大四学生IT企业求职经验全记录

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资源摘要信息:"本文档提供了关于求职过程的详细记录，特别针对IT行业的求职者。文档中不仅包括了求职者本人的大四求职经历，而且详细介绍了在申请IT企业职位时所经历的笔试和面试环节。文档的标题和描述表明，该求职者曾申请多家知名IT公司，并在其中积累了宝贵的经验。这份记录不仅对当前正在求职的大学生或者准备进入职场的人员有参考价值，也对那些希望了解求职流程和面试技巧的专业人士提供了实用的信息。 文档内容可能涉及以下几个方面： 1. 求职准备：求职者在文档中可能记录了自己如何为求职做准备，包括制作简历、准备求职信、整理作品集或者项目经验等。对于IT求职者来说，这部分可能还包括了如何针对不同职位优化技术技能和知识点的准备。 2. 公司选择：求职者可能会谈到如何根据自己的专业背景、兴趣和职业规划来选择合适的IT企业。这部分内容可能涉及到各大IT企业的文化、业务范围、发展前景和招聘需求等。 3. 笔试经历：文档中可能详细描述了各种IT企业的笔试流程，包括笔试题型、考题范围以及个人应对策略等。例如，对于编程岗位可能涉及到算法与数据结构、软件开发流程、代码调试等内容。 4. 面试技巧：求职者在文档中可能分享了在面试过程中遇到的各种类型问题，例如行为面试问题、技术面试问题，以及面试官的评价标准。此外，还有可能介绍了一些面试前的准备技巧和面试当天的注意事项。 5. 求职总结：在文档的最后，求职者可能会总结自己的求职经验，提供一些面试和求职的建议，以及反思在求职过程中遇到的问题和自身的不足。 由于文件标题中包含了“.rar_it”，这表明该文档可能是经过压缩打包的文件，仅有一个包含求职经历记录的文档“求职记.docx”。对于有意向获取这份资源的读者来说，这将是一个了解IT行业求职现状，学习求职和面试技巧的好机会。"

iDRAC-with-Lifecycle-Controller_Firmware_40T1C_WN32_2.63.60.61_A00.zip

2019-09-21 上传
iDRAC（Integrated Dell Remote Access Controller）是戴尔公司推出的一种远程访问控制器，它集成在戴尔的PowerEdge服务器系列中，提供了对服务器硬件的远程监控、管理和维护功能。Lifecycle Controller则是iDRAC的...

percona-xtrabackup-8.0.23-16-Linux-x86_64.glibc2.17.tar

2022-01-24 上传
4. 备份验证：使用`innobackupex --apply-log`命令验证备份的完整性和一致性。 四、恢复策略 1. 为了安全起见，先在测试环境中验证恢复流程。将备份文件复制到新的MySQL服务器上，进入备份目录。 2. 应用日志：...

优化以下SQL select pao.id, pao.order_no, pao.apply_time, pao.purchase_user_id, pao.purchase_user_name, pao.apply_user_id, pao.apply_user_name, pao.apply_department_id, pao.apply_department_name, pao.apply_end_time, pao.create_user_id, pao.create_user_name, pao.approve_type, pao.approve_user_id, pao.approve_user_name, pao.approve_time, pao.description, pao.order_type, pao.purchase_type, pao.storage_type, pao.compose_order_no, pao.company_id, pao.delete, pao.create_time, pao.update_time, pao.supplier_id, pao.image_path, pao.contract_id, pao.status, pao.invoice_signer_name, pao.total_amount, pao.total_amount_tax, pao.purchase_status, pao.cancel_reason, pao.print_status, pao.demand_id, pao.arrival_status, pao.supervise_num, pao.supervise_date, pao.merge_apply_id, pao.deadline, pao.remind , s.name as supplierName, paod.amount, cm.return_status as returnStatus, cm.inventory_status as inventoryStatus, cm.stock_remark, cm.merge_flag, cm.signature_file, cm.department_pass, cm.receipt_file, cm.amount_paid, cm.amount_unpaid, cm.contract_name, cm.status as contractStatus, cm.contract_no, cm.contract_amount, paod.product_name, cm.advance_payment, cm.advance_ratio, cm.currency_unit from purchase_apply_order pao left join supplier s on pao.supplier_id = s.id left join ( SELECT GROUP_CONCAT(distinct p.product_name) product_name, sum(IFNULL(amount_tax, 0)) amount, apply_order_no from purchase_apply_order_details pa left join product p on p.pn_code = pa.product_code where p.company_id = 29 GROUP BY apply_order_no ) paod on paod.apply_order_no = pao.order_no left join contract_management cm on pao.contract_id = cm.id where pao.delete = 0 and pao.company_id = 29 and deadline <= '2023-05-25 15:34:00.01' and remind = 0 and arrival_status in( 0 , 1 ) order by pao.create_time desc;

2023-05-25 上传
pao.apply_user_name, pao.apply_department_id, pao.apply_department_name, pao.apply_end_time, pao.create_user_id, pao.create_user_name, pao.approve_type, pao.approve_user_id, pao.approve_user_name, ...

