首页 磁力链接怎么用

[Udemy] Полный Python PostgreSQL Курс 2.0 (2020)

文件类型 收录时间 最后活跃 资源热度 文件大小 文件数量
视频 2022-12-9 22:12 2024-11-12 07:15 152 4.82 GB 137
磁力链接
magnet:?xt=urn:btih:c91567014c24f0fd0bd6dca2fdd358e7a22e648a
迅雷链接
thunder://QUFtYWduZXQ6P3h0PXVybjpidGloOmM5MTU2NzAxNGMyNGYwZmQwYmQ2ZGNhMmZkZDM1OGU3YTIyZTY0OGFaWg==
二维码链接
[Udemy] Полный Python PostgreSQL Курс 2.0 (2020)的二维码
种子下载(838888不存储任何种子文件)
种子下载线路1(迅雷)--推荐
种子下载线路2(比特彗星)
种子下载线路3(torcache)
3条线路均为国内外知名下载网站种子链接，内容跟本站无关！
相关链接

Udemy Полный Python PostgreSQL Курс 2 0 2020

文件列表
  1. 1. Introduction/1. Welcome to this course!.mp439.71MB
  2. 2. A Full Python Refresher/1. Introduction to this section.mp420.49MB
  3. 2. A Full Python Refresher/3. Variables in Python.mp432.13MB
  4. 2. A Full Python Refresher/4. String formatting in Python.mp427.91MB
  5. 2. A Full Python Refresher/5. Getting user input.mp421.54MB
  6. 2. A Full Python Refresher/6. Writing our first Python app.mp416.44MB
  7. 2. A Full Python Refresher/7. Lists, tuples and sets.mp426.42MB
  8. 2. A Full Python Refresher/8. Advanced set operations.mp420.37MB
  9. 2. A Full Python Refresher/9. Booleans in Python.mp423.17MB
  10. 2. A Full Python Refresher/10. If statements.mp444.66MB
  11. 2. A Full Python Refresher/11. The in keyword in Python.mp411.21MB
  12. 2. A Full Python Refresher/12. If statements with the in keyword.mp442.42MB
  13. 2. A Full Python Refresher/13. Loops in Python.mp453.41MB
  14. 2. A Full Python Refresher/14. List comprehensions in Python.mp430.86MB
  15. 2. A Full Python Refresher/15. Dictionaries.mp436.39MB
  16. 2. A Full Python Refresher/16. Destructuring variables.mp434.12MB
  17. 2. A Full Python Refresher/17. Functions in Python.mp444.63MB
  18. 2. A Full Python Refresher/18. Function arguments and parameters.mp437.97MB
  19. 2. A Full Python Refresher/19. Default parameter values.mp418.05MB
  20. 2. A Full Python Refresher/20. Functions returning values.mp435.19MB
  21. 2. A Full Python Refresher/21. Lambda functions in Python.mp438.55MB
  22. 2. A Full Python Refresher/22. Dictionary comprehensions.mp423.75MB
  23. 2. A Full Python Refresher/23. Unpacking arguments.mp451.44MB
  24. 2. A Full Python Refresher/24. Unpacking keyword arguments.mp444.73MB
  25. 2. A Full Python Refresher/25. Object-Oriented Programming in Python.mp489.66MB
  26. 2. A Full Python Refresher/26. Magic methods _str_ and _repr_.mp436.76MB
  27. 2. A Full Python Refresher/27. @classmethod and @staticmethod.mp480.77MB
  28. 2. A Full Python Refresher/28. Class inheritance.mp453.69MB
  29. 2. A Full Python Refresher/29. Class composition.mp435.18MB
  30. 2. A Full Python Refresher/30. Type hinting in Python 3.5+.mp431.89MB
  31. 2. A Full Python Refresher/31. Imports in Python.mp458.48MB
  32. 2. A Full Python Refresher/32. Relative imports in Python.mp454.22MB
  33. 2. A Full Python Refresher/33. Errors in Python.mp487.72MB
  34. 2. A Full Python Refresher/34. Custom error classes.mp442.14MB
  35. 2. A Full Python Refresher/35. First-class functions.mp448.54MB
  36. 2. A Full Python Refresher/36. Simple decorators in Python.mp450.13MB
  37. 2. A Full Python Refresher/37. The 'at' syntax for decorators.mp428.91MB
  38. 2. A Full Python Refresher/38. Decorating functions with parameters.mp414.39MB
  39. 2. A Full Python Refresher/39. Decorators with parameters.mp435.92MB
  40. 2. A Full Python Refresher/40. Mutability in Python.mp424.55MB
