字符串替换(you替换成we)⭐

该博客介绍了如何使用C语言编写程序来实现将输入字符串中的所有'you'替换为'we'的功能。程序通过读取多行输入,逐行处理字符串,并利用条件判断找到并替换目标子串。替换操作在内存中完成,输出替换后的结果。

编写一个C程序实现将字符串中的所有"you"替换成"we"

Input

输入包含多行数据

每行数据是一个字符串,长度不超过1000
数据以EOF结束

Output

对于输入的每一行,输出替换后的字符串

Sample Input

you are what you do

Sample Output

we are what we do

思路:while中用gets输入字符串,用strlen判断输入的字符串的长度(for循环里要用到),

判断第i个字符&&第i+1个字符&&第i+2个字符是否等于相应的数。

相等的话直接修改,然后i+=2即可。不相等直接输出这第i个数

实现代码:

#include<stdio.h>
#include<string.h>
int main()
{
    char a[1010];
    int i,j,n;
    while(gets(a))
    {
        n=strlen(a);
        for(i=0;i<n;i++)
        {
           if(a[i]=='y'&&a[i+1]=='o'&&a[i+2]=='u')
            {
                printf("we");
                i+=2;
            }
            else
            {
                printf("%c",a[i]);
            }

        }
        printf("\n");
    }
    return 0;
}

 