SELECT t1.supplier_id, t1.ky_count, t1.ky_amount, IFNULL(t2.ky_refund_count,0) as ky_refund_count, IFNULL(t2.ky_refund_amount,0) as ky_refund_amount FROM ( SELECT a.supplier_id, count( DISTINCT c.order_no ) AS ky_count, SUM( IFNULL( c.record_amount, 0 )) / 100 AS ky_amount FROM settle_order a INNER JOIN settle_order_receipt b ON a.order_id = b.order_id INNER JOIN cash_withdrawal_record c ON b.third_trade_no = c.order_no WHERE a.is_del = 0 AND a.order_time >= '2023-05-28 00:00:00' AND a.order_time < '2023-05-29 00:00:00' AND a.order_type in (70,75) AND a.supplier_id IN (78,63,58,57,64,72,71,74,83,77,70,69,67,82,65,87,73,59,66,60,86,85,79,80,84,90) AND b.channel_code = 61 AND c.con_bank_account_no IN ( 247, 325 ) AND c.record_status = 1 AND c.record_time > '2023-05-01 00:00:00' GROUP BY a.supplier_id ) t1 LEFT JOIN ( SELECT a.supplier_id, count( DISTINCT b.order_no ) AS ky_refund_count, SUM( IFNULL( b.record_amount, 0 )) / 100 AS ky_refund_amount FROM settle_order_refund a INNER JOIN cash_withdrawal_record b ON a.third_refund_id = b.order_no WHERE a.is_del = 0 AND a.order_type in (70,75) AND a.apply_time >= '2023-05-28 00:00:00' AND a.apply_time < '2023-05-29 00:00:00' AND a.supplier_id IN (78,63,58,57,64,72,71,74,83,77,70,69,67,82,65,87,73,59,66,60,86,85,79,80,84,90) AND a.channel_code = 61 AND b.con_bank_account_no IN ( 247, 325 ) AND b.record_status = 5 AND b.record_time > '2023-05-01 00:00:00' GROUP BY a.supplier_id ) t2 ON t1.supplier_id = t2.supplier_id order by t1.supplier_id asc

2023-06-10 上传
AND a.supplier_id IN (78, 63, 58, 57, 64, 72, 71, 74, 83, 77, 70, 69, 67, 82, 65, 87, 73, 59, 66, 60, 86, 85, 79, 80, 84, 90) AND b.channel_code = 61 GROUP BY a.supplier_id ``` 同样的，对于另一...

转换为hive， STR_SQL:=' INSERT INTO jyfx_PRODUCT_ACCEPT_2022 SELECT A.obj_id,null,A.apply_obj_spec,null,A.create_date,A.region_id, A.create_ORG_ID,sysdAte,null,A.cust_order_id, A.ORDER_item_id,null,null,null, A.BELONG_lan_id,create_staff FROM ord_so.order_item@to_CRM_TEST A WHERE A.order_item_cd = ''1300'' and A.status_cd in (''301200'',''201300'') AND to_char(A.create_date,''yyyymmdd'') >= to_char(sysdate-35,''yyyymmdd'') AND A.SERVICE_OFFER_ID=4010100000 '; EXECUTE IMMEDIATE STR_SQL; --执行了一个名为STR_SQL的动态SQL语句。 COMMIT; --提交了之前的事务 INSERT INTO JOB_TIME_REC VALUES('jyfx_HOUR',V_START_TIME,SYSDATE, (SYSDATE-V_START_TIME)*24*3600,'受理'); --将一条记录插入到JOB_TIME_REC表中，包括了'jyfx_HOUR'、V_START_TIME、SYSDATE、(SYSDATE-V_START_TIME)243600和'受理'这些值。 COMMIT; --提交这次插入操作的事务 V_START_TIME:=SYSDATE;--将V_START_TIME的值更新为当前的系统时间

2023-07-13 上传
SELECT A.obj_id, NULL, A.apply_obj_spec, NULL, A.create_date, A.region_id, A.create_ORG_ID, current_date, NULL, A.cust_order_id, A.ORDER_item_id, NULL, NULL, NULL, A.BELONG_lan_id, create_staff ...

使用xtrabackup2.4.28版本对MySQL恢复时，执行innobackupex --apply-log --redo-log /backup/2023-07-16_23-08-34/ --incremental-dir=/backup/--incremental-basedir出现xtrabackup: error: applying incremental backup needs target prepared with --apply-log-only.