  41. 2. A Full Python Refresher/41. Mutable default parameters (and why they're a bad idea).mp422.26MB
  42. 3. Build a Programming Journal with Python & SQL/1. Overview of the project.mp419.24MB
  43. 3. Build a Programming Journal with Python & SQL/2. Creating our user menu.mp426.36MB
  44. 3. Build a Programming Journal with Python & SQL/3. What is SQL.mp444.14MB
  45. 3. Build a Programming Journal with Python & SQL/4. Using Python lists as an in-memory database.mp458.05MB
  46. 3. Build a Programming Journal with Python & SQL/5. A SQLite data viewer.mp437.6MB
  47. 3. Build a Programming Journal with Python & SQL/6. CREATE TABLE new tables with SQL.mp428.37MB
  48. 3. Build a Programming Journal with Python & SQL/9. How to connect to a SQLite database with Python.mp459.31MB
  49. 3. Build a Programming Journal with Python & SQL/10. Connecting to SQLite in our app.mp416.12MB
  50. 3. Build a Programming Journal with Python & SQL/11. What is a cursor.mp441.52MB
  51. 3. Build a Programming Journal with Python & SQL/12. INSERT INTO add data to a table.mp427.8MB
  52. 3. Build a Programming Journal with Python & SQL/14. How to insert data into SQLite with Python.mp435.64MB
  53. 3. Build a Programming Journal with Python & SQL/15. SELECT retrieve data from a table.mp418.24MB
  54. 3. Build a Programming Journal with Python & SQL/17. Retrieving results from a cursor.mp437.79MB
  55. 3. Build a Programming Journal with Python & SQL/18. WHERE search with SQL.mp449.62MB
  56. 3. Build a Programming Journal with Python & SQL/20. DROP TABLE deleting entire tables.mp411.54MB
  57. 3. Build a Programming Journal with Python & SQL/22. What is a SQL injection attack.mp423.71MB
  58. 4. A Movie Watchlist App with Python & SQL/1. Overview of the project.mp416.5MB
  59. 4. A Movie Watchlist App with Python & SQL/2. Three development stages of our project.mp432.77MB
  60. 4. A Movie Watchlist App with Python & SQL/3. Our starting code for this project.mp46.95MB
  61. 4. A Movie Watchlist App with Python & SQL/4. Queries we'll need for the project to begin with.mp423.45MB
  62. 4. A Movie Watchlist App with Python & SQL/5. Write the database.py file.mp441.69MB
  63. 4. A Movie Watchlist App with Python & SQL/6. UPDATE changing data with SQL.mp427.56MB
  64. 4. A Movie Watchlist App with Python & SQL/8. Write our user menu and functions.mp463.18MB
  65. 4. A Movie Watchlist App with Python & SQL/9. Watched movies second approach.mp47.75MB
  66. 4. A Movie Watchlist App with Python & SQL/10. DELETE FROM removing rows with SQL.mp414.54MB
  67. 4. A Movie Watchlist App with Python & SQL/12. Stage 2 watching movies.mp452.57MB
  68. 4. A Movie Watchlist App with Python & SQL/13. Relational data primary and foreign keys.mp427.61MB
  69. 4. A Movie Watchlist App with Python & SQL/15. Watched movies final approach.mp419.12MB
  70. 4. A Movie Watchlist App with Python & SQL/16. Stage 3 adding new watched movies.mp465.11MB
  71. 4. A Movie Watchlist App with Python & SQL/17. Auto-incrementing row IDs.mp429.11MB
  72. 4. A Movie Watchlist App with Python & SQL/19. JOIN access two tables at once with SQL.mp422.58MB
  73. 4. A Movie Watchlist App with Python & SQL/20. Use JOINs to retrieve the movies a user has watched.mp451.94MB
  74. 4. A Movie Watchlist App with Python & SQL/22. ORDER BY sort the returned table.mp413.13MB
