values except the range [0, 10]
ss::oor<int, 0, 10>
```
To define a restriction, a class/struct needs to be made which has a
**ss_valid** method which returns a **bool** and accepts one object. The type of the
conversion will be the same as the type of the passed object within **ss_valid**
and not the restriction itself. Optionally, an **error** method can be made to
describe the invalid conversion.
```cpp
template <typename T>
struct even {
bool ss_valid(const T& value) const {
return value % 2 == 0;
}
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// optional
const char* error() const {
return "number not even";
}
};
// ...
// only even numbers will pass
// returns std::tuple<std::string, int>
auto [name, age] = p.get_next<std::string, even<int>, void>();