# Static split parser

A header only "csv" parser which is fast and versatile with modern C++ api. Requires compiler with C++17 support. 

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) .   

# Example 
Lets say we have a csv file containing students in the 
following format <name,age,grade>:

```
$ 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
```
```cpp
#include <iostream>
#include <ss/parser.hpp>

int main() {
    ss::parser p{"students.csv", ","};
    if (!p.valid()) {
        std::cout << p.error_msg() << std::endl;
        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;
}
```

And if we compile and execute the program we get the following output:

```
$ ./a.out
James Bailey 65 2.5
Brian S. Wolfe 40 11.9
Bill (Heath) Gates 65 3.3
```
# Features
 * Works on any type
 * Easy to use
 * 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
```

# Usage

## 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.   

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 

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>();
```
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>();
```
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   
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
}
```
### 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]
// 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), **ss::lt** (less than), ...(see *restrictions.hpp*):
```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;
    }

    // optional
    const char* error() const {
        return "number not even";
    }
};
```
```cpp
// only even numbers will pass
// returns std::tuple<std::string, int>
auto [name, age] = p.get_next<std::string, even<int>, void>();
```
## Custom conversions

Custom types can be used when converting values. A specialization of the **ss::extract**  
function needs to be made and you are good to go. Custom conversion for an enum  
would look like this: 
```cpp
enum class shape { circle, square, rectangle, triangle };

template <>
inline bool ss::extract(const char* begin, const char* end, shape& dst) {
    const static std::unordered_map<std::string, shape>
        shapes{{"circle", shape::circle},
               {"square", shape::square},
               {"rectangle", shape::rectangle},
               {"triangle", shape::triangle}};

    if (auto it = shapes.find(std::string(begin, end)); it != shapes.end()) {
        dst = it->second;
        return true;
    }
    return false;
}
```
The shape enum will be used in an example below. The **inline** is there just to prevent   
multiple definition errors. The function returns **true** if the conversion was  
a success, and **false** otherwise. The function uses **const char*** begin and end  
for performance reasons.

## 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::error_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();
bool parser::eof();
```
Error messages can always be disabled by setting the error mode to  
**error_mode::error_bool**. An error can be detected using the **valid** method which   
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.  

## Substitute conversions

The parser can also be used to effectively parse files whose rows are not  
always in the same format (not a classical csv but still csv-like).  
A more complicated example would be the best way to demonstrate such a scenario.  

Supposing we have a file containing different shapes in given formats: 
 * circle radius
 * square side
 * rectangle side_a side_b
 * triangle side_a side_b side_c

The delimiter is " ", and the number of columns varies depending on which  
shape it is. We are required to read the file and to store information   
(shape and area) of the shapes into a data structure in the same order  
as they are in the file. 
```cpp
ss::parser p{"shapes.txt", " "};
if (!p.valid()) {
    std::cout << p.error_msg() << std::endl;
    exit(EXIT_FAILURE);
}

std::vector<std::pair<shape, double>> shapes;

while (!p.eof()) {
    // non negative double
    using udbl = ss::gte<double, 0>;

    auto [circle_or_square, rectangle, triangle] =
        p.try_next<ss::nx<shape, shape::circle, shape::square>, udbl>()
            .or_else<ss::nx<shape, shape::rectangle>, udbl, udbl>()
            .or_else<ss::nx<shape, shape::triangle>, udbl, udbl, udbl>()
            .values();

    if (circle_or_square) {
        auto& [s, x] = circle_or_square.value();
        double area = (s == shape::circle) ? x * x * M_PI : x * x;
        shapes.emplace_back(s, area);
    }

    if (rectangle) {
        auto& [s, a, b] = rectangle.value();
        shapes.emplace_back(s, a * b);
    }

    if (triangle) {
        auto& [s, a, b, c] = triangle.value();
        double sh = (a + b + c) / 2;
        if (sh >= a && sh >= b && sh >= c) {
            double area = sqrt(sh * (sh - a) * (sh - b) * (sh - c));
            shapes.emplace_back(s, area);
        }
    }
}

/* do something with the stored shapes */
/* ... */
```
It is quite hard to make an error this way since most things will be checked  
at compile time.  

The **try_next** method works in a similar way as **get_next** but returns a **composit**  
which holds a **tuple** with an **optional** to the **tuple** returned by **get_next**.  
This **composite** has an **or_else** method (looks a bit like tl::expected) which  
is able to try additional conversions if the previous failed.  
It also returns a **composite**, but in its tuple is the **optional** to the **tuple**   
of the previous conversions and an **optional** to the **tuple** to the new conversion.   

To fetch the **tuple** from the **composite** the **values** method is used.
The value of the above used conversion would look something like this
(with the restrictions applied to the values of shape - ss::nx)
```cpp
std::tuple<
    std::optional<std::tuple<shape, double>>,
    std::optional<std::tuple<shape, double, double>>,
    std::optional<std::tuple<shape, double, double, double>>
    >
```
Similar to the way that **get_next** has a **get_object** alternative, **try_next** has a **try_object**  
alternative, and **or_else** has a **or_object** alternative. Also all rules applied  
to **get_next** also work with **try_next** , **or_else**, and all the other **composite** conversions.  

Each of those **composite** conversions can accept a lambda (or anything callable) as  
an argument and invoke it in case of a valid conversion. That lambda   
itself need not have any arguments, but if it does, it must either  
accept the whole **tuple**/object as one argument or all the elements of the tuple  
separately. If the lambda returns something that can be interpreted as **false**  
the conversion will fail, and the next conversion will try to apply. 
Rewriting the whole while loop using lambdas would look like this:  
```cpp
// non negative double
using udbl = ss::gte<double, 0>;

p.try_next<ss::nx<shape, shape::circle, shape::square>, udbl>(
     [&](const auto& data) {
         const auto& [s, x] = data;
         double area = (s == shape::circle) ? x * x * M_PI : x * x;
         shapes.emplace_back(s, area);
     })
    .or_else<ss::nx<shape, shape::rectangle>, udbl, udbl>(
        [&](const shape s, const double a, const double b) {
            shapes.emplace_back(s, a * b);
        })
    .or_else<ss::nx<shape, shape::triangle>, udbl, udbl, udbl>(
        [&](auto&& s, auto& a, const double& b, double& c) {
            double sh = (a + b + c) / 2;
            if (sh >= a && sh >= b && sh >= c) {
                double area = sqrt(sh * (sh - a) * (sh - b) * (sh - c));
                shapes.emplace_back(s, area);
            }
        });
```
It is a bit less readable, but it removes the need to check which conversion  
was invoked. The **composite** also has an **on_error** method which accepts a lambda  
will be invoked if none previous conversions were successful. The lambda may  
take no arguments or one argument , a **std::string**, in which the error message  
is stored if **error_mode** is set to **error_mode::error_string**: 
```cpp
p.try_next<int>()
    .on_error([](const std::string& e) { /* int conversion failed */ })
    .or_object<x, double>()
    .on_error([] { /* int and x (all) conversions failed */ });
```
*See unit tests for more examples.*