  75. 4. A Movie Watchlist App with Python & SQL/23. LIMIT getting a certain number of rows.mp47.75MB
  76. 4. A Movie Watchlist App with Python & SQL/24. LIKE flexible searching.mp450.4MB
  77. 4. A Movie Watchlist App with Python & SQL/25. What is an index in SQL.mp437.31MB
  78. 4. A Movie Watchlist App with Python & SQL/26. Adding an index to our table for more efficient searching.mp428.47MB
  79. 5. Introduction to PostgreSQL Migrating our App/1. SQLite vs. PostgreSQL.mp430.86MB
  80. 5. Introduction to PostgreSQL Migrating our App/2. How to install PostgreSQL.mp420.11MB
  81. 5. Introduction to PostgreSQL Migrating our App/3. How to run and access PostgreSQL.mp415.57MB
  82. 5. Introduction to PostgreSQL Migrating our App/4. psycopg2 vs psycopg2-binary.mp467.97MB
  83. 5. Introduction to PostgreSQL Migrating our App/5. How to store (and not store!) sensitive information in your code.mp454.08MB
  84. 5. Introduction to PostgreSQL Migrating our App/6. Psycopg2 cursors and query parameters.mp433.57MB
  85. 5. Introduction to PostgreSQL Migrating our App/7. Auto-incrementing columns SEQUENCE and SERIAL in PostgreSQL.mp412.98MB
  86. 5. Introduction to PostgreSQL Migrating our App/8. Our changed code, and finding differences between files.mp415.85MB
  87. 6. Building a Poll App & Advanced SQL/1. Overview of the project.mp423.62MB
  88. 6. Building a Poll App & Advanced SQL/2. What is ACID.mp433.97MB
  89. 6. Building a Poll App & Advanced SQL/3. Essential queries we'll need for this project.mp459.33MB
  90. 6. Building a Poll App & Advanced SQL/4. RETURNING data from modified rows.mp442.38MB
  91. 6. Building a Poll App & Advanced SQL/5. Nested queries getting the latest poll.mp451.71MB
  92. 6. Building a Poll App & Advanced SQL/6. SQL built-in functions.mp435.74MB
  93. 6. Building a Poll App & Advanced SQL/7. GROUP BY and calculating vote percentages.mp468.5MB
  94. 6. Building a Poll App & Advanced SQL/8. PostgreSQL window functions.mp451.13MB
  95. 6. Building a Poll App & Advanced SQL/9. PostgreSQL window functions (part 2).mp437.57MB
  96. 6. Building a Poll App & Advanced SQL/10. How to use ORDER BY with window functions.mp427.71MB
  97. 6. Building a Poll App & Advanced SQL/11. How to use PARTITION with window functions.mp430.6MB
  98. 6. Building a Poll App & Advanced SQL/12. SQL DISTINCT and DISTINCT ON.mp445.23MB
  99. 6. Building a Poll App & Advanced SQL/13. The SQL HAVING clause.mp413.12MB
  100. 6. Building a Poll App & Advanced SQL/14. SQL VIEW virtual tables.mp478.6MB
  101. 6. Building a Poll App & Advanced SQL/15. How to read the PostgreSQL documentation.mp4116.4MB
  102. 6. Building a Poll App & Advanced SQL/16. Adding type hinting to our application.mp451.96MB
  103. 7. Working with dates and times/1. How to separate our database entities into models.mp462.24MB
  104. 7. Working with dates and times/2. Creating our Option model class.mp426.45MB
  105. 7. Working with dates and times/3. Changes needed in database.py.mp462.86MB
  106. 7. Working with dates and times/4. Changes needed in app.py.mp475.18MB
  107. 7. Working with dates and times/5. What is connection pooling.mp429.94MB
  108. 7. Working with dates and times/6. How to create a connection pool with psycopg2.mp431.45MB
  109. 7. Working with dates and times/7. Reduce pooling duplication with context managers.mp437.03MB
