Mark F Russo, William Neil

Streamlining Your Research Laboratory with Python

• Gebundenes Buch

Produktbeschreibung

"This book introduces Python as a powerful tool for researchers in scientific laboratories. It highlights Python's simplicity, versatility, and extensive libraries, making it ideal for automating tasks, processing data, conducting analysis, and visualizing results. Geared toward both novice and experienced programmers, the book emphasizes how Python can streamline laboratory operations, improve productivity, and enhance scientific research. It covers key features of Python, its applications in automation, data collection, analysis, and scientific computing, and provides real-world examples of its use in various research fields. With downloadable code examples and a focus on practical solutions to everyday research challenges, the book is a valuable resource for scientists looking to harness Python for their work."--

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Wiley
• Seitenzahl: 416
• Erscheinungstermin: 22. Juli 2025
• Englisch
• ISBN-13: 9781394249886
• ISBN-10: 1394249888
• Artikelnr.: 72550986

Autorenporträt

Mark F. Russo, PhD is currently on the faculty in the Department of Computer Science at The College of New Jersey. Previously, he had a multi-decade professional career in biotech and pharma with a focus on scientific computing, automation, and scientific data. William Neil is currently at Bristol Myers Squibb and has been working in the pharmaceutical industry since 1995.

Inhaltsangabe

Contents
Dedication. 1
Contents. 2
Preface. 10
Chapter 1 : Introduction. 11
Section 1.1 : Python Implementations. 11
Section 1.2 : Installing the Python Toolkit. 12
Section 1.3 : Python 3 vs. Python 2. 13
Section 1.4 : Python Package Index. 13
Section 1.5 : Programming Editors. 14
Section 1.6 : Notebook Editors. 15
Section 1.7 : Using the Jupyter Notebook Interface. 17
Section 1.8 : JupyterLite. 18
Section 1.9 : Things Change. 20
Section 1.10 : Key Takeaways. 20
Chapter 2 : Language Basics. 21
Section 2.1 : Python Interactive Console. 21
Section 2.2 : Data Types. 22
Section 2.3 : Variables and Literals. 24
Section 2.4 : Strings. 26
2.4.1 : Simple Strings. 26
2.4.2 : Multi-line Strings. 26
2.4.3 : Escape Characters in a String. 26
2.4.4 : Raw Strings. 28
2.4.5 : Formatted Strings. 28
2.4.6 : Strings as Objects. 30
2.4.7 : Characters and Encodings. 31
Section 2.5 : Expressions using Operators. 32
2.5.1 : Arithmetic Operators. 33
2.5.2 : Assignment Operators. 35
2.5.3 : Comparison Operators. 36
2.5.4 : Boolean Operators. 37
2.5.5 : Chaining Comparisons. 39
2.5.6 : Comparing Floating Point Numbers. 39
Section 2.6 : Functions and How to Use Them.. 40
2.6.1 : Invoking Functions. 40
2.6.2 : Built-in Functions. 41
2.6.3 : The math Module for Additional Mathematical Functions. 42
2.6.4 : The random Module for Pseudo-random Number Generation. 44
2.6.5 : The time and datetime Modules for Handling Dates and Times. 47
2.6.6 : The sys Module for System Interactions. 50
2.6.7 : Scope and Namespace. 51
Section 2.7 : Your First Python Program.. 52
Section 2.8 : Key Takeaways. 53
Chapter 3 : Data Structures. 55
Section 3.1 : Lists. 55
3.1.1 : Introducing Lists. 55
3.1.2 : Global Functions that Operate on Lists. 55
3.1.3 : Accessing List Elements. 56
3.1.4 : Slicing Lists. 57
3.1.5 : Lists Operators. 59
3.1.6 : Lists as Objects. 61
Section 3.2 : Tuples. 65
3.2.1 : Introducing Tuples. 65
Section 3.3 : Dictionaries. 66
3.3.1 : Introducing Dictionaries. 66
3.3.2 : Global Functions that Operate on Dictionaries. 67
3.3.3 : Accessing Dictionary Items. 67
3.3.4 : Dictionary Operators. 68
3.3.5 : Dictionaries as Objects. 69
Section 3.4 : Sets. 71
3.4.1 : Introducing Sets. 71
3.4.2 : Global Functions that Operate on Sets. 71
3.4.3 : Accessing Set Elements. 72
3.4.4 : Set Operators. 72
3.4.5 : Sets as Objects. 74
Section 3.5 : Destructuring Assignment. 75
Section 3.6 : Key Takeaways. 76
Chapter 4 : Controlling the Flow of a Program.. 77
Section 4.1 : Conditional Execution. 77
4.1.1 : If-statements. 77
4.1.2 : if-else Statements. 78