2023-07-17 上传
innobackupex --apply-log --redo-log /backup/2023-07-16_23-08-34/ --incremental-dir=/backup/--incremental-basedir ``` 并且遇到了以下错误： ``` xtrabackup: error: applying incremental backup needs ...

import cv2 import mediapipe as mp mp_drawing = mp.solutions.drawing_utils mp_drawing_styles = mp.solutions.drawing_styles mp_holistic = mp.solutions.holistic # For webcam input: filepath='F:\\video000\\ce.mp4' cap = cv2.VideoCapture(filepath) with mp_holistic.Holistic( min_detection_confidence=0.5, min_tracking_confidence=0.5) as holistic: while cap.isOpened(): success, image = cap.read() if not success: print("Ignoring empty camera frame.") # If loading a video, use 'break' instead of 'continue'. break # To improve performance, optionally mark the image as not writeable to # pass by reference. image.flags.writeable = False image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) results = holistic.process(image) # Draw landmark annotation on the image. image.flags.writeable = True image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR) mp_drawing.draw_landmarks( image, results.face_landmarks, mp_holistic.FACEMESH_CONTOURS, landmark_drawing_spec=None, connection_drawing_spec=mp_drawing_styles .get_default_face_mesh_contours_style()) mp_drawing.draw_landmarks( image, results.pose_landmarks, mp_holistic.POSE_CONNECTIONS, landmark_drawing_spec=mp_drawing_styles .get_default_pose_landmarks_style()) # Flip the image horizontally for a selfie-view display. cv2.imshow('MediaPipe Holistic', cv2.flip(image, 1)) if cv2.waitKey(5) & 0xFF == 27: break cap.release() 在这段代码中引入注意力机制，使人体步态特征更好的提取

2023-06-07 上传
# Apply attention mechanism to the key feature points or vectors. pose_attention = apply_attention(pose_landmarks) face_attention = apply_attention(face_landmarks) left_hand_attention = apply_...

WARNING:tensorflow:From E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\bert_base\bert\modeling.py:359: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version. Instructions for updating: Please use rate instead of keep_prob. Rate should be set to rate = 1 - keep_prob. WARNING:tensorflow:From E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\bert_base\bert\modeling.py:673: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version. Instructions for updating: Use keras.layers.Dense instead. WARNING:tensorflow:From E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\venv\lib\site-packages\tensorflow_core\python\layers\core.py:187: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version. Instructions for updating: Please use layer.__call__ method instead. WARNING:tensorflow:From E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\bert_base\bert\modeling.py:277: The name tf.erf is deprecated. Please use tf.math.erf instead.

2023-07-14 上传
你可以将代码中的 `Layer.apply` 替换为 `layer.__call__` 来消除这个警告。 4. "From E:\pycharm-workspace\BERT\BERT-BiLSTM-CRF-NER-master\bert_base\bert\modeling.py:277: The name tf.erf is deprecated. ...

优化代码：import openpyxl # 定义常量 apply_file = '申请名单.xlsx' summary_file = '汇总表.xlsx' apply_sheet_name = 'Sheet1' summary_sheet_name = 'Sheet1' try: # 使用with语句，确保工作簿在使用完后能够自动关闭 with openpyxl.load_workbook(apply_file, data_only=True) as wb_apply, openpyxl.load_workbook(summary_file) as wb_summary: # 获取申请表Sheet1和汇总表Sheet1 apply_sheet = wb_apply[apply_sheet_name] summary_sheet = wb_summary[summary_sheet_name] # 获取汇总表Sheet1的最大行数，并加1得到下一行的行号 next_row = summary_sheet.max_row + 1 # 从申请表Sheet1复制数据到汇总表Sheet1的下一行 for i, row in enumerate(apply_sheet.iter_rows(min_row=2, values_only=True), start=next_row): summary_sheet.append(row) # 保存汇总表工作簿 wb_summary.save(summary_file) except Exception as e: print(f"出现异常：{e}")

2023-05-23 上传
for i, row in enumerate(apply_sheet.iter_rows(min_row=2, values_only=True), start=next_row): summary_sheet.append(row) wb_summary.save(SUMMARY_FILE) except Exception as e: print(f"出现异常：{e}") ...

请帮我将这段代码改为设置4个固定的NPC代码# Spawn vehicles # -------------- batch = [] for n, transform in enumerate(spawn_points): print('n',n) print('transform',transform) if n >= args.number_of_vehicles: break blueprint = random.choice(blueprints) print('blueprints的长度', len(blueprints)) print('blueprints',blueprints) print('blueprint', blueprint) if blueprint.has_attribute('color'): color = random.choice(blueprint.get_attribute('color').recommended_values) blueprint.set_attribute('color', color) if blueprint.has_attribute('driver_id'): driver_id = random.choice(blueprint.get_attribute('driver_id').recommended_values) blueprint.set_attribute('driver_id', driver_id) blueprint.set_attribute('role_name', 'autopilot') # prepare the light state of the cars to spawn light_state = vls.NONE if args.car_lights_on: light_state = vls.Position | vls.LowBeam | vls.LowBeam # spawn the cars and set their autopilot and light state all together batch.append(SpawnActor(blueprint, transform) .then(SetAutopilot(FutureActor, True, traffic_manager.get_port())) .then(SetVehicleLightState(FutureActor, light_state))) for response in client.apply_batch_sync(batch, synchronous_master): if response.error: logging.error(response.error) else: vehicles_list.append(response.actor_id)

2023-06-10 上传
for response in client.apply_batch_sync(batch, synchronous_master): if response.error: logging.error(response.error) else: vehicles_list.append(response.actor_id) ``` 在这里，我们手动定义了4个NPC...
刘良运
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