  110. 7. Working with dates and times/8. Reduce cursor creation duplication with context managers.mp422.85MB
  111. 7. Working with dates and times/9. The Python datetime module.mp431.24MB
  112. 7. Working with dates and times/10. How to calculate new dates with timedelta.mp419.07MB
  113. 7. Working with dates and times/11. How to handle timezones with pytz.mp471.7MB
  114. 7. Working with dates and times/12. How to save dates to PostgreSQL.mp439.55MB
  115. 7. Working with dates and times/13. Add the vote date to our polling app.mp464.78MB
  116. 8. Python and Advanced PostgreSQL with psycopg2/1. Composite primary keys.mp419.22MB
  117. 8. Python and Advanced PostgreSQL with psycopg2/2. User-defined functions in PostgreSQL.mp442.71MB
  118. 8. Python and Advanced PostgreSQL with psycopg2/3. Composite types and sets in functions.mp446.25MB
  119. 8. Python and Advanced PostgreSQL with psycopg2/4. Stored procedures in PostgreSQL.mp431.41MB
  120. 8. Python and Advanced PostgreSQL with psycopg2/5. Connections vs transactions in psycopg2.mp423.65MB
  121. 8. Python and Advanced PostgreSQL with psycopg2/6. Locking in PostgreSQL.mp454.05MB
  122. 8. Python and Advanced PostgreSQL with psycopg2/7. Asynchronous psycopg2.mp425.98MB
  123. 8. Python and Advanced PostgreSQL with psycopg2/8. SQL string composition with psycopg2.mp428.31MB
  124. 9. Charting data from our tables using matplotlib/1. Overview creating graphs from poll data.mp414.96MB
  125. 9. Charting data from our tables using matplotlib/3. How to draw a line graph with matplotlib.mp416.68MB
  126. 9. Charting data from our tables using matplotlib/5. Matplotlib figures, axes, and plots.mp416.93MB
  127. 9. Charting data from our tables using matplotlib/6. The Object-Oriented Approach with matplotlib.mp417.22MB
  128. 9. Charting data from our tables using matplotlib/7. How to add multiple subplots to a figure.mp419.58MB
  129. 9. Charting data from our tables using matplotlib/8. How to draw a pie chart with matplotlib.mp456.99MB
  130. 9. Charting data from our tables using matplotlib/9. How to draw a bar chart with matplotlib.mp425.82MB
  131. 9. Charting data from our tables using matplotlib/10. How to adjust the size of a matplotlib plot.mp417.1MB
  132. 9. Charting data from our tables using matplotlib/11. How to adjust the x axis tick labels so they fit in the screen.mp426.41MB
  133. 9. Charting data from our tables using matplotlib/12. How to draw a stacked bar chart with matplotlib.mp435.38MB
  134. 9. Charting data from our tables using matplotlib/13. How to create a legend from your graphed data.mp413.74MB
  135. 9. Charting data from our tables using matplotlib/14. How to export an image with matplotlib.mp434.18MB
  136. 9. Charting data from our tables using matplotlib/15. How to create one document with multiple matplotlib plots.mp413.07MB
  137. 9. Charting data from our tables using matplotlib/16. How to create a custom legend with matplotlib.mp420.28MB
友情提示
不会用的朋友看这里 把磁力链接复制到离线下载，或者bt下载软件里即可下载文件，或者直接复制迅雷链接到迅雷里下载！ 亲，你造吗？将网页分享给您的基友，下载的人越多速度越快哦！

违规内容投诉邮箱：[email protected]

概述 838888磁力搜索是一个磁力链接搜索引擎，是学术研究的副产品，用于解决资源过度分散的问题 它通过BitTorrent协议加入DHT网络，实时的自动采集数据，仅存储文件的标题、大小、文件列表、文件标识符（磁力链接）等基础信息 838888磁力搜索不下载任何真实资源，无法判断资源的合法性及真实性，使用838888磁力搜索服务的用户需自行鉴别内容的真伪 838888磁力搜索不上传任何资源，不提供Tracker服务，不提供种子文件的下载，这意味着838888磁力搜索 838888磁力搜索是一个完全合法的系统
838888磁力链接 磁力链接bt种子搜索引擎磁力搜索 DMCA