(yolov8) D:\ultralytics-main>yolo task=detect mode=train model=yolov8n.pt data=data/blueberry.yaml batch=32 epochs=20 imgsz=640 workers=16 device=0 A module that was compiled using NumPy 1.x cannot be run in NumPy 2.0.0 as it may crash. To support both 1.x and 2.x versions of NumPy, modules must be compiled with NumPy 2.0. Some module may need to rebuild instead e.g. with 'pybind11>=2.12'. If you are a user of the module, the easiest solution will be to downgrade to 'numpy<2' or try to upgrade the affected module. We expect that some modules will need time to support NumPy 2. Traceback (most recent call last): File "D:\Anaconda3\envs\yolov8\lib\runpy.py", line 196, in _run_module_as_main return _run_code(code, main_globals, None, File "D:\Anaconda3\envs\yolov8\lib\runpy.py", line 86, in _run_code exec(code, run_globals) File "D:\Anaconda3\envs\yolov8\Scripts\yolo.exe\__main__.py", line 2, in <module> from ultralytics.cfg import entrypoint File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\__init__.py", line 13, in <module> from ultralytics.utils import ASSETS, SETTINGS File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\utils\__init__.py", line 25, in <module> import torch File "D:\Anaconda3\envs\yolov8\lib\site-packages\torch\__init__.py", line 1382, in <module> from .functional import * # noqa: F403 File "D:\Anaconda3\envs\yolov8\lib\site-packages\torch\functional.py", line 7, in <module> import torch.nn.functional as F File "D:\Anaconda3\envs\yolov8\lib\site-packages\torch\nn\__init__.py", line 1, in <module> from .modules import * # noqa: F403 File "D:\Anaconda3\envs\yolov8\lib\site-packages\torch\nn\modules\__init__.py", line 35, in <module> from .transformer import TransformerEncoder, TransformerDecoder, \ File "D:\Anaconda3\envs\yolov8\lib\site-packages\torch\nn\modules\transformer.py", line 20, in <module> device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), D:\Anaconda3\envs\yolov8\lib\site-packages\torch\nn\modules\transformer.py:20: UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at ..\torch\csrc\utils\tensor_numpy.cpp:84.) device: torch.device = torch.device(torch._C._get_default_device()), # torch.device('cpu'), Ultralytics 8.3.207 Python-3.10.18 torch-2.1.1+cu118 CUDA:0 (NVIDIA GeForce RTX 4050 Laptop GPU, 6140MiB) engine\trainer: agnostic_nms=False, amp=True, augment=False, auto_augment=randaugment, batch=32, bgr=0.0, box=7.5, cache=False, cfg=None, classes=None, close_mosaic=10, cls=0.5, compile=False, conf=Non e, copy_paste=0.0, copy_paste_mode=flip, cos_lr=False, cutmix=0.0, data=data/blueberry.yaml, degrees=0.0, deterministic=True, device=0, dfl=1.5, dnn=False, dropout=0.0, dynamic=False, embed=None, epoch s=20, erasing=0.4, exist_ok=False, fliplr=0.5, flipud=0.0, format=torchscript, fraction=1.0, freeze=None, half=False, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, imgsz=640, int8=False, iou=0.7, keras=False, kob j=1.0, line_width=None, lr0=0.01, lrf=0.01, mask_ratio=4, max_det=300, mixup=0.0, mode=train, model=yolov8n.pt, momentum=0.937, mosaic=1.0, multi_scale=False, name=train16, nbs=64, nms=False, opset=Non e, optimize=False, optimizer=auto, overlap_mask=True, patience=100, perspective=0.0, plots=True, pose=12.0, pretrained=True, profile=False, project=None, rect=False, resume=False, retina_masks=False, s ave=True, save_conf=False, save_crop=False, save_dir=D:\ultralytics-main\runs\detect\train16, save_frames=False, save_json=False, save_period=-1, save_txt=False, scale=0.5, seed=0, shear=0.0, show=Fals e, show_boxes=True, show_conf=True, show_labels=True, simplify=True, single_cls=False, source=None, split=val, stream_buffer=False, task=detect, time=None, tracker=botsort.yaml, translate=0.1, val=True, verbose=True, vid_stride=1, visualize=False, warmup_bias_lr=0.1, warmup_epochs=3.0, warmup_momentum=0.8, weight_decay=0.0005, workers=16, workspace=None Overriding model.yaml nc=80 with nc=2 from n params module arguments 0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2] 1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2] 2 -1 1 7360 ultralytics.nn.modules.block.C2f [32, 32, 1, True] 3 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2] 4 -1 2 49664 ultralytics.nn.modules.block.C2f [64, 64, 2, True] 5 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2] 6 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True] 7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] 8 -1 1 460288 ultralytics.nn.modules.block.C2f [256, 256, 1, True] 9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5] 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] 12 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1] 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] 14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] 15 -1 1 37248 ultralytics.nn.modules.block.C2f [192, 64, 1] 16 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] 18 -1 1 123648 ultralytics.nn.modules.block.C2f [192, 128, 1] 19 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] 21 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1] 22 [15, 18, 21] 1 751702 ultralytics.nn.modules.head.Detect [2, [64, 128, 256]] Model summary: 129 layers, 3,011,238 parameters, 3,011,222 gradients, 8.2 GFLOPs Transferred 319/355 items from pretrained weights Freezing layer 'model.22.dfl.conv.weight' AMP: running Automatic Mixed Precision (AMP) checks... Traceback (most recent call last): File "D:\Anaconda3\envs\yolov8\lib\runpy.py", line 196, in _run_module_as_main return _run_code(code, main_globals, None, File "D:\Anaconda3\envs\yolov8\lib\runpy.py", line 86, in _run_code exec(code, run_globals) File "D:\Anaconda3\envs\yolov8\Scripts\yolo.exe\__main__.py", line 6, in <module> File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\cfg\__init__.py", line 990, in entrypoint getattr(model, mode)(**overrides) # default args from model File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\engine\model.py", line 800, in train self.trainer.train() File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\engine\trainer.py", line 235, in train self._do_train() File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\engine\trainer.py", line 356, in _do_train self._setup_train() File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\engine\trainer.py", line 293, in _setup_train self.amp = torch.tensor(check_amp(self.model), device=self.device) File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\utils\checks.py", line 795, in check_amp assert amp_allclose(YOLO("yolo11n.pt"), im) File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\models\yolo\model.py", line 83, in __init__ super().__init__(model=model, task=task, verbose=verbose) File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\engine\model.py", line 153, in __init__ self._load(model, task=task) File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\engine\model.py", line 297, in _load self.model, self.ckpt = load_checkpoint(weights) File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\nn\tasks.py", line 1501, in load_checkpoint ckpt, weight = torch_safe_load(weight) # load ckpt File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\nn\tasks.py", line 1448, in torch_safe_load ckpt = torch_load(file, map_location="cpu") File "D:\Anaconda3\envs\yolov8\lib\site-packages\ultralytics\utils\patches.py", line 120, in torch_load return torch.load(*args, **kwargs) File "D:\Anaconda3\envs\yolov8\lib\site-packages\torch\serialization.py", line 993, in load with _open_zipfile_reader(opened_file) as opened_zipfile: File "D:\Anaconda3\envs\yolov8\lib\site-packages\torch\serialization.py", line 447, in __init__ super().__init__(torch._C.PyTorchFileReader(name_or_buffer)) OSError: [Errno 22] Invalid argument
最新发布
10-11
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