4.1.3 : If-elif-else Statements. 80
4.1.4 : If-statement Strategies. 82
4.1.5 : Truthy and Falsy Values. 85
4.1.6 : Conditional Expressions. 86
Section 4.2 : Repeated Execution. 88
4.2.1 : While-statements. 88
4.2.2 : For-statements. 93
4.2.3 : For-statements with Range. 95
4.2.4 : Break and Continue. 96
4.2.5 : Comprehensions. 98
Section 4.3 : Key Takeaways. 99
Chapter 5 : Custom Functions and Exceptions. 101
Section 5.1 : Defining Custom Functions. 101
Section 5.2 : Arguments and Parameters. 106
Section 5.3 : Names and Scope. 109
5.3.1 : Local vs. Global 109
5.3.2 : Built-in and Nonlocal Scope. 111
Section 5.4 : Scope vs Namespace. 113
Section 5.5 : Organizing your Code with Modules. 114
Section 5.6 : Decorators. 116
Section 5.7 : How Things Go Wrong. 118
Section 5.8 : Python Exceptions. 119
Section 5.9 : Handling Exceptions. 120
Section 5.10 : Raising Your Own Exceptions. 123
Section 5.11 : Key Takeaways. 126
Chapter 6 : Regular Expressions. 128
Section 6.1 : Matching Literal Text. 128
Section 6.2 : Alternation. 129
Section 6.3 : Defining and Matching Character Classes. 129
Section 6.4 : Metaclasses. 130
Section 6.5 : Pattern Sequences. 130
Section 6.6 : Repeating Patterns with Quantifiers. 130
Section 6.7 : Anchors. 132
Section 6.8 : Capturing Groups. 133
Section 6.9 : Regular Expressions in Python. 135
Section 6.10 : Project - A Formula Mass Calculator. 136
Section 6.11 : Key Takeaways. 143
Chapter 7 : Working with Data. 144
Section 7.1 : A File System Primer. 144
Section 7.2 : Text Files. 145
Section 7.3 : Reading and Writing Text Files. 147
Section 7.4 : Working with Comma-Separated Values (CSV) Files. 153
Section 7.5 : The csv Module. 157
Section 7.6 : Reading and Writing Excel Spreadsheet. 158
7.6.1 : openpyxl Workbook Object. 159
7.6.2 : openpyxl Worksheet Object. 160
7.6.3 : openpyxl Cell Object. 161
Section 7.7 : Project - Generate a Random Sample Layout in a Spreadsheet
161
Section 7.8 : Project - Forecast Monthly Sample Processing. 163
Section 7.9 : Managing the File System.. 168
7.9.1 : The Path Object. 168
7.9.2 : Path Properties. 169
7.9.3 : Path Attributes. 170
7.9.4 : Operating a Path. 170
7.9.5 : Combining Paths. 172
7.9.6 : The shutil Module for High-level File Operations. 172
Section 7.10 : Walking a File System Tree. 173
Section 7.11 : Project - Find Duplicate Files. 174
Section 7.12 : Working with Zip Files. 176
7.12.1 : ZipFile Object. 177
7.12.2 : zipfile.Path Object. 177
7.12.3 : Creating Zip Archives. 178
Section 7.13 : Working with Standard Data Formats. 179
7.13.1 : JSON - JavaScript Object Notation. 179
7.13.2 : json Python Module. 180
7.13.3 : XML - Extensible Markup Language. 182
7.13.4 : Python XML modules. 183
7.13.5 : Other Standard Data Formats. 189
Section 7.14 : Key Takeaways. 189
Chapter 8 : Web Resources. 191
Section 8.1 : TCP/IP Networks - What You Need to Know.. 191
8.1.1 : Internet Protocol (IP). 191
8.1.2 : Transmission Control Protocol (TCP). 192
8.1.3 : Connections and Ports. 192
8.1.4 : Application-layer Protocols. 192
8.1.5 : IPv4 vs. IPv6 Addresses. 193
8.1.6 : Proxy Servers. 193
Section 8.2 : Introduction to Hypertext Transfer Protocol (HTTP). 194
8.2.1 : The Uniform Resource Locator (URL). 195
8.2.2 : Anatomy of an HTTP Request. 196
8.2.3 : Anatomy of an HTTP Response. 198
Section 8.3 : Web Services and the Python Requests Module. 199
8.3.1 : HTTP GET Requests and the Response Object. 200
8.3.2 : HTTP POST Requests. 201
8.3.3 : Binary Responses. 202
8.3.4 : Customizing the Request Object. 205
8.3.5 : Verifying Certificates and Encryption. 205
8.3.6 : Other Request Module Options. 206
Section 8.4 : Project - Print Weather Forecast for a Location. 207
8.4.1 : National Weather Service API Web Service. 207
8.4.2 : Getting Forecast URL from Geolocation. 209
8.4.3 : Loading and Processing Forecast Data. 209
8.4.4 : Completed Program to Generate Temperature Forecast. 210
Section 8.5 : Project - Scraping HTML Page Content. 213
Section 8.6 : Key Takeaways. 218
Chapter 9 : Data Analysis and Visualization. 220
Section 9.1 : JupyterLab. 220
Section 9.2 : Scientific Plotting with Matplotlib. 222
