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https://github.com/ztl-uwu/py-vtest

An OI test-data generation & std test tool.
https://github.com/ztl-uwu/py-vtest

oi python test-data

Last synced: 13 days ago
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An OI test-data generation & std test tool.

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README

        

# py-Vtest

![[LICENSE](https://github.com/ZTL-UwU/py-vtest/blob/main/LICENSE)](https://img.shields.io/github/license/ZTL-UwU/py-vtest?style=flat-square)
![Code Size](https://img.shields.io/github/languages/code-size/ZTL-UwU/py-vtest?style=flat-square)

An OI test-data maker & std test tool.

## Mode

1. **vmake**: Automatically generate test-data with user-provided standard solution and Maker (described below).
2. **vcheck**: Execute a solution on set of test-data like an OnlineJudge does.
**WARNING: No sandbox protection, don't run any untrusted code!**

## Maker

A Maker is an executable that generates the input of a single test case.

**How to write a Maker?**

1. Read the subtask ID (starting from 1), a single integer from `stdin`.
2. Output the input data to `stdout`.

## Usage

1. Create `vtest.conf`.

**The format of `vtest.conf`**:

```plaintext




...

```

**Example**:

```plaintext
AplusB 5
data
5
15
20
20
40
```

2. The file structure will be like this

```plaintext
.
├─ // Auto Generated
│ ├─ .1.1.in
│ ├─ .1.1.out
│ ├─ ...
│ ├─ ...in
│ └─ ...out

├─ mk_ // Compile yourself
├─ std_ // Compile yourself
├─ run_ // Compile yourself
├─ vmake.py // Downloaded
└─ vcheck.py // Downloaded
```

## Example

Here is a example of generating test-data of the _A + B problem_ and testing a solution of it.

1. Create an empty folder.
2. Create `vtest.conf` with the following content:

```plaintext
AplusB 2
data
6
4
```

3. Download `vmake.py` and `vcheck.py`.

You can use the following commands if you prefer CLI or simply click `Download Zip` in the project repository page and extract `vmake.py` and `vcheck.py`:

```bash
wget https://github.com/ZTL-UwU/py-vtest/raw/main/vmake.py
wget https://github.com/ZTL-UwU/py-vtest/raw/main/vcheck.py
```

4. Create a standard solutoion as an executable named `std_AplusB`.

For example, the following code is a C++ version of a standard solution of _A + B problem_, compile it into `std_AplusB`:

```cpp
// std_AplusB.cpp
#include

int main() {
long long a, b;
std::cin >> a >> b;
std::cout << a + b;
return 0;
}
```

Compile commands:

```bash
g++ std_AplusB.cpp -o std_AplusB
```

5. Create an executable named `mk_AplusB` which is a Maker (described above).

For example, the following is a C++ version of the test-data Maker, compile it into `mk_AplusB`:

```cpp
// mk_AplusB.cpp
#include
#include

int main() {
int subtask_id;
std::cin >> subtask_id;

if (subtask_id == 1) {
std::mt19937 rng(std::random_device{}());
std::cout << rng() << " " << rng();
}

if (subtask_id == 2) {
// In this subtask, we will generate larger inputs
// which can hack solutions without using long long.
std::mt19937_64 rng(std::random_device{}());
std::cout << rng() << " " << rng();
}

return 0;
}
```

Compile commands:

```bash
g++ mk_AplusB.cpp -o mk_AplusB
```

6. Run `vmake.py`.

You can use the following command or simply double-click on `vmake.py`:

```bash
python3 vmake.py
```

The output is similar to the following:

```plaintext
Start Making data for AplusB.

Making subtask #1
[ 10%] Made case #1.1: (9.0ms)
[ 20%] Made case #1.2: (2.17ms)
[ 30%] Made case #1.3: (5.08ms)
[ 40%] Made case #1.4: (2.53ms)
[ 50%] Made case #1.5: (4.01ms)
[ 60%] Made case #1.6: (3.81ms)
Making subtask #2
[ 70%] Made case #2.1: (1.99ms)
[ 80%] Made case #2.2: (3.06ms)
[ 90%] Made case #2.3: (2.04ms)
[100%] Made case #2.4: (3.4ms)

Summary:
Slowest case: #1.1 (9.0ms)
```

Now you can see the generated data in the `data` folder.

```
.
├─ data
| ├─ AplusB.1.1.in
| ├─ AplusB.1.1.out
| ├─ ...
| ├─ AplusB.2.4.in
| └─ AplusB.2.4.out
```

7. Lets try another solution without using `long long` (who cannot pass the test).

This is a C++ version of a wrong solution, compile it into `run_AplusB`:

```cpp
// AplusB_wrong.cpp
#include

int main() {
int a, b;
std::cin >> a >> b;
std::cout << a + b;
return 0;
}
```

Compile commands:

```bash
g++ AplusB_wrong.cpp -o run_AplusB
```

8. Run `vcheck.py`

You can use the following command or simply double-click on `vcheck.py`:

```bash
python3 vcheck.py
```

The output is similar to the following:

```plaintext
Start checking subtask #1
[ 10%] Case #1.1: Answer Correct (2.56ms)
[ 20%] Case #1.2: Answer Correct (2.33ms)
[ 30%] Case #1.3: Answer Correct (2.6ms)
[ 40%] Case #1.4: Answer Correct (7.18ms)
[ 50%] Case #1.5: Answer Correct (2.22ms)
[ 60%] Case #1.6: Answer Correct (2.24ms)
Start checking subtask #2
[ 70%] Case #2.1: Wrong Answer (3.17ms)
[ 80%] Case #2.2: Wrong Answer (2.85ms)
[ 90%] Case #2.3: Wrong Answer (2.28ms)
[100%] Case #2.4: Wrong Answer (2.76ms)

Summary: WA
Total time: 30.2ms
Slowest case: #1.4 (7.18ms)
--------------------------------
AC: 6 [ 60%]
WA: 4 [ 40%]
RE: 0 [ 0%]
```

## Todo

1. Add `.exe` suffix on Windows in `vcheck.py` and `vhack.py`. (see #2)
1. Introduce `vhack.py` in README.
1. Add a `zh-cn` version of the README introduction.
1. Extract shared codes in `vmake.py`, `vhack.py` and `vcheck.py`.
1. Auto generate subtask configuration files for HustOJ, LibraOJ, HydroOJ and more (maybe `vconf.py` ?).
1. Use command-line arguments rather that fixed `std_xxx`, `mk_xxx` stuff.
1. Check inputs with a codeforces styled validator (maybe `vvalidate.py` ?).
1. Write an introduction and documention about libvmake.