9.2.1 : The pyplot Submodule. 223
9.2.2 : The pyplot.plot() function. 223
9.2.3 : Customizing a Plot. 224
9.2.4 : Multiple Curves on a Single Plot. 225
9.2.5 : Additional Plot Types. 227
9.2.6 : Multiple Axes on a Single Figure. 227
9.2.7 : Other Useful Functions. 229
9.2.8 : Project - Plotting Weather Forecast. 229
9.2.9 : Project - A Custom Microplate Heat Map. 231
9.2.10 : Other Scientific Plotting Libraries. 235
Section 9.3 : NumPy - Numerical Python. 236
9.3.1 : Creating ndarray Objects. 236
9.3.2 : Working with ndarray Objects. 236
9.3.3 : Accessing and Updating ndarray Elements. 237
9.3.4 : Broadcasting. 239
Section 9.4 : pandas DataFrame. 240
9.4.1 : Creating and Inspecting DataFrames. 240
9.4.2 : Filtering DataFrames. 243
9.4.3 : Project - A Screening Experiment. 246
Section 9.5 : SciPy - A Library for Mathematics, Science, and Engineering.
254
9.5.1 : Descriptive Statistics with SciPy. 254
9.5.2 : Hypothesis Testing. 255
9.5.3 : Project - Running Hypothesis Tests on Two Samples. 256
9.5.4 : Project - Comparing Liquid Handler Syringe Performance. 258
9.5.5 : Linear Regression. 260
9.5.6 : Fitting Nonlinear Models to Data. 261
9.5.7 : Project - Four-Parameter Logistic Regression. 264
Section 9.6 : Key Takeaways. 269
Chapter 10 : Report Generation. 271
Section 10.1 : BytesIO Object. 271
Section 10.2 : Generating Reports in Microsoft Word. 272
10.2.1 : Document Object. 273
10.2.2 : Paragraph Object. 274
10.2.3 : Run Object. 275
10.2.4 : Picture and InlineShape Objects. 276
10.2.5 : Table Object. 277
10.2.6 : Project - Generate a Complete Word Report. 279
Section 10.3 : Generating Microsoft PowerPoint Presentations. 282
10.3.1 : Presentation Object. 283
10.3.2 : Slide Objects. 284
10.3.3 : SlideShapes Object. 284
10.3.4 : Length Objects. 285
10.3.5 : Table Object. 287
10.3.6 : Project - Generate a PowerPoint Document with Figures and Tables.
289
Section 10.4 : Generating PDF File Reports. 293
10.4.1 : ReportLab PDF Generation Process. 294
10.4.2 : Creating a Canvas Object. 294
10.4.3 : Setting Canvas Styles. 294
10.4.4 : Managing Text Blocks with PDFTextObjects. 297
10.4.5 : Canvas State Stack. 299
10.4.6 : Drawing Images. 300
10.4.7 : PLATYPUS for Page Layout. 302
10.4.8 : Project - Generate a Complete PDF Report. 303
Section 10.5 : Sending E-mail Programmatically. 306
10.5.1 : Simple Mail Transfer Protocol 306
10.5.2 : SMTP Mail Server. 307
10.5.3 : Send a Simple Email Message. 307
10.5.4 : Sending Email Messages over a Secure Connection. 310
10.5.5 : Building an Email Message with Attachments. 311
Section 10.6 : Serving Results with an HTTP Server. 314
Section 10.7 : Key Takeaways. 315
Chapter 11 : Control and Automation. 317
Section 11.1 : Concurrency in Python. 317
Section 11.2 : Asynchronous Execution. 319
Section 11.3 : Concurrent Programs with AsyncIO.. 320
Section 11.4 : Asynchronous Instrument Control and Coordination. 324
11.4.1 : Project - Integrated Laboratory System Control and Coordination.
324
Section 11.5 : Communicating over a Serial Port. 332
11.5.1 : Reading Barcodes from a Serial Port. 334
11.5.2 : Project - Scanning Sample Tasks into a Running Controller. 339
Section 11.6 : Execute Remote Commands over HTTP. 341
11.6.1 : A Basic HTTP Server with aiohttp. 341
11.6.2 : Routing an HTTP Request to a Custom Python Function. 343
Section 11.7 : Persistent Network Connections using a WebSocket. 347
11.7.1 : A User Interface for an Asynchronous Networked Programs. 348
11.7.2 : WebSocketResponse and FileResponse Objects. 348
11.7.3 : Project - A Browser-Based WebSocket Message Broadcaster. 349
11.7.4 : Project - A Browser UI to Schedule Samples for Analysis. 357
Section 11.8 : Responding to File System Changes. 361
11.8.1 : Watching a Directory for Changes with watchfiles. 361
11.8.2 : File System Monitoring Options. 363
Section 11.9 : Executing Tasks on a Schedule. 365
11.9.1 : sched Module. 365
11.9.2 : Project - Taking and Sending Images on a Schedule. 367
Section 11.10 : Key Takeaways. 371
Postface. 373
References. 374
Appendix A: ASCII American Standard Code for Information Interchange. 377
Index. 378